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Mlchigzzin State
University

 

 

 

This is to certify that the

thesis entitled
The Managerial, Production, and

Financial Implications of Dairy Farm
Expansion in Michigan and Wisconsin.

presented by

Gregg Lewis Hadley

has been accepted towards fulfillment
of the requirements for

 

Masters degree in Agricultural Economics

 

mﬂz

Major professor

05-04-01
Date

 

0-7639 MS U is an Afﬁrmative Action/Equal Opportunity Institution

 

 

 

 

 

 

 

 

PLACE IN RETURN Box to remove this checkout from your record.
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DATE DUE DATE DUE DATE DUE
CL 1 5 25-97

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6/01 C‘JCIRC/DateDUOpGS-p. 15

 

 

 

THE MANAGERIAL, PRODUCTION AND FINANCIAL IMPLICATIONS OF
DAIRY FARM EXPANSION IN MICHIGAN AND WISCONSIN

By

Gregg Lewis Hadley

A THESIS
Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of
MASTER OF SCIENCE
Department of Agricultural Economics

2001

 

 

ABSTRACT

THE MANAGERIAL, PRODUCTION AND FINANCIAL IMPLICATIONS OF
DAIRY FARM EXPANSION IN MICHIGAN AND WISCONSIN

By

Gregg Lewis Hadley

This research examines the managerial, production, and ﬁnancial effects that dairy
farm expansion had on twenty Michigan and Wisconsin managers and their dairy
operations. These farms conducted at least one expansion during 198 8 - 1998 that was
characterized by a twenty percent or more herd size increase that also required
improvements in or additions to facilities, equipment and human resources. The research

was conducted to provide dairy farm managers with current information from which to

base dairy farm expansion decisions.

Average herd size increased by 92 percent to 569 cows. Most of the managers
were deemed to have above average herd management ability. They expanded primarily to
improve proﬁtability. The expansions were not accompanied by an initial decrease in
productivity, reproduction, or herd health measures, but biosecurity problems were
evident on most dairies. Labor productivity improved on most dairies, but most managers
still desired human resource management training and skills to further improve
productivity. Most managers faced public relations problems before, during, and after
expansion. Outsourcing enterprise activities was common among the dairies, as was the
internalization of initial milk marketing, milk hauling and veterinary care. On average, net

farm income increased, and the total economic costs of production decreased.

C0pyright by
Gregg Lewis Hadley
200 l

ACKNOWLEDGMENTS
I would like to thank my advisory committee for their insight and thoughtful
recommendations. I would also like to thank the twenty dairy farm managers who took the
time to participate in this research. Without their assistance, this thesis would not have

been possible.

:‘1

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................... x
LIST OF FIGURES ...................................................................................................... xiii
KEY TO ABBREVIATIONS ........................................................................................ xiv

CHAPTER I. INTRODUCTION

1. Background Information ....................................................................................... 1
H. Expansion Terminology ........................................................................................ 1
III. Problem Statement ............................................................................................... 2
IV. Goals and Objectives: ........................................................................................... 4

CHAPTER H. METHODS AND PROCEDURES

I. Case Study Analysis ............................................................................................. 7
II. Participant Determination and Sample Size ........................................................... 7
HI. Survey and Interview Methods ............................................................................. 9
IV. Data Preparation ................................................................................................. l 1

CHAPTER III. FARM AND MANAGER CHARACTERISTICS

I. Introduction ........................................................................................................ 13
11. Farm Descriptive Statistics .................................................................................. 14
III. The Eﬂ'ect of Expansion on the Manager’s Job Description ................................. 16
IV. Management Skills: Previous Expansion Experience .......................................... 17
IV-a. Expansion Classiﬁcation .......................................................................... 18

V. Management Skills: Herd Management Ability ................................................... 19
VI. Management Skills: General Management Skills ................................................ 21

VII. Management Skills: Essential Management Skills ............................................... 23

VIII. Conclusions ........................................................................................................ 26

CHAPTER IV. WHY DO MANAGERS CHOOSE DAIRY EXPANSION?

I.

II.

IV.

Introduction ................... l ..................................................................................... 27
Why Managers Expand Dairy Operations ............................................................ 3O
Expansion Reasons by Expansion Classiﬁcation .................................................. 32
III-a. Expansion Reasons by Initial Expander Managers ................................... 33
III-b. Expansion Reasons by Subsequent Expander Managers ........................... 34
III-c. Expansion Reasons by Rapid Expander Managers ................................... 35
Conclusions ........................................................................................................ 36

CHAPTER V. THE EFFECT OF DAIRY FARM EXPANSION ON MILK

3-4

as:

PRODUCTION, REPRODUCTION, HERD HEALTH AND CROP

PRODUCTION

Introduction ........................................................................................................ 38
Research Pr0positions ......................................................................................... 40
Effects on Production ......................................................................................... 42
Problems Constraining Production ...................................................................... 47
IV-a. Pre-expansion Production Problems ........................................................ 47
IV-b. Post Expansion Production Problems ...................................................... 49
The Effects on Reproduction .............................................................................. 53

Reproduction Problems ...................................................................................... 56

VI-a. Pre-expansion Reproduction Problems .................................................... 56

VI-b. Post Expansion Reproduction Problems .................................................. S 8

VI-c. Conclusions Concerning Reproduction Problems ..................................... 59

VII. The Effect of Expansion on Herd Health ............................................................. 60
VIII. Herd Health Problems ......................................................................................... 63
VIII-a. Problems Constraining Pre-expansion Herd Health ................................ 63

VIII-b. Post Expansion Herd Health Problems .................................................. 64

IX. The Incidence of Post Expansion Biosecun'ty Problems ....................................... 66
X. The Eﬂ‘ect on Crop Yield and Quality ................................................................. 69
XI. Conclusions ........................................................................................................ 71

CHAPTER VI. THE EFFECT OF DAIRY FARM EXPANSION ON LABOR

IH.

IV.

V.

VI.

PRODUCTIVITY AND HUMAN RESOURCE MANAGEMENT

Introduction ........................................................................................................ 73
The Effects on Labor Productivity: Milk/FTE .................................................... 76
The Effects on Labor Productivity: TLME/cwt .................................................. 78
How HRM Problem Importance Changed as Dairies Expand .............................. 79
Desired HRM Skill Training ............................................................................... 83
Conclusions ........................................................................................................ 85

CHAPTER VII. THE EFFECTS OF ENVIRONMENTAL COMPLIANCE, PUBLIC

II.

III.

IV.

RELATIONS AND ZONING ON DAIRY FARM EXPANSION

Introduction ........................................................................................................ 87
EPZ Problems Anticipated and Encountered ....................................................... 89
The Residential Background of EPZ Complainants ............................................. 92
Annualized Manure Management Technology Costs ........................................... 94
Conclusions ........................................................................................................ 96

vii

CHAPTER VIII. THE EFFECTS OF EXPANSION ON SPECIALIZATION,

I.

II.
III.
IV.
V.

VI.

OUTSOURCING AND INTERNALIZATION

Introduction ....................................................................................................... 98
Measuring Specialization .................................................................................... 99
Pre- and Post Expansion Outsourcing ............................................................... 101
Consulting Services Used by Extension Dairy Managers ................................... 106
Intemalization ................................................................................................... 108

Conclusions ...................................................................................................... 11 1

CHAPTER IX. THE FINANCIAL IMPLICATIONS OF EXPANSION

I.

II.

E

.2

aaaa§§s<

Introduction ...................................................................................................... 1 13
Financial Deﬁnitions ......................................................................................... 114
Balance Sheet, Price and Cost Adjustments ....................................................... 118
The Effect of Expansion on Firm Solvency ........................................................ 119
The Effect of Expansion on Net Farm Income ................................................... 120
The Effect of Expansion on Return to Operator’s Capital and Management ...... 122
The Effect of Expansion on Management Income ............................................. 124
The Effect of Expansion on Return on Assets and Return on Equity .................. 126
Expansion Net Present Values and Internal Rate of Return Estimates ................ 127
Initial and Subsequent Expander Change in MI Breakeven Prices ...................... 130
The Effect of Debt per Cow on Post Expansion ROA.............. ......................... 132
Conclusions ...................................................................................................... 134

viii

CHAPTER X. EXPANSION SUCCESS PREDICTION

I. Introduction ...................................................................................................... 137
II. Production Estimation ...................................................................................... 137
111. Proﬁt Estimation ............................................................................................... 141
IV. The Useﬁrlness of The Management Inventory Test .......................................... 143
V. Conclusions ...................................................................................................... 145

CHAPTER XI. SUMMARY

Summary ....................................................................................... . ............................... 147
APPENDICES
Appendix I. 1998 -— 2000 Upper Midwest Dairy Expansion Survey ......................... 152
Appendix II. 1998 ~—- 2000 Upper Midwest Dairy Expansion Study

Interview Guide .................................................................................... 163
Appendix III. Rolling Herd Average Comparison ........................................................ 176
Appendix IV. Management Inventory Scores by Manager ........................................... 178
Appendix V. Sample NPV Calculation ....................................................................... 180
BIBLIOGRAPHY
Bibliography ................................................................................................................. 186

ix

 

la

Table 1.
Table 2.
Table 3.
Table 4.
Table 5.
Table 6.
Table 7.
Table 8.

Table 9.

Table 10.
Table l 1.
Table 12.
Table 13.

Table 14.

Table 15.
Table 16.
Table 17.
Table 18.

Table 19.

LIST OF TABLES

Farm Descriptive Statistics ............................................................................ 15
Previous Expansion Experience ..................................................................... 18
Expansion Classiﬁcation ................................................................................ 18
Management Inventory Scores by Expansion Classiﬁcation ............................ 19
The Most Essential Dairy Management Skills ................................................. 25
Expansion reasons Indicated by Managers ...................................................... 32
Expansion Reasons Indicated by Initial Expander Managers ........................... 34
Expansion Reasons by Subsequent Expander Managers ................................. 35
RHA Indexes and Sample RHA Adjustment ................................................... 42
Eﬂ‘ects on Pre- and Post Expansion Production .............................................. 43
Comparison of Actual and Projected RHA ..................................................... 45
Pre- expansion Production Problems .............................................................. 48
Post Expansion Production Problems ............................................................. 51
Effect on Reproduction Measures .................................................................. 55
Pre-expansion Reproduction Problems ........................................................... 57
Post Expansion Reproduction Problems ......................................................... 59
Eﬁ‘ect on Culling rate, Cow Mortality and Youngstock Mortality ................... 62
Pre-expansion Herd Health Problems ............................................................. 64
Post Expansion Herd Health Problems ........................................................... 65

Table 20.
Table 21.
Table 22.
Table 23.
Table 24.
Table 25.
Table 26.
Table 27.
Table 28.
Table 29.
Table 30.
Table 31.
Table 32.
Table 33.
Table 34.
Table 35.
Table 36.
Table 37.
Table 38.
Table 39.

Table 40.

 

Biosecurity Problem Incidence ....................................................................... 67
Contagious Diseases Encountered After Expansion ........................................ 68
The Effect on Crap Quality and Yield ............................................................ 70
Improved Crop Yields and Quality ................................................................. 71
Pre- and Post Expansion Milk/FTE ................................................................ 77
Pre- and Post Expansion DWE/cwt ................................................................ 79
HRM Problems Indicated by Expansion Managers ......................................... 82
HRM Education Topics Desired by Managers ................................................ 84
Employee Educational Programs Desired by Managers .................................. 85
EPZ Problems Anticipated and Encountered by Expansion Managers ............. 91
Residential Background of Complainants ....................................................... 93
Annualized Manure Management Technology Cost Comparison .................... 96
Pre- and Post Expansion Diversiﬁcation Index Results ................................. 100
The Manager’s Use of Pre- and Post Expansion Consulting ......................... 102
Additional Outsourcing Desired by Expansion Managers .............................. 104
Consulting Services and Sources Utilized by Managers ................................ 107
Before and After WACC, BL and KL ............................................................. 117
Average Expansion Farm Balance Sheet Values ........................................... 119
The Effect of Expansion on Net Farm Income .............................................. 121
The Effect of Expansion on ROCM .............................................................. 123
The Effect of Expansion on MI .................................................................... 124

Table 41.
Table 42.
Table 43.
Table 44.
Table 45.
Table 46.
Table 47.
Table 48.
Table 49.
Table 50.
Table 51.
Table 52.
Table 53.

Table 54.

Table 55.

Table 56.

The Effect of Expansion on ROA and ROE .................................................. 126
Estimated NPV and [RR of Select Expansion Dairies ................................... 129
A Comparison of Changes in Breakeven Prices ............................................ 131
The Effect of Debt per Cow on ROA ........................................................... 132
Debt Measurement and Return on Assets Correlation ................................... 134
Post Expansion RHA Estimation Summary .................................................. 139
ANOVA Table for the Estimation of Post Expansion RHA .......................... 139
Coefﬁcients for the Estimation of Post Expansion RHA ............................... 139
Wilks’ Lambda for Discriminant Function .................................................... 141
Classiﬁcation Function Coefﬁcients .............................................................. 141
Post Expansion ROA Estimation Summary .................................................. 143
ANOVA Table for the Estimation of Post Expansion ROA .......................... 143
Coefﬁcients for the Estimation of Post Expansion ROA ............................... 143
Post Expansion Dairy Worker Expense per Hundredweight Estimation
Estimation Summary .................................................................................... 145
ANOVA Table for the Estimation of Post Expansion Dairy Worker

Expense per Hundredweight ......................................................................... 145
Coefﬁcients for the Estimation of Post Expansion Dairy Worker Expense

per Hundredweight ...................................................................................... 145

xii

LIST OF FIGURES

Figure 1. Initial Telephone Interview .............................................................................. 8

xiii

ACI:

DHIA:
DI:

DIRECT:

EXP:

F ACCHG:

HERD:

HRM:

KEY TO ABBREVIATIONS

Average calving interval
Average days open
Risk adjustment factor for leverage ﬁrm
Risk adjustment factor for unleveraged ﬁrm
Management Inventory controlling score variable
Debt to asset ratio
Debt to equity ratio

Dairy Herd Improvement Association
Diversiﬁcation index
Management Inventory directing score variable
Debt long term
Debt short term
Dairy worker expense per hundredweight of milk shipped
Equity debt
Environmental, public relations and zoning
Expansion experience variable
Facility technology change variable
Herd size variable
Human resource management
Internal rate of return

Capital to labor ratio

xiv

NFI:

NPV:
ORGANIZE:
PLAN:
POSTRHA:
PRERHA:

PVCF :

ROA:
ROCM:

ROE:

S/C:
SCALE:
SCC:

Cost of leveraged capital
Cost of long term debt capital
20 yr. avg. return of S&P 500
Cost of short term debt capital
Dairy worker expense per hundredweight of milk shipped
Management income
Milk shipped per year per full time employee & manager
Net farm income
Net present value
Management Inventory organizing score variable
Management Inventory planning score variable
Post expansion rolling herd avg. variable
Pre expansion rolling herd avg. variable
Present value of cash ﬂows
Rolling herd average
Return on asset
Return to operator’s capital and management
Return on equity
Risk free rate of return
Services per conception
Scale of expansion variable

Somatic cell count

 

SCORE:

SPECIAL:

STAFF:

Composite management inventory score variable
Degree of specialization variable

Management Inventory staﬁing score variable
Total milk ration

Value marginal product of capital

Value marginal product of labor

Weighted average cost of capital

CHAPTER I
INTRODUCTION
I. BACKGROUND INFORMATION
Dairy farms are becoming fewer and larger. In Michigan and Wisconsin, the total
number of dairy farms decreased from 35,000 in 1993 to 25,700 operations in 1999, a
decrease of 27 percent. During the same period, the number of dairy farms milking 200 or
more cows increased from 500 in 1993 to 950 farms in 1999, an increase of 90 percent
(NASS, 2000).

When done properly, expansion can offer great opportunities for dairy farm
owners and managers to increase proﬁtability, invest in labor saving technologies, and
improve their quality of life. Conversely, a poorly planned and implemented expansion can
threatens farm viability. Dairy owners, managers, and advisors need to understand how
expansion aﬁ‘ects a dairy farm and its managers in order to make informed expansion
decisions.

This research presents the results of a set of case studies that investigate the
expansion achievements and problems of 20 dairy operations prior to, during, and after
expansion. It provides insight into how producers prevented, handled or mishandled
problems.

11. EXPANSION TERMINOLOGY

An “expansion ” was deﬁned as a farm that exhibited a one-time herd size increase

of 20 percent or more between 1988 and 1998 or more that required improvements in or

additional units of labor, machinery or facilities. Prior research indicated that expansion

dairies typically faced a critical transition period of decreased productivity and ﬁnancial
performance lasting for two years after expanding (Stoll, 1974). For the purposes of
before and after expansion comparisons in this thesis, “pm—expansion ” refers to the two
years prior to expanding a dairy. “Post expansion ” refers to the ﬁrst two years after
expanding, including the expansion year.

The general manager of an expansion dairy is referred to as either the “manager"
or the “expansion manager” in this research. An operation whose expansion manager
had no previous expansion experience was deﬁned as an “initial expander. ” An
operation with an experienced expansion manager was deﬁned as a “subsequent

expander. ” An operation that expanded more than once during the post expansion

9

period was classiﬁed as a “rapid expander. ’
III. PROBLEM STATEMENT
Many dairy producers believe that expansion is a means to be more competitive,
earn additional income, and accommodate additional partners. Poorly planned expansions
affect not only the expanding dairy operation and manager, but the local agricultural
economy. Lenders, milk marketing organizations, agribusinesses, construction companies,
private consultants, laborers, and other local businesses all stand to gain (lose) from a
successful (unsuccessful) expansion. This is the “multiplier effect.”
The threat of a failed dairy expansion is very real. Prior management success with
a smaller dairy does not necessarily mean that the producer will be successful at the
eXpanded herd size. As a dairy farm increases its size, so increases the complexity of the

magement process. Managers of smaller dairies, many of whom supply much of the day-

2

to-day labor, tend to focus on herd and crop management activities. Increasing dairy farm

size puts greater focus on new management areas, where the manager may have limited

experience or capability. These areas include, but are not limited to:

l)
2)
3)
4)
5)
6)

7)

determining the ﬁnancial requirements and implications of an expansion;
dealing with potentially decreased productivity during the transition period
hiring, training, evaluating and retaining employees;

sourcing an adequate supply of quality animals, land, and feed inputs;
meeting environmental regulations;

managing public relations; and,

minimizing zoning complications.

Despite the fact that expansion managers face new challenges, little research has

been conducted concerning the problems they face. Therefore, managers may make

decisions with incomplete or inaccurate information. Without quality information, the

chances of a failed expansion increase.

IV. GOAL AND OBJECTIVES

9

The goal of this research was to conduct primary managerial economic research on

recent expansion dairies in order to provide managers with more modern information from

which to base expansion decisions. The research objectives was to determine expansion:

1)
2)
3)

3)

justiﬁcations;
effects on manager activities;
impacts on production, herd health, and reproduction;

consequences for human resource management;

5)
6)
7)

3)

implications for environmental, public relations and zoning issues;
ramiﬁcations for specialization and outsourcing;
impacts on ﬁnancial performance; and,

characteristics for success.

There are many possible justiﬁcations for expanding a dairy (e.g., to increase

income, to decrease costs per cwt. of milk, and to increase labor and management

specialization). Understanding why managers expand is important to properly plan an

expansion and to evaluate expansion success.

An expanded dairy operation can be a complex organization. This complexity has

profound implications for manager activities. For instance, the manager needs to develop

skills in possibly unfamiliar management disciplines (i.e., human resource, risk or ﬁnancial

management). Understanding how previous expansion managers have dealt with

management activity adjustments provides insight on which to base future expansion

decisions.

Overly optimistic and pessimistic assumptions concerning post expansion

production, reproduction, and herd health have negative effects for a dairy expansion. If

too optimistic, the resulting production problem results in an unproﬁtable expansion. If

too pessimistic, the expansion may be improperly sized or forgone completely. Thus, it is

important for managers and advisors to be aware of an expansion’s effect on production,

reproduction, and herd health.

Understanding how expansion affects human resource management issues is

iInportant. Although the cow to employee ratio generally increases with expansion, more

employees are typically hired. Many managers, especially initial expanders, have limited
human resource management skills. This inexperience can lead to poor expansion results
as more and more of the production activities are conducted by hired employees.

An expansion not only affects the manager, it also can have both positive and
negative effects on the community. Numerous articles in popular press and ﬁrming
magazines cite instances where expanding farm operations had problems complying to
environmental standards, appeasing the odor and trafﬁc concerns of the local population,
and expanding under zoning ordinances. Dealing with these problems can be time
consuming for the expansion manager. Understanding how an expansion is affected by
these issues and how managers prevented or handled these problems increases the chances
of a successﬁrl expansion.

In the past, many Upper Midwest dairies milked cows, raised all of their
replacement animals, and grew forages as well as cash crops. Today, many nﬁnagers are
specializing their dairy ﬁrms by outsourcing some activities (e.g., raising replacement
animals and harvesting crops) and internalizing other activities (e.g., milk hauling). Making
managers and advisors aware of the different outsourcing and internalizing options assists
managers in making specialization decisions.

A modern expansion is an expensive venture. It is not uncommon to spend in
excess of $5,000 per cow (including the cost of the cow) to build a new facility and ﬁll it

to capacity. Understanding how expansion aﬁects ﬁnancial performance is, of course, an

important research objective.

As mentioned earlier, expansions are a complex process. To reduce this

complexity, it would be beneﬁcial to managers, advisors and lenders to have a model that
identiﬁes the key expansion characteristics for production and ﬁnancial success. Thus, a
research objective is to develop models that predict expansion success.

The research objectives, the relevant literature, research propositions, and the
methods used to analyze the propositions will be further addressed in later chapters, but

ﬁrst, Chapter II lays out the research methods and procedures for this thesis.

CHAPTER II

METHODS AND PROCEDURES

This chapter concerns the procedures followed to gather the data and information
needed for the 1998 -— 2000 Upper Midwest Dairy Expansion Study. It describes how the
study’s participants were selected, the survey and interview documents, and how the data
were prepared for analysis. The analysis methods for speciﬁc expansion issues are
discussed in their respective chapters.

1. Case Study Analysis

While many managers face similar problems, the relative degree of severity of each
of those problems varies from expansion to expansion. Furthermore, those who face
similar problems may ﬁnd different solutions based upon the resources available to them.
Because of the disparity in problem severity and optimal solutions, this research used case
study analysis to explore the expansion problems and possible solutions. Because the case
study interviewing process is less regirnented than a strict survey analysis, the researcher
has the ability to conduct a more “in depth” discussion into areas of particular interest
with each individual interviewee (Vin, 1994). By doing so, this study reports both the

common and the unique problems and solutions as well as the underlying conditions that

made them prevalent.
II. Participant Determination and Sample Size
To be classiﬁed as an expansion dairy, a dairy had to undergo a one-time herd size

increase of more than 20 percent between 1988 and 1998 that required improvements in

—- or additional units of -—- labor, machinery or facilities. Potential expansion managers
from Michigan and Wisconsin were discovered using Telfarm,l extension, and agribusiness

CODIBCIS.

After determining the potential dairies for this study, the respective dairy
producers were interviewed via telephone to determine their willingness to participate. For
a listing of the possible questions for this telephone interview, please see Figure 1.

Figure 1. Initial Telephone Interview

 

l. I am conducting dairy expansion research for the Department of Agricultural
Economics at Michigan State University. Could I take ﬁve minutes of your time to ask

you some questions?

2. I understand that you have undergone an expansion within the past seven years, is
this correct?

3. When did you expand your dairy operation?

4. What was your pre-expansion herd size? Your post-expansion?

5. Participating in this study requires completing a survey (time needed: approximately
1.5 hours) and participating in an interview (time needed: approximately 2 hours).

Would you be able to devote this much time to this study?

6. Would you be willing to share actual ﬁnancial and production records for this study?

7. Would you be willing to answer ﬁnancial and/or production records in more relative
terms?

 

 

 

Thirty managers were contacted by telephone to determine if they would

participate in this study. Due to manager acceptance and case study research efﬁciency

M

' Telfarrn is the Michigan State University Extension ﬁrm ﬁnancial record keeping
system

reasons, twenty expansion managers were chosen. The participating managers agreed to
COOperate in a mailed survey, a face-to-face interview, and any subsequent follow-up
interviews necessary to complete this research. Once the producer agreed to participate in
this research, his or her dairy was assigned a herd number to insure anonymity.
III. SURVEY AND INTERVIEW METHODS
The producers were told that they may participate using one of two
survey/interview types — “Survey/Interview A ” or “Survey/Interview B. ” Participation in
“Survey/Interview A” involved the producer engaging in a highly detailed survey and
interview. The producer contributed pertinent ﬁnancial and production records for at least
the last two years before expanding and the ﬁrst two years after expanding. If the
producer was unwilling or unable to divulge the speciﬁc numerical answers to the survey
questions, they were informed that they could still participate in the study by participating
in “Survey/Interview B.” Survey/Interview B was developed so that producers could
answer questions in more relative terms. All managers agreed to participate in
Survey/Interview A.

Survey/Interview A was conducted in two stages. In Stage I, the producers were
given a survey to complete (Appendix I). This survey contained closed ended questions
concerning the farm demographics and numeric-oriented production/ﬁnancial questions. If
this stage was not completed in a timely fashion, an appointment was made to conduct the
survey in a face—to—face format.

Section I of the survey gathered general demographic information including herd

size, acreage, cropping enterprises and personnel requirements for the dairy. Sections II,

 

III, and IV concerned production, herd health and reproduction information. This
information was needed to determine if expansion adversely affected or improved
production and herd performance. Section V concerned expansion investment data for
cattle and facilities. This information was used to characterize the relative size of
expansion and to determine expansion proﬁtability information. The survey instnrment
concludes with a brief questionnaire. This questionnaire is used by Michigan State
University Extension personnel to determine the management characteristics of the
principal manager. This information was used to determine which overall management
skill.

Stage II was conducted in a face-to-face format. During the interview phase, more
open-ended questions were asked to discover the potentially more compelling issues each
individual producer faced during his or her expansion. The Interview Guide can be seen in
Appendix H.

Many of the sections in Interview Guides A and B were separate from the issues
covered in the survey. Others complemented the survey questions, allowing for more
enriching information. For instance, Section II, like in the survey, concerns production
issues. In the survey component, however, the manager merely indicated the expansion’s

impact an production. In the interview portion of this study, the producer was allowed to
state which problems were the top three pre- and post-expansion milk production

problems, rank the seriousness of each problem, and state their opinion on their causes.

10

 

The issues covered in the Interview Guides A and B included:

general expansion questions;

production, herd health and reproduction issues;

outsourcing;

expansion investments and ﬁnancing;

facility design and construction;

human resource management;

general management issues;

environmental regulations, neighbor relations, and zoning compliance; and,

expansion success.

While participating in the survey and interview, the producers were allowed to

signify if any questions were too sensitive in nature. If the producer was hesitant to answer

a question, the question was dropped from the individual’s survey.

IV. Data Preparation

The time of the pre-expansion and post expansion periods occurred varied from

producer to producer. Accordingly, the production and price data had to be adjusted in

order to properly compare ﬁrms.

With the exception of milk price, all other data were indexed to reﬂect 1998 levels

by using indices and production data for the 1990-1998 period from Agricultural

Statistics (NASS, 2000). Milk production was standardized by adjusting the ﬁrms’

 

 

 

 

 

 

 

 

 

 

Rolling Herd Average (RHA) by an index where the average US. RHA equals one.2
Expenses and assets were prorated by using the Index for Production (all commodities)
for prices paid by farmers. Asset values were adjusted by using the simple average of the
Index for Farm Machinery and the Index for Building Materials.

Rather than adjusting milk prices to 1998 levels, which had the highest milk price
for the 1990-1998 period, the milk price was indexed to a $13.50/cwt gross price. This
price was chosen as it is a common price to use when budgeting dairy projects. All other
prices were adjusted to 1998 levels. The Prices Received by Farmers Index for Feed
Grains and Hay was used to adjust crop prices. Calf, cull cows and replacement dairy
cattle were priced according to the 1998 Marketing Year Average Price Received by
Farmers of $78.80 per calf, $33.70 per cwt for cull cattle, and $1,120 per replacement
dairy cow.

As enterprise ﬁnancial statements were unavailable, dairy and crop mix sales were
an issue. To remedy this, returns were allocated between dairy and other enterprises by

percentage of Gross Farm Income.

2 The average production for the last 365 days calculated by dividing total yearly
production by the total yearly cow days to determine the average daily production. The
average daily production is then multiplied by 365 days to determine the RHA (DRMS,
1999)

12

CHAPTER III
FARM AND MANAGER CHARACTERISTICS
I. Introduction
In an analysis of dairy farm expansions, it is important to know the characteristics
of the expansions and managers including the size of the farms before and aﬁer expansion,
how specialized the dairy farms were prior to and during expansion, and the skill levels of
the managers. Also, is it possible to classify expansions in order to provide more
meaningful comparisons and to determine which speciﬁc managerial skills were most
important with regard to the expansion?

The purpose of this chapter is to address these issues and draw inference that will
beneﬁt expansion managers and advisors. This will be done by exploring the following
seven research propositions:

1) changes occur in the expansion managers job responsibilities from pre-to

post expansion;

2) the herd management ability of the expansion managers is higher than the

typical manager participating in the Dairy Herd Improvement Association
(DHIA);

3) individual expansion managers exhibit discemable strengths and

weaknesses in general management skill areas;

4) the managers of different expansion classiﬁcation types (initial,

subsequent, and rapid), exhibit discemable strengths and weaknesses in

general management skill areas; and,

13

 

3h"

5) there are speciﬁc management skills (i.e., ﬁnancial management)

that were deemed essential for managing the expansion dairies.
II. Farm Descriptive Statistics

In order to have greater insight into how expansion impacts ﬁrm performance, it is
important to have a basic understanding of the characteristics of the participating
operations. Table 1 shows pre- and post expansion herd size, rolling herd average,
manager and employee numbers, as well as farm acreage characteristics.

Pre-expansion, the average herd size was 296 milking cows. Initial herd size
ranged from 60 cows to 1,071 cows with 6 herds having less than 100 cows and 3 herds
having more than 500 cows. Five herds were housed in tie stall or stanchion facilities.

With the exception of one farm without cropping activities, all pre-expansion dairies had
forage enterprises and ﬁve also had cash grain enterprises. Two farms were diversiﬁed into
signiﬁcant operations outside of milking cows and cropping activities. One farm was a
division of a ﬁmily corporation that also had milking equipment and ﬁrm implement
dealerships as well as a land development division. The other ﬁrm with outside operations
was diversiﬁed with dairy, custom heifer raising, cash forage production, cash grain
production, and cattle brokering enterprises.

Average tillable acreage was 978 acres for a cow per acre ratio of 0.30. Rolling
herd average (RHA) for the two years preceding expansion ranged from 15,248 to 28,794
pounds of milk per year for an average of 21,900 pounds. The average milk shipped per
year was 5,317,295 pounds. The ﬁrms were staffed by an average of 2.5 managers, and

the number of ﬁrm laborers employed (expressed in the number of full and part-time

14

laborers, not full time equivalents) was 7. Of these employees, 5 were dedicated dairy

employees and the remaining were crop labor specialists.

 

 

 

 

 

 

 

 

 

 

Table 1. Farm Descriptive Statistics (18 Farms)
Pre—expansion Post Expansion Change (%)

Sample Size 18 18 NA
Herd Size (Cows) 296 569 92
Crop Acreage 978 1,069 9
Cows/Acre 0.30 0.53 77
Rolling Herd 21,900 23,064 5
Average
(lbs/cow/year)
Estimated Milk 5,317,295 10,999,283 107
Shipped! Year (lbs)
Number of Managers 2.50 3.40 36
Total Dairy 5.10 8.50 67
Employees
Total Employees 7.00 10.70 ' 53

 

 

 

 

 

Post expansion average herd size doubled to 569 cows. The smallest post

expansion herd size was 120 cows and the largest was 1,350 cows. All tie stall technology

facilities were abandoned in favor of free stall technology facilities. Despite the large

increase in herd size, tillable crop acreage increased by 9 percent. The cows per acre ratio

increased to 0.56. RHA for the ﬁrst two years following expansion ranged from 18,500 to

27,841 pounds and on the average increased by 5 percent to 23,064 pounds. The resulting

irnpact of the increase in herd size and increased production per cow caused an increase in

milk shipped per year of 107 percent to an average of 10,999,283 pounds. The expanded

15

 

dairies required an average of 3.4 managers (an increase of 36 percent) and 10.7
employees (an increase of 53 percent), of which 8.5 were dedicated dairy employees.
III. The Effect of Expansion on the Manager’s Job Description

Expansion can bring about changes in the manager’s job responsibilities. In many
cases, the manager during the pre-expansion phase conducted labor activities as well as
management activities. Post expansion, managers typically ﬁnd that their labor activities
decrease and their management activities increase signiﬁcantly.

The managers were asked to describe the percentage of time dedicated to
management activities for both the pre- and post expansion periods. Prior to expanding,
the (average amount of time dedicated to management activities was 40 percent. If the 100
percent answers of three managers are removed, however, the average percentage of time
dedicated to management drops to 27.4 percent. Post expansion, the percentage of time
dedicated to management activities increased to 64.2 percent. If the same three managers
who dedicated 100 percent of their time to management during the pre-expansion period
are removed, the average percentage of dedicated management time was 57 percent.
Many managers stated that the amount of time spent on the dairy didn’t change ﬁom pre-
to post expansion. Expansion did allow them to delegate labor and some control activities
to employees, which enabled the managers to increase dedicated management time.

Another change that occurred among these managers from pre- to post expansion,
one that is hard to quantify, is the nature of their job responsibilities. During the pre-
expansion phase, a typical answer was “J ack-of-all-trades” or “laborer and manager.”

Only 6 out of 20 managers gave job descriptions with speciﬁc management activities (such

16

as human resource manager, ﬁnancial manager, public relations) mentioned. Post
expansion, 15 of the managers gave manager job descriptions with speciﬁc activities
mentioned.

Thus, the management job responsibilities, from both a dedicated management
time perspective and a speciﬁcity perspective, changed ﬁom pre- to post expansion.
Assuming these results hold for the general population, managers who are contemplating
expansion but think “I spend 80 hours a week on a 100 cow dairy, how can I possibly
nﬁnage a 500 cow dairy?” should feel at ease. The delegation of labor and lesser
management activities enables expansion managers to substantially alter their job
description without necessarilyincreasing the amount of work time.

IV. Management Skills: Previous Expansion Experience

“Practice makes perfect ” goes the old adage. Thus, managers who have prior
expansion experience should have less problems coping with the challenges of expansion.
The expansion experience of the mergers interviewed varied. To provide better insight
concerning how expansion affected ﬁrm performance and whether an expansion was
successﬁrl, it is important to quantify the expansion experience of the participants and to
group expansions according to the manager experience level.

Using the expansion deﬁnition previously described in Chapters I and II, ten
expansion managers had no expansion experience (Table 2). One of these inexperienced
expansion managers had no previous dairy management experience; however, he was

familiar with dairy production due to his previous employment as a dairy nutrition

17

consultant. Six managers experienced expansion once before, and 4 managers had

expanded their operations at least twice.

 

 

 

 

Table 2. Previous Expansion Experience ( 20 Farms)
Expansion Experience Number of Managers
No Previous Expansions 10
One Previous Expansion 6
Two Previous Expansions or more I 4

 

 

 

 

IV-a. Expansion Classification

Three types of expansion classiﬁcations were deﬁned in Chapter I based upon the
expansion manager’s experience: initial expanders, subsequent expanders, and rapid
expanders. The expansion types are shown in Table 3. Despite having 10 inexperienced
expansion managers, eight operations were classiﬁed as “initial expanders. ” The
operations of the two remaining inexperienced expansion managers were classiﬁed as
“rapid expander” units. The remaining ten operations were classiﬁed as “subsequent

expander ” operations.

 

 

 

 

Table 3. Expansion Classification (20 Farms)
Expansion Classiﬁcation Number of Operations
Initial Expander 8
Subsequent Expander 10
Rapid Expander - 2

 

 

 

 

18

V. Management Skills: Herd Management Ability

While expansion experience provides one measurement of management ability, it is
not an all encompassing measure of dairy management ability. By investigating pre-
expansion RHA as a proxy, the expansion manager’s initial herd management ability is
examined.

A common suggestion given to would be expanders is “to get good before getting
big. ” Assuming that this is practiced, managers who expand their operations should have
higher'milk production than their peers. Typically, managers who participate in DHIA
exhibit higher RHA than managers who do not. To explore if expansion managers might
be considered “the best of the best” with regard to herd management ability, the
individual farm’s pre-expansion average unadjuSted RHA was compared to the average
US. Annual DHIA RHA (Appendix 111) information to determine if the expansion
managers exhibited higher herd management ability.

Mean pre-expansion RHA was 20,706 pounds/cow/year with a variance of 3,654
pounds. There was sufﬁcient evidence at a 95 percent signiﬁcance level to conclude that
the participants’ pre-expansion RHAs were higher than the average US DHIA RHA.

Thus, the expansion managers exhibited higher herd management ability ( as measured by
RHA) than their average DHIA counterpart. In all, ten herds exceeded the critical increase
of 1,474 lbs of milk needed to be signiﬁcantly higher than mean US DHIA RHA.

This does not necessarily imply that managers should have high production levels

prior to expansion in order to have high production following expansion. Two herds were

19

 

 

ill

13L”

signiﬁcantly below mean US DHIA RHA, but, through expansion were able to correct the
production problems that plagued their pre-expansion operation.

Prior to expansion, one low producing herd operated four smaller dairies and had
problems with manager focus, labor specialization, labor turnover, and forage quality. By
combining his four smaller dairies into one operation and then expanding, the expansion
manager corrected these problems and achieved an increase in RHA of 4,000 pounds for
the post expansion period.

The manager of the other low producing dairy stated that his pre-expansion
production problems were related to bull breeding, the inability to feed a total mixed
ration (ﬁcility issue), and cow comfort (facility issue). Expansion did allow the producer
to start using artiﬁcial insemination (through hiring specialized labor), but, because it takes
two years before the artiﬁcially sired offspring could have entered his herd, this expansion
induced improvement could not have contributed to his post expansion RHA increase of
5,000 pounds. Expansion did, however, allow the producer to feed a total mix ration and
to improve cow comfort, which did help to improve production.

While “getting good before getting big” is generally good advice to insure that
herd management skills are suﬁciently high for expansion, there are instances when
expansion can help alleviate production problems. If expansion can remedy the problems
causing poor pre-expansion production — such as management focus, labor specialization
and facility issues - then expansion may be advisable even with low pre-expansion
production. This is especially true if the manager has other management skills conducive

to large dairy management.

20

 

in;

VI. Management Skills: General Management Skills

Good herd management skills tend to be scientiﬁc or technical in nature and may
not correlate well with the skills needed to be an effective business manager. Cornell
University Extension developed a Management Inventory test to measure a manager’s
relative competence in the management areas of planning, organizing, stafﬁng, directing,
and controlling (Harsh, et al, 1995). The Management Inventory test works by having the
manager respond to a series of statements concerning management scenarios. The
managers ranked the statement between 1 and 5. A “1 ” indicated that the manager
strongly disagrees with the statement. A “5” indicated that the manager strongly agrees
with the statement. Nineteen managers participated in this exercise. The results for
individual managers are summarized in Appendix 4 and by expansion classiﬁcation group
in Table 4.

The high composite Management Inventory score was a 25.2, the low a 16.6, and
the mean a 21.5 with a sample standard deviation of 2.7. Initial expanders, those without
previous expansion experience, earned a composite score of 21.9, subsequent expanders a
close 21.7, and rapid expanders a 19.5. It should be noted, however, that there were only
two rapid expanders. One of these managers earned a composite score of 22.4 while the
other earned a score of 16.6.

It appears that the individual managers seemed most adept at “controlling” skills
and least adept at “organizing ” skills. This might imply that the managers may need
assistance from advisors in organizing dairy activities following expansion, but, once

organized, need little assistance in controlling the implementation of those activities.

21

Nevertheless, there was insufﬁcient evidence at the 95 percent signiﬁcance level to
conclude that the individual manager management inventory scores varies by skill type.‘
The research proposition that expansion rmnagers show discemable strengths and
weaknesses in management skill areas was not supported. The expansion managers were

consistent in their scores across the planning, organizing, stafﬁng, directing, and

 

 

 

 

 

 

 

 

controlling skills.
Table 4. Management Inventory Scores by Expansion Chssiﬁcation
( 19 Farms)
Initial Subsequent Rapid Mean Std. Dev.

Planning 21.8 21.6 19.0 20.8 1.5
Organizing 20.6 21.0 19.0 20.2 1.1
Stafﬁng 21.5 23.2 20.5 21.7 1.4
Directing 21.8 21.1 18.5 20.5 1.7
Controlling 23 .8 21.6 20.5 21.9 1.7
Composite 21.9 21.7 19.5 21.02 1.3
Std. Dev. 1.2 0.9 0.9 0.7 .

 

 

 

 

 

 

 

 

There were similar results when analyzing whether managers of differing expansion
classiﬁcation types exhibited discemable strengths and weaknesses among management
skills. “Initial expanders ” were most competent in controlling skills and least competent
in organizing skills. “Subsequent expanders ” scored highest in stafﬁng and lowest in

organizing. “Rapid expanders ” were proﬁcient in stafﬁng and controlling but not in

' Fm,” --= 2.49 > PM,” = 0.98

22

directing. Statistically, however, there was insufﬁcient evidence to conclude that initial,
subsequent, and rapid expander management inventory scores varied by skill type.2

The research proposition, that managers of different expansion classiﬁcation types show
discemable general management skill strengths and weaknesses was not supported.

What do the general management skill results imply for managers and advisors?
Because of the lack of a statistical difference in scores between general skill type
(planning, organizing, stalling, directing, and controlling), there seems to be little
statistical evidence for managers to take, or for advisors to create, programs designed to
improve any one skill type. As there was a difference in composite Management Inventory
Score between managers, the Management Inventory score may provide good predictive
ability of expansion success if composite Management Inventory score proves correlated
to expansion success. This topic is examined in a later chapter.

VII. Management Skills: Essential Management Skills

The previous two sections dealt with the managers’ general management skills
(planning, organizing, stafﬁng, directing, and controlling) as determined by a self
evaluation method. This section is concerned with the speciﬁc management skills (i.e.,
ﬁnancial management, operations, risk, etc.) required to be an effective dairy manager as
determined by the expansion managers’ experiences.

In an effort to determine the most essential rmnagement skills, the managers were
asked to choose the top three management skills needed to proﬁtably run a large dairy

ﬁ'om a list of eleven alternatives (Table 5). The results were then arranged by number of

’ Fm“, = 3.48 > me = 0.81

23

ﬁrst rank, second rank, third rank, total responses, and a dominant (weighted) score. For
the dominant score, a “ﬁrst rank” response earned 3 points, a “second rank” response
earned 2 points, and a “third rank” response earned 1 point.

Five speciﬁc management skills scored consistently higher regardless of the
ranking method: human resource, ﬁnancial, operations, herd and strategic management.3
Human resource management skills was the most important managerial skill as it received
the most overall votes (10 votes) and was the highest scoring category (23 points) due to
its 6 ﬁrst rank votes. Financial, herd, operations, and strategic management skills each
earned 7 overall votes to tie for second essential management skill. When the dominant
scores were analyzed, however, both ﬁnancial and operations management were tied for
the second highest scoring category with 15 points each. Herd management was the fourth
highest scoring category with 14 points, and strategic management came in ﬁfth with 11
points.

Despite numerous popular press and trade articles citing environmental
management as an important topic, this management area received only 1 ﬁrst rank
response. Many managers stated that prior to expansion they thought environmental
management would have been more important. Nevertheless, the majority of managers felt
that it was relatively simple to adhere to or surpass state regulations and recommendations
concerning environmental issues. With increasing environmental pressure, it would be

interesting to see how this management area changes in priority over time.

3 Strategic management concerns establishing and evaluating a ﬁrm’s vision, mission, 10118
term goals, and operating parameters. Operations management is the management of the
productive processes to achieve the ﬁrm’s goals.

24

 

ill

Table 5. The Most Essential Expansion Dairy Management Skills ( 14 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

Specific First Second Third Total Dominant

Management Rank Rank Skills Rank Skills Responses Score‘
Skill Skills

Human 6 1 3 10 23
Resource
Operations 3 2 2 7 15
Financial 2 4 1 7 15
Herd 2 3 2 7 14
Strategic 0 4 3 7 11
Environmental l 0 0 1 3
Risk 2 O 0 2 2 2
Commodity 0 0 1 l 1
Marketing
Estate 0 0 0 0 0
Facility and 0 0 0 0 0
Equipment

 

 

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1
2 Includes all forms of risk management other than commodity marketing

The implications of these results are that expansion managers need human
resource, ﬁnancial, operations, herd and strategic management skills to be effective
expansion dairy managers. Managers should determine whether or not they need
assistance in these skill areas prior to expanding. If he or she is deﬁcient in any of the
areas, they could either hire employees who have those skills or seek appropriate
educational programs. Expansion advisors may want to consider conducting workshops to
educate managers in these essential management areas. Advisors should remember,

however, that these managers tested high in herd management ability as measured by their
25

 

pre-expansion RHA. If good herd management ability is apparent, it may behoove
advisors to concentrate more heavily on evaluating human resource, ﬁnancial, operations,
and strategic management skills of the expansion manager.

VIII. Conclusions

On average, the dairy farms increased herd size by 92 percent to 569 cows. This
increase was accompanied by a 67 percent increase in dairy speciﬁc employees to 8.5, a
slight decrease in crop employees, and an increase in cows/acre ratio of 77 percent to
0.53.

Half of the expansion dairy managers had experienced previous expansions. This
led to 8 expansions being classiﬁed as initial expanders, 10 as subsequent expanders, and
two rapid expanders. The herd management ability of the managers was deemed high as
the pre-expansion RHA of the farms were higher than their US. DHIA counterparts.

There was a statistical difference between individual managers and expansion type
in overall general management skill. There was little variation in the ﬁve general
management skill areas of planning, organizing, stafﬁng, directing, and controlling across
managers.

The ﬁve highly important managerial skills were human resource management,
ﬁnancial management, operations management, herd management and strategic
management. Managers should become familiar with these managerial topics or hire

employees or advisors with skills in these areas prior to expanding.

26

 

v}

it!

iii

5‘“
.4

Chapter IV
Why Do Managers Choose Dairy Expansion?
1. Introduction

There are many reasons to expand a dairy farm, including both proﬁt and non-
proﬁt reasons (i.e., to improve the quality of a manager’s life). Nott noted that a common
expansion reason was to solve a surplus springing heifer problem (1968). In a study
conducted by Brake, et al. — producers expanded in order to accommodate additional
partners or to utilize excess land or labor (1968). In 1974, Stoll found that managers
contemplated future expansions to accommodate additional labor or family members, to
reduce excess facility capacity, and to adopt new technologies (1974).

In 1988, Chavas and Magand used a time-varying Markov process to look at US.
dairy farms in an attempt to explain their growth and distribution. The authors found that
while relatively high milk prices induced entry into all size categories of dairy farms, it
tended to discourage expansion. Conversely, low relative milk prices seemed to encourage
expansion. While this may seem like reverse economic logic, to the authors this ﬁnding
indirectly indicated that proﬁts on dairies may be used more for ﬁmily living expenses than
for reinvestment in dairying.

In a 1992 article, Erven compiled a paper on the advantages and disadvantages of
expansion. The advantages of expansion included potential economies of size, net income
advantages of bigger volume, bargaining power, accommodating new partners, and
intangibles such as gaining prestige. Disadvantages included potential inconsistencies in

ﬁrm lifestyle goal, diseconomies of size, increased risk, and stress.

27

In a presentation at the Expansion Strategies for Dairy Farms National Conference

in 1994, Hering cited seven typical reasons that producers give for expansion. They

included the following:

1)
2)
3)
4)
5)
6)

7)

outlook of the ﬁrture requires expansion (efﬁciency);

personal goals, such as new members being brought into the farm;
personal satisﬁction goals;

ﬁxed costs are not being covered properly;

milk price decline';

to quickly increase cash ﬂow; and,

industry trend.

Of these, Hering stated that long term planning probably occurred if an expansion

justiﬁcation was based upon one or more of the ﬁrst three reasons. Thus, the justiﬁcation

for expansion may indeed be valid. The latter four reasons indicate to lenders that there

are some problems with the operation and that the expansion my be ill advised. These

conclusions were based only upon personal observations.

Understanding why managers expand their dairy operations is important for at

least three reasons. First, understanding expansion reasons enables managers, advisors and

researchers to more accurately determine an expansion’s overall success. For example,

assume a manager decided to expand to improve proﬁtability and to increase the time

Spent With his or her family. Upon expanding, however, the operation became more

—¥

' It is assumed for this research that Hering meant cash ﬂow problems and not that ﬁrrners
expand because of low prices.

28

proﬁtable but the manager did not enjoy increased family time. If an advisor, researcher or
manager only considered the increased proﬁtability as a measure of success, the success of
the operation might be overstated.

Secondly, some lenders use the primary expansion justiﬁcation as one of many
methods to evaluate the advisability of a potential expansion (Hering, 1994). Managers
with more proﬁt oriented reasons are viewed as being less risky than those with non-proﬁt
reasons (i.e., to quickly increase cash ﬂow). Because expansion reasons are used to
evaluate potential expansions, it is important to know why many managers decide to
expand.

A third reason is to inform the public. Many people are concerned that farm
expansion is correlated with environmental damage and the demise of family farms. Full
page advertorials in popular periodicals and on the internet demonstrate these concerns
(Turning Point Project, 1999). They question whether or not society should allow
expansion to occur and why a manager would want to expand. It is not uncommon for
farm managers to defend their expansion decision in public and argue before a hearing
panel of the beneﬁts of expansion to the community. It is important for managers, advisors
and researchers to have an understanding of expansion reasons in order to better inform
the public of dairy expansion beneﬁts.

This chapter explores why managers expand their dairy operations. Speciﬁcally,
this chapter will test the following research propositions:

1) the managers’ primary, most common and dominant expansion reason is

29

proﬁtz; and,
2) the managers of initial expander operations will cite more non-pro ﬁt
reasons (i.e., increased family time) than subsequent expanders.
11. Why Managers Expand Dairy Operations
The managers participating in this study were asked to rank their top three reasons
for expanding. The research proposition that the most common “ﬁrst rank”reason for
expanding would be proﬁt oriented was not supported. The most common “ﬁrst rank”
reason was “improved quality of life” with 6 “ﬁrst rank” responses (Table 6). The
producers deﬁned quality of life improvements as the ability to spend more time with their
families, to take vacations, and to do less physical labor. It is important to note, however,
that the ability to enjoy these improvements occurs only if an expansion is ﬁnancially
successﬁil. Quality of life was followed closely by “improved proﬁtability” with 5
. responses. Two managers indicated that they expanded when their present facilities
needed replacing. Two other managers responded that they expanded to serve as a
managerial challenge (having met their management objectives at a smaller herd size, they
decided to challenge themselves by expanding). Other ﬁrst ranked expansion reasons
included “to dairy on a full-time basis”, “to accommodate new partners”, “to increase cash

ﬂow”, and “natural growth.”3

2 The primary reason is the manager’s principal or “ﬁrst rank” reason for expansion. The
most common expansion reason is one that is mentioned the most regardless of rank.
The most dominant reason refers to the reason that earns the highest score when
allocating weighted scores for ﬁrst-, second- and third rank reasons.

3 “Natural growth” refers to expanding by maintaining a low mature cow culling rate and
incorporating the majority of all heifers into the herd

30

 

fl

is:

The most common overall reason for expansion - considering all ﬁrst, second or
third rank reasons - was “improved proﬁtability.” Managers indicated improved
proﬁtability as an expansion reason 16 times in the survey. Thus, the proposition that the
most common expansion reason is proﬁt oriented was supported. “Improved quality of
life” was mentioned as a reason 8 times. “To replace a worn facility” and “human resource
issues” tied for the third most common expansion reason with each earning 5 responses.

To quantify the rankings, points were assigned relative to a reason receiving a ﬁrst,
second or third ranking to determine the dominant reason. A “ﬁrst rank” reason earned 3
points. A “second rank” reason earned 2 points, and a “third rank” reason earned 1 point.
The results of the dominance scoring concurred with the “most common reason” results
except that the “human resource issues” reason fell to fourth place. Thus, there is strong
evidence to support the premise that dairy managers expanded their operations to improve
proﬁtability. Other important reasons included improved quality of life, human resource
issues, replacing worn facilities, and managerial challenge.

There are two implications of these results. First, managers or advisors can
concentrate primarily on proﬁt measurements when determining expansion success. The
second implication is that managers and advisors should also evaluate other factors that
are important in the success of an expansion including quality of life, human resource, and
facility replacement issues when educating the public on why managers expand dairy

operations.

31

Table 6. Expansion Reasons Indicated By Managers ( l9 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Reason First Second Third Total Dominant
Rank Rank Rank Responses Score‘

Reasons Reasons Reasons

Improved 5 6 5 16 33

Proﬁtability

Improved Quality 6 1 1 8 21

of Life

To Replace a Worn 2 2 l 5 11

Facility

Human Resource 0 4 1 5 9

Issues

Managerial 2 l 0 3 7

Challenge

To Accommodate l 0 O l 3

New Partners

To Dairy Full Time 1 O 0 l 3

To Increase Cash 1 O 0 l 3

Flow

Natural Growth 1 0 O l 3

To Experiment with O 1 0 1 2

Technology

Health Concerns 0 0 1 1 1

Strategic Goal 0 0 1 l l

Compatibility

 

 

 

 

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1
III. Expansion Reasons by Expansion Classification

It was stated above that understanding the justiﬁcation of expansion assists in
determining the strategic success of an expansion. Because managers differ in experience

and pre-expansion endowments, managers in diﬁerent expansion classiﬁcations may have

32

different expansion justiﬁcations and, thus, different measures of expansion success. This
section examines expansion reasons by classiﬁcation.
III-a. Expansion Reasons by Initial Expander Managers

Of the “initial expander” managers, 3 indicated that their ﬁrst rank expansion
justiﬁcation was “improved quality of life” (Table 7). Once again, the manager’s quality of
life improvement is typically dependent upon the expansion’s ﬁnancial success. Two stated
that they primarily expanded to improve proﬁtability. Expansion due to worn out
facilities, to accommodate additional partners, or natural growth were each mentioned 1
time as a primary expansion reason.

Disregarding reason rank, the most common reason among initial expanders was
improved proﬁtability with 7 responses. Improved quality of life was mentioned 5 times,
and replacing a worn facility earned 4 responses as the third most common reason. The
results of the dominance score concurred with the most common reason results.

It can be inferred from these results that initial expanders expand in order to
improve proﬁtability with improved quality of life as another important reason for
expansion. This implies that managers and advisors should weight improved proﬁtability
and improved quality of life factors quite high when planning or judging the success of an

initial expansion.

33

Table 7. Expansion Reasons from Initial Expander Managers ( 8 Farms)

 

 

 

 

 

 

 

 

 

 

Reason First Second Third Total Dominant
Rank Rank Rank Responses Scorel

Reasons Reasons Reasons

Improved 2 2 3 7 13

Proﬁtability

Improved Quality of 3 l 1 5 12

Life

To Replace a Worn l 2 l 4 8

Facility

Human Resource 0 2 O 2 4

To Accommodate 1 O 0 1 3

New Partners

Natural Growth 1 O 0 l 3

Health Concerns 0 0 1 1 1

Strategic Goal 0 0 l 1 l

Compatibility

 

 

 

 

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank == 1
III-b. Expansion Reasons by Subsequent Expander Managers

Four subsequent expander managers indicated that their ﬁrst rank expansion
reason was “improved proﬁtability” (Table 8). “Improved quality of life” was the primary
expansion reason for two managers. “To replace a worn facility,” “to increase cash ﬂow”,
and “to accommodate new partners” were each mentioned once as a ﬁrst rank expansion
reason.

The most common expansion reason, considering all reason ranks, for subsequent
expanders was “increased proﬁtability” with 17 responses. There was a tie for the second

most common expansion justiﬁcation as “improved quality of life,” “to replace a worn

34

 

nil-In];.rthllrsl—lrlu..~i~ADh~hi..C\xthi m.

facility” and “human resource advantages” were each mentioned twice. Once again, the

results for reason dominance concurred with the most common reason results.

When comparing between “initial” and “subsequent” expanders, subsequent

expansion managers placed less importance on quality of life improvements as a ﬁrst rank

expansion goal. Managers, researchers and advisors can concentrate primarily on proﬁt

issues when planning or determining the success of a subsequent expansion

 

 

 

 

 

 

 

 

 

Table 8. Expansion Reasons from Subsequent Expander Managers (9 Farms)
Reason First Second Third Total Dominant
Rank Rank Rank ‘ Responses Scorel
Reasons Reasons Reasons

Inmroved 4 2 l 7 l7
Proﬁtability

Improved Quality 2 O 0 2 6
of Life

To Replace a Worn l 1 0 2 5
Facility ‘

Human Resource 0 2 0 2 4
Advantages

To Increase Cash Flow I 0 0 1 3
Accommodate New 1 O 0 1 3
Partners

Managerid 0 1 0 1 2
Challenge

 

 

 

 

 

 

 

 

III - c. Expansion Reasons from Rapid Expanders

‘ Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1

There were only two rapid expander operations in the survey. One manager stated

that the ﬁrst rank reason be expanded his Operation was to dairy on a full time basis.

Previously, this manager farmed on a part time basis and was a full time consulting

3S

 

V1

C0

nutritionist for a feed manufacturing company. The second manager’s ﬁrst rank reason
was to meet new managerial challenges. Having had a successful cattle brokering and
registered dairy operations, this manager felt that expanding his dairy operation would
satisfy that desire. Both managers listed “improved proﬁtability’ ’as their second rank
reason and “improved quality of life” as their third rank reason. With only two rapid
expander operations in this study, it is difﬁcult to draw any inferences as to why rapid
expander managers expand their Operations.

IV. Conclusions

The dairy managers generally expanded their operations to increase proﬁt. Some
of the other common reasons included improving the manager’s quality of life, replacing a
worn facility, human resource issues, and to serve as a managerial challenge. When
comparing initial expanders and subsequent expanders, initial expanders more commonly
rank “improved quality of life” as a ﬁrst rank reason.

The implications of these results are that managers, researchers, and advisors can
concentrate primarily on proﬁt when planning an expansion or judging the success of one.
If the expansion is an initial expansion, however, the advisor should be aware the quath
of life improvement is an important reason for a manager conducting an initial expansion.
Thus, managers and advisors should also consider quality of life improvement when
planning and judging the success of an initial expander operation.

Using the primary (ﬁrst rank) expansion reason as a method for determining the
feasrbility of an expansion may be misleading. Even in cases when ﬁrst rank expansions

were not proﬁt oriented (i.e., improve quality of life), the most common and dominant

36

reason were proﬁt oriented.
Finally, when educating the public on the reasons dairy managers expand their
operations, managers and advisors can inform the public that managers expand for proﬁt,

quaﬁty of life, human resource, worn facility replacement, and managerial challenge issues.

37

Chapter V

The Effect of Dairy Farm Expansion on Milk Production, Reproduction, Herd
Health and Crop Production

I. Introduction

As a dairy expands, the manager faces many challenges. The managers in earlier
studies were challenged by poor cattle adjustment, inability to feed according to
production, and increased workload. These challenges led to poorer production, herd
health, and reproduction performance (Stoll, 1974).

Stoll found that Michigan producers saw an 8.3 percent (914 pounds) decrease in
milk per cow per year during the post expansion transition period. Milk production levels
did not rise above pre-expansion levels until the fourth year following expansion. Earlier
work by Corley, et a]. (1964), McKinney (1965), Wright (1971), LaDue and Bratton
(1966) and Brown and White (1973) also support the premise that milk production
declines as herds expand. Other post expansion performance factors reported by Stoll
(1974) include:

1) the time required to harvest crops increased 5.4 percent;

2) culling increased 2.4 percent;

3) veterinary usage increased 13.1 percent;

4) calf losses increased 8 percent;

5) reproduction problems increased 119 percent; and,

6) forage quality declined.

These problems were attributed to poor cattle adjustment, the inability to feed according

38

to production, increased workload, and poor quality feed. Lower culling rates is often
mentioned as a reason for the production decline following expansion. The Stoll study
contradicts this assumption. These results often caused advisors and managers when
plarming expansions to formulate budgets using poorer production, herd health and
reproduction performance levels during the post expansion transition period.

The expansions in the earlier studies were much smaller than the expansions
examined in this study. Thus, there was less opportunity for labor and management
specialization in these earlier expansions. Furthermore, the early expansions were unable
to capitalize on modern feeding, genetic, facility, and management information
technologies of today.

A production factor correlated with herd size, but not necessarily expansion, is
milk production. In dairy farm business analyses conducted in Michigan by Nott (1996)
and in Wisconsin by Brannstrom (2000), milk per cow per year increases with herd size.
St-Pierre also showed this correlation (1998). This does not mean, of course, that a
manager can increase herd size an expect an increase in milk. Weersink and Tauer looked
at the causality between dairy farm size and productivity (1991 ). Using multivariate
Granger-causality tests, the authors found that the causality runs from dairy size to
technology adoption, which in turn increases productivity.

Recent expansions may be in a better position to utilize technology to reduce cattle

and feeding adjustment problems and counteract the workload challenge through
management and labor specialization Other issues — such as procuring large groups of

cattle while maintaining biosecurity, establishing operating procedures for delegated tasks,

39

learning human resource management, and adjusting to new facility and feed technologies
— can challenge modern expansion managers. How well and how quickly managers adjust
to these as well as other challenges will affect the expansion dairy’s milk production, herd
health and reproduction, and crop perforrmnce.

The purpose of this chapter is to evaluate the impact that the expansion had on
production, herd health and reproduction. Knowing these impacts will allow for more
precise economic analysis of the proposed expansion. Furthermore, having an
understanding of the production, herd health, and reproduction problems helps future
expanders in safeguarding against those problems.

[1. Research Propositions

In order to determine the effect that expansion has on production, herd health and
reproduction, the following research propositions are addressed:

1) pre-expansion milk, butterfat, and protein production exceeds post

expansion production;

2) reproduction and animal health problems increase after expanding;

3) the most problematic production, reproduction and animal health problems

are different than pre-expansion problems in these areas;

4) those managers who have strict biosecurity protocols have less bio-security

incidence than herds without such protocols; and,
S) crop quality and yield decrease after expansion.
Understanding how expansion affects ﬂuid milk, butterfat and milk protein

production is important as they are the primary sources of revenue. Given the larger scale

40

of recent expansions this production decline may still hold today for a couple of reasons.
First, a greater proportion of the growth is achieved by purchased cattle. Thus, managers
may have less control of the production potential of the herd. Second, the scale of recent
expansions tends to force managers to transform ﬁom a herd management mentality
(where the manager concentrates on managing the performance of the cattle) to a dairy
farm systems management mentality (where the manager concentrates on managing the
peeple and procedures to optimize the performance of the farm). If a manager is slow to
make this management transition, production may be adversely affected.

Conversely, genetics may be more homogenous and feeding and housing
technology more advanced than in the early studies. Expansion may also allow greater
specialization in labor and management. Thus, post expansion milk production may
increase.

It is also important to understand how the problems confronted in pre-expansion
change after expansion. By understanding how problem priorities change, future
expansion rmnagers may be able to develop plans to diminish the effects of these
problems.

Because modern expansions typically requires the co-mingling of cattle from
numerous sources, bio-security (minimizing the threat of an infectious disease) is an

inrportant dairy expansion issue. These diseases are costly in terms of decreased
production, treatment and replacement costs. One method of mrnrmrzrng the incidence of

infectious diseases is to develop bio-security protocols that establish standards for testing,

41

immunizing, and quarantining purchased cattle. This chapter examines whether such bio-
security protocols reduce the incidence of infectious diseases.
III. Effects on Production

To determine expansion effects on production -- Rolling Herd Average (RHA),
butterfat percentage, and milk protein percentage data were collected for the last two
years preceding the expansion and the two years following expansion. All RHA data was
adjusted to reﬂect 1998 production levels. Table 9 shows how the indices were calculated
and how hypothetical RHA were indexed to reﬂect 1998 equivalent production levels.

Table 9. RHA Indexes and Sample RHA Adjustment

 

Year U.S. DHIA Average RHA Index

 

 

 

 

 

 

 

 

 

(lbs)
1998 20,209 1 .000
1997 19,815 0.980
1996 19,192 0.950
1995 19,271 0.953
1994 19,129 J 0.947
1993 18,719 I 0.926

 

Seventeen farms had sufﬁcient production data to compare pre-expansion and post
expansion RHA. The results are summarized in Table 10. Pre-expansion RHA ranged
from 15,248 to 28,794 pounds of milk with a mean of 22,075 pounds. Although the null
research proposition states that pre-expansion RHA exceeds post expansion levels, mean
post expansion RHA exceedai pre-expansion levels. The average post expansion RHA

was 23,228 pounds and ranged from 18,388 to 28,056 pounds. The data was analyzed

42

 

using a two-sided t-test (pooled variance method) to determine if the average pre-
expansion RHA was equal to the average post expansion RHA. The pre-expansion RHA
were equal at the 95 percent level.l This lack of a statistical difference between pre- and
post expansion RHA is in contrast to the earlier work showing a post expansion RHA that

was signiﬁcantly less than pre—expansion levels.

 

 

 

 

 

 

 

 

 

 

Table 10. Eﬁ‘ects on Average Pre- and Post Expansion Production ( l7 Farms)
Rolling Herd Butterfat Yield Milk Protein Yield
Average (lbs) (lbs) (lbs)
Before After Before After Before After
Sample Mean 22,075 23,228 769 810 675 716
Standard Deviation 3,746 3,140 157 123 l 17 100
High 28,794 28,056 986 1,019 849 867
Low 15,247 18,388 542 666 482 574
Sample Size 17 15 14

 

 

 

 

 

 

Four farms increased RHA by more than 2,000 pounds. On three of these farms,
the managers attributed the RHA increase to moving into more technically modern
facilities and having more specialized management and labor. The fourth manager of this
group credited his RHA increase to moving out of an overcrowded facility and to
increasedmanagement and labor specialization.

Three herds experienced RHA decreases. Decreases in RHA ranged ﬁom 50

pounds to 500 pounds per cow. One manager attributed the RHA decrease to the inability

' tmn= 0.973 < t M,,,,,,,,,= 2.0378

43

of his cattle to adjust to the new ﬁee stall facility. This manager previously operated a
registered dairy in a tie stall facility. The cattle were mature and accustomed to tie stalls
rather than free stalls. All of the mature cattle from the pre-expansion facility were culled
within a year. Another manager believed that his slight RHA decline occurred due to
overcrowding and problems with acidosis, a nutritional disorder. The third manager’s
purchased cattle had calving problems which led to his decline in production. These
calving problems were due in part to the purchased cattle gaining too much weight during
an extended dry cow period. The extended dry cow period problem was attributed to
buying cattle from a seller with poor reproduction records, Who inaccurately estimated
calving dates. The ﬁnal expansion manager’s RHA declined due to housing the additional
cows in old heifer facilities and by overcrowding their pre-expansion free stall facility.

To assess whether or not there was a decrease during the ﬁrst post expansion year
but not observed in the two-year post expansion average RHA, the pre-expansion average
RHA was compared to the ﬁrst year post expansion average RHA. The average ﬁrst year
post expansion RHA was 23,098 pounds, which exceeded the pre-expansion average
RHA by 1,023 pounds. Thus, this proposition is rejected as well.

As the milk increased, the post expansion butterfat and milk protein yield also
increased. Mean butterfat production increased from 769 pounds to 810 pounds. Mean
milk protein production increased from 675 pounds to 716 pounds.

Having increased post expansion milk production per cow does not necessarily
mean that the expansion had no negative effects on milk production. A farm can expand its

herd without an initial decrease in production but fall behind the industry growth rate. To

44

investigate this, each farms’ post expansion RHA was compared to its projected

production had that production grew at the same rate as the typical U.S. dairy farm

participating in DHIA (Table 11).

 

 

 

 

Table 11. Comparison of Actual and Projected RHAI
Actual Post Actual Post Projected Projected
Expansion Expansion Post Post

Year 1 RHA Year 2 RHA Expansion Expansion
(lbs) (lbs) Year 1 RHA' Year 2 RHAl
Sample Mean 22,075 23,228 21,321 21,685
Standard Deviation 3,746 3,140 4,052 4,238
Sample Size 17 17 17 17

 

 

 

 

 

 

' The farms Actual RHA were adjusted to reﬂect average US. DHIA growth rates.

The farms average ﬁrst year post expansion RHA was 22,075 pounds (standard

deviation = 3,746 ). The projected ﬁrst year post expansion average RHA was 21,321

pounds (stande deviation = 4,052). As actual post expansion is greater than the

projected value, expansion did not affect growth in the ﬁrst year post expansion. The

farms also outpaced the average US. DHIA farm in the second year as well. The actual

second year post expansion average RHA was 23,228 pounds (standard deviation =

3,140). The projected second year value was 21,685 pounds (standard deviation = 4,238).

In all, the expansion farms’ milk production outgrew at a greater rate than the typical U.S.

DHIA herd.

Why do the current production results of the primary products vary so much from

the earlier studies? There are many possible explanations. It is possible that the herd

management abilities of the managers differed. While the management ability of the

45

 

managers ﬁom earlier work is unknown, the herd management capability of the
participants in this research was high (see Chapter 111). Although the recent expansion
managers generally have limited involvement in herd management activities following the
expansion, it is reasonable to assume that they expect their hired herd managers to be at
least as proﬁcient as they themselves were before expanding

Another possible reason is that today’s dairy technology is very different than in
the 1960’s and 1970’s. Many of the earlier expansion managers of the sixties and early
seventies moved from individual cow feeding to a single group, which proved to be a
diﬂicult transition (Stoll, 1974). Other possible factors include more homogenous genetics
and whether there were any differences concerning pre- and post expansion BST use.

The fact that the expansions did not experience an initial decrease in post
expansion production in the ﬁrst year or for the average of the ﬁrst two years post
expansion is an important ﬁnding. These results suggest that managers and advisors may
anticipate a post expansion RHA, RHA growth rate, butterfat yield, and milk protein yield
that is comparable to pre-expansion levels when planning or evaluating an expansion.

However, if certain problems are not controlled in the expansion, lower production
is a possibility. To assist in maintaining or improving post expansion milk production,
managers and advisors should:

1) avoid procuring very nurture, tie-stall-oriented cattle and cattle with little

production and reproduction information;

2) resist the temptation to overcrowd cattle;

3) refrain from using facilities not designed for lactating animals;

46

4) size expansions to capitalize on labor and management specialization rather

than merely increasing the managers workload; and,

5) incorporate improved facility and feeding technology whenever feasible.
IV. Problems Constraining Production

While milk and milk component production for the farms in this study on the
average did not decrease after expansion, this does not mean that production problems
were eliminated. Expansion does allow for the producer to reduce or eliminate some pre-
expansion production constraints, especially those relating to facility and labor and
management specialization. Unfortunately, not all pre-expansion problems can be
eliminated, and new problems can emerge following expansion. Understanding which
problems constrained pre-expansion production, how the expansion did or did not reduce
these problems, and what problems constrained post expansion production may assist
managers and advisors in planning ﬁrture expansions. This section examines those
problems that constrained production both before and after expansion.

The managers were asked to declare and rank problems they felt most limited their
pre- and post expansion production. The pre- and post expansion problems are listed in
Table 12 and Table 13 respectively.

IV-a. Pre-expansion Production Problems

“Cow comfort” was the most common problem constraining pre-expansion
production regardless of the ranking method. Cow comfort problems included facility
and/or stall related problems such as swollen hocks and ventilation issues. Eight managers

attributed cow comfort issues to antiquated ( l 970’s-1980’s) free stall facility design. Five

47

stated that the pre-expansion problems were caused by tie stall facility issues. Two
managers stated that the cow comfort issue was related to free stall design.

Table 12. Pre-expansion Production Problems ( 18 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Problem First Rank Second Third Total Dominant
Problems Rank Rank Responses Scorel
Problems Problems

Cow Comfort 8 8 5 21 45
Management 2 1 2 5 10
Emphasis

Feeds and 0 3 2 5 8
Feeding

Overcrowding 3 0 0 3 9
Reproduction 0 3 0 3 6
Milking l l 0 2 5
System

SCC and 0 0 2 2 2
Mastitis

2X Milking 1 0 0 1 3
Cow Age 1 0 1, 0 1 3
Employee 0 l 0 1 2
Tmnover
Freshening 1 0 0 1 3
Genetics 1 0 0 1 3

 

 

 

 

 

 

 

' Points awarded: ﬁrst rank == 3, second rank = 2, third rank =1

“Management emphasis” was the tied with “feeds and feeding” as the second
most common pre-expansion problem with ﬁve responses and was the second highest
scoring pre-expansion problem with ten points. Management emphasis was the third most

cormnon “ﬁrst rank” problem with two ﬁrst rank responses. Management emphasis refers

48

to the inability of the manager to effectively address the key problem due to time or other
constraints or due to personal preferences concerning production methods. Three
managers citing this problem stated that they could not give pr0per attention to
production problems due to a lack of labor and nmnagement specialization. The other
manager citing management emphasis problems indicated that they did not want to stress
their cows and emphasized registered livestock sales over production.

As mentioned earlier, “feeds and feeding” tied as the second most common pre-
expansion production problem with ﬁve responses. Nevertheless, due to no “ﬁrst rank”
ratings, this problem type only earned a fourth place dominant score. These problems were
related to feed ingredient quality, inadequate bunk space, the inability to effectively
conduct group feeding and the absence of a total mixed ration feeding system.

“Overcrowding” earned three “ﬁrst rank” responses making it the third highest
scoring production problems. It is unknown whether the managers who had this problem
were decreasing culling rates to have more animals available for their expansion projects,
had a prior pattern of overcrowding their facilities, or because of other reasons, such as a
surplus of heifers.

IV-b. Post Expansion Production Problems

The most common and the highest scoring “post expansion” production problem
was “cow comfort” with seven responses and a dominant score of sixteen points.
However, in terms of “ﬁrst rank” problems, it was second after SCC and mastitis. All but
one manager who had the “cow comfort” problem expanded by adding on to their

antiquated pre-expansion free stall facility. Thus, their cow comfort problem was still

49

present on at least part of their herd. The other manager had a modern facility, but was
unhappy with its design. He indicated that it was built with regard to labor efﬁciency and
not cow comfort.

“Milking System” and “Feeds and Feeding” tied as the second most common post
production problem with ﬁve responses, the third highest dominant score with eleven
points. Problems with the milking system, which tied with “cow adjustment” as the third
most common “ﬁrst rank” problem, had to do with parlor size/herd size relationships.
Many modern facilities are designed with a parlor that is just large enough to accomplish
the daily milkings. Unfortunately, this can cause the cows to stand in the pre-milking
holding areas for a long period of time where they are unable to eat or drink.

There were a variety of reasons for “Feeds and Feeding” problems. One manager
believed that his farm had a comparative advantage in forage production and also had a
low cow/acre ratio. Because of these reasons, the manager chose to feed a higher forage
ration resulting in rations with lower energy. Another had difﬁculty in feeding his herd in a
consistent manner and had crop quality issues. Both of these feeds and feeding issues were
related to workload and labor specialization issues. Another manager cited the lack of
bunk space. He believed that it was a problem inherent with his six-row free stall facility
design. This manager wishes he had built a four-row facility because they have more bunk

space per cow.

50

lab!-

Pro

(or

Mil

5's

lab

PM

 

Table 13. Post Expansion Production Problems (Farms =20)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Problem First Rank Second Third Total Dominant

Problems Rank Rank Responses Scorel
Problems Problems

Cow Comfort 3 3 l 7 16

Milking 2 2 1 5 l 1

System

Feeds and l 4 O 5 11

Feeding

SCC and 4 0 0 4 12

Mastitis

Genetics 1 2 0 3 7

Labor Issues 1 2 0 3 7

Procedural 1 1 1 3 6

Development

Biosecurity 1 1 0 2 5

Cow 2 0 0 2 6

Adjustment

Management 1 0 l 2 4

Emphasis

Overcrowding 1 0 l 2 4

Reproduction 0 l l 2 3

2X Milking l 0 0 l 3

F reshening 0 0 1 l 1

Low Cull 1 0 0 1 3

Rate

Reduced 1 0 O l 3

Individualized

Cow Care

 

51

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1

 

“SCC and Mastitis” was the third most mentioned problem with four responses.
SCC problems also earned the second highest weighted score with twelve points and was
the most common ﬁrst rank problem with four ﬁrst rank responses. Unfortunately, no
manager citing this problem had discovered its origin.

“Cow Adjustment” tied with “Milking System” as the third most common “ﬁrst
rank” problem with two ﬁrst rank responses. In both of the cow adjustment instances, the
expansion entailed moving ﬁom a tie stall to a ﬁ'ee stall facility.

Cow comfort problems, generally a facility designs issue, were still prevalent
problems following expansion, albeit less so than pre-expansion. Managers who still had
post expansion cow comfort problems tended to add on to their antiquated pre-expansion
facility as a low cost method to expand. If pre—expansion facilities are causing cow
comfort or other facility-induced problems, managers and advisors need to carefully
consider the marginal beneﬁts and marginal costs of building a more modern, but more
expensive, facility that will correct these problems as compared to utilizing existing
facilities.

Managers should also careﬁrlly consider holding pen time when planning their
expansion facilities. In many instances, the managers felt that they placed too little
importance on these issues, and the cows lost potential production because the cows are

are too long away from feed and water for extended time periods.

52

mi

ca.
,

UT.

Another important facility consideration is the amount of bunk space. While six-
row facilities can typically be built for less expense, four-row facilities have more bunk
space available per cow.

It appears from the research that being a large enough operation to have adequate
ﬁeld and feeding personnel is as important as having specialized management and milkers.
If not, feed quality and feeding efﬁciency may hinder production.

Finally, for those who are planning to use cattle accustomed to tie stalls to
populate free stall expansion facilities, expect to have problems with the cattle adjusting to
a free stall environment, resulting in lower production and higher culling.

V. The Effects on Reproduction

Having poor reproductive performance can be costly to a dairy. The actual cost
can vary depending upon herd speciﬁc factors. Because there is a potential with dairy
expansion to have numerous problems that can divert the manager’s attention,
reproductive performance can decrease. Stoll found that the incidence of reproductive
problems increased by 12 percent the ﬁrst year following expansion.

This section examines the results of an analysis of pre- and post expansion
reproductive performance. The following reproduction measures are analyzed: services
per conception (S/C), average days open (ADO), average calving interval (AC1), and bull
usage. The ﬁrst three were chosen as they are common reproductive performance
measures used in the industry. The fourth benchmark, bull usage (expressed as a
percentage of pregnancies), was analyzed because some farmers are relying more heavily

on herd bulls as a means to address reproduction problems associated with artiﬁcial

53

insemination (i.e., poor estrus detection, high services per conception, time to conduct the
activities).This section also examines how reproduction problems changed during the
expansion process.

The four reproduction benchmarks were amlyzed using a one sided t-test (pooled
variance method) to determine if pre-expansion and post expansion benchmarks were
equal. The descriptive statistics and analysis results are summarized in Table 14.

As shown by the sample sizes displayed in Table 14, participation in this part of the
research was low. Mean S/C changed from 2.14 to 2.06 services. The post expansion S/C
was not signiﬁcantly greater than the pre-expansion S/C at a 95 percent signiﬁcance level.2
The ACI, ADO, and bull usage increased. Nevertheless, the three post expansion
benchmarks were not signiﬁcantly different at a 95 percent signiﬁcance level.3

For services per conception, the manager with the most improvement decreased
his S/C by 1.13 services. On this farm, the only major change ﬁom pre-expansion was
that the responsibility for reproductive management was delegated to another person.
Thus, management specialization may be the cause of this signiﬁcant improvement.

The largest increase in post expansion AC1 was from 12.65 to 13.35 months. The
wager attributed the problem to poor conception rates during periods of extreme heat
stress. The herd’s post expansion AC1, despite the decline in performance, was still better

than the sample post expansion mean of 13.42 months.

Ztmlf»: 0:317, teriticula=.05,16= 1-746

3 AC1: 1,“ .,= 0.775, t m ,0, ,,= 1.734; p-value = 0.767
ADO: tm,,=0.396,tm,=‘o,w= 1.812
Bull Usage: tm22= 0.239, t m,,_05,22= 1.717

54

 

 

 

 

 

 

 

 

 

 

 

Table 14. Effect on Reproduction Measures
Services per Average Days Average Bull Usage
Conception Open Calving (Percentage)
Interval
(Months)
Before After Before After Before After Before After
Mean 2.14 2.06 118 122 13.2 13.4 29 33
High 3.5 2.9 138 138 14.5 15 100 100
Low 1.5 1.5 92 97 12.4 12.3 0 0
Std. Deviation .59 .42 16.7 16.1 .65 1 .73 43 44
Sample Size 9 6 10 12

 

 

 

 

 

 

One manager increased bull usage from 20 to 60 percent after expanding. The

manager stated that they were facing many reproduction problems with their purchased

mature cattle. They decided to increase bull usage rather than letting the farm’s

reproduction performance slip. The manager who experienced the largest increase in AC1

also increased his bull usage. To help reduce his herd’s calving interval, he increased bull

usage from 0 to 11.5 percent.

The results from this analysis suggest that expansion managers might experience a

slight, however, statistically insigniﬁcant change in herd reproductive performance. These

results conﬂict with Sto 11’s earlier research which showed signiﬁcant increases in the

incidence of reproductive problems. A possible reason for this difference is artiﬁcial

insemination practices. Many managers in Stoll’s work had only just begun to artiﬁcially

inseminate cattle without the aid of an artiﬁcial insemination technician. This may have

meant that the managers had to endure poorer reproductive performance while they were

55

 

re;

C111

F?

(.8.

h

learning and/or were more attentive of reproductive issues and diagnosed more
reproduction problems than when they were using a genetic company’s technician.

Another possible reason is that earlier expansions were of smaller scale than
current expansions. Thus, the expansion merely increased the manager’s workload instead
of increasing specialization. Current expansions have the potential for increased
reproduction management specialization.
V1. Reproduction Problems

To determine whether reproduction problems changed after expanding, the
managers were asked to list and rank their most economically signiﬁcant pre- and post
expansion reproduction problems. The results are displayed in Tables 15 and 16
respectively.
VI-a. Pre-expansion Reproduction Problems

“Estrus Detection” and “Cystic Cows” were tied as the most common pre-
expansion reproduction problem, and as the most common “ﬁrst rank” problem (Table
15). “Estrus Detection” earned the highest dominant score for pre-expansion reproduction
problems with nineteen points. “Cystic Cows” had the second highest dominant score with
eighteen points.

On ﬁve of the farms where estrus detection was a problem, facility design was the
attributing cause. of the problem. Four of these were tie stall facilities and the other was a

free stall facility. Because tie stall facilities limit cow-to-cow interaction, estrus detection

56

111

C03]

y. HQ

. Maw.

 

 

 

 

 

 

Table 15. Pre-expansion Reproduction Problems ( l6 Farms)

Problem First Rank Second Third Total Dominant

Problem Rank Rank Responses Scorel
Problem Problem

Estrus 5 2 0 7 19
Detection

Cystic 5 1 1 7 18
Cows

Conception 3 2 0 5 13
Retained 1 2 1 4 8
Placentas

Uterine 2 0 1 3 7
Infections

 

 

 

 

 

 

 

 

‘ Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1

was more difficult. The ﬁ'ee stall facility’ 5 estrus detection problem was also attributed to
a design issue. The cows in the free stall area were not readily viewable by workers at
their work stations causing many instances of standing estrus to go unnoticed.

Like many of the reproduction problems encountered in this survey, the cause of
the cystic cow problem was unknown on six of the inﬂicted herds. Other cystic cow
problem sources included herd age, embryo transfer complications, and poor nutrition.

The third most common reproduction problem was “Conception.” It was the third
highest scoring problem and the third most common “ﬁrst rank” problem, as well. The
conception problem sources were unknown in all but two cases. One manager attributed
his problem to heat stress. The other attributed the conception problem to his six-row ﬁ'ee
stall facility. These facilities typically have fewer head locks per cow than four-row

facilities. Thus, this manager’ 3 ability to inseminate the cows in estrus was reduced.

57

As a ﬁnal observation, if the tie stall herds were removed ﬁ'om the sample, then the
most common pre-expansion reproduction problems would be cystic cows, conception,
and retained placentas. Estrus detection would tie with uterine infections as the least most
cormnon problem.

VI-c. Post Expansion Reproduction Problems

For post expansion reproduction problems, “Conception” tied with “Cystic Cows”
as the most common problem and as the second most common “ﬁrst rank” reproduction
problem. It also earned the highest dominant score with 17 points (Table 16). The source
of the conception problems were known in only three cases. These were attributed to heat
stress, bull-to-cow ratio, and the previously mentioned six row free stall facility design
issue.

Besides being tied with “Conception” as the most common and as the most
common “ﬁrst rank” problem, “Cystic Cows” was the second highest scoring post
expansion reproduction problem with 15 points. In one instance, this problem was
attributed to nutrition, but the source of the problem was unknown in the other cases.

Estrus detection was the third most common post expansion reproduction
problem, the third highest scoring problem with 13 points, and was the third mo st
common “ﬁrst rank” problem. The problem dropped in importance after expansion. The
decline in prominence was attributed to the abandonment of tie stall facilities and the
proper training of all numagers and workers (as opposed to just the herd mamger and

assistant herd manager) to detect estrus. Those who had estrus detection problems

58

attributed it to facility design, hairy hoof wart (a virus that makes the cow uncomfortable
standing) and a poorly trained staff.

Table 16. Post Expansion Reproduction Problems ( 16 Farms)

 

 

 

 

 

 

 

 

Problem First Second Third Total Dominant
Rank Rank Rank Responses Score'

Problem Problem Problem

Conception 4 1 1 6 l7

Cystic Cows 4 1 l 6 15

Estrus 3 2 0 5 13

Detection

Retained 2 1 0 3 8

Placentas

Aborted 1 0 O 1 3

Pregnancies

Estrus O 0 1 1 1

Synchronization

Uterine 0 0 1 1 1

Infections

 

 

 

 

 

 

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1
VI-c. Conclusions Concerning Reproduction Problems

Overall, the top three pre-expansion reproduction problems — estrus detection,
cystic cows, and conception, were the top three reproduction problems post expansion.
Alter expansion, however, estrus detection was replaced as most prominent pre-expansion
reproduction problem by conception. The decline in estrus detection problems was caused
by moving ﬁom tie stalls to free stall facilities and training all personnel to detect cows in

estrus.

59

Thus, managers expanding from tie stall Operations can expect improved estrus
detection, especially if all employees are properly trained. TO help promote estrus
detection, the expansion facilities should be built in a manner that managers and laborers
can Observe the cows. Managers who have conception problems may want to consider the
beneﬁts of have a four-row facility as compared to a six-row facility.

VII. The Effect of Expansion on Herd Health

Poor herd health decreases dairy proﬁtability by reducing output, increasing animal
treatment cost, or the premature culling Of an aninml. Stoll found that herd health
problems, culling rates, and youngstock mortality increased with expansion (1975).
Because herd expansions involved in this study are larger than earlier studies, many
expansion managers are forced to purchase cattle from many sources. This co-mingling of
cattle may increase the risk of infecting a herd with Johnes, BVD, tuberculosis, hairy wart,
as well as other contagious diseases, creating a biosecurity problem

The impact of expansion on herd health was investigated in this study. First, did
three herd health measures, culling rates, cow mortality and youngstock mortality,
increase following expansion? Second, how expansion affected the type of herd health
problem is examined. Third, biosecurity herd health issues are analyzed by investigating
the types of biosecurity problems encountered on individual farms, the number of cows
exposed to each disease, and whether or not biosecurity protocols were effective at
reducing the incidence Of such diseases.

The three herd health measures were analyzed using a one sided t-test (pooled

variance method). The descriptive statistics and analysis results are summarized in Table

60

l7. Producer participation in this part of the survey was low. It is unclear why managers
failed to provide information concerning culling rates and cow mortality. The low
participation rate in providing youngstock mortality information can be explained by the
use Of custom youngstock growing services by several ﬁrms in the study.

Mean post expansion culling rate decreased instead Of increasing as proposed.
Thus, the proposition Of an increase in culling rates is rejected. Five herds experienced
decreases that were relatively larger than the sample. One of these managers was making a
conscientious effort to decrease his culling rate to 25 percent, which he felt would be more
proﬁtable. Three other herds with signiﬁcantly lower culling rates were housed in tie stalls
prior to expanding. A possrble explanation for the decreased culling rates among these
herds was a reduction in tie stall problems including lameness and respiratory diseases.
These problems were ranked by the three managers as one of their top three pre-expansion
herd health problems prior to expanding and were absent in the post expansion ranking.
The ﬁfth manager experiencing a signiﬁcantly decreased culling rate had abnormal hoof
growth, mastitis, and reproduction as his tOp three pre-expansion herd health problems.
These problems were not ranked post expansion, and might explain the farm’s culling rate
decrease.

Only one farm showed a substantial increase. The increase on this farm was
attributed to two herd health problems. This herd had post expansion problems with
mastitic ﬁrst lactation heifers and hairy hoof wart. Neither Of these problems were

prevalent before expanding-

61

Cow mortality increased as expected from 2.7 percent to 3.34 percent. This

increase was insigniﬁcant at a 95 percent level" Three farms experienced cow mortality

increases greater than 0.97 percent. Unfortunately, the justiﬁcation of these increases

cannot be determined from the research data. NO farm saw a signiﬁcant decrease in cow

mortality.

Youngstock mortality also increased from. 4.7 to 6.9 percent after expansion. The

post expansion mortality was not signiﬁcantly greater than pre-expansion at a 95 percent

signiﬁcance level.’ Only one herd saw an increase that was greater than the critical

distance of 4.09 percent. This herd saw their pre-expansion youngstock mortality increase

from 5 to 20 percent after expanding. The numager indicated that this increase was related

to housing. They tried to house calves and unbred heifers in their Old tie stall facilities,

which proved unsuitable for youngstock raising.

 

 

 

 

 

 

 

 

 

 

Table 17. Effect on Culling Rate, Cow Mortality, and Youngstock Mortality
Culling Rate Cow Mortality Youngstock
Mortality
Before After Before After Before After

Mean 32.4 30.3 2.7 3.4 4.7 6.9
High 43 40 5 5.5 10 20
Low 20 20 1 1 1 1
Standard Deviation 6.5 5.6 1.2 1.3 3.2 6.3
Sample Size 13 10 9

 

 

 

 

 

 

‘ t m, ,,= 1.224, t cm, ,__ 0,. ,8: 1.734; p-value = 0.874

51m, .,= 0.958, t m, , ,0, ,6: 1.746; p-value = 0.816

62

Earlier research indicated that youngstock mortality and culling rates increased
statistically. The expansion managers in this study did not display a similar pattern. Their
post expansion herd health benchmarks were essentially the same as pre-expansion Thus,
post expansion costs associated with culling and mortality may be no higher on a relative
basis than pre-expansion.

VIII. Herd Health Problems

The managers were asked to list and rank their most economically signiﬁcant herd
health problems in order to see which problems declined and which problems increased
with expansion. The results for the pre- and post expansion periods are listed in Tables 18
and 19 respectively.
VIII-a. Problems Constraining Pre-expansion Herd Health

Larneness was the most common, the highest scoring, and the most common “ﬁrst
rank” pre-expansion herd health problem (Table 18). Seven managers who faced this
problem attributed the lameness to poor free stall design issues. Four attributed the
lameness to their pre-expansion tie stall facilities. Two managers responded that feeding
problems caused their cows’ lameness, and another indicated that genetics contributed to
their cows’ feet and leg problems.

“Mastitis and SCC” was the second most common, the second highest scoring,
and the second most cormnon “ﬁrst rank problem. Poor stall design was believed to be the
cause of the mastitis problem in four cases. “Old parlor facilities and equipment” was

credited twice, as was “labor issues”. Three managers were unsure about their mastitis

problem origin.

63

lal

\

 

a)

Table 18.

Pre-expansion Herd Health Problems ( l8 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Problem First Second Third Total Dominant
Rank Rank Rank Responses Scorel
Problem Problem Problem

Lameness 7 3 1 11 28
Mastitis and SCC 5 4 1 10 24
Misc. 2 2 3 7 13
Reproduction

Hairy Hoof Wart 2 1 0 3 8
Misc. Herd 1 1 l 3 6
Health

Misc. Respiratory 0 1 2 3 4
Displaced 1 l 0 2 5
Abomasums
Freshening Issues 0 1 0 1 2

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1

Reproduction problems were the third most common herd health problem and the

third highest scoring pre-expansion herd health issue. Reproduction problems tied with

“hairy hoof wart” for third most common “ﬁrst rank” problem. The most common cause

of these reproduction problems was nutrition, but labOr and herd age were also mention.

Reproduction problems 1nd unknown sources on two farms.

VIII-b. Post Expansion Herd Health Problems

“Mastitis and SCC” was the most common overall post expansion, the highest

scoring post expansion problem, as well as the most common “ﬁrst rank” post expansion

herd health problem (Table 19). The problem’s source was unknown in ﬁve cases. Two

Table 19.

Post Expansion Herd Health Problems (20 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

Problem First Second Third Total Dominant
Rank Rank Rank Responses Scorel

Problem Problem Problem

Mastitis and SCC 5 3 3 11 24

Lameness 2 3 4 9 13

Hairy Hoof Wart 3 2 1 6 14

Displaced 3 2 0 5 13

Abomasums

Misc. Herd 2 l l 4 9

Health

Misc. 2 2 0 4 10

Reproduction

Freshening Issues 2 1 0 3 8

Misc. Respiratory 0 2 0 2 4

Johnes 1 0 0 1 3

BVD 0 1 0 1 2

Salmonella 0 0 1 1 1

 

 

 

 

 

 

 

 

' Points awarded: ﬁrst rank = 3, second rank = 2, third rank = 1
managers cited equipment problems. Overcrowding, labor issues, a sucking heifer, and
poor stall design were each cited one time for this problem.

The second most common problem was “Lameness”. Lameness was the third
highest scoring problem with thirteen points. It was tied with other herd health problems
as the third most common “ﬁrst rank” problem. Facility problems such as poor concrete or
stall design was the attributed cause on 6 farms. Nutrition was cited as the problem’ 5

cause on two farms, while genetics was mentioned once.

65

Hairy hoof wart was the third most common herd health problem with six total
respOnses. If this and the other biosecurity-type diseases mentioned -—— BVD, Johnes, and
Salmonella —— were considered as a whole, biosecurity-type diseases problems would
have been the most prominent post expansion herd health problem.

Based on the farms in this study, managers who are experiencing facility-induced
lameness problems may see improvements post expansion if the proper technology is
adopted. There also appears tO be a tendency for mastitis to increase in prominence after
expanding. Unfortunately, the reasons for the majority of mastitis cases were unknown.
Nevertheless, expansion managers should make mastitis prevention an important post
expansion priority. It also appears that biosecurity problems will be a major post
expansion challenge. The next section examines how these expansion dairies were effected
by biosecurity-type diseases.

IX. The Incidence of Post Expansion Biosecurity Problems

A pre- to post expansion herd health change was the increase in infectious herd
health problems (BVD, Hairy Hoof Wart, Johnes, Pneumonia, Salmonella, and Strep.Ag.).
These diseases can become commonplace on herds that purchase cattle. Biosecurity
protocols can be developed to reduce biosecurity risk, assuming that these protocols are
implemented (Gardner, 2000).

Biosecurity protocols were in place on seventeen of the twenty expansion dairies
(Table 20). This meant that 11,459 of the 12,694 cows in this research were protected by
a program to reduce the risk of infectious disease. Of these seventeen farms, only seven

farms representing 3 ,635 cows had bio security programs that included quarantines.

66

 

 

 

 

 

Table 20. Biosecurity Problem Incidence ( 20 Farms)
Protocol Type Total No Biosecurity Biosecurity
Problems Problems
Farms Cows Farms Cows Farms Cows
None 3 1,235 0 0 3 1,235
Immunization and 10 7,824 2 2,691 8 5,133
Testing Only
Immunization, 7 3,635 3 1,320 4 2,315
Testing, and
Quarantine

 

 

 

 

 

 

 

 

Fifteen farms experienced biosecurity problems resulting in a potential contagious

disease exposure of 8,683 cows; however, only one ranked the problem as being

economically severe. Three Of theses herds had no biosecurity protocol. Eight of the

seventeen farms had biosecurity protocols that included immunization and testing but not

quarantine requirements. Four farms with quarantine procedures experienced a disease

outbreak. In all, 7,448 (65 percent) cows contracted a contagious disease despite

biosecurity protocols.

Five farms reported no biosecurity problems. Two had protocols that included

immunization and testing only. The other three farms had protocols that included

quarantines.

The research proposition that managers who have strict biosecurity protocols will

exPerience reduced disease problems seems supported. The three farms who did not have

protocols experienced outbreaks, and those that experienced no outbreaks had protocols

in place. Nevertheless, there are two unnerving facts. First, twelve farms had biosecurity

67

 

programs and still had outbreaks Of contagious diseases. The nature OfJOhnes may explain
part of this discrepancy. The test for Johnes is not reliable for youngstock, and many
producers believed that their Johnes problem came from purchased calves. Another
possrhle explanation is the degree to which the protocols were implemented.

Unfortunately, biosecurity protocol implementation was not covered in this research.

Second, 12 ﬁrms expanded without quarantine procedures, which is considered a
necessity for biosecmity programs. Many managers who did not quarantine animals stated
that they did not have enough facilities to quarantine all Oftheir purchased anirmls without
seriously decreasing their herd size at start up.

The types Of diseases encountered varied. BVD, Hairy Hoof Wart, Johnes were
each diagnosed on four farms (Table 21). Four ﬁrms had instances Of contagious diseases
that could not or were not diagnosed. Three farms experienced pneumonia outbreaks. One
ﬁrm had difﬁculties with Sahnonella, while another herd had a Strep Ag. outbreak.

Table 21. Contagious Diseases Encountered After Expansion ( 15 Farms)

 

 

 

 

 

 

 

 

 

 

Disease Type Farms Exposed Cows Exposed

BVD 4 1,637
Hairy Hoof Wart 4 2,535
Johnes 4 2.245
Pneumonia 3 2,156
Strep Ag. 1 530
Salmonella 1 340
Undetermined diseases 4 2,470

 

 

 

68

Hairy Hoof Wart was potentially exposed to the most cows with 2,535.
Undetermined diseases were exposed to 2,470 cows. The potential Johnes exposure was
2,535 cows. Pneumonia was exposed to 2,156 cows. The potential BVD exposure was
1,637 cows. Strep Ag and Salmonella exposure was limited to 530 and 340 cows
respectively.

Increasing biosecurity is a major challenge for expansion managers. In this survey,
all ﬁrms without a biosecurity protocol were exposed to contagious diseases. Even those
with protocols, especially those with no quarantine programs, experienced some
biosecurity problem. Having enough facility space to quarantine an expansion dairy’s
initially large number of purchased animals seems to be a problem. Being that this
quarantine space is only needed for the ﬁrst two years, expansion managers may want to
consider renting unused facilities from other ﬁrmers.

X. The Effect on Crop Yield and Quality

The ability to produce or procure forages and crops Of sufﬁcient quality and
quantity directly aﬁ‘ects the proﬁtability of dairies. Earlier research found that crOp yields
and quality declined after expansion. The managers attrrhuted these declines to the
inability to timely harvest the additional forage required by the expanded herd size (Stoll,
1974). The managers of this study were asked to explain how their expansion affected
crop quality and yield. The results are summarized in Table 22.

Unlike Stoll’s research, managers experiencing a decline in crop yield and quantity
were small in number. One manager experienced a decline in both corn and corn silage

yields, and another manager experienced a decline in alﬁlﬁ yield and quality. The manager

69

all

M

 

CO

with a decline in both enterprises attributed the problem to labor constraints. This dairy
was the smallest dairy in the research, and couldn’t afford specialized crOp employees. The
other manager stated that he had difﬁculties in getting his custom harvester to harvest at
the appropriate time.

Table 22. The Effect on Crop Quality and Yield ( 15 Farms)

 

Effect Corn and Corn Silage Alfalfa

 

Farms Experiencing 8 6
Improved Crop Production

 

Farms Experiencing NO 6 7
Clﬁnge in Crop Production

 

Farms Experiencing Poorer 1 2
Crop Production

 

 

 

 

 

Eight managers experienced improved yield and quality for corn production. For
alfalfa production, 6 managers indicated that they experienced improved post expansion
yield and quality.

Reasons given for the improved crop yields and quality are summarized in Table
23. Gaining sufﬁcient size to have laborers and managers dedicated exclusively to crOp
and forage production and using custom harvesting arrangements were the two most
common reasons for crop production irnprovements. As indicated earlier, a couple Of
farms had milk production problems related to custom harvesting. It should be noted that
those who used custom harvesters and experienced improvements in crop quality and yield
maintained harvest timing control; the manager who used custom harvesters and had
poorer crop production did not have this control. Two managers stated that increasing

their ﬁrms reliance on corn silage allowed them to become more experienced with the

70

crop, which culminated in better corn silage production. One manager stated that his
forage production improved after he realized that he had neglected

Table 23. Improved Crop Yields and Quality (8 Farms)

 

 

 

 

 

 

 

Reason Number of Managers Citing
Management and Labor Specialization 3
Custom Harvesting 3
Increased Forage Experience 2
Management Emphasis 1
Better Varieties 1

 

 

 

that aspect of his operation. One manager cited recent technological innovations with corn
silage varieties as beneﬁcial to their improvements.

The implications Of this research is that expansion does not necessarily mean
poorer crop yields and quality as earlier research might suggest. Implement, seed,
agronomic, and harvesting technologies have improved greatly since the 1970’s.
Furthermore, expansions tend to be Of suﬂicient size to allow for increased crop and
forage specialization and custom harvesting arrangements can be obtained that enables the
manager to have the forages harvested on a more timely basis.

XI. Conclusions

Despite previous research, there was no overall decrease in production,
reproduction, and herd health performance measures after expanding for the average herd
in this study. This ﬁnding can be attributed tO improved post expansion technology and

increased rmnagement and labor specialization (among other reasons). It should be noted,

71

box

C01

however, that the sample was biased towards managers with above average production
skills (Chapter 3). These results suggest that managers should not necessarily accept the
conventional wisdom that post expansion production, reproduction and herd health
performance will, in most cases, initially decrease. Expansion Offers managers the
opportunity to reduce the incidence Of ﬁcility- or technology-induced production,
reproduction, and herd health problems. Biosecurity problems do seem to affect expansion
dairies. Managers should work with veterinarians to reduce the incidence Of contagious

diseases and consider renting ﬁcilities to quarantine cattle.

72

Chapter VI
The Effect of Dairy Farm Expansion on Labor Productivity and Human Resource
Management
1. Introduction
Increased post expansion labor productivity, as deﬁned by pounds of milk shipped
per full time dairy worker (employee and manager) equivalent (milk/FIE) or total dairy
worker expense per cvvt of milk shipped (DWE/cwt) has been reported previously.I St-
Pierre noted that milk shipped per emplOyee increased as herd size increased (1998).
Karszes, Knoblauch, and Putnam found that both milk/FIE and DWE/cwt increased as
dairies expanded in New York (1998). The research found that herds which expanded by
35 percent or more during the 1993 to 1997 period increased milk/FTE from 794,855 in
1993 to 1,029,524 pounds in 1997, an increase of 30 percent.2 Total dairy worker expense
per hundredweight decreased ﬁ'om $2.99 tO $2.26 per hundredweight for the same period.
This labor productivity improvement can be viewed as positive if other important aspects
Of the business has not suﬂ‘ered.
As a dairy expands, generally more hired labor is used, enabling the manager to
delegate more specialized labor and operational management tasks. Because these
employees typically do not have a ﬁnancial stake in the Operation and the manager is

typically unable to directly supervise all employees, the manager shifts the responsibility

 

' DWE/cwt includes expenses for hired labor and a charge for unpaid labor and
management.

2 The average herd size increased from 270 cows to 428 cows for the same period.

73

without necessarily providing the necessary incentives and training to insure that the
responsibilities are conducted correctly. This may create a situation where the delegated
activities may be performed at sub-optimal levels.

Optimizing labor productivity requires effective human resource management
(HRM). The importance of human resource management was shown earlier in Chapter V.
Whereas only three managers (who were all subsequent expanders) speciﬁcally mentioned
HRM as part of their pre-expansion job responsibilities, l3 managers included it in their
post expansion job responsibilities. Furthermore, when the managers were asked to select
and rank the most important speciﬁc skills needed for expansion dairy management, HRM
earned the highest dominant score, the most “ﬁrst rank” ratings and the most responses
regardless of rank.

Unfortunately, the HRM experience Of many managers prior to expansion is Often
limited. Managing immediate family members or one or two employees is less complex
than managing a larger, more diverse, typically non-ﬁrnily work force (Surnrall, 1999). It
is important to understand the effects dairy expansion has on HRM issues in order to
enhance labor productivity on expansion dairies.

The effect Of dairy expansion on labor productivity and human resource
management is examined in this study The following research propositions are investigated
in this chapter:

1) Signiﬁcant improvements occur in post expansion labor productivity (as

measured by milk shipped per full time equivalent and total dairy worker
expense per hundredweight) when compared tO pre-expansion levels.

74

2) Human resource management problems change in importance from pre- to
post expansion.3

3) Expansion managers desire extension and outreach based training programs
to inform them about human resource management issues and to provide
vocational training for ﬁrm employees.

As noted earlier, labor productivity should improve as herd size increases. In ﬁct
many managers gave improvements in labor productivity and human resources as one Of
many justiﬁcations for dairy expansion (Chapter IV). Whether these improvements occur
is tested by analyzing two labor productivity measures, milk/FT E and TLME/cwt.

The second proposition concerns how a ﬁrms HRM problems change in
importance as dairy famrs expand. More laborers are typically hired as dairies expand.
Some managers can focus more time on HRM post expansion due to increased
management and labor specialization. Hiring more laborers and focusing more time on
management may contribute tO more HRM problems being identiﬁed by the manager and
changes in the types Of problems encountered.

The third proposition concerns determining the HRM education and employee
training needs of expansion managers. Because a dairy manager’s HRM experience may
be limited, managers may desire assistance in improving their HRM skills as well as their
employee vocational abilities. Understanding these needs enables advisors and educators
to prepare educational programs that provide managers with pertinent HRM information

and dairy employees with needed vocational skills.

 

3 HRM problems may include poor employee motivation or the inability to provide
beneﬁts among others.
75

II. The Effects on Labor Productivity: Milk/FTE

Good labor productivity is a major ﬁctor for determining the long-run
competitiveness of a dairy business. Labor productivity should increase as management
and labor specialization increase. In this section, one labor productivity benchmark,
milk/FTE, is measured and analyzed to determine if milk/FTE signiﬁcantly improves with
expansion.

Table 24 displays pre- and post expansion milk/FTE. Pre-expansion milk/FTE for
all ﬁrms averaged 686,656 pounds/FTE, ranging from a low of 210,511 to a high Of
1,523,957 pounds/FTE.‘ Post expansion, average milk/FTE increased, as expected, by 34
percent to 917,981 pounds per year, ranging ﬁom a low of 406,843 to a high of
1,871,364.’

TO determine if post expansion milk/FTE was greater than pre-expansion levels, a
one tailed, pooled variance t-test was used. At the 95 percent signiﬁcance level, there was
sufﬁcient evidence to conclude that post expansion milk/FTE was signiﬁcantly greater
than pre-expansion milk/FTE.‘5

The initial expander group’s mean milk/FIE increased by 26 percent from 565,340
to 711,513 pounds. Post expansion milk/FIE ranged from 406,844 to 911,011 pounds.

Subsequent expanders increased their milk/FIE by 38 percent from 783,263 to 1,083,155

pounds/FT'E.

‘ Pre-expansion herd size averaged 295 cows.
5 Post expansion herd size averaged 596 cows.

6 tulle-.05, 34 = 2'032 > tubule-£05, 34 = 1692

76

Table 24. Pre- and Post Expansion Milk/FTE‘ ( 18 Farms)

 

 

 

 

 

 

 

 

Issue Pre-expansion Post Expansion Change
(lbs.) (lbs.) ('/o)
All Farms Milk / FTE 686,656 917,980 33
Std Deviation (All Farm) 316,341 365,001 NA
Initial Expander Milk/FTE 565,340 711,513 26
Std Deviation (Initial 264,675 219,891 NA
Expander)
Subsequent Expander 783,710 1,083,155 38
Milk/FTE
Std Deviation 372,224 414,712 NA
(Subsequent Expander)

 

 

 

 

 

' Milk shipped per full time equivalent (includes all managers and dairy employees)
Managers should reallocate labor and capital to favor more capital intensive

technology (thereby allowing a higher, more proﬁtable cows/employee ratio) if the value
of the marginal product of capital (VMPK) increased relative to the value Of the marginal
product of labor (VMPL). Pre- and post expansion VMPK and VMPL were estimated to
determine if the VMPK increased with respect to the VMPL after expanding.

Unfortunately, due to having an under identiﬁed model (e.g., data was not available for
other ﬁctors of production) the resulting VMPK and VMPL were erroneous. As an
alternative, the capital to labor ratio (K/L) was estimated by dividing the ﬁrms market
value assets by the dairy worker expense. Pre-expansion, the m was 3.8. Post expansion,

this ratio increased tO 4.9. This suggests that the managers reallocated their capital and

labor inputs to utilize more capital

77

Both initial expander and subsequent expander Operations signiﬁcantly improved
their milk/FTE labor productivity benchmark as expected. This improvement is thought to
be due (in part) to the adoption Of labor saving technology. The change in the m ratio
may support this premise. It should be noted, however, that the labor saving ﬁcility and
equipment technology typically requires larger ﬁnancial capital outlays. This can make
ﬁnancing the business more difﬁcult and makes the dairy more sensitive to production,
interest rate, output price, and input price variation.

111. The Effects on Labor Productivity: DWE/cwt

While milk/FTE is a measure of productivity, it provides little information
concerning the labor costs associated with that productivity. Thus, the annual DWE/cwt
milk were estimated for the dairies. DWE/cwt decreased as expected with increased labor
productivity (Table 25). Mean pre-expansion DWE/cwt was $5.14, ranging ﬁ‘om a low of
$2.05/cwt to a high of $10.93. The higher ﬁgure came ﬁom a dairy with a relatively large
number of managing partners, which meant higher worker costs. Post expansion
DWE/cwt milk decreased tO an average of $2.94. Post expansion DWE/cwt ranged ﬁom a
low Of $1.67 to a high of$6.16. At a 95 percent signiﬁcance level, there was sufﬁcient
evidence to conclude that post expansion DWE/cwt were less than pre-expansion
DWE/cwt.7

For initial expanders, DWE/cwt milk decreased ﬁom $5.81 pre-expansion to$3.10

post expansion. Subsequent expanders decreased DWE/cwt of milk produced from $3.36

to $2.70.

§

71mg. = 2.599 >tm,-_,,,,, = 1.692

78

Table 25. Pre- and Post Expansion DWE/cwtl ( 17 Farms)

 

 

 

 

 

 

 

Issue Pre-expansion Post Expansion Change ('/o)
(Slcwt) ($Icwt)

All Farm DWE/cwt milk 5.14 3.50 - 32
Std. Deviation (All Farm) 2.30 1.37 NA

Initial Expander DWE/cwt milk 4.85 3.34 -31
Std Deviation (Initial 1.94 ' 1.37 NA
Expander)

Subsequent Expander 3.91 2.63 -33

DWE/cwt milk

Std Deviation (Subsequent 2.52 1.31 NA
Expander)

 

 

 

 

 

 

' Manager and employee salary and wage expense per 100 pounds Of milk.
Conventional wisdom holds that as herd size increases, labor emciency should
improve because Of labor saving technology adoption, specialization and economies Of
size. This premise was supported by the data Most expansion managers experienced a
signiﬁcant improvement in total labor and management expense per hundredweight. Those
who did not either failed to adopt technology to improve labor efﬁciency or faced a highly
competitive labor environment. These results suggest that managers can expect to
experience lower management and labor expense per hundredweight Of milk.
IV. How HRM Problem Importance Change as Dairies Expand
Although labor productivity improved as dairies expanded, the expanding dairies
experienced HRM problems. For the farms in this study, especially initial expanders,
managing human resources before expanding meant managing a srmll number of full

and/or part-time employees. On some pre-expansion ﬁrms, the manager and laborers

79

W0

C01

the

worked side-by-side completing daily chores. On these ﬁrms, training and task organizing
consisted Of “do-as-I-do” techniques. Motivation and evaluation were conducted while
the work is being done, if at all. Pre-expansion HRM problems recognized by managers
centered around employee availability and quality issues, especially during periods of low
unemployment.

‘ More employees are typically employed following expansion. Because of the
increased labor and management specialization, the manager is better able to concentrate
on rmnagement issues. Thus, the manager’s ability to diagnose and solve HRM problems
may grow. Besides employee availability and quality issues, the manager encounters more
hurmn resource problems. Some Of these problems may occur due to the dynamic nature
of managing a larger workforce. Others may have been present but not recognized by the
manager during pre-expansion. The manager soon realizes the value of organizing and
delegating. Standard Operating procedures and employee handbooks are Often required.
Training and evaluating programs are developed and administered. The manager must now
motivate many workers instead of a few. Because of these changes, such as how to
evaluate employees, group dynamics and employee motivation, become important to the
manager.

This section examines whether human resource management problems grow in
scope and change in priority after expansion. TO accomplish this, the managers were asked
to indicate the pre- and post expansion HRM problems they experienced.

The most cormnon pre-expansion HRM problem encountered by managers was

“fullctime employee availability.” Seven managers stated that they had problems ﬁnding a

80

suitable number of candidates (Table 26). Most attributed this availability problem to the
current low employment rate.

Finding part-time employees of suitable quality was diﬂicult for six managers.
Many managers credited this problem tO competing with other businesses, both farm and
non ﬁrm, for quality part-tirne employees.

Six managers also indicated “communicating” with employees as problematic.
Many responded that they had difﬁculty in ﬁnding time in their pre-expansion daily
routines to discuss issues with their employees.

The HRM problems changed post expansion. Ten managers found “evaluating”
employees to be the greatest post expansion HRM difﬁculty. Several managers
commented it was difficult to establish an evaluation criteria that treated everyone ﬁirly
' but was ﬂexrble enough to accommodate individual strengths and weaknesses.

“F ull-time employee availability” and “communicating” with employees tied as the
second most common post expansion HRM problem with 9 managers indicating each.
Most of the producers still indicated that full tirne-employee availability was difﬁcult due
to the current low unemployment rate. Unlike pre-expansion, several managers stated that
time was not a constraint on communicating with employees. Instead, it was inexperience
in communicating with employees that caused diﬁculties in this area.

When evaluating how HRM problems change from pre- to post expansion, it is
irrlportant to consider the percentage change in the indicated HRM problem. “Evaluating”
employees had the largest percentage increase (233 percent). “Achieving the manager’s

perfornumce goals for the employees” and “full-time employee quality” tied for the second

81

largest percentage increase with a 167 percent increase. “Training” was another HRM

problem that saw a 133 percent increase.

Table 26. HRM Problems Indicated by Expansion Managers (20 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Issue Pre-expansion Post Expansion Percentage
Responses Responses Change
Evaluating 3 10 233
Providing Beneﬁts 3 6 200
Achieving Performance 3 8 167
Goals
Full-time Employee 3 8 167
Quality
Training ' 3 7 133
Determining Selection 3 5 67
Requirements
Compensating 3 5 67
Retaining 4 6 50
Communicating 6 9 50
Manager Availability 3 4 33
Part-time Employee 3 4 33
Availability
Manager Quality 4 5 25
Full-time Employee 7 9 22
Availability
Part-time Employee 6 7 17
Other 3 4 33

 

 

 

 

 

 

82

When analyzing expansion plans with managers, it is important to consider how
HRM problems will likely change post expansion. Assuming the problems experienced by
ﬁrms in this study will be similar to the problems faced in future expansions, the
availability of full-time employees will probably still be difficult. Other problems such as
evaluating, communicating, ﬁnding qualiﬁed employees, achieving performance goals for
employees, and training become increasingly critical as they are pertinent to achieving
good labor productivity. To reduce these potential post expansion problems, managers
should gain exposure to these issues prior to expanding.
V. Desired HRM Skill Training

Dairy ﬁrm managers look to land-grant universities and other agencies to provide
them with research, education, and extension/outreach programs designed to make them
better managers. The expansion managers were asked to consider desired educational
programs to improve their HRM skills (Table 27).

Improving communication and employee motivation skills received the most
responses with 5 managers indicating a need to improve in these areas. Four managers
desired training in evaluating procedures and HRM legal issues. Three responded that
additional assistance in training techniques would be beneﬁcial. Disciplining, group
dynamics, hiring, and compensating were each indicated by 2 managers. Only one manager

indicated a lack Of interest in such training.

83

Table 27. HRM Education Topics Desired by Managers (20 Farms)

 

HRM Skill Area

Managers Responding

 

Communication

5

 

Motivation

 

Evaluation

 

Legal Issues

 

Training Techniques

 

Disciphnmg' °

 

Group Dynamics

 

H' .

 

 

Compensating

 

5
4
4
3
2
2
2
2

 

For ﬁrm labor training programs, the managers clearly ﬁvored farm task training

(Table 28). Twelve managers desired animal husbandry programs for their employees.
Six indicated a need for milker training programs. Of non-farm task needs, two managers

indicated the need for programs designed to improve employees in each of the following

areas: 1) communication, 2) working in a group setting, and 3) self improvement

programs (to imprOve employee self esteem). One manager ﬁvored conducting all

employee training in-house and was not interested in Oﬁ-site employee training programs.
The majority of expansion managers desired speciﬁc training to overcome their

HRM problem areas. Managers who are contemplating expansion should seek out such

training.

84

 

Table 28. Employee Educational Programs Desired by Managers (20 Farms)

 

 

 

 

 

 

Subject Managers Responding
Animal Husbandry 12
Milking Procedures and Education 6
Communication 2
Working in a Group Setting 2
General Self Improvement 2

 

 

 

 

VI. Conclusions
This study indicates that expansion has potential beneﬁts in terms Of labor
productivity. Post expansion milk/FTE and DWE/cwt. milk improved over pre-expansion
levels for both initial and subsequent expander Operations as expected. These
improvements were due in part to managers abandoning more labor intensive technology
in ﬁvor of more capital intensive, but labor saving, technology. An analysis of the
capital/labor changes supported this reallocation. This reallocation, however, may require
more capital as labor saving technologies tend to be expensive. If this is done by debt
capital, the dairy is more sensitive to interest rate, output price, and input price variation.
Hmnan resource management problems changed pre- to 'post- expansion. The
problems that showed the highest increase in occurrence were those associated with
evaluating, achieving manager performance goals for the employees, ﬁnding qualiﬁed full-
time employees, and training. TO help alleviate these problems, the managers were
interested in educational programs designed to improve their HRM skills in such areas as

communication, motivation, and evaluation. Employee training programs, particularly in

85

the areas of animal husbandry and milking techniques, were desired by the mamgers to

improve their employees’ work quality.

86

Chapter VII

The Effects of Environmental Compliance, Public Relations and Zoning on Dairy
Farm Expansion

1. Introduction

Expansion managers are expanding their dairies in a landscape that is increasingly
urbanized. An expansion dairy is likely to ﬁce opposition from neighbors who are
concerned with Odor issues (Brake, et al, 1994). Many believe that ﬁrm expansion is
correlated with environmental damage. Popular full page advertorials in periodicals and on
the internet demonstrate these concerns (Turning Point Project, 1999). This changing rural
landscape has led many states to enact strict environmental quality laws (F ulhage, 1997)
and zoning restrictions on livestock production units (Bartock, 1993). For instance,
Wisconsin, with twelve farms participating in this research, have special manure
management requirements for dairy ﬁrms that exceed 1,000 animal units (700 dairy cows)
and additional site speciﬁc regulations in areas designated as a “Priority Watershed.”

This research explored how dairy ﬁrm expansion was affected by environmental,
public relations, and zoning (EPZ) issues. The following research questions are addressed:

1) What EPZ problems were anticipated by the expansion manager?

2) What EPZ problems were encountered during and after expansion?

3) Did managers who took a pro-active approach to EPZ problems encounter
less problems than those who did not?

4) What were the residential backgrounds (agricultural, rural non-agricultural
urban) of EPZ complainants?

5) What were the costs associated with environmental compliance?

87

The research propositions are:
1) Producers who anticipate environmental, public relations, and zoning
problems and take preventive countermeasures beyond those required have

less enviromnental, public relations, and zoning problems than those who
did not.

2) The rmjority of EPZ complainants have urban backgrounds.

3) The mean annualized manure management technology costs per
hundredweight Of milk for expansion dairies with less than 700 dairy cows
exceed those with more than 700 dairy cows.

Many managers are informed about potential EPZ problems prior to expansion.
Periodical, trade, and research articles have discussed expansion management problems
relating to environmental, public relations, and zoning issues. Some experienced expansion
managers and advisors recommend adopting strategies and technologies that exceed
minimum animal waste handling requirements and tO pro-actively address EPZ issues
(Sattler, 2000).

EPZ problems may increase as rural areas become more populated by residents
with little agricultural background. Understanding the background Of EPZ complainants is
important when trying to solve EPZ problems. It is unlikely that someone with an urban
background will have knowledge of how a dairy ﬁrm operates. The manager may use
public relations strategies emphasizing agricultural education when handling complaints
from people with non-agricultural backgrounds. The second research proposition

examines the proportion of complainants that had agricultural, rural non-agricultural, and

urban backgrounds.

88

Manure management and Odor reduction technology can be costly. The initial cost
of a basic manure storage system with a one year storage capacity can cost $500 per cow
(Kriegl, 1998). A lagoon cover and ﬂarner (used to reduce Odors by collecting and burning
noxious gases) cost an additional $130 per cow (Sattler, 2000). Three of the Wisconsin
managers participating in this study indicated that they selected a herd size Of less than 700
dairy cows to avoid the initial costs associated with required manure management
technology costs. Nevertheless, Fulhage estimated that the lagoon owning and Operating
costs per hundredweight Of milk decreased as herd size increased (1997). For a 100-cow
herd, manure storage and management costs were $0.43 per hundredweight of milk. For a
1000-cow herd, this number was estimated to be $0.24 per hundredweight Of milk, a
decrease of 44 percent (Fulhage, 1997). Thus, managers who make dairy size decisions
based upon the avoidance Of the costs associated with manure management requirements
may be selecting a herd size that is less eﬁcient from a manure management technology
cost basis. TO evaluate this issue, the annualized manure management technology cost per
hundredweight of milk for dairies with less than and greater than 700 cows is determined
to see if dairy ﬁrms with less tlﬁn 700 cows have higher armualized initial manure
management technology costs per hundredweight of milk than larger expansion dairies.
II. EPZ Problems Anticipated and Encountered

The expansion managers were asked whether they had anticipated post expansion
EPZ problems. Ten managers anticipated public relations problems (Table 29). Eight

producers were concerned with environmental compliance issues. Five thought getting

89

o.

zoning approval for their expansion would be difﬁcult. Five managers did not anticipate
EPZ problems.

Eleven managers indicated that public relation issues arose. These issues included
Odor complaints, losing land rental agreements post expansion, concerns about harvest-
tirne road trafﬁc, and “rumor mill” issues (unsubstantiated stories circulating about post
expansion animal death loss, ﬁnancial crises, and/or unethical treatment of animals). Five
managers experienced environmental compliance difﬁculties. These included such issues as
the amount of environmental compliance paperwork, manure spills, and waterway
contamination. Only one producer ﬁced a zoning related issue, which involved getting an
access road upgraded in order to accommodate semi-truck traﬂic. Seven managers did not
experience EPZ problems.

Of the ﬁve managers who did not anticipate EPZ problems, four encountered EPZ
problems. Three encountered public relations complaints concerning odors. A neighbor Of
the fourth manager lodged a complaint with local police concerning spilling manure on a
road.

Seven managers did not receive EPZ complaints. A common thread among these
rmnagers was the use of pre- and post expansion strategies to pro-actively deal with EPZ
problems. Five of the seven managers launched and continue to practice public relations
campaigns to educate neighbors and local ofﬁcials on dairy farming in general and their
Speciﬁc dairy operation. Two of these managers held open houses at their facilities. Three

Offered guided tours of their Operation and continues to do so. One manager participated

Table 29. EPZl Problems Anticipated and Encountered by Expansion Managers

 

 

 

 

 

 

( 20 Farms)
Anticipated Number of Number of Managers Total Number
Problem Managers Who Who Anticipated of Managers
Anticipated EPZ and Encountered Who
Problems EPZ Problems Encountered
EPZ Problems
Problems No
Problems
Environmental 8 4 4 5
Compliance
Public Relations 10 8 2 ll
Zoning 5 1 4 1
No Problem 5 4 l 7

 

 

 

 

 

 

 

‘Environmental compliance, public relations and zoning

in town and school board governance and sponsored local community events. Another
manager regularly communicated with his neighbors about EPZ issues. This manager
informs his neighbors Of manure spreading dates, does not spread on holidays or his
neighbors’ birthdays and anniversaries, and spreads manure on neighbors’ gardens for
free.

Four of the seven managers without EPZ problems adopted manure handling
technologies that exceeded their permit requirements. For example, one built concrete
runways and natural ﬁlter strips to help divert and retard run Off ﬁ'om entering nearby
streams. Another manager, whose ﬁrm is surrounded by housing developments and a golf
course, built a slurry store to make the ﬁrm more aesthetically pleasing.

Only two managers who took preventive countermeasures (in the form of public

relations campaigns or utilizing manure management technology that exceeded their
91

requirements) to minimize EPZ problems had EPZ problems. In both instances, the
manure management technology ﬁiled and odors became an issue. Since the EPZ issues
arose, one has adopted a different technology (collecting and burning off the excess gases
from the lagoon), meets regularly with neighbors, and holds guided tours of the dairy. This
manager has seen a cessation of EPZ problems. In ﬁct, his township board suggested that
he build another dairy in the township as the community is content with his operations,
and the area merchants appreciated the additional business his dairy brought to the
community. The other dairy which had ﬁiled manure management technology is currently
investigating lagoon gas burn-oﬁ’ or methane power generating technologies to help
reduce odor issues. 5

Overall, those producers who anticipated EPZ problems and took preventive
countermeasures did in fact reduce EPZ problems. Expansion managers and advisors
should consider using pro-active strategies - such as holding open houses, guided tours,
direct communication with neighbors, and/or manure handling technology that exceeds
minimum requirements — to minimize EPZ problems.
H1. The Residential Background of EPZ Complainants

Using pro-active public relations campaigns to reduce EPZ problems was
discussed in the previous section. Developing appropriate pro-active public relations
campaigns requires a general understanding of the complaining parties. For instance,
handling the EPZ complaints of someone with an agricultural background may require a

different approach than someone with a non-rural background. The non-rural background

92

complainant may require additional information concerning dairy farming and animal
waste management.

The managers were asked to identify the residential background of EPZ
complainants. The managers designated the percentage of complaints ﬁom four residential
background choices: 1) agricultural, 2) rural non-agricultural, 3) non-rural, and 4)
unknown.

Forty-six percent of the complaints were submitted by people with agricultural
backgrounds (Table 30). Complainants with urban backgrounds accounted for 29 percent
of the EPZ complaints. Seventeen percent of the complaints were submitted by people
with rural non-agriculture backgrounds. Eight percent were submitted by people of
unknown residential background.

Table 30. Residential Background of EPZ Complainants ( 20 Farms)

 

 

 

 

 

 

Residential Background Percentage of Complaints
Agricultural 46
Rural Non-Agriculture 17
Urban 29
Unknown . 8

 

 

 

The majority of the EPZ complainants did not have non-rural backgrounds.
Nevertheless, this result may be a function of the proportion of agricultural, rural non-
agricultural, and urban background residents. For instance, if the number of agricultural
background residents greatly outnumbers urban background residents, plausible scenarios

exist where the total number of agricultural background complainants exceed those of the

93

non rural complainants, but the proportion of agricultural background residents who
complain is less than the proportion of urban complainants.

This result, however, shows the importance of developing strategies to address the
EPZ concerns of residents with different backgrounds. Expansion managers and advisors
should develop EPZ problem strategies that address the concerns of people with varied
backgrounds.
IV. Annualized Manure Management Technology Costs

Advanced manure management technology can reduce EPZ complaints as
described in Section H of this chapter. Furthermore, many states regulate the manure
management and storage technology of dairy ﬁrms that exceed a certain herd size. As
indicated earlier, the initial manure management technology cost per cow can be large.
Nevertheless, this ownership and Operating costs per hundredweight of milk actually
decrease as herd size increases (Fullhage, 1997). Those who select a smaller expansion
herd size to avoid higher initial manure management technology outlays, as three
managers did in this study, my select a herd size that Offers less manure management
technology cost efficiency resulting in higher costs per cwt than a larger herd size.

The annualized cost of manure management technology‘ per 100 pounds of milk
was calculated to determine if herds with less than 700 dairy cows have higher annualized
rmnure management technology costs per hundredweight of milk than the more regulated

dairies with more than 700 dairy cows.

' Includes only those costs associated with the purchase of manure management
equipment and ﬁcilities and not the annual operating costs.

94

Ten managers submitted suﬁicient data to be considered for this research Of the
producers who did not supply manure mamgement technology cost estimates, some chose
not to because of privacy issues, others did not expand upon pre-expansion manure
storage ﬁcilities, and others had these costs integrated into the overall expansion costs.

The dairies were divided into two groups. The “small” group consisted of six
ﬁrms with an average herd size (both milking and dry cow herds) of 394 cows. The
“large” group consisted of four ﬁrms with an average herd size of 1070 cows. The initial
manure management technology costs were amortized using each ﬁrm’s pre-tax weighted
average cost of capital2 over a ten year period. When there was insufﬁcient data to
calculate an individual ﬁrm’s weighted average cost of capital, the mean weighted average
cost of capital for all ﬁrms was used. Mean amortized manure management technology
costs were $0.11 per hundredweight of milk for the small group and $0.08 per
hundredweight of milk for the large group (Table 31), indicating that economics of size
might exist for manure management technology costs. While the amortized manure
management costs per hundredweight for the small group exceeded those of the large
group, the small group’s mean was not signiﬁcantly greater than the large group’s mean
at the 95 percent signiﬁcance level.3

It is unfortunate that the sample size for this analysis was small (n=10). If these

results hold for the general population, however, managers should not be concerned with

 

2 Wittenburg, E. Dain/ Proﬁtability and Production Eﬂiciency Project: Enterprise
Accounting an Dairy Farms. 2001. This calculation appears in Chapter IX.

3 tmﬁ 0.432 <tma=001 ,= 1.860

95

the additional manure management technology costs associated with herds in excess of
700 animal units. The average manure management technology costs per hundredweight

of milk for ﬁrms with less than 700 cows appears to be as great as or exceeds the average

 

 

 

 

 

 

for those with more than 700 cows.
Table 31. Annualized Manure Management Technology Cost Comparison
(10 Farms)
Large Group1 Small Group2

Mean $0.08 $0.11
High ' $0.17 80.34
Low $0.04 $0.03
Std. Deviation 0.06 0.12
Sample Size 4 6

 

 

 

 

 

' Herds in excess of 700 dairy cows. 2 Herds with less than 700 dairy cows.
V. Conclusions

Producers who took preventive countermeasures (public relations campaigns and
more advanced manure management technology than required for permitting purposes)
did have more success at reducing EPZ complaints. The rmjority of the complainants were
of agricultural background instead of urban background as anticipated. These two facts
show that expansion managers and advisors should undertake preventive countermeasures
that encompass the concerns of all rural residents.

Despite the ﬁct that larger herds may ﬁce greater public and governmental
scrutiny concerning environmental compliance, the amortized manure management
technology costs per hundredweight of milk for ﬁrms with less than 700 cows was as
costly if not greater than ﬁrms with less than 700 cows. Expansion managers who make

96

herd size decisions based on the avoidance of higher environmental compliance standards
should investigate the difference in manure management technology costs per
hundredweight. If the results of this study hold, a larger but more regulated herd size may

have lower amortized manure management technology costs per hundredweight of milk.

97

Chapter VIII
The Eﬂ'ects of Expansion on Specialization, Outsourcing and Internalization
I. Introduction

In Chapter V, many managers attributed their success in maintaining or increasing
post expansion milk production to improved labor and management specialization. One
method to increase specialization is to outsource activities and enterprises and redirect
those activity’s labor, management and ﬁnancial resources to other activities of the ﬁrm
Another method to improve dairy specialization is to internalize the dairy enterprise
activities that were previously outsourced due to the costs of the activity relative to the
ﬁrms size.

Why are some activities outsourced aﬁer expansion while others are internalized?
Goodhue and Rausser (1997), among others, identiﬁed three factors that are critical to the
acceptance or rejection of outsourcing (internalization). Activities are outsourced
(internalized) if the ﬁrm’s production costs decrease, the product quality can be identiﬁed
and controlled, and/or coordination costs are reduced. For some activities, such as forage
harvesting, expansion may create outsourcing opportunities. Assuming the expansion
manager has a comparative advantage in milk production over forage harvesting, forage
production costs may decrease by outsourcing using a custom harvester.

Some activities, such as veterinary care, are more readily internalized as the dairy
expands. For instance, it would be cost prohibitive to maintain a veterinarian on-staﬁ‘ for a

marlagerwi’tha100cowherdbutlesssoforamanagerwitha1,000cowherd.

This research examined ﬁve main issues related to outsourcing, specialization, and

98

internalization including: 1) the degree of specialization, 2) the types of activities
outsom'ced post expansion, 3) the popularity of outsourcing, 4) whether managers
outsource management skill by hiring external consultants, and 5) whether expansion
permits the internalization of activities previously outsourced. The research propositions
for this chapter are that:

1) dairy ﬁrms become more specialized after expanding;

2) managers expand the use of outsourcing after expanding;

3) managers hire outside management expertise to supplement and

complement their own aﬁer expanding; and,

4) expansion permits the internalization of some activities that were

previously outsourced.

Identifying outsourced activities, consulting types used, and internalized activities
will beneﬁt future expansion managers and advisors by providing better information on
how to improve the post expansion dairy specialization by using this option.

II. Measuring Specialization
. Sumner and Wolf quantiﬁed dairy specialization and diversiﬁcation by US. dairy
Producing regions using various methods (2001). One method used to measure
diversiﬁcation and, conversely, specialization was the diversiﬁcation index:
Diversiﬁcation = (Cash ﬁrm sales - Milk Revenue) / Cash ﬁrm sales.
The lower the diversiﬁcation index, the more specialized the dairy. SW 311d Wolf

eStimated that the average diversiﬁcation index for Upper Midwest dairies was 0.21 and

0.19 for the US. as a whole.

99

The average pre- and post expansion diversiﬁcation index (DI) was estimated for

the ﬁrms participating in this research (Table 32). Pre- expansion, the DI ranged ﬁom

0.05 to 0.34 and averaged less than the Upper Midwest dairy region at 0.17. The average

post expansion DI decreased slightly to 0.16 after expanding. The pre-expansion DI was

not signiﬁcantly greater than the post expansion DI at the 95 percent signiﬁcance level.l

Six ﬁrms became more specialized and decreased their DI ﬁom 0.23 to 0.16. One ﬁrm’s

DI remained the same at 0.09 after expanding. Six ﬁrms became more diversiﬁed and

increased their DI ﬁom 0.13 to 0.17. Of the ﬁrms that became more diversiﬁed, it is

important to note that they were initially relatively more specialized. Four of the ﬁrms that

became more diversiﬁed had pre-expansion herds of 125 cows or less and operated only

enough acreage to meet forage and grain requirements. Post expansion, these ﬁrms were

in a position to have more cash crop sales because of expanded acreage and higher yields.

Table 32. Pre- and Post Expansion Diversiﬁcation Index Results ( l3 Farms)

 

 

 

 

 

 

 

 

Pre-expansion Post Expansion
Mean 0.17 0.16
Maximum 0.34 0.32
Minimum 0.05 0.08
Standard Deviation 0.09 0.08

 

On average, expansion did not affect specialization as measured by the

diversiﬁcation index. Using other methods of measuring diversiﬁcation — such as the

Herﬁndahl Index, the entropy index, and the specialization index -— may have shown

—_

'tmz. = 0.299 <tm,.,,,,, = 1.711

100

 

otherwise. Unfortunately, data limitations did not permit conducting these analyses.
III. Pre- and Post Expansion Outsourcing

The managers were asked to identify their pre- and post expansion outsourced
activities and enterprises (Table 33). Pre-expansion, nine managers engaged in outsourcing
and averaged 1.4 outsourced activities. “Forage and/or grain production” and “heifer
raising” were each mentioned three times by the managers and were the most common
outsourced activities. Two managers outsourced “forage and/or grain harvesting,” making
it the third most common outsourced activity. Artiﬁcial insemination, cattle procurement,
manure hauling and application, parlor maintenance, and payroll were each mentioned
once by the managers.

Post expansion, nineteen managers engaged in outsourcing with an average of 2.9
outsourced activities per ﬁrm. Thus, the second proposition was supported by the data.
After expansion, more managers engaged in outsourcing and more activities were
outsourced per farm. Many of the nineteen nﬁnagers who outsourced activities did so for
cost advantage reasons. As one manager stated, “When you expand, you have to know
your cost of production for your diﬁ‘erent enterprises, and if you ﬁnd someone better to do
something, hire them to do it.” Other managers used outsourcing to reduce their capital
investment requirements for their expansion dairy. For instance, by having other ﬁrms

conduct harvesting activities, the expansion managers were able to forgo investing in

forage and grain harvesting equipment.

101

Table 33. The Managers’ Use of Pre— and Post Expansion Outsourcing

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

( 20 Farms)
Outsourced Activity Pre-expansion Post Expansion
Forage and/or Grain Harvesting 2 12
Heifer Raising 3 9
Calf Raising 0 6
Manure Hauling and Application 1 6
Forage and/or Grain Production 3 5
Spraying (Crep) 0 3
Artiﬁcial Insemination 1 2
Planting 0 2
Parlor Maintenance 1 l
Feeding 0 1
Bedding Stalls 0 1
Payroll 1 1
Tail Chalking (for estrus detection) 0 1
Cattle Procurement 1 0
No Outsourced Activity 11 1

 

The most common post expansion outsourced activity was “forage and/or grain

harvesting,” which was outsourced by 12 managers. “Heifer raising” was outsourced by 9

ﬁnns, making it the second most common outsourced activity. Tied for the third most

cormnon outsourced activity, “calf raising” and “rmnure hauling and application” were

each mentioned 6 times by the managers. “Forage and/or grain production” was

mentioned by ﬁve managers.

102

 

Of all the outsourced activities -— bedding stalls, feeding, and tail chalking -— were
perhaps the nrost unique. On each of the ﬁrms where these activities were outsourced,
unique circumstances arose which made outsourcing feasible. For example, in the case of
the outsourced feeding activity, a neighboring ﬁrmer approached one of the expansion
managers with a proposal. The neighboring farmer had purchased a truck-mounted TMR
mixer wagon and had an employee who wanted to feed cows on a full time basis.
Unfortunately, the neighboring farmer did not have a large enough herd to acconrrnodate a
full time feeder. The manager and the neighboring ﬁrmer reached an agreement where the
neighboring ﬁrmer would feed the expansion manager’s cattle for a ﬁxed fee per day. This
allowed the expansion manager to redirect mixer truck funds and labor to higher valued
activities.

While few in number, isolated outsourcing problems arose. Some managers
experienced diseased or poorly grown heifers. One manager experienced poorer post
expansion alﬁlfa quality. In these instances, the contractual arrangements concerning
identifying and controlling quality were not well speciﬁed. For example, the one manager
who did not outsource any activity after expanding used to outsource his heifer raising
activity. After a group of heifers came back diseased and obviously poorly grown, the
manager could not negotiate a settlement with the grower as the grower was merely paid
for raising the animals and not for quality. Similarly, the manager who experienced poorer
forage quality did not specify the harvesting schedule and did not have incentives
incorporated into the contract to ensure high quality forages. These examples highlight the

importance of establishing quality standards and incentives when negotiating outsourcing

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contracts.

Table 34. Additional Outsourcing Desired by Expansion Managers (20 Farms)

 

 

 

 

 

 

 

 

 

 

 

Activity Number of Managers Responding
Crops 2
Human Resource Management (HRM) 2
Manure Hauling and Application 2
Calf Raising 1
Feed (Manuﬁctured TMR) 1
Heifer Raising 1
Marketing 1
Parlor Management and Maintenance 1
No Additional Outsourcing Desired 10

 

 

 

Another type of outsourcing problem was the inability to outsource certain
activities. The managers were asked to identify activities that they wished to outsource but
could not do so (Table 34). Crop production, HRM and manure hauling and application
were each mentioned twice by the managers. Other activities mentioned were calf raising,

a custom TMR service, heifer raising, marketing, and parlor management and maintenance
service. The inability of some managers to outsource these activities were caused by a lack
of ﬁrms offering the services desired by the managers. Despite numerous calf raising
services in one manager’s region, one manager outgrew his pre-expansion calf raisers
capacity and was unable to ﬁnd a calf raising service large enough to accommodate the
needs of his 1,000 cow herd. Having numerous ﬁrms raise his calves was deemed too

eXpensive to coordinate. Another manager wanted to enhance biosecurity by ﬁnding a

104

heifer raiser willing to exclusively raise his heifers but ﬁiled to do so. Despite numerous
marketing services available, one manager desired a service where the consultant was a
paid a ﬂat fee instead of paying per commodity or futures market transactions. He was

unable to ﬁnd a ﬁrm with such a service.

The outsourcing experiences, both positive and negative, of these expansion
managers imply that the criteria deﬁned by Goodhue and Rausser and other researchers to
make the outsourcing decision should be followed. To have successful outsourcing
programs, managers should analyze their operations to determine if an enterprise or
activity can be better performed by another ﬁrm. This entails identifying the desired quality
of the product or activity to be potentially outsourced, determining the ﬁrm’s production
costs for that activity, and ascertaining whether there are ﬁrms offering such services and
whether the outsourcing can be easily coordinated. Outsourcing contracts specifying the
fees for the service and the quality of the service and the incentives (disincentives) for
producing (ﬁiling to produce) the given quality should be developed. By making the
decision in such a manner, the manager increases the probability that an outsourcing
endeavor is successﬁrl. To ﬁcilitate this process, managers and advisors may need
additional training or the services of outside expertise in the areas of enterprise
accounting, negotiating and contracting.

Another concern expressed by expansion dairy managers is the lack of ﬁrms to
supply desired services. As an expansion manager indicated, the service infrastructure to
support large dairy operations in the Upper Midwest is often lacking. Thus, when siting a

dairy, expansion managers should consider the availability of ﬁrms willing to conduct

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outsourced activities.
IV. Consulting Services Used by Expansion Dairy Managers

With the complexities associated with dairy ﬁrm management, even highly
specialized dairies, it is difﬁcult for a single manager to manage all aspects of a dairy
operation and to keep abreast of the new developments. One method to alleviate this
problem, hiring specialized nnnagers, was alluded to earlier. Unfortunately, this is not
always cost effective for every management issue. In these circumstances, outsourcing the
management expertise by hiring consultants may be required.

Managers were asked to identity the consulting services they contracted to assist in
the management of their ﬁrm. They were also asked to indicate whether the source of the
consulting service was an agribusiness (ﬁrms offering consulting services in conjunction
with purchased agribusiness products), independent agency (a ﬁrm specializing in only
consulting services), lender, extension service or industry network panel (an advisory
panel made up of individuals from the four consulting sources).

Managers did hire consultants to supplement and complement their own
management expertise. The most common consulting service was nutrition (Table 35).
Nineteen farms used nutrition consultants. Eleven managers used nutrition consultants
from the agribusiness ﬁrms of which they purchased their feed products. Seven managers
used nutrition consultants who operated independent agencies. One manager used the
extension service for his outside nutrition expertise.

Eighteen ﬁrms hired outside ﬁrm management expertise. Agribusinesses supplied

most (8) of the ﬁrm consulting services. Five managers utilized the ﬁrm management

106

expertise offered by extension programs. Three managers used the services of independent

consultants, and two used an industry network panel.

The third most common consulting service type was agronomy. Thirteen managers
used agronomy consultants. Seven of these consultants were employed by agribusiness
ﬁrms, ﬁve were independent agronornists, and one was an extension specialist.

Table 35. Consulting Services and Sources Utilized by Managers ( 20 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

Consulting Agri- Independent Lender Extension Industry Total

Service business Agency Network

Type Panel

Nutrition 1 l 7 0 l 0 19
Farm 8 3 0 5 2 18
Management

Agronomy 7 5 0 l 0 13
Financial 0 5 1 0 0 6
Accounting 0 2 2 0 0 4
Parlor l 2 0 0 0 3
Management

Genetics 1 0 0 0 0 1
Forestry 0 1 0 0 0 1
HRM 0 l 0 _ 0 0 1
Marketing 0 0 0 l 0 l

 

 

 

 

 

 

 

 

In addition, six managers hired ﬁnancial management consultants. Five of the
ﬁnancial management consulting services were offered by independent consulting agencies
and one was employed ﬁom a lending institution. Four managers used an accounting

consulting service for income tax purposes. Three used parlor management consulting

107

services. Forestry, genetics, HRM, and marketing consulting services were identiﬁed once
by the managers.

Agribusinesses supplied the most consulting services. Agribusiness-based
consulting sources were employed 29 times; however, this number may be inﬂuenced by
selection bias. Ten of the Wisconsin expansion dairy ﬁrms were initially identiﬁed by
contacting an agribusiness that oﬁ‘ers ﬁrm and expansion consulting services that are tied
to product sales. The second most numerous source of consulting services were
independent agencies. Extension-based consulting services were used on eight occasions.
Interestingly, only the Michigan ﬁrms utilized extension-based consulting services. Three
managers employed lender-based consulting services, and 2 used a dairy industry network
panel.

It is interesting to note the lack of use of extension consulting programs, which are
typically available for free or at lower costs when compared to consulting services oﬁered
by other entities. Unfortunately, why the managers chose on source of consulting over
other sources was not determined. Thus, it is unknown if the managers perceive the
extension-based consulting services as being of lesser quality, if the extension service is
unable to service the needs of expansion dairy rmnagers, or if the extension service does
not desire to pursue the expansion dairy clientele.

V. Internalization

For some dairy activities — the production, controlling, and coordimting costs

associated withconductingthe activitywithinthe ﬁrmdecrease as dairiesexpand. The

pmposeofthissectionistodetermmewhethermamgerswereabletohuemaﬁze

108

previously outsourced activities after expansion.

Milk marketing and milk hauling activities were internalized on seven dairies.
These activities became feasible to internalize for four reasons. First, these dairies had
reached sufﬁcient size to pump milk from the coolers directly to semi truck milk carriers.
Thus, the costs associated with having to purchase a bulk milk storage tank and could be
forgone. Second, by using leased semi truck milk carriers and hired drivers, the milk
manager could afford to ship milk beyond his pre-expansion milk marketing region
(shipping milk beyond 500 miles was not uncommon with these ﬁrms). This eliminated
the managers reliance on a local milk hauler to pick up his milk and take it to a nearby
milk plant. Third, the coordinating costs associated with internalized milk marketing were
reduced. Because expansion nﬁnagers typically delegated operational duties to other
employees, the manager could afford to spend more time to solicit more lucrative milk
contracts. Fourth, the managers could efﬁciently solicit milk contracts from more milk
companies through the use of email, the internet, and ﬁx machines. One manager became
so adept at initial milk marketing that he started an initial milk marketing and hauling
service for ﬁve other large dairies in his region.

Another example of internalizing is being of sufﬁcient size to be able to hire
internal technicians for highly skilled activities. Two 1,000 plus cow dairies found that
they had reached a suﬂicient size to hire on-staﬁ veterinarians. Similarly, two of the dairy
managers who desired to continue expanding found it cost effective to hire on-staﬂ‘
eXpansion project coordinators.

The last example of internalization concerned the manager who could not ﬁnd a

109

calf raiser of sufﬁcient size to raise all of his calves. Aﬁer realizing that the coordination
costs associated with having numerous growers raise his calves were too high and that
other large dairy managers faced the same problem, the manager developed an internalized
calf raising enterprise to raise his and other large dairy managers’ calves.

Thus, the research proposition that expansion permits the internalization of some
activities that were previously outsourced proved to be true. One potential implication
associated with internalized milk marketing concerns potential milk price advantages.
Expansion managers who are unable or unwilling to internalize initial milk marketing may
ﬁce a competitive disadvantage concerning milk price. Another implication concerns
siting expansion dairies. Dairy managers who desire to internalize initial milk marketing
will place a higher priority on sites with better access to highways and interstates. Another
implication concerns the equipment demand of expansion dairies. If managers continue to
internalize initial dairy marketing and hauling, the need for equipment such as on—farm
bulk milk storage tanks will be reduced. Another possible implication concerns the need
for producer education concerning milk marketing, negotiating, contracting, arbitrage
theory, and transshipment optimization.

The implications of internalizing veterinary and expansion project coordination
activities indicates that as dairies grow in size, they will be less reliant on traditional
sources of these technically skilled activities. Thus, suppliers of these skills may desire
adjusting their strategies and tactics to continue doing business with large expansion
dairies.

110

VI. Conclusions

Specialization, as measured by the diversiﬁcation index, did not increase as
expected. Part of this lack of increase in specialization can be attributed to small, very
specialized pre-expansion dairy ﬁrms having surplus crops to sell once they expanded.

Dairy managers practiced outsourcing, hiring consultants and internalization alter
expanding. The two most common activities outsourced were “forage and/or grain
harvesting” and “heifer raising.” Should expansion managers continue to desire
outsourcing activities, a larger outsourced service industry and additional manager training
concerning enterprise cost accounting, negotiating, and contracting may be needed.

The most common consultant service was “nutrition” followed closely by “ﬁrm
management.” The most common sources for these services were agribusiness and
independent agencies. The lack of use of extension-based consulting services may indicate
a need for extension services to inquire as to why they are not servicing the consulting
needs of expansion dairy clientele.

The most cormnon internalized activity was initial milk marketing and hauling. By
internalizing these activities, the managers were able to arbitrage milk price discrepancies
between milk regions. Should internalization of initial milk marketing and hauling
continue, expansion managers may have a milk price advantage over dairies which are
unable or unwilling to internalize the activity, a reduced demand for such equipment as on-
ﬁrm bulk milk storage tanks, a reduced demand for local milk marketing cooperatives,
and a higher demand for expansion dairy sites with easy access to highways and

interstates. To more readily internalize milk marketing and hauling activities, expansion

111

mamgers may desire additional training concerning milk marketing, negotiating.

contracting, arbitrage theory, and transshipment Optimization.

112

Chapter IX

The Financial Implications of Expansion

I. Introduction
A dairy expansion requires a substantial ﬁnancial commitment. The dairy managers

in this study invested up to $5,500 per cow to build new dairy ﬁcilities, purchase
equipment and cattle. Typically, an expansion requires additional debt. Dairy managers
and lenders are concerned with post expansion ﬁnancial performance. This chapter
examines how the expansion ﬁrms were ﬁnancially affected by expansion by examining
pre- and post expansion solvency ratios, proﬁtability measurements, and estimating the
expansion net present value (NPV) and internal rate of return (IRR).

The following research propositions are explored in this chapter:

1) The relative proportion of debt used to ﬁnance assets increases with
expansion.

2) Dairy ﬁrm proﬁtability increases with expansion.

3) Initial expanders, whose initial herd size is typically smaller than subsequent
expanders, experience a larger decrease in production costs.

4) Dairy operations with a pre-expansion debt/cow ratio of $2,000 or less
and a post expansion debt/cow ratio of $3 ,000 or less are ﬁnancially more
successﬁrl than herds with less than $3,000 debt/ cow.

As dairies expand, managers use internal sources of funds, acquire new partners to

provide additional capital, or use debt to ﬁnance the expansion activities. Solvency refers

to the proportion of debt and equity used to ﬁnance assets. Firms who use more debt are

113

less solvent than those that use less debt. The ﬁrst research proposition examines how
expansion aﬁ‘ects solvency.

Two reasons for expansion offered by the managers were to increase income and
to decrease the production cost per hundredweight of milk. Jones, among others, showed
that the production cost per hundredweight decreases as herds size increased (1997). For
herds expanding ﬁom 50 to 300 cows with a 22,000 lb herd average (a production level
comparable to the average production level of this study), the production cost per
hundredweight decreased from $14.75/cwt to $13.50/cwt. The cost continue to decline at
a decreasing rate through a 1,000 cow herd size. Thus, the initial expanders should
experience a greater decrease in production cost per hundredweight and a greater increase
in proﬁtability per cow than subsequent expanders. Research propositions 2 and 3 address
these issues.

One common benchmark used to evaluate potential expansion dairy farm ﬁnancial
performance is debt per cow. Cappuzzi, Kohl and Rogers suggested that pre-expansion
debt/cow should not exceed $2,000 per cow and post expansion debt/cow should not
exceed $3,000 per cow (1994). Research Proposition 4 examines how debt per cow
affects ﬁrm ﬁnancial performance.

II. Financial Deﬁnitions

Solvency ratios include the Debt to Asset Ratio (D/ A), Leverage Ratio and the
Equity Multiplier. As they all measure solvency, only the D/ A ratio will be used in this
analysis. The D/A measures creditor claims against the ﬁrm. The D/A is calculated by

dividing a ﬁrm’s total liabilities (debt) by the value of the ﬁrm’s total assets.

114

Proﬁtability refers to the ﬁrm’s ability to generate a net return above expenses
from the use of its resources. Proﬁtability measurements exanrined in this research include
Net Farm Income (NFI), Return to Operators Capital and Management (ROCM), and
Management Income (MI). The ﬁrms’ Return on Assets (ROA) and Return on Equity
(ROE) are also examined.

NFI isameasureofaccrualincomeeamedandisthemost ﬁmiliarproﬁtability
measure among dairy ﬁrm managers. It is calculated by taking the Gross Cash Farm
Income less the operating expenses and adding or subtracting the change in inventory,
market animals, accounts receivable (payable), and capital adjustments. A drawback of
NFI is that it doesn’t take into account the labor provided by the manager and his or her
family, nor does it charge for his or her investment in the business.

The ROCM accounts for unpaid manager and family labor. This proﬁtability
measure is calculated by taking the NFI and subtracting a charge for the unpaid labor. For
this research, the charge assigned for the pre-expansion unpaid family labor was equal to
the wage earned by the post expansion hired employee conducting the psimilar activity. To
estimate the opportunity cost of the manager partner’s labor, a salary was estimated by
adding $5,000 to the herd manager salary (a lower level management position on large
dairies).

Management Income (MI) accounts for unpaid labor and a return on the
operator’s equity. MI is calculated by taking the ROCM and subtracting a charge for the
mamger’s equity invested. In this research, the charge for the owner’s equity was

calculated by multiplying the post expansion average net worth by the ﬁrm pretax

115

weighted average cost of capital (WACC). The WACC is the discount rate necessary to
compensate both debt and equity holders for what they could earn elsewhere. The pre-tax
version is calculated as follows:

WACC = (E*K0 +((D..*Km ) + (D..*K.T0)/(E+DST+D.L)
where E refers to the amount of owner equity, KL is the ﬁrm’s estimated cost of leveraged
capital, DST is the ﬁrm’s short term debt, and KmR is the estimated short term interest
rate. DLT is the ﬁrm’s long term debt obligation, and K1LTR is the estimated long term
interest rate.
KL was calculated as follows:

Kl. = Rar + (KM'RRF) 131
where RRP is the risk free rate of return (1998 T-bill Average Rate = 4.89 %), KM is the 20
year average return associated with the S&P 500 (18.38 %), and 0L is the risk adjustment
factor for a leveraged dairy ﬁrm with 1

BL = Bu (1+D/E).
BU refers to the unleveraged dairy risk adjustment ﬁctor, and D/E is the ﬁrms debt to
equity ratio. The DU for Michigan dairy ﬁrms participating in Michigan State University
Extension Telﬁrm was estimated to be 0.2321 (Wittenburg, 2001): Each ﬁrm’s pre- and

after tax WACC, BL and KL is shown in Table 36.

116

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 36. Before and After Expansion WACC, [3L and KL ( 14 Farms)
Farm Pretax WACC After Tax BL KL
(%) WACC
(70)
Before After Before After Before After Before After

101 8.49 8.47 5.43 5.42 0.27 0.27 8.55 8.54
103 8.63 10.43 5.78 6.15 0.29 0.62 8.77 13.32
104 8.55 9.20 6.84 6.16 0.28 0.36 8.65 9.76
105 10.14 9.93 8.11 6.65 0.52 0.46 11.94 11.15
106 8.23 10.48 5.27 6.18 0.25 0.66 8.24 13.81
108 9.02 10.57 6.04 6.24 0.33 0.71 9.39 14.48
113 8.64 10.31 6.92 ' 6.91 0.29 0.59 8.80 12.87
201 10.38 10.25 6.12 8.20 0.61 0.56 13.06 12.39
202 10.47 10.15 7.02 5.62 0.65 0.44 13.61 10.79
204 8.14 8.19 5.45 6.55 0.24 0.25 8.14 8.20
205 10.47 10.15 7.01 8.12 0.64 0.52 13.52 11.93
206 8.71 8.89 4.82 4.93 0.30 0.32 8.89 9.22
207 8.22 8.05 4.85 4.46 0.25 0.23 8.24 8.05
208 10.13 10.28 6.79 6.89 0.50 0.55 l 1.69 12.31

 

 

 

 

 

 

 

 

 

 

The ROA, which measures the amount of proﬁt generated per dollar of asset, is

calculated by taking the Return on Farm Assets (RFA; RFA = NFI + Interest - Managing

Partner Labor) and dividing it by the average total asset value measured using market

value. The ROE, which measures the amount of proﬁt generated per dollar of equity, is

calculated by taking the RFA minus interest and dividing this number by the average

market basis equity value.

117

 

A NPV calculation is used to determine how much additional value an investment
(I) generates in present dollars after accounting for the opportunity cost of the investment.
The NPV calculation takes an investment’ 5 aﬁer tax cash ﬂows and adjusts them for the
time value of money by the after tax WACC. For this research, it was assumed that the
ﬁrms were closely held business organizations and not C-corporations. Thus, the after tax
WACC formula used was:

WACCAM m = WACC( 1 -t).1
The initial investment costs are then subtracted from the present value of the cash ﬂows
(PVCF) to determine the NPV:

NPV = (PVCF) - I

= (((CF,/(1+k)) + ((CF2/( 1+k)2) + + ((CFn / (1+k)“)) - I.

The internal rate of return (IR) is the discount rate that makes the NPV
calculation equal to 0:

G’VCF) - I = 0,
and measures the rate of return the investment generates.
III. Balance Sheet, Price and Cost Adjustments

Because the expansions in this study occurred at different times throughout the
1988 - 1998 period, all balance sheet values, prices and costs were adjusted. All milk
revenues were adjusted to a gross milk price of $13.50 per hundredweight. Other prices,

balance sheet values and costs were adjusted to 1998 levels. The procedures for making

 

' The rmrginal tax rate was calculated using 1998 IRS guidelines for a married couple
ﬁling jointly without dependents. A ﬁve percent state income tax was also assumed.

118

these adjustments were discussed in Chapter II.

For the NPV and IRR analyses, the annual growth rate for milk production was set
at 2.41 percent per year, which was the annual growth rate in the average US. DHIA
RHA for the 1990 -1998 period. The growth rate in expenses was set at 2.14 percent,
which was the average growth rate in production costs for the 1990 - 1998 period (NASS,
2000).

IV. The Effect of Expansion on Firm Solvency

Fourteen ﬁrms had suﬂicient data to conduct a ﬁnancial analysis. The mean herd
size for the fourteen ﬁrms increased ﬁom 271 cows to 472 cows, an increase of 74
percent. The market value assets increased by 48 percent ﬁ'om a pre-expansion market
value mean of $2,243,000 to $3,309,000 (Table 37). Post expansion asset value ranged
from $618,000 to $10,851,000. The expansions were ﬁnanced through a mean increase in

liabilities of $617,000 and a mean increase in equity of $449,000. Post expansion liabilities

 

 

 

 

 

 

Table 37. Average Expansion Farm Balance Sheet Values ( 14 Farms)
Assets ($1,000)l Liabilities Equity D/A
($1,000) ($1,000) (7.)
Before After Before After Before After Before After
Mean 2,243 3,309 706 1,323 1,537 1,986 0.313 0.434
High 6,208 10,851 3,978 5,091 4,612 5,838 0.641 0.673
Low 296 618 31 34 137 263 0.036 0.007
Std. Dev. 2,] 14 2,968 1,056 1,355 1,554 2,065 0.232 0.228

 

 

 

 

 

 

 

 

 

 

‘ Market Valuation. All numbers adjusted to reﬂect 1998 dollars.

averaged $1,323,000, ranging ﬁom $34,000 to $5,091,000. Mean post expansion equity

was $1,986,000 and ranged from $263,000 to $5,838,000.

119

 

D/A increased from a pre-expansion mean of 0.3 13 to a post expansion mean of
0.434 across ﬁrms. Post expansion D/A ranged from 0.007 to 0.6738. Although the
proportion of debt used to ﬁnance the expansion did rise, the increase was insigniﬁcant at
the 95 percent signiﬁcance level.2 One reason the debt proportion did not increase as
much as expected was that 7 of the 14 managers used proportionately more equity than
debt capital to ﬁnance their expansions. Three managers increased their equity capital
through owner contributions by the expansion manager. Four expansion managers added
either ﬁmily or non ﬁmily partners.3
V. The Effect of Expansion on Net Farm Income

Table 38 displays the effect of dairy ﬁrm expansion on NFI as expressed on a per
ﬁrm, per cow, and breakeven price basis. Pre-expansion NFI averaged $104,560, with
NFI ranging from -$42,010 to $391,440. Post expansion, the NFI per ﬁrm increased to
$141,320. Eight ﬁrms increased their NFI aﬁer expanding. Only one ﬁrm experienced a
negative post expansion NFI, which was -$50,720. The highest post expansion NFI was
$446,790. While the NFI per ﬁrm increased, the post expansion mean was not
signiﬁcantly greater than the pre-expansion mean at the 95 percent signiﬁcance level‘.

NFI per cow actually decreased following expansion. Pre-expansion, mean NFI per

cow was $389 and ranged from -$42 to $1,339. Post expansion, the mean NFI per cow

 

2 t “FD,“ = 1.392 <t mp0,,” = 1.706; p-value = 0.910
3 Pre-expansion, the non ﬁrnily partners tended to be neighboring ﬁrmers who had similar

pre-expansion ﬁrm characteristics and ﬁnancial standing as the expansion manager’s
ﬁrms.

’t.....,-_,,,,, =0.809 <tm,,_05,26=1.706;p-value =0.775
120

was $299 and ranged from -$204 to $620. The pre-expansion mean NFI per cow was not
s' ' cantly greater than the post expansion mean at the 95 percent signiﬁcance level.5
Pre-expansion, the NFI breakeven price, the gross milk proice at which NFI equals
0, ranged from $9.63 to $14.68 with a mean of $12.20 per hundredweight. Post
expansion, the mean NFI breakeven price rose to $13.29, ranging ﬁ'om $12.06 to $15.32.
The post expansion NFI breakeven price was signiﬁcantly greater than the pre-expansion

mean at the 95 percent level.‘5

 

 

 

 

 

 

Table 38. The Effect of Expansion on Net Farm Income ( l4 Farms)
NFI N F] NFI Based Breakeven
($1,000/farm) (Slcow) Price ($/cwt)
Before After Before After Before After

Mean 104.58 141.31 389 299 12.20 13.29
High 391.44 446.79 1,339 620 14.68 15.32
Low -42.01 -50.72 -42 -204 9.63 12.06
Std. 106.90 132.17 417 235 1.35. 0.85
Dev.

 

 

 

 

 

 

 

 

The decrease in NFI per cow and the increase in NFI breakeven price may appear

initially alarming. It is important to note, however, that NFI per ﬁrm increased by

$36,730. Although the expenses appeared to increase per cow and per cwt of milk post

expansion, because the ﬁrms grew in size, the NFI was greater.

5 t “n.5,... = 0.704 < t m,,_,,,,, =1.706;p-value 0.754

6t“¢'.05,26 = 2.557 >tmu-.os’26= 1.706

121

Furthermore, the apparent decrease in proﬁtability per cow and per hundredweight

 

of milk can be attributed to two ﬁcts. First, as can be expected with expansions, there
was more interest and depreciation expense per cow and per cwt of milk after expanding.
Depreciation ( a non cash outlay) and interest expense increased by $321 per cow or
$1.08 per cwt of milk. Second, many of the expansion managers provided much of the
pre-expansion labor needs. Post expansion, hired employees provided the labor. As the
NFI calculation does not provide for unpaid labor, the post expansion NFI per cow and
per cwt of milk calculations more adequately reﬂects labor expense. Because of these
ﬁcts, the NFI comparison may not be very meaningful.
VII. The Effect of Expansion on Return to Operators Capital and Management

The pre-expansion ROCM per ﬁrm averaged $8,860 and ranged ﬁom -$142,200
to $347,910 (Table 39). After expanding, the farms mean ROCM was $31,580 and ranged
from -$168,500 to $355,640. The post expansion mean ROCM was not signiﬁcantly
greater than the pre-expansion mean at the 95 percent level.7

Pre-expansion ROCM per cow averaged $5 per cow and ranged ﬁom -$688 to
$542. Post expansion, ROCM per cow ranged from -$662 to $502 and averaged $67 per
cow. Despite the increase, the post expansion mean ROCM per cow was not signiﬁcantly
greater than the pre-expansion mean at the 95 percent level.8

The pre-expansion mean ROCM breakeven price was $14.77 per hundredweight
and ranged ﬁ'om $11.89 to $17.53. Post expansion, the mean breakeven price decreased

as expected to $14.53 per hundredweight with a range from $12.32 to $17.82. The pre-

7 t mamas = 0-491< t criicnla=.05,26 =1~706
8t........_,,,,,=0.282 <tm,-,,,,,,= 1.706

122

expansion mean ROCM breakeven price was not signiﬁcantly greater than the post
expansion mean.9

In the previous section, it was stated that a problem with the pre- and post
expansion NFI comparison was that the NFI calculation did not account for unpaid family
labor or a return to invested capital With the ROCM comparison, a charge is assigned for
unpaid labor. However, ROCM still does not account for varying levels of capital

investments. After expansion, the level of invested capital will have increased.

 

 

 

 

 

 

Table 39. The Effect of Expansion on ROCM ( l4 Farms)
ROCM ROCM ROCM Based
($1,000lfarm) ($lcow) Breakeven Price
($lcwt)
Before After Before After Before After
Mean 8.86 33.39 33 71 14.77 14.53
High 347.91 355.64 548 493 17.53 17.82
Low -l42.92 -168.51 -588 -677 11.89 12.32
Std. 117.51 145.32 356 351 1.79 1.50
Dev.

 

 

 

 

 

 

 

 

Before expanding, nine farms failed to earn sufﬁcient ﬁmds to fully compensate for

unpaid labor and management. The ROCM proﬁtability measures was better following the

expansion. Despite the improvements, seven ﬁrms still failed to generate a positive

ROCM. Four of the seven ﬁrms raised expansion ﬁmds by taking on additional partners.

While this allowed these ﬁrms to expand with little impact on solvency, the ﬁrms did not

9t“.-,,,,,,= 0.385 <tm¢__o,.26=1.706;p-value = .762

123

 

expand enough to compensate all managing partners. The three other ﬁrms maintained
the same number of managing partners, but they also had a high number of post expansion
managing partners relative to herd size. Among the seven ﬁrms with negative ROCM, the
managing partner salary expense was $1.78 per hundredweight. For the seven ﬁrms with
positive ROCM, the managing partner salary expense per hundredweight was $0.74.
When planning an expansion dairy, managers should be cognizant of both the debt
carrying capacity of the dairy and the dairy’s ability to generate sufﬁcient funds to
adequately compensate the managing partners for their labor and management.
VIII. The Effect of Expansion on Management Income

No ﬁrm posted a positive pre-expansion management income (MI). The pre-
expansion mean MI was -$127,060. The pre-expansion mean MI ranged ﬁom -$451,960
to -$3,500 (Table 40). Post expansion, most ﬁrms continued to be unable to compensate
the manager’s opportunity cost of his or her invested capital, as only two ﬁrms posted
positive MI. Both of the positive post expansion MI ﬁrms had negative MI prior to
expansion. The mean MI increased to -$151,020 and ranged from -$440,890 to $53,660.
Dmpite the increase, post expansion mean MI was not signiﬁcantly greater than the pre-
expansion mean at the 95 percent level.‘0

Pre-expansion MI per cow ranged from -$1405 to $-25 and averaged -$473. Post
expansion, the mean Ml per cow improved to -$320 with a range of -$920 to $158. The

post expansion mean MI per cow was not signiﬁcantly greater than the pre-expansion

 

wtmu-DSJIS = 0-478 (t m.=.os,2.=1-706

124

nrean at the 95 percent level of signiﬁcance. “

The MI breakeven price per hundredweight averaged $17.31 before expansion and

ranged ﬁom $14.48 to $21.90. Post expansion, the average Nﬂ breakeven price improved

to $16.10 per hundredweight, ranging from $13.48 to $18.92. The pre-expansion mean

was signiﬁcantly greater than the post expansion mean at a signiﬁcance level of 95

 

 

 

 

 

 

percent.12
Table 40. The Effect of Expansion on MI ( 14 Farms)
M1 M1 M1 Based Breakeven
($1,000/farm) ($lcow) Price
($lcwt)
Before After Before After Before After

Mean -127.06 -151.02 -473 -320 17.31 16.10
High -3.50 53.66 -25 158 21.90 18.92
Low -451.96 -44.89 -1,406 -920 14.48 13.48
Std. 133.78 131.49 477 323 2.16 1.53
Dev. '

 

 

 

 

 

 

 

 

While MI was still negative for twelve of the fourteen farms, 8 of the expansion

ﬁrms showed an improved ability to contribute to the opportunity cost of the managers’

equity. The mean post expansion breakeven price of $16.10 also demonstrates that these

dairy operations became much more competitive in regional and national milk production.

The MI breakeven price is lower than the average 1998 MI breakeven price of $18.40 for

 

11 t actrnlu - .05, 26 = 0994 < t criticd¢= .05, 26 = L706, p-value = 0-824

12 tma=.05,26 =1-710 >tcriticnlu=.05,26=1'706

125

 

the Upper Midwest dairy region and is better than all other US. dairy regions except the
Paciﬁc region’s MI breakeven price of $12.84 per cwt (U SDA-ERS, 2000).
IX. The Effect of Expansion On Return on Assets and Return on Equity

Up to this section, the proﬁtability measures expressed proﬁtability in absolute
terms. The ROA estimates show how well the assets generated proﬁtable returns to the
managers regardless of size. Likewise, the ROE shows how well the managers equity
generated proﬁtable returns regardless of size. Table 41 displays the estimated pre- and
post expansion ROA and ROE.

Seven ﬁrms experienced an increase in ROA and ROE, and seven ﬁrms
experienced decreases. The mean pre-expansion ROA was 3.25 percent and ranged ﬁom -
13.67 to 11.25 percent. Post expansion, the mean ROA decreased to 3.21 percent and
ranged from -7 .86 to 13.94 percent. The mean ROE also decreased after expanding. Pre-
expansion, the ROE ranged ﬁ'om -41.64 to 14.11 percent and averaged -0.26 percent.
Post expansion, the ROE ranged from -28.56 percent to 24.78 percent and averaged -1.18
percent

Table 41. The Effect of Expansion on ROA and ROE ( 14 Farms)

 

 

 

 

 

 

ROA (%) ROE (%)
Pre-expansion Post Expansion Pre-expansion Post
Expansion
Mean 3.25 3.21 0.26 -1.18
High 1 1.25 13.94 14.1 1 24.78
Low -13.67 -7.86 -41.64 -28.56
Std. Dev. 6.29 5.93 0.13 0.13

 

 

 

 

 

 

 

126

As ROA and ROE includes a charge for unpaid labor, these results were similarly

inﬂuenced as the ROCM results by those managers who used equity capital to ﬁnance the

expansion and had a large number of managing partners relative to the size of the ﬁrm

X. Expansion Net Present Values and Internal Rate of Return Estimates

The previous proﬁtability measures have been on an annual basis and have

subtracted depreciation, a non-cash outlay, from their total. A NPV calculation measures

the present value of the net cash ﬂows over an irrvestment’s life. In this subsection, the

estimated NPV and IRR (the discount rate that produces a NPV of 0) of 11 of the

expansion dairies are shown." In order to estimate the NPV of these ﬁrms, the

incremental cash ﬂows were calculated using the following assunrptions:

1)

2)

3)

4)

5)

6)

7)

The expansion’s time horizon was ten years and all assets were liquidated
at that time.

Milk revenues were calculated by multiplying the estimated change in milk
shipped per year by $13.50 per hundredweight.

Milk production increased at 2.41 percent per year.

The herds experienced a 4 % mortality and morbidity.

Bull calves were sold as bucket calves for the 1998 mean price

received by US. farmers of $78.80 per head (NASS, 2000).

33 percent of the milking herd were culled annually.

Surplus heifers were sold as springer cattle just prior to ﬁeshening for the

 

‘3 Only 11 of the ﬁrms provided expansion investment inforrmtion with suﬁcient detail to
develop estimated depreciation schedules.

127

1998 mean price received by US ﬁrmers for dairy cattle of $1,120 per
head.

8) Cull cows were sold for the 1998 mean price received by US ﬁrmers for
livestock cows of $42 1 .25“.

9) Upon liquidation in year ten, 33 percent of the dairy cows were sold as
cull animals, and the remaining cattle were sold at the dairy cattle price.

10) Purchased dairy cattle were depreciated over ﬁve years via MACRS, ﬁrm
implements were depreciated over seven years via MACRS. The parlor
equipment were depreciated over ten years via the straight line method.
The free stall facilities were depreciated over ﬁfteen years via the straight
line method.

1 1) Farm implements purchased at the beginning of the investment period and
sold at the end of year seven were assigned a market value of 25 percent of
their original purchase price. Replacement implements were assigned an
initial value at the beginning of year eight by inﬂating the original
implement’s purchase price by 2.62 percent per year. '5 The
replacement implements’ market value in year ten Was equal to ﬁfty percent
of the original purchase price. Parlor equipment at liquidation were

assigned a market value equal to ten percent of their initial cost. Free stall

 

'The 1998 mean price received by ﬁrmers for cull cows was $33.70. It was assumed that
the cull animals weighed 1250 pounds (NASS, 2000)

'5 This inﬂation estimate was calculated using the simple average of the ﬁrm machinery
and building materials production indices for the 1990-1998 period.

128

ﬁcilities were assigned a market value at liquidation equal to 25 percent of
their original value.

A sample NPV calculation is shown in Appendix 5. Seven expansions posted
positive NPV ranging from $9,488 to $1,736,698 (Table 42). Four expansions posted
negative NPV ranging from -$103,287 to -$568,876. No overall pattern was discemable
to indicate why a project had a negative or positive NPV.

The average IRR for all expansions was 4.45. The IRR for the 7 ﬁrms with
positive NPV ranged from 6.29 percent to 17.45 percent and averaged 14.02 percent. The
average IRR for the negative NPV expansions was -12.43 percent. One of the negative
NPV expansions posted a positive IRR of 5.22 percent.

Table 42. Estimated NPV and IRR of Select Expansion Dairies ( 11 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Farm Milking Herd After Tax NPV IRR
Increase WACC (8) (7.)
(Cows) (%)
101 60 5.42 209,308 14.50
103 390 6.15 807.794 16.24
104 302 6.16 9,488 6.29
105 270 6.65 -103,287 5.22
106 422 6.18 -544,925 -l.12
108 262 6.24 780,119 23.55
1 13 232 6.91 124,867 8.87
201 101 8.20 -568,876 -32.98
204 22 6.55 91,113 11.26
205 97 8.10 -565,571 -20.84
206 165 4.93 1,736,698 17.45

 

 

129

X1. Initial and Subsequent Expander Change In Breakeven Price

Earlier research showed that herds expanding ﬁ'om 50 to 300 cows with a 22,000
lb RHA decreased production costs from $14.75 to $13.50 per hundredweight and that
herd expanding beyond 300 cows continued to decline at a decreasing rate through a
1,000 cow herd size (Jones, 1997). In this research, initial expanders had a lower pre-
expansion mean herd size (107 cows) and post expansion mean herd size (349 cows) than
subsequent expanders (mean pre-expansion herd size = 430 cows; mean post expansion
herd size = 596 cows). In this section, whether or not the Initial Expanders experienced a
greater decrease in production costs (as measured by NFI and MI production costs) than
Subsequent expanders is examined.

As reported above, the mean NFI breakeven prices actually increased after
expanding. Only two of the Initial Expanders and two of the Subsequent Expanders
experienced a decrease in NFI breakeven price (Table 43). The mean NFI breakeven price
increase was $1.63 per hundredweight for Initial Expanders and $0.96 per hundredweight
for Subsequent Expanders. The Initial Expanders’ mean NFI breakeven price was not
signiﬁcantly larger than the Subsequent Expanders’ mean NFI breakeven price at the 95
percent signiﬁcance level.'6

The M] breakeven price did decrease after expanding for both the Initial
Expanders and the Subsequent Expanders. Six of the seven Initial Expanders and four of
the seven Subsequent Expanders experienced a decrease in MI breakeven price. The mean

MI breakeven price reduction for Initial Expanders was $2.12 per hundredweight, and the

 

"t“.-.o, ,, = 0.713 <tm,_,,,, = 1.782; p-value =0.753
130

mean MI breakeven price reduction was $0.29 per hundredweight for Subsequent

Expanders. The Initial Expanders MI breakeven price reduction was signiﬁcantly larger at

the 95 percent signiﬁcance level than those experienced by the Subsequent Expanders. '7

 

 

 

 

 

 

Table 43. A Comparison of Changes in Breakeven Price ( l4 Farms)
NFI Breakeven Price Change MI Breakeven Price Change
($lcwt) ($lcwt) .
Initial Subsequent Initial Subsequent
Expanderl Expanderz Expander Expander
Mean 1.63 0.96 -2.12 -0.29
Largest -0.19 -1.12 -4.72 -2.99
Decrease
Largest Increase 3.94 3.72 1.29 2.80
Std. Dev. 1.83 1.68 2.01 2.15

 

 

 

 

 

 

' Mean pre-expansion herd size = 107 cows; mean post expansion herd size = 349 cows.

2 Mean pre-expansion herd size = 430 cows; mean post expansion herd size = 596 cows.

Assuming the results of this study hold for the general population, the production

cost decrease, as measured by MI breakeven price, is larger for Initial Expanders than

Subsequent Expanders. Furthermore, the production costs continue to decline after the

 

initial expansion, but not as much. These results agree with earlier research.

As many managers relate to production costs in terms of those associated with the
NFI breakeven price rather than the MI breakeven price, many managers may incorrectly
diagnose an initial increase in NFI breakeven price as poor performance. This is not
necessarily the case, as only two dairies experienced an initial decline in the NFI breakeven

price. Managers should be reminded that post expansion dairy operations generally have

__

"t.,,..,-,,,,,, = 1.648 «MFW, = 1.782; p-value=0.935
131

proportionately more interest and depreciation expense than pre-expansion, which can

lead to initially higher NFI based production costs. Furthermore, mamgers and advisors

should be concerned with M] based costs, which consider the Opportunity costs of the

manager’s unpaid labor, management and equity.

XI. The Effect of Debt per Cow on Post Expansion ROA

To determine the effect of debt per cow on post expansion ROA, fourteen

expansion dairies were divided into two groups. The “Low Debt Group” was made up of

eight dairies who had pre-expansion debt loads of less than $2,000 per cow and post

expansion debt loads of less than $3,000 per cow. This is the preferred debt per cow level

described by Cappuzzi, Kohl and Rogers (1994). The “High Debt Group” consisted of

herds that had pre-expansion debt loads in excess of $2,000 per cow and/or post

expansion debt loads of more than $3,000 per cow. The results are shown in Table 44.

 

 

 

 

 

 

Table 44. The Effect of Debt per Cow on ROA ( 14 Farms)
Low Debt Group ' ROA High Debt Group 2 ROA
('70) W1)

Mean 1.94 4.91
High 7.55 13.94
Low -6.71 -7.86
Standard Deviation 4.57 7.49
Sample Size 8 6

 

 

 

 

' Pre-expansion debt per cow < $2,000 and post expansion debt per cow < $3,000
2 Pre-expansion debt per cow > $2,000 and/or post expansion debt per cow > $3,000

132

 

 

Although not signiﬁcantly greater at the 95 percent signiﬁcance level," it was the
High Debt Group, not the Low Debt Group, that earned the higher mean ROA. The Low
Debt Group earned a mean post expansion ROA of 1.94 percent, ranging ﬁom -6.71 to
7.55 percent. The High Debt Group earned a mean post expansion ROA of 4.91 percent,
ranging from ~7.86 to 13.94 percent.

Three relative debt measures ( the interest expense to gross farm income, debt-to-
asset, and interest expense per hundredweight of milk shipped ratios) were analyzed to
determine if another debt measurement could be developed to better predict post
expansion farm viability. Correlation coefﬁcients and R-squares were calculated to
determine the relationship between each relative debt measure and the ROA. The results
are shown in Table 45. Only the debt-to-asset ratio exhibited the anticipated negative sign
on the correlation. Nevertheless, the R-square for it and all of the other measurements
were low, with only 13.1 percent of the variance in ROA being explained by the variance
in debt per cow in the best case scenario. The two ﬁrms with the ﬁrst and second largest
ROA had an interest expense per gross farm income ratio that were second and third
highest of all ﬁrms. Conversely, the ﬁrm with the least amount of debt had a negative
ROA. Thus, no measurement of relative debt can be recommended as an accurate

predictor of post expansion viability for this group of managers.

 

‘8 t We, ,_, .05, ,2 = 0.922 < t cm“ 305.12 = 1.782; p-value = 0.808

133

Table 45. Debt Measurement and Return on Assets Correlation ( 14 Farms)

 

 

 

 

 

Debt Measurement Correlation R-square
Coefficient

Debt/Cow 0.36 0.13

Interest Expense/cwt 0.32 0.10

Debt/Asset -0.19 0.03

Interest Expense/Gross Farm Income 0.30 0.09

 

 

 

 

 

One reason that the debt measurements fail to predict post expansion viability is
that the debt level doesn’t necessarily reﬂect the management ability of the ﬁrmer. Highly
skilled ﬁrm managers may be better able to use debt to ﬁnance activities than lower skilled
managers.

Another possrble reason why the relative debt measurements ﬁlled to predict post
expansion viability concerns the costs associated with building a new facility with the
latest technology and equipment. Expansions that replace outdated facilities and
equipment can be expensive investments. It was mentioned earlier that the expansion
managers paid as much as $5,500 per cow to build, equip, and ﬁll their post expansion
facility. With dairy cattle priced at $1120 per cow, managers who try to keep their post
expansion debt load less than $3,000 may be forced to expand in much smaller increments
and/or forgo updating their technology.
XII. Conclusions

The expansion farms’ average D/A ratio increased from 0.3 1 to 0.43 . Seven of the

fourteen managers used equity capital, primarily in the form of additional partner

134

contributions, to ﬁnance expansion. This allowed the managers to expand without a large
increase in the D/A ratio.

Although the NFI per cow went down and the NFI BE price increased, NFI per
ﬁrm increased. Part of the explanation for poorer post expansion NFI per cow and NFI
BE price was attributed to the higher depreciation and interest expense that characterize
new ﬁrm investments.

While ROCM improved on a per farm, per cow, and breakeven price basis, seven
ﬁrms ﬁiled to ﬁrlly compensate the owners for unpaid labor and management. The group
that ﬁiled to generate a positive ROCM were those that expanded by taking on additional
partners or that had high pre- and post expansion partner-to-cow ratios. These ﬁrms may
have been better oﬂ‘ from an ROCM perspective to increase debt and expand to a larger
herd size in order to better compensate the managing partners.

MI also improved, especially in terms of breakeven price. MI breakeven price
decreased to a lower level than the average MI breakeven price for the Upper Midwest
and all other US. dairy regions except the Paciﬁc region. Thus, expansion embled the
managers to be more cost competitive with the average dairy producers of their own and
most other regions.

ROA and ROE decreased slightly. Once again, as ROA and ROE includes a charge
for unpaid labor, these results were similarly inﬂuenced as the ROCM results by those
managers who used equity capital to ﬁnance the expansion and had a large number of
managing partners relative to the size of the ﬁrm.

Seven of eleven expansions had positive post expansion NPV. The average IR

135

for the positive NPV expansions was 14.02 percent. The average IRR for all ﬁrms was
4.40 percent. No overall pattern was discemable to indicate why a project had a negative
or positive NPV.

As anticipated because of their smaller initial and post expansion herd sizes, the
Initial Expanders showed greater improvements in NFI and MI breakeven price. This
supports earlier work by Jones who found that ﬁrms increasing ﬁ'om 50 to 300 cows
show a larger decrease in production costs per hundredweight than larger expanding
farms.

Those that stayed within the guideline of having less than $2,000 debt per cow
before expanding and no more than $3,000 after expanding were less proﬁtable than ﬁrms
who did not. Due to the initial investment costs associated with modern expansions, this
guideline appears too restrictive. Debt per cow should be established on the merits of each

expansion investment, not solely on such a guideline.

136

Chapter X
Expansion Success Prediction

1. Introduction

It is useﬁrl to have models to predict expansion production and ﬁnancial success.
Such models inform advisors of the variables that highly inﬂuence expansion success and
to what degree. In this research project, models to predict and explain post expansion
production and proﬁt success were constructed and analyzed.
11. Production Estimation

Two models were estimated to determine post expansion milk production. The
ﬁrst used Ordinary Least Squares (OLS) to estimate post expansion RHA. The second
used discriminant analysis to determine what farm characteristics would enable managers
and advisors to discriminate whether or not a herd would produce above or below the
post expansion average RHA

Independent variables included in the OLS model used to estimate post expansion
RHA (POSTRHA) included the manager’s composite Management Inventory score
(SCORE),l the farms pre-expansion RHA (PRERHA), the manager’s expansion
experience (EXP), the presence of an enhancing facility technology change (F ACCHG),
the relative scale of the expansion (SCALE), and the degree of specialization (SPECIAL).

SCORE was selected to proxy the manager’s general management ability. As the
Management Inventory score reﬂects management ability, it was assumed that SCORE

would be positively correlated with post expansion production. PRERHA was

I The Management Inventory test is explained in Chapter III.

137

incorporated as a measurement of pre-expansion milk production capability and was
expected to be positively correlated with post expansion RHA. EXP refers to the number
of previous expansion the general manager had experienced, and, because “practice
makes perfect ” was assumed to be positively correlated to post expansion production.
FACCHG refers to whether the technology of the facility had changed. This may have
been a change from a tie stall to a modern free stall or a change from a old style ﬁee stall
barn to a modern, better ventilated, the style barn (side walls with a height of 10 feet or
more with curtain siding). It was assumed that F ACCHG was positively correlated with
production. As a larger increase in herd size is correlated with management complexity,
SCALE measures the relative increase in herd size and was expected to be negatively
correlated with production and was deﬁned as post expansion herd size divided by pre-
expansion herd size. SPECIAL refers to the degree of specialization in milk production as
measured by the number of outsourced activities. It was hypothesized that specialization is
positively correlated with production.

Tables 47 through 48 display the results of the post expansion RHA estimation.
About 85 percent in the variation of post expansion RHA is explained by the variation
among the estimation coeﬁicients. Unfortunately, the R2 is inﬂuenced by the low degrees
of freedom as there are 7 independent variables and a sample size of 16. The estimation of
post expansion RHA is signiﬁcant at an a of 0.001. The Adjusted R2 was 0.543.

The pre-expansion RHA coefﬁcient (PRERHA) was the most signiﬁcant
coefﬁcient with a signiﬁcance level of 95.9 percent. As expected, the PRERI-IA

coeﬁicient was positively correlated to post expansion production and signiﬁcant at the

138

88.7 percent level. The facility technical change coemcient (F ACCHG) was signiﬁcant at

the 98.7 percent level and exhibited a positive correlation with post expansion production

as expected.

Table 46. Post Expansion RHA Estimation Summary

 

 

 

R R Square Adjusted R Std. Error of the
Square Estimate
0.852 0.726 0.543 2141.83

 

 

 

 

 

Table 47. ANOVA Table for the Estimation of Post Expansion RHA

 

 

 

 

 

Sum of Degrees Mean Square F Significance
Squares Freedom
Regression 1.09E + 08 6 18189513466 3.965 0.032
Residual 41286864 9 4587429356
Total 1.50E + 08 15

 

 

 

 

 

Table 48. Coefficients for the Estimation of Post Expansion RHA

 

 

 

 

 

 

 

Beta Standard Error t statistic Significance
(Constant) 15042.728 6320.683 2.380 0.041
SCORE -29.318 241.042 -0.122 0.906
PRERHA 0.317 0.195 1.622 0.139
EXP ' 497.801 1491.850 0.334 0.746
FACCHG 5528.934 1788.051 3 .092 0.013
SCALE -124.548 392.296 -1.225 0.252
SPECIAL -124.548 614.637 -0.203 0.844

 

 

The other variables were much less signiﬁcant. Scale was signiﬁcant at the 74.8
percent level. It exhibited the correct correlation at -480.537. The manager’s expansion

experience exhibited the anticipated positive correlation and was signiﬁcant at 25.4

139

percent. The specialization variable is signiﬁcant at 15.6 percent. Whereas it was initially
anticipated that the SPECIAL coefﬁcient would be positively correlated to post expansion
RHA, the coefﬁcient was actually negatively correlated to post expansion production. As
the decision to outsource an activity is based on cost and not necessarily production, the
original premise that increased specialization increases production may have been
incorrect. Composite Management Inventory scores were the least signiﬁcant variable at a
9.4 percent signiﬁcance level. The SCORE coefﬁcient also exhibited an unexpected
negative correlation with post expansion production.

Tests for multicollinearity showed that severe multicollinearity was present
(Condition Index > 30 at 35.373). This means that:

l) accurate estimation with the regression will prove difﬁcult due to the

estimators having large variances and covariances;

2) conﬁdence intervals are wider;

3) one or more t ratios are insigniﬁcant;

4) the goodness-of-ﬁt, R2 , is higher than normal; and,

5) the estimators and their standard errors will be sensitive to small changes

in the data.

Next, a discriminant function was used to determine what characteristics could
discriminate farms with post expansion RHA above and below the sample’s average post
expansion RHA. The variables made available for the discriminant analysis included
PRERHA, SCALE, FACCHG, SCORE, and the following problem variables: the

presence of biosecurity, post expansion crop yields and/or quality, freshening, holding pen

140

time, genetics, cystic ovaries, cow comfort, settling, heat detection, and somatic sell
count or mastitis problems.

Only PRERI-IA was selected for the discriminant ﬁmction (Tables 49 through 50)
with the presence of each problem type favoring above average post expansion
production. Thus, the best determinant of post expansion production based upon this
discriminant analysis is pre-expansion production. It should be noted, however, that this
analysis may be hampered by the small samme size.

Table 49. Wilks’ Lambda for Discriminant Function

 

Wilks’ Lambda I Chi-square r df F Signiﬁcance '
0.363 I 13.695 l l l 0.000J

 

 

 

Table 50. Classification Function Coefﬁcients

 

 

 

 

 

 

 

 

Grouping
Above Average RHA Below Average RHA
PRERHA 0.004376 .003342
(Constant) -55.7 17 -3 2.774

 

III. Profit Estimation
An OLS regression was used to estimate post expansion ROA. The ROA was 1
chosen as the dependent proﬁtability measure for three reasons. First, ROA is less
inﬂuenced by the debt and equity characteristics of the farm as is the case with ROE of
MI. Second, as opposed to NFI, ROA provides for unpaid labor and interest paid. Third,

being a percentage, ROA is not inﬂuenced by scale as is the case of NFI, ROCM, and MI.

141

Seven independent variables were chosen to estimate ROA Herd size (HERD)
was selected as increasing herd size is correlated with lower production costs per unit
(Jones, 2000). The debt to equity ratio (DIE) was chosen to represent the effect that
leverage has on proﬁtability. Dairy worker expense per hundredweight of milk shipped
(LABORS) was used to proxy the manager’s ability to direct resources and assumed to be
negatively correlated with proﬁt. Expansion experience (EXP) was selected as it was
assumed that the manager’s expansion experience would be positively correlated with
proﬁt. Facility technology change (F ACCHG) was used as it was strongly correlated with
production and assumed to be positively correlated with proﬁt. The post expansion RHA
(POSTRHA) was used to represent the post expansion productive capabilities of the farm
and was assumed to be positively correlated with proﬁt. The manager’s composite
Management Inventory was included to represent the manager’s general management
ability.

The estimation of post expansion ROA (Tables 51 through 53) was signiﬁcant at
the 14.7 percent level with 37.3 percent of the variance explained by the variance in the
explanatory variables. The signiﬁcance of any single explanatory variable was low and two
explanatory variables (POSTRHA and SCORE) had incorrect signs. Severe

multicollinearity was present as the Condition Index > 30 at 138.099.

142

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 51. Post Expansion ROA Estimation Summary
r R R Square Adjusted R Std. Error of the
Square Estimate
0.610 0.373 -0.506 7.5597
Table 52. ANOVA Table for the Estimation of Post Expansion ROA
Sum of Degrees Mean Square F Significance
Squares Freedom
Regression 169.692 7 24.242 0.424 0.853
Residual 285.743 5 57. 149
Total -455.435 12
Table 53. Coefficients for the Estimation of Post Expansion ROA
Beta Standard Error t statistic Significance
(Constant) 18.194 86.173 0.211 0.841
HERD 0.004334 0.012 0.375 0.723
D/E 3.346 5.640 0.593 0.579
LABORS -2.448 2.798 -0.875 0.422
EXP 3.196 6.029 0.530 0.619
FACCHG 5.136 19. 1 19 0.269 0.799
POSTRHA -0.00013 16 0.002 -0.063 0.952
SCORE -0.669 2.716 -0.246 0.815

 

 

 

 

 

 

 

III. The Usefulness of The Management Inventory Test

Perhaps the most striking implication of the post expansion production and proﬁt

estimation models is the lack of explanatory power of the composite Management

Inventory score. The Management Inventory score is a popular instrument used by

extension programs to discern a manager’s relative competency in the general

management skill areas of planning, stafﬁng, organizing, controlling, and directing.

143

In this section, the Management Inventory is scrutinized again by determining its
ability to predict post expansion dairy worker expense per hundredweight (LABORS).
LABORS was selected as the general management skill areas seem most directly
applicable to human resource management. The independent variables in the model
included the respective scores for the planning (PLAN), staﬁing (STAFF), organizing
(ORGANIZE) controlling (CONTROL), and directing (DIRECT) aspects of the
Management Inventory. It was assumed that all skills would be negatively correlated to
LABORS. The results of the estimation are shown in Tables 54 through 56.

Only 42 percent of the variability of LABOR$ was explained by the variance in the
explanatory variables. The adjusted R2 was 0.129. The F statistic for the estimation was
1.446 and was signiﬁcant at signiﬁcance level of 71 .1 percent. The CONTROL coefﬁcient
was the most signiﬁcant at the 91.5 percent level but was positively correlated to
LABORS. ORGANIZE was signiﬁcant at a 89.6 percent level and was negatively
correlated to LABORS. PLAN was negatively correlated to LABORS and signiﬁcant at
an 75.9 percent signiﬁcance level. STAFF was signiﬁcant at the 71.5 percent level but was
positively correlated to LABORS. Directing was only signiﬁcant at the 13.2 percent level
and was positively. correlated to LABORS.

Due to the estimation’s low overall signiﬁcance, low coeﬁcient signiﬁcance on
seemingly important variables (i.e., DIRECT), and erroneous coefﬁcient correlations with
LABORS, the Management Inventory scores do not seem to be a good predictor of

human resource management ability as measured by LABORS. Nevertheless, it should be

144

noted that the estimation was plagued by severe multicollinearity as the Condition Index

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

>30 at 56.283.
Table 54. Post Expansion Dairy Worker Expense per Hundredweight
Estimation Summary
R R Square Adjusted R Std. Error of the
Square Estimate
0.648 0.420 0. 129 0.9469
Table 55. AN OVA Table for the Estimation of Post Expansion Dairy Worker
Expense per Hundredweight
Sum of Degrees Mean Square F Significance
Squares Freedom
Regression 6.484 5 l .297 1.446 0.289
Residual 8.966 10 0.897
Total 15.450 15
Table 56. Coefﬁcients for the Estimation of Post Expansion Dairy Worker
Expense per Hundredweight
Beta Standard Error t statistic Significance
(Constant) 6.561 2.658 2.468 0.033
PLAN -0. 145 0.1 17 -1.248 0.241
STAFF 0.152 0.135 1.130 0.285
ORGANIZE -0.431 0.241 -1.791 0.104
CONTROL 0.195 0.102 1.914 0.085
DIRECT 0.020 0.1 15 0.170 0.868

 

 

 

 

 

 

 

IV. Conclusions
The estimates of post expansion RHA, post expansion ROA, and post expansion

dairy worker expense per hundredweight were plagued by severe multicollinearity. Thus,

145

 

 

the value of these models in providing information concerning post expansion RHA, ROA,

or the usefulness of the Management Inventory test is questionable.

When using discriminant analysis to predict above and below average post
expansion RHA, only the pre-expansion RHA was selected. In this sample, the producers

who had higher than average pre-expansion production had higher than average post

expansion production.

146

 

FE“

CHAPTER XI
SUMMARY
This research reports the results of case studies of twenty Michigan and Wisconsin

dairy farms that underwent a one time dairy herd expansion of 20 percent or more during
1988 through 1998. On average, the dairy farms increased herd size by 92 percent to 569
cows. This increase was accompanied by a 67 percent increase in dairy speciﬁc employees
to 8.5 and an increase in cows/acre ratio of 77 percent. The herd management ability of
the managers was considered high as the pre-expansion production per cow of the farms
were higher than their US. DHIA counterparts.

The managers expanded their operations to increase proﬁt. Some of the other
common reasons included improving the manager’s quality of life, replacing an old and
obsolete facility, human resource issues, and to serve as a managerial challenge.

Five speciﬁc managerial skills were identiﬁed by the managers as essential for large
operations as a result of expansion These speciﬁc managerial skills include human
resource management, ﬁnancial management, operations management, herd management
and strategic management. Managers should become familiar with these managerial topics
or hire employees or advisors with the needed skills.

Despite previous research, on average the farms in this study did not experience
adverse effects with regard to production, reproduction, and herd health measures aﬁer

expanding. This ﬁnding may be attributed to a sample bias towards better managers,
improved post expansion technology and increased management and labor specialization.

These results suggest that expansion managers do not necessarily have to endure initial

147

 

decreases in post expansion productivity. In fact, expansion may offer the manager the
opportunity to reduce the incidence of facility- or technology-induced production,
reproduction, and herd health problems.

Although there was no decrease in herd health performance measures, biosecurity
problems did seem to affect expansion dairies. Managers should work with their
veterinarians to reduce the incidence of contagious diseases and consider renting vacant
barns to quarantine purchased cattle.

Post expansion milk shipped per ﬁill time worker equivalent and the total dairy
worker expense per hundredweight of milk improved as compared to pre-expansion levels.
These improvements were due in part to managers abandoning more labor intensive
technology in favor of more capital intensive technology.

Human resource management problems changed pre- to post expansion. The
problems that showed the highest increase in occurrence were those associated with
evaluating employee performance, setting and achieving performance goals for the
employees, full-time employee quality, and training. To help alleviate these problems, the
managers were interested in educational programs designed to improve their HRM skills
in such areas as communication, motivation, and evaluation.

Producers who took preventive countermeasures (e. g., public relations campaigns
and more advanced manure management technology) had more success at reducing
environmental, public relations and zoning complaints. Although it was anticipated that the
majority of the complainants would be of non-rural background, the majority of

complainants had agricultural backgrounds. Expansion managers and advisors should

148

 

undertake preventive countermeasures that encompass the concerns of all rural residents.

Despite the fact that larger herds may face greater public and governmental
scrutiny concerning environmental compliance, the amortized manure management
technology costs per 100 pounds of milk for farms with less than 700 cows was equal to
or greater than farms with less than 700 cows.

Return on assets decreased for the average expansion, but a larger number of the
expanded dairies had higher net farm income. While return to capital and management
improved on a per farm, cow, and breakeven price basis, seven farms failed to fully
compensate the owners for unpaid labor and management. Managers are encouraged to
not only consider the debt carry capacity of their expansion dairies but also the managing
partner salary carrying capacity as well. The management income breakeven price
decreased to a lower level than the average management income breakeVen price for the
Upper Midwest and all other US. dairy regions except the Paciﬁc and Southwestern dairy
regions. Thus, expansion enabled the managers to be more cost competitive with the
average dairy producers of their own and other regions.

OLS equations was developed to predict post expansion production per cow and
return on assets. Only the pre-expansion production per cow and improved facility
technology variables were signiﬁcant, but severe multicollinearity was present. A
discriminant analysis was conducted to determine if farm, production, reproduction and
herd health characteristics could classify those farms with above average milk production
per cow ﬁom those with below average production. Pre-expansion milk production per

cow was the only capable of doing so. An OLS equation was used to predict post

149

expansion return on assets. Unfortunately, the model was insigniﬁcant and severe
multicollinearity was present. A model used to determine the explanatory power of
Cornell University Extension’s Management Inventory concerning total dairy worker
expense per hundredweight was examined. Only organizing and controlling variables
proved signiﬁcant, but, again, severe multicollinearity was present.

It should be noted that the farm sample size for this research was small and biased
towards better managers. Further research should include more expansion operations and
with managers of varying expertise to detemiine whether the results previously discussed
will hold for a larger population. Research should also be conducted to ﬁnd better
methods cf managing human resources, minimizing environmental, public relations and
zoning problems, and making, monitoring and evaluating outsourcing and internalization

decisions.

150

APPENDIX I

1998 —— 2000 UPPER MIDWEST DAIRY EXPANSION SURVEY

151

 

——_ :ﬂﬁﬂ” 9~4~ ‘ ' ‘
4

 

1998 — 2000 UPPER MIDWEST DAIRY EXPANSION SURVEY

** FORM A"
L General Demographic Information

Please ﬁll out the following table. “Pre-expansion” refers to the average values for the two
years prior to the year of your expansion. Post-expansion refers to the average values for
the years following your expansion.

 

Subject Pre-expansion Post-expansion

Herd Size (Milking) Number

 

 

Dry Cow Number
Heifer Number

 

 

Dairy Beef

 

Acreage (Owned)
Acreage (Rented)
Alfalfa Hay/Haylage Acreage

 

 

 

Corn Silage Acreage

 

Grass Hay/Silage Acreage

 

Small Grain Hay/ Silage Acreage

 

Corn Acreage

 

Soybean Acreage

 

Wheat Acreage

 

Other Crop Acreage

 

Number on Management Team

Number on Milking Crew

 

 

Number on Feeding and Outside
Crew

 

Number on Field Crew

Number of General Laborers

 

 

 

 

 

 

152

Please ﬁll out the following three tables concerning your milk production, herd health, and
reproduction values. If you have expanded more recently than 5 years ago, your
information is very important to us. Please ﬁll in for the years that pertain to your
operation’s expansion

i1 PRODUCTION INFORMATION

 

Year Milk/Cow Milk Fat % Milk Protein %
(RHA)

 

2 Years Before
Expansion

 

1 Year Before
Expansion

 

Expansion Year

lst Year Aﬁer
Expansion

2nd Year After
Expansion

3rd Year After
Expansion

4th Year After
Expansion

5th Year After
Expansion

 

 

 

 

 

 

 

 

 

 

 

153

III. Herd Health

 

Year

Culling %

Cow
Mortality %

Youngstock
Mortality %

Calving
Mortality %

 

2 Years Before
Expansion

 

1 Year Before
Expansion

 

Expansion
Year

 

lst Year Aﬁer
Expansion

 

2nd Year After
Expansion

 

3rd Year After
Expansion

 

4th Year After
Expansion

 

5th Year After
Expansion

 

 

 

 

 

 

154

 

 

IV REPRODUCTION

 

Year Average Average Days Average Bull Usage %
Services per Open Calving
Conception Interval

 

2 Years Before
Expansion

 

1 Year Before
Expansion

 

Expansion
Year

lst Year After
Expansion

2nd Year After
Expansion

3rd Year After
Expansion

4th Year After
Expansion

5th Year After
Expansion

 

 

 

 

 

 

 

 

 

 

 

 

V INVESTMENT INFORMATION

Please ﬁll out the next two tables to the best of your ability.

 

 

 

 

Cattle Investments
Issue Number Purchase Number. Leasing
Purchased Price Leased Price
Mature Cattle
Springing Heifers
Heifers

 

 

 

 

 

 

 

155

Facility Investments

 

Issue

Pre-expansion
Capacity

Post-
expansion
Capacity

New or

Remodeled
9

Type

Cost

 

Parlor (Stalls
and cows/hour)

 

Nﬁlking Herd
Barn (Stalls)

 

Dry Cow Barn
(Stalls)

 

Heifer Barn
(Stﬂls)

 

Calf Facilities
(Stalls)

 

Silo’s or
Bunkers

 

Commodity
Shed

 

Hay Storage

 

Manure
Storage

 

 

Other
L J

 

 

 

 

 

 

156

 

VI MANAGEMENT INVENTORY

Please answer the following survey questions. This last part of this questionnaire should
take approximately ten minutes.

(From Michigan State University Extension’s “AA/[AP — Animal Management
Advancement Project for Michigan Produce, ” pp. 6 - 10) To conduct this survey, please
indicate how strongly you agree or disagree with the statement. For instance, circling “1“
would indicate that you strongly disagree with the statement. Circling a “5" would indicate
that you strongly disagree with the statement.

1)

2)

3)

4)

5)

6)

7)

3)

The goals and objectives of my business are clear and oﬁen written. I
1 (strongly disagree) 2 3 4 5 (strongly agree)

Everyone working with me has very clear responsibilities, and I often write
down those responsibilities.

1 (strongly disagree) 2 3 4 5 (strongly agree)

I can clearly tell if someone is doing a good job and why they are doing
well.

1 (strongly disagree) 2 3 4 5 (strongly agree)
People I work with put in 110% effort to get the job done.

1 (strongly disagree) 2 3 4 5 (strongly agree)
I regularly match daily performance against standards I have set.
1 (strongly disagree) 2 3 4 5 (strongly agree)

Given several things to choose from, I ﬁnd it difﬁcult for me to make the
right choice.

1 (strongly disagree) 2 3 4 5 (strongly agree)
Major problems within the business are the owner’s responsibility.
1 (strongly disagree) 2 3 4 5 (strongly agree)

Evaluating people’s skills and their ability to ﬁt into jobs is difﬁcult for me.

157

9)

10)

11)

12)

13)

14)

15)

16)

17)

1 (strongly disagree) 2 3 4 5 (strongly agree)
Motivating people is something I do not do well.
1 (strongly disagree) 2 3 4 5 (strongly agree)

People who work with me don’t control themselves and need a boss to do
it.

1 (strongly disagree) 2 3 4 5 (strongly agree)

The big picture and the details are very clear to me. I know where I’m
going and how to get there.

1 (strongly disagree) 2 3 4 5 (strongly agree)
I have clear procedures for routine chores.

1 (strongly disagree) 2 3 4 5 (strongly agree)
I plan and carry out good training for everyone working for me.
1 (strongly disagree) 2 3 4 5 (strongly agree)
I know when to let someone else take over a job and do it his or her way.
1 (strongly disagree) 2 3 4 5 (strongly agree)

The quantity and quality of reports I get is suﬂicient for the level of control
I want.

1 (strongly disagree) 2 3 4 ' 5 (strongly agree)

I think on my feet and plan as I go along rather than ﬁgure out the details
ﬁrst.

1 (strongly disagree) 2 3 4 5 (strongly agree)
When I am in charge, I like to make all of the decisions.

1 (strongly disagree) 2 3 4 5 (strongly agree)

158

18)

19)

20)

21)

22)

23)

24)

25)

26)

People working with me are not well trained and don’t know how to do
their jobs.

1 (strongly disagree) 2 3 4 5 (strongly agree)

Most communication concerning my business comes from the top and
trickles down.

1 (strongly disagree) 2 3 4 5 (strongly agree)

The records I use do not keep me well informed of my progress towards
goals.

1 (strongly disagree) 2 3 4 5 (strongly agree)

I am very creative and can easily come up with 10 ideas to solVe a problem.
1 (strongly disagree) 2 3 4 5 (strongly agree)

People working with me are responsible and accountable for what they do.
1 (strongly disagree) 2 3 4 5 (strongly agree)

Setting the wages for my employees is easy for me.

1 (strongly disagree) 2 3 4 5 (strongly agree)

The people working for me know what is going on and stay informed of
problems and successes.

1 (strongly disagree) 2 3 4 5 (strongly agree)

Those working for me are familiar with the controls and standards that
have been set and help to monitor them for problems.

1 (strongly disagree) 2 3 4 5 (strongly agree)

I’m not good with details, and often miss the little things when making a
plan.

1 (strongly disagree) 2 3 4 5 (strongly agree)

159

27)

23)

29)

30)

Good workers in my business don’t need to have clearly deﬁned roles and
responsibilities.

1 (strongly disagree) 2 3 4 5 (strongly agree)

I have difﬁculty recruiting a good selection of applicants for any job I have
open.

1 (strongly disagree) 2 3 4 5 (strongly agree)
Communication is usually not written even when it is important.
1 (strongly disagree) 2 3 4 5 (strongly agree)
By the time I know I have a problem, it’s too late to do much about it.

1 (strongly disagree) 2 3 4 5 (strongly agree)

160

VII. EXPANSION SUCCESS

 

ISSUE Year Year-1 Year 1 Year 2 Average Average
-2 (Expansion Before After
Year)

 

Proﬁt/Cow

 

Proﬁt/Stall

 

Debt/Cow

 

Net Farm
Income

 

Total Assets
(cost)

 

Total Assets
(market)

 

Total Liability

 

Total Farm
Revenues

 

Revenues From
Dairy

 

Revenues From
Crops

 

 

 

 

 

 

 

 

 

161

Appendix II
1998 -— 2000 UPPER MIDWEST DAIRY

EXPANSION STUDY
INTERVIEW GUIDE — A

162

1998 — 2000 UPPER MIDWEST DAIRY
EXPANSION STUDY
INTERVIEW GUIDE — A

Department of Agricultural Economics
Michigan State University

163

l)
2)
3)
4)
5)
6)
7)
8)

9)

1)
1a)

2)

3)

4)

4a) '

5)

1)
2)

General Expansion Questions

How many times have you expanded your dairy before?

For your current expansion, why did you decide to increase your herd size?
Please generically describe your most current expansion decision making process.
In what year did you decide to expand your dairy herd?

What was your target herd size for your expansion?

Why and how was this size chosen?

In what year did you start your expansion?

How many months did it take to reach your targeted herd size?

What were your top ﬁve goals for the expansion?

Production Issues

In general, what were the expansion’s impact on crop quality and yields?
Why?

What were your top three problems concerning pre-expansion milk production
issues? Ranking?

What do you believe were the causes of these problems?

What were (are) your top three post-expansion production problems? Ranking?
If there is a difference in the pre- and post- expansion list, why?

What do you believe were (are) the causes of these post-expansion problems?

Herd Health Issues
What were the three major herd health problems prior to expanding? Ranking?

What do you believe were the causes of these problems?

164

3)
3a)

4)

1)

2)

3)
3a)

4)

1)
2)

3)

4)

1)

2)

3)

4)

 

What has been your top three post-expansion herd health problems? Ranking?
If different from the pre-expansion problems, why?

What do you believe were (are) the causes of these post-expansion problems?
Reproduction Issues

What were your top three pre-expansion reproduction problems? Ranking?
What do you believe were the causes of these problems?

What were the top three post-expansion production problem? Ranking?

If diﬁ‘erent than pre-expansion problems, why?

What do believe are the causes of these post-expansion reproduction problems?
OUTSOURCING

What management or production areas did you outsource pre-expansion and why?
Post-expansion?

What consulting services (private, agribusiness, or extension based) do you use on
an ongoing basis and why? Who supplies these services?

Is there a production or management area that you wish you could outsource?
Which area is it? Why can you not currently outsource this area?

EXPANSION INVESTMENTS

What problems did you encounter sourcing animals?
Did animal sourcing problems limit your expansion size?

Did you encounter any biosecurity issues in sourcing animals? If so, what was the
outcome? If not, how did you guard against these problems?

If you were to expand in the future, would you use a different animal sourcing
strategy?

16S

5)

6)
7)

8)

9)
10)

11)
12)
13)

14)

Did you purchase additional land for your expansion? Why did you decide to
purchase additional land?

On average, how much did you pay per acre for the additional acreage?
Did you rent/lease additional acreage for your expansion? If so, why?

On average, how much were you able to rent/lease the additional acreage for per

. acre?

What land procurement problems did you encounter?
Did land procurement issues limit your herd size? If so, how?

Were you required by environmental regulations to purchase more land than you
wanted?

If you were to expand in the future, what changes would you make regarding land
procurement?

What major problems were encountered in building or remodeling your facilities?
Please rank the tap three problems in terms of severity.

If you were able to go back to your expansion planning period, what would you do
differently concerning facility investments?

166

Investment in Additional Equipment

 

Issue Type HP/SIZE No. New vs Purchase Cost
Used vs Leased

 

Tractor l

 

Tractor 2

 

Tractor 3

 

Planting/Cultivating
1

 

Planting/Cultivating
2

 

Planting/Cultivating
3

 

Forage Harvesting 1

 

Forage Harvesting 2

 

Forage Harvesting 3

 

Feeding 1

 

Feeding 2

 

Feeding 3

 

Pay loader/Skidsteer

 

Manure Handling 1

 

Manure Handling 2

 

 

 

 

 

 

 

 

Other ( )

 

 

15) What problems were encountered in procuring equipment?

16) If you were advising another producer undergoing a similar expansion about
equipment procurement, what would you tell the producer?

VI] FACILITY DESIGN AND CONSTRUCTION

In the following table, please indicate (by checkmark) who conducted the design and
construction duties.

167

 

 

Issue Self PCE CCE Contractor Agrbusiness Private Other
(1) (2) Consultant Farm
Consultant

 

Business
Planning

 

Grants and
Permits

 

Site Selection

 

Facility
Design

 

Environment

 

Dairy/F arm
Equipment
Research and
Procurement

 

Excavation

 

Concrete

 

Framing
Electrical
Heating/Air

 

 

 

Plumbing
Finish Work

 

 

Dairy/Farm
Equipment
Installation
(1) Private consulting engineer (2) Construction company engineer

 

 

 

 

 

 

 

 

 

 

168

 

1) Did your expansion project go over-budget? Ifso, by how much?
2) What were the major reasons for going over-budget?

3) Did you experience any delays in the designing and construction process? Ifso,
what caused the delays and how long were they?

4) If you were to do the expansion all over again, what would you different
concerning facility design and construction?

VIH FINANCIAL CAPITAL

 

Source Pre-expansion % Post-expansion %

Self

 

 

Farm Credit Services
Local Ag Lender
National Ag Lender

 

 

 

Insurance Company

 

Mortgage Company

Relative(s) (Lender)

Relative(s) (Shareholder)

‘ Outside Individual(s) (Lender)
Outside Individual(s) (Shareholder)
Milk Marketing Organization (Lender)

 

 

 

 

 

 

Milk Marketing Organization
(Shareholder)

Agribusiness (Lender)

 

 

Agribusiness (Shareholder)
Other:
TOTAL%

 

 

 

 

 

 

 

 

169

1)

2)

3)

4)

5)

Did ﬁnancial limitations of your pre-expansion ﬁnancial sources force you to
reduce your expansion target size? If so, by how much?

Did the ﬁnancial limitations of your pre-expansion ﬁnancial capital source force
you to investigate alternative sources? If so, what dimculties did you encounter?

Of present debt, what % is short term?

If your expansion project went over-budget, did you encounter any difﬁculties in
procuring ﬁnancing for the cost overrun? Please explain.

Post—expansion, did you experience high interest rates charged for loans to your
dairy? If so, by how much did it increase or decrease?

170

IX. HUMAN RESOURCE MANAGEMENT

Please indicate problems encountered concerning human resource management and rank
according to severity?

 

Issue Pre- Pre-expansion Post- Post-
expansion Severity expansion expansion
Relevance (Rank Top Relevance Severity
Three) (Rank Top 3)

 

Determining
selection
requirements

 

Finding proper
quantity of
managers

 

Finding proper
quantity of full
time employees

 

Finding proper
quantity of part
time employees

 

Finding quality
managers

 

Finding quality
full time
employees

 

Finding part
time employees

 

Training
employees

 

Evaluating
employees

 

Achieving your
performance
goals for
employees

 

 

 

 

 

 

 

171

 

Compensating
employees

 

Providing
insurance

 

Providing
housing

 

Retaining
employees

 

Communicating
with employee

 

Other:
L
_)

l) Concerning the top three human resource management problems, why are they
problematic?

 

 

 

 

 

 

2) How are you planning to or how did you alleviate these problems?

3) Did you ﬁnd that you had to adjust your human resource management style from
pre- to post-expansion? Why or why not?

4) If there were an unlimited number of educational programs designed to assist you
in becoming a better human resource manager, what human resource management

areas would be important to you and why?

5) If there were an unlimited number of educational/vocational programs designed to

assist your employees in becoming better dairy employees, what
educational/vocational programs would you encourage your employees to take?

6) Typically, how much would you pay for someone starting in the following

 

 

 

positions:

° Herdsperson
° Milker

° Feeder

- Field

 

172

 

 

1)

2)

5)

6)

XI.

1)

2)

3)

4)

5)

General Management Issues

Ifyou were to write a pre-expansion job description for yourself, what would it

say?
For post-expansion, has the description changed? If so, how?

Ifyour job description has changed, which changes did you foresee taking place
prior to expanding?

Which changes surprised you?

ENVIRONMENTAL, NEIGHBOR RELATIONS, AND ZONING
COMPLIANCE

What problems concerning environmental regulations, neighbor relations, and
zoning compliance did you anticipate during your expansion planning process?

Were your concerns realized? How did you handle these problems?

What unanticipated environmental regulations, neighbor relations, and zoning
compliance issues arose during your expansion?

How did you address these issues?

Of your neighbor relations problems, what percentage of complaints arose from
neighbors who had an urban/suburban, rural, or farming background? In your
opinion, which group’s complaints were the most severe?

173

XII. EXPANSION SUCCESS

 

Issue Year -2 Year -1 Year 1 Year 2
(Expansion
Year)

 

Proﬁt/Cow

 

Proﬁt/Stall

 

Debt/Cow

 

Net Farm Income

 

Total Assets (cost)

 

Total Assets (market)

 

Total Liability

 

Total Farm Revenues

 

Revenues From Dairy

 

 

 

 

 

 

Revenues From Crops

 

 

1) For the two years pre-expansion, did you have any cash ﬂow problems? Ifso, for
how long did these occur? To what was the cash ﬂow problem attributed?

2) After the expansion, did you encounter cash ﬂow difﬁculties? Ifso, when and for
how long did they endure? To what are the cash ﬂow diﬁculties attributed?
3) In terms of your personal goals for this expansion, was the expansion successful?

Did the expansion generate enough positive returns to justify your additional risk?

4) Are you glad you expanded? Would you or are you considering expansion in the
ﬁiture? Why or why not?

174

APPENDIX III

ROLLING HERD AVERAGE COMPARISON

175

Rolling Herd Average Comparisons ( 18 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Farm Pre-expansion Average Farm Average US
Period RHA DHIA RHA
(lbs/cow/year) (lbs/cow/year)
101 1991 - 1992 14,000 18,750
103 1993 - 1994 21,000 18,900
104 1995 - 1996 25,000 19,250
105 1994 - 1995 15,000 19,200
106 1995 - 1996 27,300 19,250
107 1996 - 1997 18,500 19,500
108 1994 - 1995 22,250 19,200
110 1996 - 1997 23,000 19,500
112 1996 - 1997 26,050 19,500
113 1996 - 1997 26,150 19,500
201 1992 - 1993 18,000 18,750
202 1995 - 1996 19,490 19,250
203 1996 - 1997 19,000 19,500
204 1991 - 1992 17,150 18,600
205 1995 - 1996 21,000 19,250
206 1990 - 1991 21,050 18,200
207 1992 - 1993 20,500 18,750
208 1993 - 1994 19,300 19,200
Mean NA 20,706 19,1 14
Standard Deviation NA 3,654 374
Sample Size NA 18 18

 

 

 

 

176

 

APPENDIX IV

MANAGEMENT INVENTORY SCORES BY MANAGER

177

Management Inventory Scores By Manager ( 19 Farms)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Farm Planning Organizing Stafﬁng Directing Controlling Composite
Score

101 22 20 22 24 20 21.6
102 14 19 18 14 18 16.6
103 22 21 25 26 24 23.6
104 23 21 23 20 24 22.2
105 23 22 25 22 24 23.2
106 22 19 19 17 24 20.2
107 24 27 25 24 26 25.2
108 16 21 23 21 19 20.0
1 10 28 23 28 21 23 24.6
1 l 1 24 19 23 23 23 22.4
1 12 27 23 23 24 27 24.8
1 13 20 19 19 20 20 19.6
201 19 19 21 16 21 19.2
203 17 16 20 17 13 16.6
204 19 19 16 21 23 19.6
205 25 22 24 25 29 25.0
206 24 22 25 24 26 24.2
207 19 22 23 22 21 21.4
208 18 18 20 20 20 19.2
Mean 21.4 20.6 22.2 21.1 22.4 21.5
Std. 3.7 2.4 3.0 3.3 3.7 2.7
Dev.
High 28 27 28 26 29 25.2
Low 14 16 16 14 13 16.6

 

 

 

 

 

 

 

178

 

Appendix V

Sample NPV Calculation

179

Assumptions for Calculating the Expansion NPV

In order to estimate the expansion NPV of these farms, the incremental cash ﬂows were

calculated using the following assumptions:

1)

2)

3)

4)

.5)

6)

7)

It was assumed that the expansion’s time horizon was ten years and
that all assets would be liquidated at that time.

Milk revenues were calculated by multiplying the estimated change in milk
shipped per year by $13.50 per cwt and that milk production would
increase by 2.41 percent per year.

Capital gains were assessed a tax of twenty percent. All other taxable
income was taxed at the managing partner’s estimated federal marginal tax
rate plus a ﬁve percent state income tax.

It was assumed that the herds would experience a 48 percent bull calf crop.
The bull calf sales were sold as bucket calves for the 1998 mean price
received by US. farmers of $78.80 per head (NASS, 2000).

It was assumed that there would be a 48 percent heifer crop and that 33
percent of the milking herd would be culled annually. Surplus heifers were
sold as springer cattle just prior to freshening for the 1998 mean price
received by US farmers for dairy cattle of $1,120 per head. Cull cows were
sold for the 1998 mean price received by US farmers for livestock cows of
$33.70 per cwt (N ASS, 2000). Cull cows were assumed to weigh

1250 pounds. Upon liquidation in year 10, 33 percent of the dairy cows
were sold as cull animals. The remaining cattle were sold at the dairy cattle
price.

Purchased dairy cattle were depreciated over ﬁve years via MACRS. Farm
implements were depreciated over 7 years via MACRS. The parlor
equipment were depreciated over 10 years via the straight line method.
Free stall facilities were depreciated over 15 years via the straight line
method.

For farm implements purchased at the beginning of the investment period
and sold at the end of year 7, the implements were assigned a market value
of 25 percent of their original purchase price. Replacement implements
were assigned an initial value at the beginning of year 8 by inﬂating the

180

original implement’s purchase price by 2.62 percent per year.1 The
replacement implements’ market value in year 10 was equal to 50 percent
of the original purchase price when liquidated in year 10. Parlor equipment
at liquidation were assigned a market value equal to 10 percent of their
initial cost. Free stall facilities were assigned a market value at liquidation

equal to 25 percent of their original value.

NPV Calculation for Farm 103

Marginal Tax Rate (t) = 0.41 %

After Tax WACC = 6.15 %

 

 

 

 

 

 

 

 

 

 

 

1) Calculation of After Tax Revenues = [(1) + (2) + (3) +(4)]* (l-t)
Year (1) (2) (3) (4) Revenues
Milk Sales Calf Sales Heifer Sales Cull Cow *
Sales (l-t)

1 $1,127,022 $14,751 $0 $0 $673,646
2 1,154,071 14,751 0 0 732,122
3 1,181,768 14,751 65,520 0 744,603
4 1,210,131 14,751 65,520 48,282 789,824
5 1,239,174 14,751 65,520 54,183 810,440
6 1,268,914 14,751 65,520 54,183 827,987 .
7 1,299,368 14,751 65,520 54,183 845,955
8 1,330,553 14,751 65,520 54,183 864,354
9 1,363,486 14,751 65,520 54,183 883,195
10 1,395,186 14,751 65,520 54,183 1,083,858

 

 

 

 

 

 

 

 

‘ This inﬂation estimate was calculated using the simple average of the farm machinery
and building materials production indices for the 1990-1998 period.

181

 

 

 

 

 

 

 

 

 

 

 

 

2) Tax Implication of Capital Gains
Year Liquidated Asset Market Value Capital Gain Tax
or Loss Implication
1 Purchased Cattle $54,183 -$62,985 $25,824
2 Purchased Cattle 72,063 -3 5,843 14.696
3 Purcha? Cattle 72,063 7,621 -1,524
4 Purchased Cattle 17,880 4,205 -841
5 None 0 0 0
6 None 0 0 0
7 Equipment 35,998 17,240 -3448
8 None 0 0 0
9 None 0 0 0
10 Facility and 272,956 207,006 -41,401
Equipment

 

 

 

 

 

 

 

182

3) Calculation of After Tax Cash Flows (ATCF); (1) - (2) + (3) + (4) + (5) = ATCF

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Year (1) (2) (3) (4) (5) ATCF
Revenues Expenses Depreciation Assets Tax
“ " * Sold Implication
(H) (14) (t)

1 $673,646 $467,356 54,029 $54,183 $25,824 $340,325
2 732, 122 459,620 74,034 72,063 14.696 433,294
3 744,603 497,100 63,222 72,063 -1,524 381,265
4 789,824 537,669 50,906 17,880 -841 320,099
5 810,440 585,654 34,116 0 0 258,903
6 827,987 610,976 33,799 0 0 250,810
7 845,955 636,945 33,799 35,998 -3448 275,359
8 864,3 54 659,767 36,803 0 0 241,389
9 883,195 682,012 41075 0 0 242,258
10 1,083,858 715,914 38,170 272,956 -41,401 637,668

 

183

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4) Calculation of Net Present Value (NPV) = (1) - (2)
Year ATCF (1) Invested (2) N PV
Present Capital Present (1)-(2)
Value of Value of
ATCFl Invested
Capital2
0 $0 $0 $1,498,977 $1,498,977 -$ 1,498,977
1 340,325 320,608 131,040 123,448 $197,160
2 433,294 384,541 0 0 384,541
3 381,265 318,762 0 0 318,762
4 320,099 252,1 19 0 0 252,1 19
5 25 8,903 192,104 0 0 192,104
6 250,810 175.318 0 0 175,318
7 275,359 181,325 104,206 68,620 1 12,705
8 241,389 149,747 0 0 149,747
9 242,258 141,579 0 0 141,579
10 637,668 351,071 0 0 351,071
NPV: 776,128

 

 

 

1Present Value of ATCF = ATCF * Present Value Discount Factor.
The Present Value Discount Factor = 1/ (1+ k)Year where k = (After Tax WACC)/ 100

2 Present Value of Invested Capital = ATCF '1‘ Present Value Discount Factor.

184

 

BIBLIOGRAPHY

185

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188

           

MlL HlGAN STATE LIBRARIES

1293 02177 0791

 

 

 

 

    
 

 

 

L’ﬁl- _ —:u:: -