_..—..............‘.-<,."~. ‘”‘ PHYSICAL DISTRIBUTION PATIERNSINTHEIV -. ~- - ' METALS SERVICE CENTER INDUSTRY ‘ Thesis for the Degree of Ph. D; MICHIGAN STATE UNIVERSITY - I ~ ‘ PETER MICHAEL LYNAGH 1970 ' LIBRARY THESIV Michigan State University This is to certify that the thesis entitled PHYSICAL DISTRIBUTION PATTERNS IN THE METALS SERVICE CENTER INDUSTRY presented by Peter Michael Lynagh has been accepted towards fulfillment of the requirements for _Eh_._D__degree inMarketing 8: Transportation Adm. ”V [/7 __ x .' / I_)~"J--J~- 1‘ ‘ ‘ / {/Xiajor professor DMe May 12, 1970 0-169 ABSTRACT PHYSICAL DISTRIBUTION PATTERNS IN THE ETALS SERVICE CENTER INDUSTRY By Peter Michael Lynagh The subject matter of this research is physical dis- tribution patterns as they exist in the Metals Service Center industry. The specific purposes of this research were to: (1) compare the existing physical distribution patterns with a maximum performance model (2) determine if size will affect the relationship of a Metals Service Center to the maximum performance model (3) determine if profit will affect the relationship of a Center to the maximum performance model (A) compare differences of opin- ion regarding customer service among those holding differ- ent jobs within the Center. The first phase of the research was to develop a maximum performance model of physical distribution patterns for this industry. This model describes, verbally, the system that should be in operation in this industry. This model contains thirty—seven of the most important physical distribution factors. The system was broken down into three sub-classifications -- order processing which Peter Michael Lynagh contained ten f'arztors, warehousehandling which contained ten factors, and transportation which had seventeen factors. A measurement system was developed based on a four point scale. When a sample Center was completely congruent with the model on a factor, three points were awarded. Zero points were scored on a factor when the sample Center was the antithesis of the model. The second phase of the research was to select a sample of Centers, study their physical distribution pat- terns and then compare these patterns with the model. I Twenty—four Service Centers comprised the sample. These twenty-four were selected to give the study variety in terms of the type of product sold and size of Center. In addition, some Centers were independent while others were part of a chain. These Centers were located in seven geographic regions covering most of the United States. Personal interviews which lasted about eight hours were conducted at each Center. The final phase of the research evaluated differences of opinion regarding customer service among those holding different Jobs within the Center. If the Center is to be a cohesive unit and work as a system, then.incumbents in various assignments should share similar attitudes toward customer service. The Job classifications were inside sales, outside sales, warehouse manager and company exe- cutive. Each respondent within the Job classifications Peter Michael Lynagh at the twenty-four sample Centers was given a questionnaire. This questionnaire contained ten questions relating to service. ' Based on the research results, Metals Service Centers are presently performing the physical distribution functions below the levels suggested in the maximum performance model. This is true for the entire physical distribution system and for each of the sub—classifications -- order processing, warehouse handling and transportation. The research showed that no significant_difference exists between Metals Service Center of various size and the maximum performance mOdel. This was true for the entire system and for each 0f the sub-classifications. The research findings also showed that no difference exists between Metal Service Centers of various profit classifications and the model. This was true for the complete physical distribution operation and for each of the sub—classifications. The research results showed that no significant dif- ference of opinion exists regarding customer service among those holding different Jobs within the Metals Service Center. PHYSICAL DISTRIBUTION PATTERNS IN THE METALS SERVICE CENTER INDUSTRY By Peter Michael Lynagh A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Marketing and Transportation Administration 1970 Q} ACKNOWLEDGMENTS This thesis was made possible through the generous contributions of many people. This author wishes to extend to each of them his sincere appreciation. Specifically, I wish to express my gratitude to the following individuals and organizations: The Steel Service Center Institute whose fellowship made this research possible. A special debt of gratitude is extended to those Centers which cooperated in the study. Their encouragement and assistance was most helpful.‘ Robert G. Welch, president of the Steel Service Center Institute, and his excellent staff. At every stage of this research, Mr. Welch and the Institute were there to give guidance and encouragement. Dr. w. J. E. Crissy, committee chairman, who gave unselfishly so much supervision, help and inspiration. A special thank-you for everything. Dr. Frank H. Mossman, committee member, who guided my course work. Dr. Mossman gave much of his time and know- ledge. Dr. Donald J. Bowersox, committee member, who gave this thesis guidance and direction. His special efforts are greatly appreciated. My wife, Pat, who was always a source of inspiration, and willingly made many sacrifices. Muchas gracias! ii TABLE OF CONTENTS ACKNOWLEDGMENTS. . . . . . . LIST OF LIST OF LIST OF Chapter I. 11. III. IV. TABLES . . . . . . . FIGURES. . . . . . . APPENDICES. . . . . . INTRODUCTION . . . . . Importance of_Research .4 General Research Design. Presentation of Material PHYSICAL DISTRIBUTION MANAGEMENT Physical Distribution Defined. . Objectives of a Physical Distribution System . . History of Physical Distribution. Physical Distribution Functions Physical Distribution of Steel RESEARCH DESIGN AND SAMPLE Definition of the Problem Specific Statement of the Hypotheses Physical Distribution Model Conduct of the Research. Sample Design . . . . PHYSICAL DISTRIBUTION MODEL General Us e of Models . Model of Physical Distribution Patterns Measurement. . . . . iii Page ii vii viii l2 l2 16 18 24 37 ’43 MI “5 146 A7 53 57 57 6O 72 (Nundmu' Page V. IWXIIHIMINPAL HES ULTS . . . . . . . . 75 introduction . . . . . . 75 Comparison of Sample Centers and the Model . . . . . . 77 Experi.mental Results Based on Size . . . 81 Experimental Results Based on Profit . . 86 VI. COMPARATIVE ANALYSIS -— ATTITUDES ON CUSTOMER SERVICE AMONG JOB HOLDERS IN THE CENTER. . . . . . . . . . . . . 9I Physical Distribution and the Systems Approach . . . . . . . . . . . 91 Research Findings. . . . . . . . . 92 V11. CONCLUSIONS AND RECOMMENDATIONS. . .. . . 109 Introduction . . 109 Physical Distribution Compared with the . Model . . . . . 109 Analysis of the Physical Distribution Systems. . . . . . . . . . . . 126 Future Research . . . . . . . . . 138 APPENDICES . . . . . . . . . . . . . . lU6 BJBLIOGRAPHY . . . . . . . . . . . ,. . 197 iv Ti.) 1') .L 6‘ 1. 8. 10. l]. 13. 1.1; 0 LIST OF TABLES Page Distribution of Points Allocated to the Sample Centers. . . . . . . . . . . 79' Distribution of Points Allocated to the Sample Centers on Basis of Size . . . . . 83 Distribution of Points Allocated to the Sample Centers on Basis of Profit . . . . 87 The Degree to Which Centers Feel Service is Important to Their Customer . . . . . . 93 Significance of Service When Physical Products Are Identical . . . . . . . . . . . 95‘ Attitudes on Whether Centers Overstress Customer Service . . . . . . . . . . 96 Attitudes on Whether Centers Understress Customer Service . . . . . . . . . . 97 Self-Rating of Centers Comparing Their Ability to Give Customer Service with the Ability of the Center's Top Competitors . . . . . . 99 Major Causes for Failing to Meet the Cus- tomer's Desired Service Level. . . . . . 101 The Most Important Aspect of Quick Delivery Service As Determined by Respondents . . . 102 Perceived Competitive Advantage Held Over Competitors. . . . . . . . . . . . 10A Perceived Competitive Advantage Which Competitors Have . . . . . . . . . . 106 Most Frequently Lodged Complaints About Customer Service . . . . . . . . . . 107 Summary Table of the Points Scored by Sample Centers . . . . . . . . . . . . 113 Table Page 15. Mean Score of Sample Centers Compared with the Maximum Score of the Normative Model . . 177 16. Difference Between the Mean Number of Points Scored on Order Processing by Small and Large Centers . . . . . . . . . . . 181 17. Difference Between the Mean Number of Points Scored on Warehouse Handling of Small and Large Centers . . . . . . . . . . . 182 18. Difference Between the Mean Number of Points Scored on Transportation of Small and Large Centers . . . . . . . . . . . 183 19. Difference Between the Mean Number of Points Scored by Small and Large Centers . . . . 18A 20. Difference Between the Mean Number of Points Scored on Order Processing of Low and High Profit Centers. . . . . . . . . . . 185 21. Difference Between the Mean Number of Points Scored on Warehouse Handling of Low and High Profit Centers . . . . . . . . '. 186 Difference Between the Mean Number of Points Scored on Transportation of Low and High Profit Centers. . . . . . . . . . . 187 P0 P0 23. Difference Between the Mean Number of Points Scored by Low and High Profit Centers . . . 188 2". Compilation of the Chi-Squares Used in Chapter VI . . . . . . . . . . . . 189 vi LIST OF FIGURES Figure 1. Distribution of Steel From the Mine To the Customer . . . . . . . . 2. Basis for Assignment of Maximum Points for Physical Distribution Model . . . . . vii LIST OF APPENDIC‘S Appendix Page A. The Data Collection Instruments . . . . 1H7 B. Allocations of Points to Sample Centers . . . . . . . . . . . . 167 C. Statistical Computations. . . . . . . 175 viii CHAP'l'ER I INTRODUCTION Importance of Research Metal Service Centers serve as the distribution arm of the metals industry. Centers1 are set up to service buyers who do not have the volume to purchase from the mill. Centers purchase from the mill in carload or truck- load quantities. Metals are received at the Center, placed in storage racks, selected, in some cases pre— production processed, then less—than-carload or less-than- truckload shipments are sent to the final customer. Cen- ters are classified under S. I. C. 5091 as "Ferrous Metals Service Centers and Non-Ferrous Metals Service Centers". At one time, Centers were almost exclusively in the business of performing wholesale function. Large quanti- ties of metal would be purchased from the mill; smaller quantitities would then be sold to customers generated by the Center. Today pre—production processing is a vital 1Throughout this thesis Metal Service Centers will be referred to as Centers. zuul inux)rtant.;wirt of'tJio atngivity (>f truérnoderVIIMarvi(ué Contcrn thsventy—fdAn31u3r cent (H‘:ill orders slflquuxl by the Centers are processed in some manner.1 Metals Service Centers handle a variety of products. Steel, aluminum, brass, bronze and copper are the primary metals carried. Centers also carry plastics and compos— ites, as well as metals coated with various other mate- rials such as vinyl. Steel is the major product moving through Centers. In 1968, Centers handled 16.1 million tons of domestic steel products. These represented 17.5 per cent of the total tons shipped by the domestic mills. There are over A00 firms which belong to the Steel Service Center Institute, a trade association representing firms in the steel industry; and, these A00 operate 900 Centers across the country.2 Traditionally, many of these Centers are small family—run businesses. In addition, there are other Centers which do not belong to the SSCI. SSCI members do in excess of 80 per cent of the business shipped.3 Physical diStribution is a major competitive factor in the Metals Service Center industry. The product is 1Robert G. Welch, President of the Steel Service Center Institute, in a letter to this writer, dated April 23, 1970. ') “Steel Service Center Institute, 1969—1970 Roster of Members (Cleveland, Ohio: Steel Service Center Institute, 19695, p. H. 3Robert G. Welch, op. cit. n - homogeneous and the general level of prices is approxi- mately the same between Centers in the same area. Loca— tion does not provide a competitive edge as major popula- tion centers have many competing Centers. In New York City, there are 70 Centers which belong to the Steel Ser- vice Center Institute.1 Promotion is important, espe- cially inside and outside selling, but often promotion is centered around the Center's physical distribution capa- bility . The focal point of competitive action becomes the activities which must be undertaken in order to affect delivery of the product to the customer at the desired time. In this industry, first day delivery is expected ‘on non-processed order. Delivery requirements for pro— cessed orders are set by demand conditions in an area for a particular type of processing. If a firm is to be an effective competitor, it must be able to quote compe— titive delivery dates and have the physical distribution , system to back up these commitments. Studies in this industry of various segments of the physical distribution system have been made. This thesis will look at physical distribution as a unit, i.e., not order processing by itself, but order processing as a link in a system designed to see that the customer's order lSteel Service Center Institute, op. cit., p. A. A is delivered at the right place at the right time. Cen— ters must see the interrelationship of various physical distribution functions, and make sure that individuals working within the system see the overall needs. Customer service is one aspect of physical distri- bution. It is the intent of the physical distribution system to achieve a desired customer service level at the lowest cost possible. VMany Centers operate on a very small profit margin. A return of six per cent on net profit before taxes is conSidered very good in this induse try. Profits shrink when physical distribution is inef- ficient and costly. This research focuses on areas wherein physical distribution economies can be realized. Specifically, then, the present research is designed to analyze physical distribution patterns in the Metals Service Center industry. This study is important because it is aimed at improving physical distribution of the Metal Service Center. This is not only each Center's major competitive weapon, it bears directly on the Center's economic effectiveness. Stating the purpose of the research in problem form it is to: (1) determine those physical distribution acti— vities undertaken by Metal Service Centers to make sure that the customer's order is delivered on time; (2) build a maximum performance model of physical distribution in this industry; (3) determine if large or small Centers \J'l come closer to the maximum performance model; (A) deter- mine if more profitable or less profitable Centers come closer to the maximum performance model; (5) compare differences of opinion regarding customer service among those holding different jobs within the Center; and (6) determine those physical distribution areas wherein improvements can be made, and which provide fruitful areas for future research. General Research Design1 The overall aim is to construct a maximum performance model of physical distribution patterns in the Metals Service Center industry, to develop actual dataregarding the existing patterns in this industry, and then to make a comparison between what should be and what is. The second part of the research is intended to evaluate differences of opinion regarding customer service among those holding different jobs within the Center. Initially the problem was to develop an approach for securing information about physical distribution patterns in the Metals Service Center industry. The first method considered was the use of a mail questionnaire to cover the entire population of Centers throughout the United States; this extensive mail questionnaire would then be backed up by several relatively short personal interviews. The second method considered was to select a few lDetailed coverage can be found in Chapter 3. representative Centers and to carry out extensive per- sonal interviews with each one. The latter method was selected. The next decision had to do with the number of Cen— ters to be sampled. Enough sample Centers were required in order to make the sample representative with respect to size, geographic location and type of product carried.‘ It was felt that the research would be most meaningful if it included as many Centers as possible; however, time and expense were factors working to keep the number down. A review of the needs of the research was carried out and related to the categories of Centers which should be covered. It was felt that this researCh should cover most geographic areas in the country, study both large and small Centers, sample Centers carrying various types of products and include single-Center operations and multi-branch Centers. Twenty-four Centers were selected to be sampled, because it was felt that this number would give the research the representativeness desired. Any number less than 2A would have emitted a necessary ele— ment. It was assumed that any number in excess of 2A would have added information, but this additional infor- mation would have involved too much extra time and expense. These 2“ Centers are located in seven geographic areas: New England, Mid-Atlantic, Mid—West, Ohio Valley, South, Southwest and Far West. Three Centers were selected from the Mid—Atlantic, South, and Far West, five were selected from the Mid-West and two from the Ohio Valley and the Southwest. From these regions, Centers were selected so as to provide Centers of various sizes. Thirteen Centers with sales of $10 million or more and 11 with sales of less than $10 million were selected. Thirteen single plant Centers were selected and 11 Centers from multiple plant companies. Size selection was weighted with product variety. The study included the general line carbon steel Centers and specialized Centers handling a more limited line. Specialized products included uncoated carbon steel sheets, stainless steel and alloy bars, carbon steel tubing, aluminum and stainless steel, cold rolled steel and pre— cision ground and chrome plated precision shafting. Once the number of Centers to be visited and their locations had been determined, the next step was the development of instruments which would be used to collect the data. Instruments were developed to gather informa- tion from three separate areas: (1) data about the char— acteristics of the Center; (2) data about the physical distribution activities of the Center; (3) data about attitudes toward customer service by various job classifications within the Center. Examples of these instruments can be found in Appendix A. The first instrument developed was the company "Data Sheet”. This was sent out to each of the respond— ents two weeks prior to the visit and was included with a letter of introduction. This instrument was mainly designed to secure answers to questions about the gen- eral organization and operation of the Center. "Data Sheets” asked questions regarding such areas as Net Sales, and were used to classify the Centers on relevant variables and to familiarize the interviewer with the Center prior to the personal interview. A personal interview schedule was the next instru- ment developed. By the use of this instrument a pattern was set up for the interviews, insuring coverage of top— ics and consistency from interview to interview. in basic design, the personal interview schedule was divided into six major sections. Each of the six sections was designed to cover the order from pre-receipt planning to customer delivery. Section I comprises general overall questions best answered by a company officer. Section II contains questions covering the order processing activi- ties. Section III relates to problems of warehouse and transportation scheduling. Warehouse design, methods and Operations are covered in Sections IV and V. The final section deals with the areas of transportation. 'Phe third data gathering instrument used was the ”Internal Questionnaire". In this instrument the ques- tions asked relate to customer service and how the respondent's Center compares with competitors in the area of service. identical questionnaires were given to four or five job groups within the Center. The general purpose was to obtain the respondent's feeling about the adequacy of the Center in the area of customer service. Each Center was given four copies of the "Internal Questionnaire," or five copies if they had a traffic department. One copy each went to the inside salesman, outside salesman, warehouse manager and a company officer. "Internal Questionnaires" were left with the president for distribution and were to be mailed back to the writer upon completion. Once the three instruments were developed, the Steel Service Center Institute arranged with a Center on the east coast to act as a test Center. All three instruments were pre-tested, and revisions were made based on the results. A planned schedule of visits to all areas was set up. Several weeks prior to the proposed visit, the Steel Service Center Institute sent letters to the various Cen- ters apprising them of the study and asking for their cooperation (See Appendix A). Shortly after the letter from the Steel Service Center Institute was sent, a 10 letter was mailed to the Center requesting permission to conduct a pit'rsonal interview on a specified date. This letter also contained the company "Data Sheet" which the Center was requested to fill out and return. Personal interviews were arranged on the basis of one full day for each interview. Such an arrangement worked out reasonably well. A full day was adequate in most cases; however, there were a few interviews which did not require the complete day and others where one day was not long enough. Interviews began with the company executive who answered the broad overall questions relative to physi- cal distribution. After the session with the company executive, the next step involved inside sales. When the interview was completed with the inside sales department, the next step was to carry the interview out to the ware- house. In the warehouse, interviews included the ware- house manager, shipping clerk and traffic manager, if there was one. Sometime during the warehouse interview, a tour was made of the warehouse itself. Directly after these interviews, a report was writ— ten summarizing the physical distribution patterns of the Center visited that day. Thus, from the three basic instruments, an all day interview, and a written report on each Center have evolved the data which are the bases of this thesis. 11 Presentation of Material Chapter 11 is concerned with physical distribution management. This chapter includes a working definition of physical distribution, a brief history of the physical distribution concept and a review of the basic function of physical distribution. In Chapter III a detailed description of the research design is presented. In Chapter 1V the maximum performance physical distribution model is described. Chapter V contains the statistical analysis of the findings broken down according to size and profit. In Chapter VI the findings on the attitudes toward customer service among those holding different jobs within the Center are presented. Conclusions and recommendations are given in Chapter VII. CHAPTER II PHYSICAL DISTRIBUTION MANAGEMENT Physical Distribution Defined The National Council of Physical Distribution Man— agement has broadly defined physical distribution as: A term employed in manufacturing and commerce to describe the broad range of activities concerned with efficient movement of finished products from the end of the production line to the consumer, and in some cases includes the movement of raw . materials from the source of supply to the begin- ning of the production line. These activities include freight transportation, warehousing, materials handling, protective packaging, inven- tory control, plant and warehouse site selection, order processing, market forecasting and customer service.1 According to Bowersox, Smykay and Lalonde, "Physi— cal distribution management is defined as that responsi— bility to design and administer systems to control raw material and finished goods flow."2 To some people, physical distribution ”refers to that portion of a 1National Council of Physical Distribution Manage— ment, Executive Offices, 307 N. Michigan Avenue, Chicago, Illinois. 2Donald J. Bowersox, Edward W. Smykay and Bernard J. LaLonde, Physical Distribution Management (New York: The Macmillan Company, 1968), p. 5. 12 l3 logistics system concerned with the outward movement of products from the seller to the customer or consumer."1 Charles Taff defines physical distribution as "the management of movement, inventory control, protection, and storage of raw materials and processed or finished goods 2 to and from the production line." The American Market— ing Association defined physical distribution as "the movement and handling of goods from the point of produc- tion to the point of consumption or use."3 Some view physical distribution management as part of a larger concept, business logistics. Business logis- tics has been defined as "the management of all activities which facilitate movement and the coordination of supply and demand in the creation of time and place utility in goods.”u Another definition of business logistics is 1John F. Magee, Physical Distribution Systems (New York: McCraw—Hill, Inc., 1967), p. 2. 2Charles A. Taff, Management of Traffic and Physical Distribution (Ath ed.; Homewood, Illinois: Richard D. Irwin, Inc., 1968), p. 6. 3Definitions Committe of the American Marketing Association, "19MB Report," The Journal of Marketing, (October, 1948), p. 202. “J. L. Heskett, Robert M. Ivie and Nicholas A. Glas- kowsky, Jr., Business Logistics (New York: The Ronald Press Company, 1963), p. 21. I” that it ”is the process inherent in a distribution system that moves materials and products from their producer to their consumer."l Logistics is defined as "the science concerned with the logical arrangements of the functional areas required to achieve a desired goal. Thus, the logistics of distri— bution systems is the science concerned with the logical conceptual arrangement of the movement system facilities in such a way that a given desired goal is attained."2 Logistics has also been defined as ”the act of managing the flow of materials and products from source to user."3 Under a business logistics approach, the supply or inbound distribution system is often called "Materials Management." Dean S. Ammer says that materials manage- ment would embrace all activities conerned with materials except those directly concerned with designing or manu- facturing the product. He includes purchasing, control, traffic, shipping, receiving and stores.14 Materials 1David McConaughy, ed., Readings in Business Logis- tics, (Homewood, Illinois: Richard D. Irwin, 1967). 2Frank H. Mossman and Newton Morton, Logistics of Distribution Systems (Boston: Allyn and Bacon, Inc., 1965), p“ u' 3John F. Magee, Industrial Logistics, (New York: McCraw—Hill, 1968), p. 2. ”Dean S. Ammer, Material Management (rev. ed., Homewood, Illinois: Richard D. Irwin, Inc., 1968), p. 12. management covers all phases of the logistics of supply and acquisition.1 Materials management is referred to by others as physical supply. Physical supply has been defined as "the portion of a logistics system concerned with the inward movement of materials or products from source to buyer."2 To further complicate the semantic problem, there are other terms and definitions. "Rhochromatics" has been called a scientific approach to the management of material flows."3 "Marketing Logistics" attempts to tie together several of the related aspects of the adminis- tration of the economic firm, more specifically promotion and logistics.“ While there are many different definitions of physi- cal distribution and several varied ideas as to what it covers, there is concensus on the fact that physical dis- tribution is concerned with movement and the creation of time and place utility. Physical distribution is 1Paul T. McElhiney and Robert I Cook, The Logistics of Materials Management (Boston: Houghton Mifflin Com- pany, 1969): p. v. 2Magee, Industrial Logistics, op. cit., p. 2. 3Stanley H. Brewer, Rhochromatics, A Scientific Approach to the Management of Material Flows (Seattle, Washington: Bureau of Business Research, University of Washington, 1960), p. 3. “Norton E. Marks and Robert Martin Taylor, eds., iarketing Logistics (New York: John Wiley & Sons, Inc., 1967), p. 1x. 16 concerned with having orchids at the university flower shop the day of the homecoming dance and not in Hawaii. it is concerned with having steel at the customer's receiving dock when he wants it, at the lowest total cost possible. In this thesis physical distribution is assumed to mean the design and administration of systems controlling the flow of both finished goods and raw materials.1 Objectives of a Physical Distribution System Once the definition of physical distribution is established, it then becomes a problem to set forth objec- tives of physical distribution. What should guide mana- gers in designing and administering systems controlling finished goods and raw materials flow? The objective of a good physical distribution system should be the meeting of the stated corporate customer service policy at the lowest total cost.2 This objective is achieved by a bal- ance of cost and service because "no physical distribution system can simultaneously maximize customer service and n3 minimize distribution cost. lBowersox, Smykay and LaLonde, op. cit., p. 5. 2Ibid., p. 113. 3Philip Kotler, Marketigg Management (Englewood Cliffs, New Jersey: Prentice-Hall, Inc., 1967), p. A20. 17 These objectives of physical distribution are dif— ficult to achieve because it is hard to develop accurate customer service standards and precise cost figures. Ser— vice standards are measured in time consumed from the point at which the order is placed until the order is delivered to the customer. Measuring just what the cus- tomer requires in the way of service is difficult because the customer will often ask for the highest level of ser— vice and be willing to settle for something a little less. Service is difficult, also, because there are other vari— ables to consider besides time, e.g., dependability, com- munications and convenience.1 Given a required level of customer service, then, the physical distribution system should attempt to meet that service date at the lowest total cost. All physical distribution costs must be looked at together and com— bined to achieve the lowest overall cost. This total cost approach is different from the old system wherein an attempt was made to minimize costs in each functional area. Under the old system, it was possible to raise total cost by minimizing costs in one area, e.g., the selection of rail transportation might lower transporta- tion costs, but increase inventory cost and warehouse cost. 1John F. Gustafson and Raymond Richard, "Customer Service in Physical Distribution," Transportation and Dis- tribution Management, (April, 1964), pp. 19—23. 2United Air Lines Profit Analyzer (Chicago: United Air Lines, Inc., 19613. 18 it is necessary, under a total cost approach, to know all of the costs of physical distribution. Not all firms have this information and the accuracy of those costs that are available is sometimes questionable. In the present research an assumption is made that the objective of physical distribution is the achievement of a desired level of customer service at the lowest total cost. History of Physical Distribution Earlnyevelmeent Around the turn of the twentieth century, the United States shifted from an agrarian economy to an industrial economy. With this came widespread mass production. Dis- tribution problems began to take on major significance as large manufacturers replaced wholesalers as dominant factors in the distribution of goods. As distribution became more important and problems grew, there emerged a number of books and articles on the marketing function.1 These early writers tended to equate physical dis- tribution mostly with transportation and storage. 1The material on the development of Physical Dis- tribution is based on an article by Bernard J. LaLonde and Leslie M. Dawson, "Early Development of Physical Dis— tribution Thought," in Bowersox, LaLonde and Smykay, eds., Readings in Physical Distribution (New York: The Mac— millan Company, 1969), p. 9. 19 'Plu: (Mirlj/ 'IirilujlnyOLx' iAEXLLK of‘ tin; lifl’O':; fKHl— (irally (navered.tfiu3 physicmil distrdinition zuwxi in a section or chapter on 'transportation.‘ Grad— ually, however, as the task of distributing an increasing amount of differentiated products to regional and national markets grew, greater re- cognition was given to the deeper stfategic im- plications of physical distribution. Some of the early pioneers in this area were Arch W. Shaw, Paul Cherington, Fred E. Clark and Theodore N. Beckman. In the latter 1920's, Ralph Borsodi began to look into the costs of physical distribution. Borsodi said in 1927 that, "The day is gone when the recipe for fabulous profit was simply production, more production and still more production. The golden age of production is past. The age of distribution is upon us."2 In 1929, Richard Webster wrote an article entitled, "Careless Physical Distribution: A Monkey Wrench in Sales n3 Machinery. Webster talked about coordinating such activities as plant location, warehousing, freight rates, packaging and inventory control. Other authors in the 1Bernard J. LaLonde and Leslie M. Dawson, "Pioneers in Distribution,” Transportation and Distribution Manage— ment, (June, 1969). 2Ralph Borsodi, The Distribution Age (New York: D. Appleton & Company, 1929), p. 3. 3Richard Webster, "Careless Physical Distribution: A Monkey Wrench in Sales Machinery," Sales Management, Vol. XIX (July 6, 1929), p. 21. late 1920's and early 1930's were looking at the integra— tive nature of the physical distribution activities. Ralph Breyer1 and Paul Converse2 were two of the major contributors during this period. The literature was somewhat muted in the area of physical distribution during the depression and World War II periods. While World War II may have been a period of limited writing, the physical distribution problems over— come by the United States in World War II were signifi— cant. Integration of physical distribution activities was necessary during the war in order to carry on a mili— tary conflict in both Europe and Asia. Growth of Physical Distribution After the second World War, interest developed in marketing. There was a tremendous growth in the product line of many companies. The "marketing concept" was developed which turned the focus of the firm to the cus- tomer. "The 'marketing concept' involves, among other “.3 things, a consumer—oriented approach to marketing 1Ralph F. Breyer, The Marketing Institution (McGraw- Hill Book Company, 193“). 2Paul D. Converse, Selling Policies (Englewood Cliffs, New Jersey: Prentice—Hall, Inc., 1927). 3Charles F. Phillips and Delbert J. Duncan, Market— ing Princioles and Methods (6th ed.; Homewood, Illinois: Richard D. Irwin, Inc., 1968), p. 56. 91 lWarkcd.zlcgnmnnxitiornlunhan iml‘take IllflCC. 'UWarktfll:segnmwh- tation consists of viewing a heterogeneous market as a number of smaller homogeneous markets in response to dif— fering product preferences among important market seg- ments."1 Instead of producting one black telephone and using advertising to capture various tastes, multi- colored telephones in various styles were produced. Market segmentation means that more items are in inventory with attendant increases in the cost of carry— ing inventory and with the need for efficient inventory management. Distribution centers must carry wider lines of products. Selection in the distribution center becomes more difficult. Transportation problems are increased by the necessity for consolidating many differ- ent products. Order processing problems increase because the order is not for ten items of "A", but is for one item of "A”, one of "B", and one of "C", etc. Wider product lines cause changes in packaging and require variations in material handling equipment. In the late 1950's, many business organizations were confronted with a cost—profit squeeze. Costs were increasing faster than revenues and the opportunity for economies in production were limited. Under the 1Wendell R. Smith, "Product Differentiation and Market Segmentation As Alternative Marketing Strategies,‘ in The Environment of Marketing Behavior, ed. by Hello— way and Hancock (New York: John Wiley and Sons, 196“), D. 305. I functional approach to distribution, each area was man- aged separately and costs were high. Management began to realize that the profit—cost squeeze might be alleviated by more effective physical distribution management. It was also during the late 1950's that great advances were made in automated data processing equipment. Physical distribution management entails the integration of many functions. All functions must work together in order to achieve the lowest total cost consistent with good customer service requirements. This sounds very good; however, a man with a pad and pencil can hardly work out all of the possible combinations. Multivariate problems, previously too complex to handle, are easily solved with the computer. The capabilities and potential of the computer fit the requirements of physical distri- bution very nicely. Along with the development of auto— matic data processing equipment came the systems approach to management. Under the systems approach, the firm maxi- mizes profit by analyzing all components of the business enterprise and the interaction of these components upon one another.1 Other major factors during the 1950's and early 1960's which helped the growth of the physical distribution concept were: (1) changes in customer demand patterns in 1Charles A. Taff, Management of Traffic and Physical Distribution (Nth ed.; Homewood, Illinois: Richard D. Irwin, Inc., 1968), p. A. 23 terms of location; (2) increased competition both domes- tic and foreign; and, (3) the impact of the trend toward conglomerate mergers on procurement and distribution sys- tems.1 Physical Distribution in Maturity Physical distribution began to get recognition in the early part of the twentieth century in the marketing text books. The focus of attention of this early period was on the distribution of commodities and its role as a marketing function. The individual elements which make up physical distribution as we know it today were around, but there was no extensive treatment of all of the elements as a unit. During the 1950's and early 1960's, the functional areas of physical distribution were integrated, and the concept of a physical distribution system came into being. It is not, then, that physical distribution has actually grown out of marketing or traffic management;2 rather it 1Lewis M. Schneider, "Milestones on the Road of Physical Distribution," Reflections on Progress in Market— igg, American Marketing Association (December, 1963), pp. 395-396. 21h Charles Taff's original book on traffic manage- ment, the author defines traffic management as "the myriad aspects of the purchase of transportation and transporta- tion service by shippers or consignees, . . ., which will include the use of facilities and equipment at a price or rate consistent with the services rendered in order to effect the efficient movement of persons and property from one point to another." has been a regrouping of many related functions to form a new whole, physical distribution. Many traffic manage— ment educators were significantly involvedlin the growth of the physical distribution concept, but the real leader— ship came from the industry buyers and suppliers of trans- portation.l . Physical distribution is in a period of refinement. "The years since 1965 have been characterized by a refine- ment in basic concepts and a development of greater pre— cision in the tools of analysis."2 The base has been set, physical distribution must now grow and develop from that base. Physical Distribution Functions It is difficult to specify exactly what functions should be included under physical distribution because each firm has a different set of functions in its physi- cal distribution department. There are differences here, some of which are related to the different definitions of physical distribution. Some of the areas that might be included in physical distribution are: transportation, 1Donald J. Bowersox, "Physical Distribtuion in Semi— Maturity," Air Trangportation,(January, 1966), pp. 9—11. 2Donald J. Bowersox, "Physical Distribution Develop— ment, Current Status and Potential," in Readings in Physi— cal Distribution Management ed. by Donald J. Bowersox, Bernard J. LaLonde and Edward W. Smykay (New York: The Macmillan Company, 1969), p. 368. inventory control, warehousing, materials handling, pack— aging, site selection, order processing, and information systems. Transportation This is the area wherein the traffic manager has traditionally been in managerial control. Traffic mana— gers generally have control over the actual movement of people and material. They are responsible for the plan- ning, direction, selection, procurement and use by the organization of all the aspects of transportation.1 Traffic management started as a specialized aspect of purchasing.2 Some of the more specific functions inclu- ded here are the procurement of all transportation and the management and operation of private transportation fleets. Perhaps the greatest emphasis in transportation is on the movement of freight; however, the movement of peo- ple is also very important. Effectively handling a house— hold goods movement or making the transportation aspects of the annual meeting come off smoothly can lead to greater confidence in the distribution department and pay dividends in later freight movement progress. lTaff, op. cit., p. 9. 2Kenneth J. Flood, Traffic Management, (2nd ed.; Dubuque, Iowa: William C. Brown Cempany Publishers, 1963), p. 7. :26 Traffic managers also are the experts on the costs of transportation, and work with the carriers to get lower rates and better classification of items. They also audit transportation charges and file loss and dam- age claims against carriers. Traffic managers must be familiar with the legal aspects of transportation as well. This might include working with local commissions, or the interstate Commerce Commission. Traffic managers should he the ones who know the legal obligations and restraints of transportation. Another vital role of this department would be to control all shipments in the distribution pipeline. Activi— ties here might include expediting and tracing of ship- ments, diversion or reconsignment of shipments, procure— ment of equipment, and establishing transportation con- tracts. In some companies, this department is often the authority on international shipments. Traffic managers also develop consolidations which lower distribtuion costs and improve service. Inventory Control "Inventories have their justification in terms of the extent to which they contribute to the effective over- all operations and profitability of an organization."1 lNorbert Lloyd Enrich, Inventory Management (San Francisco: Chandler Publishing Company, 1968), p. 11. 97 inventory management has always been difficult from the firm's point of view. Sales has traditionally been inter— ested in a high finished goods inventory; production and purchasing might like large raw material inventories; and, finance wants very little capital tied up in any kind of inventory. These issues of inter-department con— flict must be solved for the overall good of the firm.1 Inventory management is defined as "the sum total of those activities necessary for the acquisition, stor- age, sale, disposal or use of material."2 Primary among the problems of inventory management are the questions of what to order, when to order and in what quantity or volume to order. What to order depends on good research as to what the market will demand. Not only is it important to know what the market will want, but the firm must gener— ate information about the volume of each item, the cus— tomer purchasing the item, the critical—value of this item to the customer and the costs associated with being caught out of stock on a particular item. Inventory forms a buffer between production and sales and the effectiveness of any inventory management program depends llbid., p. xiii. 2James A. Pritchard and Robert H. Eagle, Modern Inventory Management (New York: John Wiley & Sons, Inc., 1965), p. 2. largely on an ability to make some sort of reasonably accurate forecast of usage or sales. All inventory mod— els depend on a forecast of sales.1 Stockouts are a major problem. When customer relations are damaged, the reputation of the firm as a dependable source of supply is harmed.2 It is a very difficult matter to determine the probably cost of a lost sale or a lost account. In addition to stockout costs, there are other costs which affect inventory management. There are the costs associated with procur- ing the units of stock, costs of carrying the items in inventory, costs of filling customer orders and the cost of operating the data gathering and control procedures 3 for the inventory system. These costs must be balanced in order to achieve the lowest total cost. Problems of when to order are related to the order cycle and forecasting requirements. Firms must know when the material will be required, how long it will be in lJoseph Buchan and Koenigsberg, Scientific Inven— tory Management (Englewood Cliffs, N. J.: Prentice—Hall, Inc., 1963), p. 28. 2James A. Constantin, Principles of Logistics Man— agement (New York: Appleton—Century Crofts, 1966), p. 322. 3George Hadley and Whitin, Analysis of Inventory Systems (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1963), P. 10. in transit, what length of time it takes to communicate the order and to process the order. How much to order generally requires the balancing of the cost of ordering and the cost of carrying inven- tory. The most commonly used method here is the economic order quantity (EOQ).l Mathematically, this formula is usually expressed as: r .-. ——._ —. . _ 2 as -1 i a = Ordering Cost per Order s = Annual Sales Rate 1 = Interest Cost per Unit per Year The EOQ method is subject to many limitations, but it can serve as a foundation upon which a firm may develop more sophisticated systems. Warehousing Twenty or 30 years ago, warehousing was looked on as a necessary evil. Warehousing was basically a storage function which had goods held near the market prior to con- sumption. This was necessary because production and con— sumption were not coordinated.2 Today the warehouse, or as it is more commonly known now, the distribution center, lBowersox, Smykay and Lalonde, o . cit., p. 20“. ’) “Fred Clark, Principles of Marketing (rev. ed.; New York: The Macmillan Company, 1932), p. 368. 30 emphasizes the movement of goods. Centers are placed strategically throughout the firm's market territory in order to facilitate the movement to the customer. Cen— ters are added or deleted to achieve a lower distribution cost or gain better service.1 The ideal system would find orders "being received, blended into customized orders, and shipped to the next node in the distribution channel without the goods coming to rest within the confines of the distribution center."2 "Delivery time has become an essential tool of mar— keting; frequently, providing shorter delivery time is used instead of lowering prices to attract the customer. This marketing technique is one of the main reasons why the field of warehousing is expanding so rapidly."3 The distribution center concept has made the ware— housing function important in the physical distribution system. The problem is that sometimes obsolete methods are coupled with crowded conditions resulting in slower 1Donald J. Bowersox, "The Distribution Center Loca— tion Problem," Houston Business Review, (Winter, 1965), p. A1. 2Norman E. Daniel and J. Richard Jones, Business Logistics: Concepts and Viewpoints (Boston: Allyn and Bacon, Inc., 1969), p. xi. 3Creed Jenkins, Modern Warehouse Management (New York: McGraw-Hill Book Company, 1968), p. l. 31 materials movement and extra handling with attendant increases in operating expenses. John F. Magee lists eight major functions a ware- '3 house performs:“ l. Receives Coods 1dentifies Goods Sorts Goods Dispatches Goods to Storage Holds Goods Recalls, Selects or Picks Goods Marshalls the Shipment Dispatches the Shipment Some of the major problems which must be answered in order that these functions be carried out deal with the overall warehouse evaluation and requirements, warehouse construction and finance which includes site selection, construction cost factors and facility design factors; warehouse layout, efficiencies in operations including handling-time standards, space-utilization standards and performance control reports; evaluation, selection and maintenance of handling and storing equipment; the sched— uling of operations such as receiving, processing, order picking and shipping; and, the development of cost and administrative controls.3 1Andrew J. Briggs, Warehouse Operations, Planning and Management (New York: John Wiley & Sons, Inc., 1960), p. l. 2 John F. Magee, op. cit., p. 73. 5Jenkins, op. cit., p. v. 32 Problems related to site selection and materials handling are often included under separate categories. This is done because the difficulties connected with these two areas go beyond distribution warehousing. Site selec- tion would go beyond the warehouse location and include also such factors as plant location. Likewise, problems of materials handling will go beyond the warehouse and would include movement in the plants and other areas. Materials handling "embraces the basic Operations in connection with the movement of bulk, packaged and individual products in a semi—solid or solid state by means of gravity-, manually— or power-actuated equipment and within the limits of an individual producing, fabri— cating, processing or service establishment."1 Materials handling is moving things from one place to another and arises not by itself but within the context of a larger system.2 Packaging Packaging is something every manufacturing firm does. It is difficult to say just where in the organization pack— aging lies. Packaging organization varies so greatly from lD. Oliphant Hayes, Materials Handling Equipment (Philadelphis, Pa.: Chilton Company, 1957), p. viii. 2William T. Morris, Analysis for Materials Handling Management (Homewood, Illinois: Richard D. Irwin, 1962), p‘ 30 company to company that only a few accurate generaliza- tions can be made. In some firms packaging is a part of the production operation; in other firms packaging is part of the marketing department, and in a majority of firms packaging falls somewhere between the two extremes.1 Packaging may be defined as "the preparation of goods for ’) SiLlpHKBHt. arkl InaId _ m m . m m _ I B m a Z . m A _ o m \ fill... m x a e \ w m \ _ _ _ l _ \ e m mooem _ Atril :1t*r\/it:e Lkrrltcri' 1:1(hizzt1'v , 1,1né p1"cd)1(:un; urithar‘ I“CLSCZlIW111 i n this thesis are; hoes size affect the Centers' physical distribution patterns? Do high profit Centers have better physical distribution systems than low profit Centers? hoes the job an individual performs in the Center affect his attitude toward customer service? l. . . . I"red N. Kerlinger, Foundations of Behavioral Pesearch (New York: Holt, Rinehart and Winston, Inc., 1905;, p. 19. This research is designed to ascertain the answers to these three basic problems. because problems cannot be scientifically solved, they must be expressed in hypothesis form. Problems and hypotheses are closely related; however, hypotheses, when properly stated can be tested. The following section outlines the hypotheses used in this thesis. Specific Statement of the Hypothesis A hypothesis is defined as, "a tentative assump- tion made in order to draw out and test its logical or empirical consequences."l Hypotheses are a vital and important part of research. Hypotheses are important because they are the working instruments of theory. Also, hypotheses can be tested and "enable man to get outside himself."2 "A problem really cannot be scien- tifically solved if it is not reduced to hypothesis form because a problem is a question, usually of a broad nature, and is, in and of itself, not directly testable."3 Through a hypothesis, research achieves direction; prob— lems can be solved and the premises underlying these prob- lems can either be supported or not supported. lWebster's Seventh New Collegiate Dictionary (Spring- field, Mass: G. and C. Merriam Company, 19637, p. A10. 2Kerlinger, on. cit., p. 22. 31bid., p. 23. In; This research is structured to test the following null hypotheses. Hypothesis 1: No differences exist between Metal Service Centers of different size groups and the maximum performance physical distribution model. Hypothesis 2: No differences exist between Metal Service Centers of various profit classifications and the maximum performance physical distribution model. Hypothesis 3: No differences of opinion exist regarding customer service among those holding different Jobs within the Metal Service Center. Physical Distribution Model The physical distribution model to be used in this thesis is a verbal, maximum performance model. This model is verbal because the variables and their relationships are described in prose rather than mathematically. It is a maximum performance model because it purports to show how things should be in physical distribution under ideal conditions rather than describing things as they actually are. There are three parts to the model based on three sub-sections of the Center's physical distribution system. The first part of the model covers the inside sales activi- ties. Each major activity which takes place during the [17 period from when the order is received until it is sent to the warehouse is described in prose according tohow this activity should be carried out. The other two areas covered are the warehouse and transportation. The ware- house sections cover those activities from when the order is received in the warehouse until it is shipped. Trans— portation covers all those activities which must be car— ried out in delivering the order. Conduct of the Research Survey research is a branch of investigation that studies large and small populations by selecting and studying samples chosen from the population to discover the relative incidence, distribution and interrelation- ships of variables.1 Survey methods are generally clas— sified as: personal interview, mail questionnaire, panel, telephone and controlled observation.2 Of these, the personal interview and mail questionnaire seemed most appropriate for the present research. The latter was eliminated because in order to cover the total physical distribution system, mail questionnaires would have to have been rather lengthy. This would have increased the lack of response and made the job of analyzing the respon- ses furnished more difficult. Poor response would have 1Kerlinger, op. cit., p. 393. 2Ibid., p. 397. 148 made it impossible to make valid generalizations. The use of the mail questionnaire would limit the amount of personal observation of such things as warehouse design tr congestion on the shipping dock which were believed to be a necessary part of this study. Personal interviews with a limited number of Centers was finally selected as the data collecting method. Per— sonal interviews would provide for detailed observations, clarifications of questions, probing into weak areas, finding the proper person to answer each of the questions. It was felt tht the personal interview would provide the maximum amount of information and allow for flexibility in individual situations. Data gathering for the second part of the study dealing with attitudes toward customer service by various job holders within the Center was handled through a ques- tionnaire. The questions asked were short, direct and required no explanations or probing. it was felt that response would be good if these questionnaires were left with one of the Center's top managers for distribution to the appropriate personnel at the time of the personal interview. instrument Development Three instruments were developed in order to gather data for this thesis, the company data sheet, a personal interview schedule, and internal questionnaire (see ”9 Appendix A). The company data sheet was a short two page questionnaire which was set up to provide some basic infor— mation about the Center prior to the personal interview. Data sheets contained questions about the Center's product line, profit, number of employees, and markets. The data sheet not only provided background information about the Center, it also provided the information which allowed Centers to be categorized and provided more personal inter- view time for questions about physical distribution be— cause routine company information questions had already been asked. Personal interview schedules were set up in six sections: company officer, order processing, scheduling, selecting, packing and shipping and transportation. The company officer was placed first so that the interviewer could introduce himself to the Center's top management and help to assure cooperation throughout the Center. In addition, the company officer was asked questions which might be considered classified, for example, those deal— ing with costs and those which covered the complete opera— tion, such as physical distribution policy. The remainder of the schedule was arranged to cover three major areas: inside sales, which included all oper— ations from receipt of the order until it goes to the ware- house; warehouse operation, which covered the order from the time when it arrived in the warehouse until it was 50 shipped; and, transportation, which covered fleet opera- tion and maintenance, delivery scheduling, routing and transportation rates. Internal questionnaires were the final data gather— ing instruments used. This questionnaire was designed to determine attitudes about the Center's ability to provide customer service and compete with other Centers in this area. Each Center was to have this instrument completed by a company executive, inside salesman, outside salesman, warehouse manager and traffic manager. When these three instruments had been drafted, they were pre—tested at an eastern Center and revised where necessary. Personal Interview Program There were seven geographic areas which were to be samples: the Far West, Southwest, South, Mid-West, Ohio Valley, Mid—Atlantic and New England. Personal interview trips were scheduled to each of these areas. All but the Mid-West and Mid-Atlantic were to be covered in one trip. It would take two trips to cover the Mid—West; Mid- Atlantic trips were made individually. Three weeks prior to the personal interview, a let— ter was mailed by Mr. Robert Welch, President of the Steel Service Center Institute, to the Centers selected to be interviewed (see Appendix A). This letter was the initial contact with the Center to be visited, and told the Center [)1 something about the thesis, solicited cosperation and informed the recipient that he would be contacted shortly about an interview date. A week after Mr. Welch's letter was sent, a letter was mailed to the Centers to be visited. This letter of intrwxiucticni COIHAJJHCd.iJlC ctnmaany (ulta sinxat ammizi self1 addressed envelope. In addition, it set up a specific date for the personal interview and asked if that date was acceptable. Conduct of the Interviews Letters of introduction specified the time that the interview was to begin. Interviews were set up to last the whole day from_9:OO A.M. until 5:00 P.M. Personal interviews began with a company officer, in many cases the president of the Center. This first phase of the interview lasted from one—half hour to an hour. During this period, the first part of the personal interview schedule was completed. The next part of the interview took place with the inside sales manager. During this part of the interview, which lasted about two hours, all phases of order proces- sing functions were covered. After lunch, the interview began with the warehouse manager. This interview lasted two hours, if the company had a traffic manager, and three if there was no traffic manager. During this portion of the interview, a tour of the warehouse was taken. If the Center had a traffic manager, the final hour was spent with him. Most interviews terminated with a return visit with the company officer, and sometimes other staff members. Answers were requested to questions which could not or would not be answered in the other areas. It was during this final session that the internal questionnaires were left with the company officer. Response and Follow-Up Response to the personal interview was 96 per cent successful, i.e., 96 per cent of the Centers interviewed answered all of the questions to the best of their ability. Not all of the questions were answered, because some Cen— ters did not have the information. The four per cent answered some of the questions, but claimed some of the questions required a confidential answers, and failed to respond even though the information was available. Two—thirds of the internal questionnaires were returned without a second request. For the other one—third, a follow-up letter was mailed about a month after the per— sonal interview. ln two cases, a third request for replies was sent out by Mr. Welch. Internal questionnaires were completed by all but one Center, which refused to circulate the questionnaire. Samplt>lkn3ign H 0 Sampling is taking any portion of a population, or universe, as representative of that population or uni— verse."l This portion of the population is then consid- ered to be representative of the whole universe. It is best to use as large a sample as possible in order that the principle of randomisation be allowed to work and that the sample be as closely representative of the pop— ulation as possible. At first it was thought that a sample of ll Centers would be adequate. This figure was eventually expanded to 2“. It was felt that ll Centers would not provide enough variety in terms of product line, geographic loca- tion, profit and size, and that a sample of this size would not be representative of all Centers. In the final analysis, it was determined that 2“ Centers would be sampled. This number would allow for a good representation of Centers and yet still allow for detailed interviews with each Center. Additional samples beyond 2“ were considered; however, it was felt that the time and cost of additional interviews was high when com- pared with the added information that might be obtained from the additional interviews. The selection of the 2“ Centers to be included in the survey was done in conjunction with the Steel Service 1Kerlinger, op,_cit., p. 52. _——-_—— I) 1‘ Center institute. Since the members of the Institute have a long and extensive knowledge of the industry, it was felt that they could help make the sample represen- tative. Twenty-four Centers were selected on a purposive basis so as to give the sample representativeness in terms of size, product and geography. Center size varied from small, BO-man one-Center operations to large, thousand—man multi—Center operation. In the sample were 13 Centers in which sales were $10 million or more and ll Centers with sales less than $10 million. Thirteen Centers were part of regional or national operations, while ll were single Center opera- tions. Ten Centers employed less than 100 people, and IA Centers employed more than 100. Centers comprising the sample were also selected based on the type of product sold. General line carbon steel Centers are the most prevalent type of Centers, so the largest number came from this class of Center. There were 1“ general line carbon steel Centers in the sample. In addition, the sample included three Centers which specialized in steel plates or sheets; three Centers which specialized in aluminum or stainless steel; one Center specializing in carbon steel tubing; one Center special- izing in stainless steel and alloy bars; one Center spe- cializing in cold rolled steel; and, one Center special— izing in chrome plated precision shafting. \Jfi Geographically, it was decided to attempt to cover as many different areas in the country as possible, and yet still retain some control over travel cost and time. Five Centers were selected from the Mid-West, which was the largest number selected in any area. This was jus— tified because the Mid—West is the geographic center of power in this industry. Pour Centers were selected from the West Coast. The West Coast was included particularly for its association with the aerospace industry. Four Centers were sampled in the South. It was felt that in this territory, Centers would cover larger geographical areas and serve less heavily industrialized markets. Pour Centers were selected in the Mid-Atlantic region in close priximity to many mills and ports where imported steel would be a competitive factor. New England pro— vided three Centers for the sample. Climate, competition and types of users make New England unique. Two Centers were selected in the Southwest in order to cover some Centers which serve an expansive area. Two Centers were selected in the Ohio Valley because of the heavy industry located in this area. This research was designed in order to examine physi— cal distribution patterns in the Metals Service Center irnhistry anni to LKHJBleIM} thrrziffect (H':;ize arnly>rofit (n: these [Hitternn:. Attlttflhfli towcuwl custonwwignrrvictrznnong VilI'l()LIS Jf dliiPUiflJitfll irl dul_lVUlfv, lmlxirnixtm; tlm: UtlmliZQNJiO{l(3f equipment and helps maintain low distribution costs. Special handling has a chain reaction, and bottlenecks occur in other areas throughout the physical distribution systenL First morning delivery is desirable on non-processed orders. Competition in this industry has made first morn- ing delivery on non—processed orders a necessity. When a customer calls in for a non—processed order, he knows that the (Xmater”;3 eonmmWJitor (uni makma the chélivermz conmdianent, if that Center cannot. Fast delivery on processed orders is desirable. This is related to the previous point. in most markets, the delive*y standard for various types of processed orders is known. In Seattle, for example, orders requiring slitting may take four days to process. Four days becomes standard, and customers begin to look upon four days as the delivery date Centers must meet. Transportation costs should be minimized. It is incumbent upon the Centers to reduce the total cost of transportation. As previously stated, this must be done 7? in full cognizance of the systems approach and with the awareness of the fact that such cost must be reduced in relation to a stated customer delivery standard. Centers should engage in back-hauling material to as great an extent as possible. Costs incurred in re— turning to the Center empty are joint in that the costs incurred in delivering the material automatically create the costs to return to the Center. Since the trucks must return to the Center empty, any type of freight which can be brought back, e.g., buy-outs or purchases from the mill, will help reduce the cost of delivery. The preceding part of this chapter has outlined a max- imum performance physical distribution model. This model is used as a point of reference to compare what occurs in the real world with what should be occurring. In order to do . . 1 this, a system of measuring the real world must be devised. Measurement A four point scale is designed to measure how close the sample Centers come to the model depicted above. If the Center has complete congruence with the model, then three points are awarded. if the Center's activities are the antithesis of the model, then no points are awarded. (See Figure 2.) If a Center were to match the model on every point in the three areas--order processing, ware- house handling and transportation——then that Center would 1 See footnote one, p. 56. 73 .Houos ceausnanuouc acouuaca you queaoa assaxus go causewanna sou nauamou.~ ousuuu Haannxoun no coaugco zousoahsn: can nonazupsa Han: ooa>uoo auscuuao uoow cud) acouuauCOU nunoo 304 wcacuoa unnau on» so vouo>aflou uwaucoonmn cw“: >uo>daou Hoaooon uo chOEa EJEaCHz nue>HLu co scene on a: no» monsooooum own: mmpaacco«unmsc Haw: no>auu an weacmoHca ox man mLo>o can 05mm ecu mxme no: uflsozm ano>upu zen Lug many can QOpn Lon unwavr Eseaxmx oHnHmnoq mm macaw see m< oaoammoa mm zfia>moz an Tendon om wcfioo no“ mCOQOL noew 29H: camcofl exosnb oea>nmn ano>ufiov pupae; Deepen canamnon acouxo umwusonm ecu cu new: coHumuLoancaLs mum>apm veuaflaus mourn; aaamg coHyuwHom 0p Lofina econ ueafiscwzou «sancxoun nunoo oan huo>aaoo cheapo ho auo>afiou aaaooom naopuCOo uo>uho noauaaaouu n.uosoumso go co«ua:«£pouoa Lo>anu an wcaomo~cs ho acouxm nape m.po>«uu us» go cusps: uv>dnu a an awe non mean» he Lamasz econ Lon unwaoz can» Lon maoum do Locus: ommccou xozpe gonad wcauuscom do cocuo: cofipmupoamcmua uum>apn mafia: god condom ommcco» ucgonuso nousou codpwpnonncaue coHumuLonmcaup do meaazvocom 23H8nvm LmEOuwzo voom cpaz acmumamCOe mambo 304 Ensuefie a o» uaox we efizozn mmadev zeadaficu vanammoa mm mafimuufiflaz 3m» me o; Uflsogn envsu mxespu ecofi so: vaaocn an>uLa madaadcm no; new: on vasogm mesa» cnmvcmum . ucofiaooxo on vfizocm Eeummm ecdxomm ucwflauuxw on eazonm Eoumxm mcaflocmz namfipouwx ucmfiaouxo on vasozm Chance omsonohmx uomofiaso up oflzonn nucoeunaamc Honuuoo coauusuoum weamnovnuw co poouuo Ezeuc«e w o>w£ oasocm wcdmnvoona ceauoscopanonm uooo azaavc mcaaaacm naawonaaaz wcaumoanxoaue mesa» madaafinm Eounxn weaxomx Emunzn meaavcwn naaunoum: swanoo onsoconoz Hepucou coauosvonm vomnooona ceauosvonauopa one coax: unwouo no weaazuocom czHnguon LoEOpmzu 000m cud: acounHmCOU numoo 304 omzonmuaz on» On nacho oz» no acoEQ>oe cane: wadmvaOLa name do ems m>amcmuxm vow: moocuve “moacmzovz aLvEOunzo no; a: gem who nwvoo can: nuozuoe Haoucmnooz awn on» usocw30Lzu >Hc0>o w>anam mpocno ococnoao» an o>anhm unsoEm Ezeuxmz nasaom mmeaxaz pom nanmm oszmmuomm wcamecm: fleauman mumw Louuo cm penumc: 0» ma codaaooo whoopo go mcHanan Hmaooam pace mcwmmcoopa nacho ea oooam weamnooona auao auuco Loopo xoozo aaoouo Houpcoo aneuco>cH o>uppa nuovho can: cede Loucoo on» an nooho as» no Ha>anu< LOuomm ceausndnunao Havanhnm mmomo .< Bm. Note that Table 1 contains not only the mean score on order processing, but also mean scores obtained on each factor. inspection reveal; that Centers do their best job on order receipt where they limit the number of orders received via non-standard methods, limiting the number of orders handled on a special basis and in the speed with which orders are processed. Centers do least well on order processing cost, method of order entry and their methods of controllinv inventory. Jarehcuse Handling There are ten physical distribution factors in ware- house handling with each factor allocated a maximum of three points. Thus. as in the case of order processing, the maximum score obtainable is 30. The average score on warehouse handling was found to be 16.63, which is short of the 30 point maximum. This difference is significant at the five per cent lev,l. Table 1 contains not only the mean score on ware— house handling, but also mean scores obtained on each factor. Inspection reveals that Centers do their best job on the use of standard shipping times, on the limita— tion placed on drivers unloading and in the reduction of l o o o O 0 Appendix C contains the statistical data used in this chapter. 79 TABLE l.--Distribution of points allocated to the sample Centers. Physical Distribution Factor Total Points Mean All Centers Scores 1. Arrival of the order at the Center 55 2.29 2. Receipt of the order throughout the day “1 1.71 3. Method of controlling inventory 26 1.08 A. Extent of credit check “0 1.67 5. Method of order entry 22 .92 6. Extent of the use of data processing 29 1.21 7. Speed in order processing US 1.88 8. Order processing cost 20 .83 9. Number of orders handled on a special basis U9 2.0M 10. Where the decision on special handling is made 52 1.75 Total Points Crder Processing 369 Average Score Order Processing 15.37 Average Number of Points Per Factor 1.5“ 11. Affect of pre-production processing on scheduling “2 1.75 12. Degree of production control 33 1.38 13. Warehouse design 25 1.0M 1A. Naterials handling system 32 1.33 15. Packing material 36 1.50 16. Use of standard shipping times 65 2.71 17. Degree of loading by drivers 58 2.u2 18. Degree will calls 50 2.08 19. Causes in shipping delays 3“ 1.U2 20. Warehouse costs 23 1.00 Total Points Warehouse Handling 399 Average Score Warehouse handling 16.63 Average Number of Points Per Factor 1.66 21. Scheduling orders prior to selection U0 1.67 22. Use of daily transportation routes “3 1.79 23. Outbound tonnage 58 2.42 2U. Reason for using private transportation A8 2.00 25. Method of acquiring their private fleet “9 2.0“ 26. Weight per loaded truck 31 1.29 27. Stops per trip 29 1.21 28. Weight per stop 25 1.0u 29. No. of trips per day per driver 37 1.5U 30. Nature of driver's daily trip 37 1.5“ 31. Amount of unloading by driver 31 1.29 32. Determination of customer's facilities 25 1.0U 33. Extent of control over drivers 39 1.63 3 . Per cent of orders requiring special delivery H3 1.79 35. Ability to deliver orders on first morning 40 1.67 36. Extent of back-haul activity 3“ 1.U2 3 . Transportation costs 35 1.U2 Total Points Transportation 6A3 Total All Sample Centers 1511 Average Score Transportation 26.78 Average Number of Points Per Factor 1.58 Average Score All Centers 58.79 Average Number of Points Per Physical Distribution Factor 1.59 80 will calls. They do least well on warehouse costs, ware— h;wiints per factor. They did least well on order processing where they average only 1.5M points per physical distribution factor. Transportation was in between warehouse handling and order processing, as Centers averaged 1.58 points per physical distribution factor. lixperdrmental lhasults Erased on Size Order Processing Drder processing contains ten physical distribution factors with each factor allocated a maximum of three points. Thus, as explained in section one, the maximum score obtainable by any Center is 30. The average score (s. L) for‘:unnll.(7ent«nna was l)4.73, vdiile tin? avertume scorwe for ltuum? Centers vur: a littl£311hmher at 1J3.92. A test {The the significance of the difference between these two means was used. This difference is not significant at the five per cent level. Table 2 contains not only the mean score on order processing for large and small Centers, but also mean scores obtained on each factor. Small Centers do best on standardizing the arrival of the order at the Center, processing orders quickly and in reducing the number of orders handled on a special basis. Small Centers do least well on order processing cos , methods of order entry and methods of controlling inventory. Large Cen— ters do not differ from small Centers in what they do well and what they dc poorly. Warehouse Ilandlirm Warehouse handlinu contains ten physical distribu- tion factors with each factor allocated a maximum of three points. Thus, as explained in section one, the maximum score obtainable by any Center is 30. The average score for small Centers was 15.6“, while the average score for large Centers was a little higher at l7.U6. A test for the significance of the difference between these two means was used. This difference is not significant at the five per cent level. TABLE 2.——Distribution of points allocated to 83 Centers based on size. Physical Distribution Factor Small Large Total Points Mean Total Points Mean All Centers Score A11 Centers Score 1. Arrival of the order at the Center 23 2.09 32 2.96 2. Receipt of the order throughout the day 21 1.91 20 1.59 3. Method of controlling inventory 10 .91 16 1.23 9. Extent of credit check 18 1.69 22 1.69 5. Method of order entry 8 .73 19 1.08 6. Extent of the use of data processing 11 1.00 18 1.39 7. Speed in order processing 22 2.00 23 1.77 8. Order processing cost 8 .73 12 .92 9. Number of orders handled on a special basis 22 2.00 27 2.08 10. Where the decision on special handling is made 12 1.73 23 1.77 162 207 Average Score 19.73 15.92 Average Number of Points Per Physical Distribution Factor 1.97 1.59 11. Affect of pre-production processing on scheduling 19 1.73 23 1.77 12. Degree of production control 15 1.36 18 1.39 13. Warehouse design 2 1.09 13 1.00 19. Materials handling system 13 1.18 19 1.96 15. Packing material 19 1.27 22 1.69 16. Use of standard shipping tires 27 2.95 38 2.92 17. Degree of loading by drivers 22 2.00 36 2.77 18. Degree will calls 18 1.69 32 2.96 19. Causes in shipping delays 17 1. 5 17 1.31 20. Warehouse costs 15 1.3 _9 .69 172 227 Average Score 15.69 17.96 Average Number of Points Per Physical Distribution Factor 1 56 1.75 21. Scheduling orders prior to selection 17 1.55 23 1.77 22. Use of daily transportation routes 13 1.18 30 2.31 23. Outbound tonnage 27 2.95 31 2.39 29. Reason for using private transportation 19 1.55 31 2.39 25. Method of acquiring their private fleet 13 1.73 30 2.31 26. Weight per loaded truck 16 1.18 18 1.39 27. Steps per trip 10 1.95 13 1.00 28. Weight per stop 11 .91 15 1.36 29. No. of trips per day per driver 20 1.00 26 2.00 30. Nature of driver's daily trip 17 1.82 17 1.31 31. Amount of unloading by driver 11 .55 19 1.08 32. Determination of customer's - facilities 11 1.00 19 1.08 33. Extent of control over drivers 17 1.55 22 1.69 39. Per cent of orders requiring special delivery 18 1.69 25 1.92 35. Ability to deliver orders on first morning 15 1.36 25 1.92 36. Extent of back-haul activity 12 1.09 22 1.69 37. Transportation costs 18 1.69 16 1.23 271 372 Average Score 29.69 28.62 Average Number of Points Per Physical Distribution Factor 1.95 1.68 Average Score All Centers 55 62 Average Number of Points Per Physical Distribution Factor 1.99 1.68 605 806 89 Table 2 contains not only the mean score on ware— house handling for large and small Centers, but also mean scor s obtained on each factor. Small Centers do best on the use of standard shipping times, limiting the amount of loading done iy drivers and on controlling the effect of pre—produetion processing on scheduling. Large Centers do not differ on ’he first two factors above, but their third best factor is the control of will-calls. Both large and small Centers do least well in warehouse design. Email Centers do pocrly on materials handling s stems and racking systems, Whereas large Centers do poorly on warehouse co ts and on the causes of shipping delays. Transportation Transportation 0 ntains seventeen physical distri- bution factors with each factor allocated a maximum of three points. Fhus, as explained in section one, the maximum score obtainable by any Center is 51. The average score for small Centers was 29.09, while the average score for large Centers was a little higher at 28.62. A test for the significance of the difference between these two means was used. This difference is not signifi- cant at the five per cent level. Table 2 contains not only the mean score on trans— portation for large and small Centers, but also mean scores obtained on each factor. Small Centers do their hrst Job on the use of private transportation for out— hound tonnaxe. «ending their drivers on different routes and in their method of acquiring their private fleet. Large Centers do best on the same factors except they do better on good reasons for using private transportation instead of sending their drive*s on different routes. Small Centers do poorly in weight per stop, determination of customer's facilities and on back—haul activity. Largo Centers do poorly on stop: per trip, the amount of unloading done by drive's and on determining customer's facilities. qWWtil] I’hguti ." II? N J Q. I u k ) ’ v —~ #4 (D H C‘ \JW C) H C7\ 0 “J \N D «7 AK". 7 “’1‘ C i (.1 1 KLQ ‘ n - r‘ .¢ ' 4 yr ’r‘ 8 11 ' A-(‘xii lulu/I‘ll L4» $00.1 AJVKJAY‘ ch‘) 1.6 Schedulinr orte Cse of dailv tr w—1 H (D HH U1 0 *3 | L, <* \Ii \OLQ l—J ‘0 fl ()3 o \ 1. . flutbound tonnar ~-I (I) {‘1‘ h \_;_, 27 2.25 2U 2.00 2, 1.92 16 1.33 o :e'zn‘rzn “(“11" v-I-lrg rn¥~ . . 'AL‘VA‘ 1 . 41. ... .31.. 1 .’\) H) F‘ ,‘ P.) h D v~ y._ 4 V a Kethod cf acqu1ring their private fleet . Weight per loadei trucx m._ (V.. x \. "V n HHHHHHHHMF~.,1R,)hJF—J FHF—‘UWWOVWF‘JO—JOUWO' 23 f C 2 1, 5 27. Stops per trip 1‘1 .‘8 10 .83 28. Weight per stop 12 0 13 1.08 29. 20. of trips per day per driver 19 . 8 18 1.50 30. Xature of driver's iaily trip 19 . 8 18 1.50 31. Amount of unloasinr ty Jriver lb . 7 17 1.32 32. Deternination of custofier's f; Lll‘ies 1D . 7 11 .92 33. Extent of ointrcl o‘er driVer: 17 .'2 22 1.83 3“. Per cent of order: rJQJirirr stwcirl ”J H |'—' \1 U1 0) M delivery 1.83 . Ability to deliver orders on first morning Extent of back-haul activity r" ~ n . iransportaticn cest. LU \n f‘) 1.92 17 1.u2 l.h2 1.50 16 1.33 335 308 Average Score 27.92 25.67 Average hunter of Points Per Physical Iistribution Fac LUNA.) ‘JO‘\ PH C1143» p.) ‘ 111‘ N H x] tor 1.6“ 1.51 Average Score A11 Centers 60.75 56.83 fiverage Number of Points Per Physical Pistriiution Factor 1.6M 1.5“ 729 682 {,l' ()[adprogg rind run-(mujmv; thr' vxt'0m, of credit checks. 'l'hm/ dn) 1(ulsi, weal] (in (JF’HJF y>rtu:e:n:irut canzt, {netJiodxs oI' irr- ventory control and method of order entry. Pairediotrte iiaruilirur Warehouse handlinr contains ten physical distribu- tion factors with each factor allocated a maximum of three points. Thus, as eXplained in section one, the maximum score obtainable by any Center is 30. The average score for low profit Centers was 16.50, while the average score for high profit Centers was a little higher at 16.75. .A test for the sinnificnnce of the difference between these two means was used. Thih difference is not significant at the five per cent level. Table 3 contains not only the mean score on warea house handling for high profit and low profit Centers, but also mean scores obtained on each factor. Low profit Centers and high profit Centers do best on the'use of standard shipping times, limited loading by drivers and controlling will—calls.m Both do their lowest scoring on warehouse costs and warehouse design. Transportation Transportation contains seventeen physical distri— bution factors with each factor allocated a maximum of three points. Thus, as explained in section one, the maximum score obtainable by any Center is 51. The average score for low profit Centers was 27.92, while the average score for high profit Centers was a little lower at 25.67. A lind, for tlu>;;htnificamvx3 of timaciifferermma betweeri these two means was used. Th's difference is not signifi— cant at the five per cent level. Table 3 contains not only the mean score on trans— portation for low and high profit Centers, but also mean scores obtained on each factor. Low and high profit Centers do their best job on using private transportation for outbound tonnage, their reasons for using private transportation and on their method of acquiring their private fleet. how profit Centers do their lowest scorm ing on weight per stop, controlling the drivers' Unload— ing and determining customer facilities. .High profit Centers dc wors -n rtops per trip, determining.cusé tomer's facilities and weight per stOp. Total Physical his— tribution System The normative model contains 37 physical distribu- tion factors with each factor allocated a maximum of three points. Thus, as explained in section one, the maximum score obtainable by any Center is 111. The average score for low profit Centers was 60.75, while the average score for high profit Centers was a little lower lower at 56.83. A t9st for the significance of the 90 difference between these two means was used. This differ- ence is not significant at the five per cent level. Table 3 shows that there was no difference between low prOfit and high profit Centers in terms of their per- formance on the three physical distribution groupings. loth did their best job on warehouse handling and their poorest on order processing. Note that Table 3 shows that the differences between groups was greater for high pro? 3 t (Nanter’s . This chapter has presented the results of the re— nearch undertaken in this thesis with respect to compare ing the physical distribution systems of sample Centers with the maximum performance model. The following chapter presents the research findings which compare the attitudes on customer service among job holders in the Center. The final chapter presents the conclusions and recommendations. CHAPTER VI CHWPARATlVE AHALYSTS—-ATTITUDES ON CUSTOMER Sl'IRVIClfi AWN-1G JOB I'EOLDERS IN THE CENTER Physical Distrubution and the §ystems Approach in Chapter ll it was stated that the objective of physical distribution is the achievement of a desired level of customer service at the lowest total cost. The desired level of customer service is attained when the correct order is delivered to the right place at the right time. In the Service Center industry, customer service standards are high. Non-processed orders are re- quired on a next day basis as a rule, and processed orders are required the next day after a back—log period. This backelog period is based on the type of processing being done and on the demand for that type of processing in that area at that time. The original intent of Chapter VI was to study the attitudes toward customer service of various categories of customers and to compare these findings with attitudes toward customer service of various Job categories within the Center. It developed that a study of the customer views was not feasible because of the time and expense 91 92 llIthIVle zin Ccfl1t6i*. It 1;: hyywith(u3izevi truit 117 ttur C(Hiter* is to he a cohesive unit and work as a system, then incumbents in various assignments should share similar attitudes toward customer service. 50search Findings Nine ques,ionn were asked of those in four Job classifications within the Center-—inside sales, outside sales, warehouse mamager and top management. In each instance a null hypothesis was set that any variation in responses among employees was attributable to sampling (‘I'T‘OP . lHuFUIWJIHC(‘hmm hmEOpmSO ULMZOQ MCHHm®Q QED CH moflmthMHU OZ .. m . . x . u lull: x oo.oofl Hm mm mm mm :m q¢eoe w, OH.H wl on ml on ml on ml on .m: pamppoaeflcs mym> m~.ma ma va m Amv m Amv m nmv m pcmppoqu mfi.m~ mp mmfiv ma Away 0H ANHV ma Amfiv Hm ucmpgoasH hpm> pcmo Hmpoe m o m o m o m 0 Law a 3 m H mmcogmmm soamefiMHmmmHo now .LmEOpmSO pflmgu 0p pamppanH ma mofi>me Hmmm mpmucmo £0H£3 0p mmpmmc maeln.: mqmLom LoEOpmso oospfipum so mdsopm coozpoo mocopmMMHo osmoHMflsme oz u. mm.e mo. mx v mo. mx OOH as mm mm mm gm sauoe WI Is. as M as m as m. as m 02 m m nov a poo H flow 0 no 0 we» acme fleece m o m o m o m e Lee. E 3 m. H coapmefiefimmaac no .eofl>son Logoumdc nwmppmpo>o mpmwsco hmxpmflz CO m®©3paup¢ll.m MAMd» 97 moa>pmw LoEOpmSO so oeomaa mumspm osmsou mospfippe co masosm somspmo mosesmmmao osmofigficwfim oz .. l mm.> mo. x v H:.w .x m m OOH Hm mm mm mm am Art"orm Service The second group of Questions aimed at the attitudes. of participants regarding the ability of their Center to perform service. Even if there is the proper amount of stress placed on customer service, do the Centers respond in such a manner as to get an advantage over their competitors? I The first question asked respondents to compare the ability of their Center to give service with the service capabilities of their top competitors. One per cent felt that their Center was well below their tOp competitors and one per cent felt they were below. Thirty per cent were of the opinion that they were about the same. Forty-one per cent felt their Center was above tOp competitors and twenty—seven per cent felt they were well above (see Table 8). A chi—square test was applied to determine if there were a difference between job classifications in their opinion of the service capability of their Center in com— parison with top competitors. The calculated chi-square was 33.19 which is larger than the critical chi-square of 21.03. Hence it can be inferred that differences in rmn*p(nise Eire {sigxiifiCXInt. 'r ‘i CU —c o rt) H (I) [1.] L7 -1 -\ ~\ \J competitor ".4 C . V spon «F 8 Re M Lil LI] C) T“ D 1.2 r~1' O) (0) I \ (O) /\, k. \./ C) (O? v--1 f‘x \/ Below 9 9 (o ) (Vi /\ V, Ln (7) 0") Same “I 37 (9) r—1 0\ (9) 10 (6) 10 /\ C) r'i Above (6) \ Q (6) Well Above 100 23 TOTAL 21.93 .05 33.19 X X is rejected. H 0 U} -H ilit "b , uA cap sentiment regarding the service Center compared with their top Competitor. 11’] There is a significant difference of the participants' IMO The second qUHHtiHH asked for reasons why Centers do not HHVP the ability to gIVe service. Respondents Were asked what they felt were the greatest causes of delay in delivering an order to a customer when he wants it. Forty—one per cent felt that delays occurred in the order processing area. Twenty—three per cent felt that delays come about in the scheduling function, and eleven per cent thought that most delays occur in selecting. Fourteen per cent felt that delays occurred in packing and shipping, and eleven per cent attributed delays to transportation and other factors (see Table 9). The computed chiwsquare showed that the differences aiw> rn3t asiguiifi43arng. Whij(3r' A13)LHZCL1 (if (3cn)d lhviivery Service? Each respondent was asked what he felt was the most important aspect of quick delivery service. Forty—five ptw'iéent.(if tin? Oi iffiipuihk‘ntfi [Wilt tfliat (irden° prwxae81xing was most important. Another %2 per cent felt that scheduling was the most vital aspect of quick delivery service. Eight per cent thought the most important aspect was selecting and 15 per cent mixed among packing, shipping, transportation, poor inventory control and a combination of all factors (see Table 10). Here, too, a chi—square test was used to determine if there were a significant difference of opinion between lOl mHmmepoamm pomnmo on HHom n. . x . x MO HO m v on HH m OOH HO mm mm mm :m qeeoe HH OH Amv m Amv : HMO H HmO m gmnso new cowpoupoamCMpB 3H mH Ame m Hmv m Ame m Ame m mcHaqum Ocm wconmO HH OH Amv H HMO m Amv : HMO m mchomHmm mm HO Amv m Amv : HOV m HOV OH wcsHsemeom Ha em AOO HH HOV O AOO OH HOH O mchwmoopm tango _cmO Hmsoo m O m o m o m o .M m. m E 3 H oncoammm COHmeHeHmmmHO pom .4mpmH oewrhmm meHmoc m.LoEopm3c ecu pome ou msflaflmm pow momsmo LmeFII.m mqmscm OLO>HHmo xOst mo uocdmm ucmpcooefl pmoe cablu.oa mqm OH NH H2O O H2O m H3O a Hmv H mch posOopm wcoppm mm mm ANO OH HOV OH HOV m HNO : mOHssmm spm>HHmO pcmHOHemm OH O HNO O HOV : HOV m Hmv m spHHmso possess OH MH Amv : Amv m AC m Hmv m mmHmm itsO Hmsos m O m O m O m O .Hmwm N...» H mmcoammm coHmeHeHmmmHo OOO .mpopfiwodsoo Lm>o pawn ommpcm>om m>fluwpmdfioo II' umswmotmauu.HH MHmem 105 there is no difference between classifications is rejected, and the differences are inferred to be sig— nificant. The question of competitive advantage was reversed, and each respondent was asked what major competitive advantage top competitors held over his Center. Thirty- five per cent of the respondents felt that price was their competitor's top advantage. Twenty-five per cent felt that variety in product line was their competitor‘s major advantage, and eighteen per cent felt that theircompeti- tor's top advantage was a strong product line. Twelve per cent were of the opinion that either sales or better delivery service was their competitor's top advantage. The remaining ten per cent was spread among product quality, better processing equipment and no advantages (see Table 12). The chi-square test showed that differences are significant. The final question regarding customer service asked respondents what they felt was the most frequently lodged complaint against their Center. Forty-nine per cent of the respondents thought that price was the most frequently lodged complaint. Thirty-five per cent felt that ineffi- cient delivery service was the most frequent complaint. The remaining fifteen per cent was made up of product quality, small product line and others (see Table 13). 106 mHmecuoamm pomnem u. OO.Hm OO. Ox A mO.Hm Ox OOH HO mm mm mm :m HOBOB OH O HOV O HOV H Amv m [HOV m Osmepo NH HH HMO . O HOV m HMO m AOO O ssm>HHmO use m mammllmowkrhmm. ON ON HOV, OH HOV O HOV H HOV O mcHH poseosm :H muers> OH OH HOV O “:O m AOO O H3O O Och poseosm mcospm Om mm HOV : HOV O HOV HH LOO O OOHLO peso Hence O O m o O O O O LOO z m H emcoamem QOHOOOHOHOOOHO OOO .osme msoeHuodEco :OHSS ommccm>sm o>fluepeo8oo 107 memeuoqsm was pushes Op HHmm .. mm.mH mo. Ux v wm.m mx C OOH Hm mm mm mm :m Hme hpm>HHoQ useflofimmecw m: m: AMHV ma AHHV m “HMO m Amav mm moHLm ccmo fimpoa m o m 0 m o m 0 tom 2 3 m H emcoamem sofipmofimflmmmfio mom mewsgm LesoanO users npzflmamsoo eowpoa mapcmswosm pmoEII.MH mqmdh 108 A chi—square test was used to see if there were a significant difference of opinion between job classifica— tions regarding the most frequently lodged complaints against their Center. The computed chi-square was 6.26 which was low r than the critical chi-square of 12.59. The hypothesis that there is no difference of opinion between job classifications holds. This chapter compared attitudes about customer service among job holders in the Center. Ten questions were asked of an inside salesman, an outside salesman, the warehouse manager and a company executive. In seven cases there was no difference of opinion among job holders. Differences of opinion occurred with reSpect to a Center's ability to give service, a Center's perceived advantage and a Center's perceived idea of their competitor's top advantage. The following chapter analyzes the findings in this chapter and Chapter V, and makes suggestions for improvements in physical distribution. CHAPTER VII CONCLUSIONS AND RECOMMENDATION Introduction The intent in this chapter is to summarize the research findings, to make recommendations for improving physical distribution in the Metals Service Center industry, and to present suggestions for future research. Section one will draw conclusions based on the survey results presented in Chapters V and VI. Section two will analyze the existing physical distribution system. The final section presents suggestions for future research. Physical Distribution Compared with the Maximum Performance Model Based on the research results, Metal Service Centers are presently performing the physical distribution functions below the levels suggested in the maximum performance model. Centers are below the model for the total physical distribu— tion systems, as well as for each of the sub-groupings--order processing, warehouse handling and transportation. The sample Centers averaged 58.79 points, which was signifi- cantly below the maximum of 111 points. In each of the three physical distribution sub— groupings the average score was significantly below the 109 110 in:ix innirn E(:()I%} Licu:::ili [(3. tlzinig)](: (3(3Y1L(3I'U {lV(3r’an(?(i '1‘ . 3'] points in order processing out of a possible 30 points. This difference was significant. In warehouse handling, the sample Centers averaged 16.63 points, which was significantly below the maximum of 30 points. The average score for transportation was 26.79, which is significantly below the maximum of 51 points. Centers do their best job in warehouse handling where they average 1.66 points per physical distribution factor (see Table 1). They perform best in using standard shipping times, limiting the amount of loading done by drivers and in controlling the number of will—calls. Centers perform most poorly on warehouse costs, due to the fact that many Centers dorbt know their costs, and in warehouse design. In some cases the poor design is due to inadequate planning, but in many cases Centers have outgrown their present facilities. Centers do second best on transportation where they average 1.58 points per physical distribution factor. Centers do their best job on shipping outbound tonnage by their own trucks, sound methods of acquiring their private fleet and on sound reasoning for using private transporta— tion. They do their worst job on maximizing the weight of their trucks both in total and per step, and in deter- mining their customers' receiving facilities. lll Centers do worst on order processing where they average 1.5“ points per physical distribution factor. Centers do their best job in standardizing the arrival of the order at the Center, reducing the number of orders handled on a special basis and fast order processing. They score lowest on order processing cost, the method of order entry and on the method of controlling inventory. In this section, then, the performance of all sample Centers was compared with the model. The next section summarized the results of the research when Centers are broken down according to two key vari- ables, size and profit. it will be recalled that the basic problems under research in this thesis were said to be: Does size affect the Center's physical distribution patterns? Do high profit Centers have better physical distribution systems than low profit Centers? Does the Job an individual performs in the Center affect his attitude toward customer service? Three null hypotheses were set related to these specific problems. The hypotheses were: I. No difference exists between Metal Service Centers of different size groups and the maximum perfor- mance physical distribution model. II. No differences exist between Metal Service Centers of various profit classifications and the max- imum performance physical distribution model. 112 ill. No differences of opinion exist regarding customer service among those holding different jobs within the Metal Service Center. The next part of this chapter presents an analysis of the research undertaken to test these hypotheses. Hypothesis 1: Size The research results supported the hypothesis that no difference exists between Metal Service Centers of various size and the model. Small Centers received a total of 605 points, while large Centers received 806 points (see Table 14). The average score for small Centers was 55 and for large Centers the average score was 62. There was no significant difference between these two means. The point total of large Center is closer to the maximum point total of the model, and it is inferred that large Centers are more like the maximum performance model, but there was no significant difference between the mean scores. Large Centers average higher scores than small Centers is each of the three groupings; however, there was no significant difference at the five per cent level of confidence between the average score of small Centers and the average score of large Centers, in each of these groupings. It can be noted in Table 1H that large Centers and small Centers are farthest apart in transportation and closest together in order processing. :m.a mm.mm mwm :m.a ms.om mmm A¢BOB Hm.H s©.mm mom :m.a mm.sm mmm cofipmpsoomcmsa we.“ ms.mfi How mw.a om.wa wmfi muflaocmm mesonosm3 ::.H m:.:a mma mo.a mm.mm mma wcfimmooosm Loose swam zoq pamosm mw.a .mw mom m:.a .mm mom Q< Hmuoe osoom coo: mwmso>< Hobos mcfiososc soflosoflspmwo Hmoemmem czopxmopm oHQEmm .msmueeo ofios m up pmsocn menace one no oaomp massesulu.nfi numdh llu ln order processing, major differences between large and small Cente's occur in physical distribution factors 1, 2, 5 and 6 (see Table 2). Large Centers receive a higher percentage of their orders by telephone than do small Centers. Small Cente's tend to be better than large Centers in achieving an even flow of orders through- out the day. In order entry, the major differences are that large Centers rely on mechanical means such as flexi-writers and small Centers used more handwritten order entry systems. The final major area of difference in order processing is in the extent to which data pro- cessing is used. Small Centers average only one point on the extent of the use of data processing, whereas the large Centers average 1.39 points on this factor. in warehouse handling, the major areas of difference arise in factors 17, 18 and 20 (see Table 2). Large Centers do not use drivers for loading to any great extent. Ninety—one per cent of the large Centers claim that less than 25 per cent of their drivers load their own trucks and average 2.77 on this factor. This percentage drops to US per cent for small Centers, which average only two points on this factor. Large Centers have fewer will— calls; seventy per cent of the large Centers said that less than five per cent of their outbound tonnage has will- calls. They average 2.U6 points on this factor. Only 36 per cent of the small Centers said that less than five per 115 rent of their business was will-calls, and they average only 1.6“ points on this factor. Small Centers do better than large Centers in warehouse costs. Small Centers average 1.36 points on this factor, while large Centers average only .69 points. In transportation, major differences arise with respect to physical distribution factors 22, 2M, 29 and 36 (see Table 2). Sixty—four per cent of the large Centers have transportation schedules set up and in use, while only 27 per cent of the small Centers have such schedules. In contrast, 54 per cent of the small Centers have no tranSportation schedules, while only 16 per cent of the large Centers have no schedules. The result is that large Centers average 2.31 on this factor, while small Centers average only 1.18 points on this factor. Fifty—four per cent of the large Centers use private transportation for better delivery service, whereas only 27 per cent of the small Centers use private transporta— tion for better delivery service. Thirty-six per cent of the small Centers claim to use private transportation for lower cost while only eight per cent of the large Centers gave this reason. Fifty-four per cent of the large Centers said that less than 25 per cent of their drivers made more than one trip per day, whereas only nine per cent of the small Centers said that less than 25 per cent of their drivers made more than one trip per day. The final major 116 point of difference between large and small Centers is in the area of back-haul. Large Centers average 1.69 points on this factor; small Centers average only 1.36 points. There is no significant difference between the scores of small and large Centers. Large Centers do perform better than small Centers and more closely approximate the maximum performance model. There is a tendency for large Centers to approximate more closely the model in each of the physical distribution func- tional areas, order processing, warehouse handling and transportation. Hypothesis II: Profit The research finding“ supported the hypothesis that no difference exists between Metal Service Centers of various profit classifications and the maximum performance model. Low profit Centers received a total of 729 points and high profit Centers received a total of 682 points- (see Table 1U). The average score for low profit Centers was 60.75, whereas the average score for high profit Centers was 56.83. There was no significant difference at the five per cent level of confidence between these two means. The data in Table 1“ indicates that low profit Centers do better than high profit Centers in order pro— cessing and transportation. In order processing, low profit Centers average 16.33 points while high profit 117 Contrast average only 1.14.14? points. Low profit Centers average 27.02 points in transportation, while high profit Centers average 25.67 points. For the warehouse handling group, high and low profit Centers are almost even. High profit Cente*s average 16.75 points while low profit Centers average 16.50 points. In order processing the main differences are in physical distribution factors 7 and 8 (see Table 3). Only two of the twelve high profit Centers were in the top one—third in terms of Speed in order processing, whereas six of the twelve low profit Centers were in the top one—third in terms of Speed. As a result, on factor 7, low profit Centers averaged 2.25 points while high profit Centers averaged 1.50 points , with respect to order processing cost, the lower one-third of the Centers in terms of cost were low profit Centers. Half of the low profit Centers did not know their order processing cost, whereas 66 per cent of the high profit Centers did not know these costs. Low profit Centers average 1.17 points while high profit Centers averaged .50 points. There are few differences in warehouse handling between low and high profit Centers. Differences occur in factors 18 and 20 (see Table 3). Sixty-six per cent of the high profit Centers claimed that less than five per cent of their outbound tonnage was will-calls, and they aVerage 2.25 points. Only 50 per cent of the low 118 profit Centers claimed that less than five per cent of their tonnage was will-calls, and they average 1.92 points on this factor. in the area of warehouse costs, “2 per cent of the low profit Centers do not know their vmrehouse kindling costs as compared with 58 per cent of iiu‘ hi;41 profdi, COIH(‘PS. Low guwnfit;(3entc~w3 avesuuge !.25 (”1 tin. WUYW‘hthZC (wh:t ikicttn’, wiuareen; higfii pzwifit (Writers only average .75 points. The major areas of difference were factors 22, 27, 3% and 35 in transportation (see Table 3). Only two of the tWelve high profit Centers were in the top one-third in terms of speed in order processing, whereas six of the twelve low profit Centers were in the tOp one-third in terms of speed. As a result, on factor 7, low profit Centers averaged 1.50 points. With respect to order processing costs, the lower one-third of the Centers in terms of cost were low profit Centers. Half of the low profit Centers did not know their order processing cost, where s 66 per cent of the high profit Centers did not know these costs. Low profit Centers average 1.17 points Whilt high profit Centers averaged .50 points. There are few differences in warehouse handling between low and high profit Centers. Differences occur in factors 18 and 20 (see Table 3). Sixty-six per cent of the high profit Centers claimed that less than five per cent of their outbound tonnage was will-calls, and 119 they average 2.25 points. Only 50 per cent of the low profit Centers claimed that less than five per cent of their tonnage was will-calls, and they average 1.92 pwints on this factor. in the area of warehouse costs, #2 per cent of the lrw profit Centers do not know their warehouse handling costs as compared with 58 per cent of the high profit Centers. Low profit Centers average 1.25 on the warehouse cost factor, whereas high profit Centers only average .75 points. The major areas of difference were factors 22, 27, ii and 35 in transportation (see Table 3). In twelve out of the seventeen physical distribution factors, low profit Centers scored as well as or better than high profit Centers. In factor 22, 25 per cent of the low profit Centers used no daily tranSportation schedules, whereas 42 per cent of the high profit Centers used no daily transportation schedules. in factor 27, four of the twelve low profit Centers were in the low one-third in terms of number of stOps per trip while only one of the twelve high profit Cente's was in the low one-third. Half of the high profit Centers iad no information avail— able about steps per trip while only one-third of low profit Centers did not know this figure. High profit Centers do a slightly better job of controlling their drivers, as they average 7.83 points on this factor, while low profit Centers average only 1.142 points. In terms of lRO factor 35, low profit Centers are slightly better at delivering orders on the first morning. Eight of the twelve low profit Centers were in the top two—thirds in terms of their ahility to deliver orders on the first morning. Only five of the fifteen high profit Centers were in the top two—thirds. It was anticipated that Hypothesis II would be rejected, but it was expected that high profit Centers would be significantly higher than low profit Centers. When the research was designed, the feeling was that high profit Centers would be closer to the model than low profit Centers. The reason that low profit Centers scored more points than high profit Centers may rest in the fact that Centers are in a period of heavy investment in transportation equipment, materials handling equipment, warehouse racking equipment, automated inventory controls, automated order entry and large amounts of processing equipment. Investment in these facilities would increase the efficiency of the physical distribution system; however, profit would suffer in the initial stage of investment and use. These investments, however, may provide the basis for better profits in the long run. Based on the results of the tests in the functional areas, low and high profit Centers do not differ signifi- cantly in their relationship to the maximum performance model. While there is no significant difference, low profit Centers tend to perform better than high profit Centers in the area of order processing and transportation. Hypotiwnyhs Ill: fknnsonnel The research results support the hypothesis that no difference of opinion exists regarding customer service among those imlding different jobs within the Metal Service Center. in seven out of the ten questions asked there was no significant difference among the Job classi— fitxititWh3. All Job classifications feel that service is impor- tant. The only variation is that top management is not as emphatic as the other three groups (see Table N). All Job groups feel that one Center can handle an order better than another, even if the product is physically identical (see ”able 5). Another approach in trying to determine the impor- tance of customer service to various groups within the Center was to ask each respondent how he felt his Center stressed customer service. The first question asked whether or not respondents felt their company overstressed customer service, and 98 per cent felt that customer service was not overstressed (see Table 6). The second question asked if customer service was understressed, and 80 per cent of the respondents felt that customer service was not understressed (see Table 7). 122 While there is no significant difference between the groups in their attitude toward the amount of str ss placed on customer service, it should be noted that there is a slight discrepancy between the company execu— tives and the other three groups. The executives are in 100 per cent agreement that customer service is not understressed. Inside salesmen, outside salesmen and warehouse managers are not that convinced. It should also he noted that the executives were the least emphatic group in terms of their feeling about the importance of customer service. Forty—three per cent of the top management group replied something less than very impor- tant. The overall percentage of those replying less than very important was 21 per cent. Sixty-eight per cent of the respondents feel that they are either above or well above their top competitors when it comes to customer service (see Table 8). For this question, there was a significant difference between the groups. The major difference arises with the inside sales group where thirteen of the twenty—four respondents felt that they were about the same as their top competitors. This is just one less response than those of all three other groups combined. Only six of the twenty-four respondents in the inside sales group felt that their Center was above their top competitor. This is below the other groups. The same is true for the response "well above"; although, here the inside sales group is close to the other groups. Respondents were asked what they felt were the greatest causes of delay in delivering an order to a customer when he wants it. There was no significant difference in perception among the groups. ‘Inside sales- men seem to feel that delays occur because of scheduling, whereas the other three groups tend to feel that delays occurred because of order processing. The inside sales group has the major responsibility for order processing, and this may explain the difference (see Table 9). There was no significant difference of opinion between groups on the question of the most important aspect of quick delivery service (see Table 10). Forty— five per cent of the respondents felt that order process- ing was the most important factor. The warehouse group feels that scheduling is the most important aspect, as 50 per cent of the respondents answered this way. It is noted that only 18 per cent of the warehouse group felt that the greatest cause of delay was scheduling. There was a significant difference of opinion about the perceived competitive advantage held over tOp competi- tors (see Table ll). The major difference of opinion lies in the area of efficient delivery service. The warehouse and top management groups felt that efficient delivery service was their Center's major competitive advantage, 121! while the sales groups were not strongly in favor of efficient delivery service as a reason. Inside sales favored strong product line as the major advantage, while outside sales favored variety in product line. Both sales groups failed to select sales as the key competitive advantage. lnferentially, this argues well for the system's perspective. These groups seem to be thinking in terms of the total Center, not Just their own depart- ment. There also was a significant difference of opinion with regard to the competitive advantage of the Center's top competitors (see Table 12). Thirty-two of the 91 respondents felt that price was their competitor's top advantage—-only one respondent felt that price had been his company's competitive advantage. Twenty-three of the respondents felt that variety in product line was their competitor's top advantage, while 16 felt that their competitor's advantage was a broad product line. Top management does not feel that price is their competitor's big advantage, whereas the other three groups do, particularly the outside sales group. Those groups which were not strong believers in variety in product line as a competitive advantage, i.e., warehousemen and executives, tend to feel that this is an advantage of their competitors. Forty-three per cent of top management felt that efficient delivery service was their major competitive 125 advantage and none felt that it was a major advantage of their'(unnpetit order, clflnfluld be re-evaluatmi. Handling within the warehouse appears to be an area which facilitates the physical distribution activities within the Center. Most Centers rely on various types of overhead cranes for movement, the extent and variety depending upon the size of the Center. Almost two-thirds of the large Centers use either stacker cranes or side- loaders for part of their movement. One Center used an automatic stacker crane system for certain types of slow waving products. Storage facilities in the warehouse are an aid to physical distribution. Many of the larger Centers have gone to stacker racks, which allow for the orderly, neat placement of material and provide for maximization of the use of the cube storage space in the warehouse. Likewise, many Centers have programmed their product demand and have arranged the items in inventory in such a manner that most demanded items are most easily accessible. While the storage area itself is neat, well-equipped and facilitates the movement of goods, the shipping dock does not always accomplish these same results. Often the storage racks, while providing the storage area itself with an elaborate system of stacker racks, are a forgotten elrment on the shipping dock. In many cases, material on the dock is scattered at random. Likewise, the storage area might have a beautiful system of overhead cranes, but the shipping area suffers from lack of equipment. WWHfiflfl nvzladicnt on tin) shiguiing dtxfl< are Ineflectmxi in tin? answers giVon by Centers regarding delays in shipping. Half of the respondents felt that shipping delays were related to some aspect of handling equipment or to poor facilities on the shipping dock. l‘ruirirapcar‘tELt.i(iri Through transportation the customer physically receives the material he desires, presumably at the time he wants it. This is the basic concept of the physical distrdiuition syznxnn-—that (anatomers rwuueive thefixs orders winrn tiley iieiwi tinnn. in terms of total tonnage, most Centers are motor transportation oriented. Tmis ijuxhrdes both inbound and outbound tonnage. A little over half of the inbound tonnage comes into Centers via motor carrier. There are certain advantages to receiving material by truck, and some Centers are geographically tied to motor transporta- tion. Cente's should study the transportation pricing by various modes and how this relates to purchasing. Perhaps there can be more usc made of rail transportation, such 135 as piggy—hack service. There may even be advantages to some form of inbound pooling with other Centers in the Hf‘Cfl. Centers are almost completely motor transportation oriented for their outbound tranSportation, and most of this is private transportation. Seventy per cent of all mutbound transportation moves in private transportation. Approximately 60 per cent of the Centers' outbound tonnage is delivered locally. Therefore, much of the Centers' transportation problems are related to local delivery. The private transportation fleet of Service Centers is operated on a lease basis by a little over fifty per cent of the Centers; an additional forty per cent own their own equipment. Large Centers prefer to lease and small Centers prefer to own; however, there does not appear to be any standards by which the buy or lease decision is reached. lndeed, there appears to be some contradiction. Those who own do so because they claim it is Cheaper. A favorite reply was, "Why let the leasing company make money?" Those who lease also feel that it is cheaper this way. Their reasoning is based on the opportunity cost of the capital invwsted in the transportation equipment. Most of the Centers' own trucks are loaded during the night for deliVery the next day. These trucks are usually gone for the day, although a few drivers in most of the Centers return for a second trip. Non—union til'iV¢‘l‘:‘. :u‘o lunr't- llH‘Vlf/ to make Hm venom! run than union 'Jr'i‘~;'v~r'.‘. lwuul 1.1'Ilr'k;; ZJI’P l.(_:1(l(r(i with 19,000 to 1‘.,00() pounds and gmwrally make around 15 stops. Over-the-road thit‘lec £1Vt"l".'i;?‘(’ 30,000 pounds and make approximately 20 stops. Most drivers who do the Centers' delivery work are unionized. Drive s generally make different runs every day, but Uh per cent of Centers responding said that their drivers make the same run every day. In roughly 80 per cent of the cases, the Center has information about tin: ('u.:t tinit tile clr‘iv<3r has. hi: material bundled properly, knows what ..he receiving hours are, and known the conditions at the consignee's. While at the consignee's, the driver generally helps with some unloading, and half of the Centers have the driver do all of the unloading. When the driver's trip is over, he may either bring a buy—out back to the Center or stop by a mill and return a mill shipment. In roughly US per cent ofthe cases, Centers have no methods of checking on the driver's delivery time. Driver checks may not he completely Useful in all circumstances, but in most cases they would seem to work for the benefit . oi the Center. Control over the driver's delivery time can lead to a more efficient use of the Center's fleet, give management the information it needs to determine where 137 changes are needed, help the Center provide better customer service and help keep the drivers honest. Most physical distribution efforts of the Center are geared toward first day delivery, and in about half of the cases, orders are delivered by this date. Most of the orders delivered beyond the first day have pre- production processing involved, and customers know that all competitive delivery dates generally will be beyond tdruvt day. Special handling is necessary in about five per cent of the cases to deliver an order on time. Special delivery means that some interruption in the physical distribution procedure must be made by the Center. Five per cent seems low, but this figure is an average. On some days the percentage may be high, and on other days i t; will be very low. Each Center should endeavor to measure the loss it will incur if special handling is not used and match this against the additional cost of special delivery. in calculating the loss, Centers should esti- mate the probability of the lost sale, the probability of the loss of future sales, and the probability of the loss of the account. If the marginal loss of SpGCial delivery is greater than the marginal cost, then Special delivery should be undertaken. Physical distribution plays a vibrant role in the Service Center industry. In the concluding part of this ljo chapter, some suggestions will be made as to how this system can be improved. Future Research Any research project should lead to suggestions for future research. lr this thesis focus was on the total physical distribution system. Much of the suggested research is related to detailed research in more Specific areas. Recommendations will be defined according to those areas with which this study was concerned, i.e., order processing, warehouse operation and transportation, plus an additional area on the complete system. OIWior‘ PIKJC(HBSlIlg Each Center should make a complete study of its order entry procedure. Special emphasis here should be placed on the proper allocation of the inside salesman's time, neatness, clarity and readability of orders, speed in order processing, and cost. There appear to be many Centers which have the salesman write the order. Some Centers use a flexiwriter, others use a typist. Some Centers have four copies of the order, others ten; and, each Center has a different size order and different color conuiiruitituis. Frequently today the computer is regarded as the elixir which cu es all ills. This is not the case here, however. There is too little use made of computers in 139 order processing. Inventory control is particularly neglected with respect to the computer. It seems that the industry has become tied into the Kardex system and is nuntt rwiluctantt tr)<:ut tars crnwi. idlere>zire lmnqefiin: to Kardex, but certainly there is merit in a study to delineate the advantages of computerized inventory control. Such a study could be made by a quantitative methods man. This study could show what programs are available, how they can be implemented, what size firm can best take advantage of such programs and where benefits can be derived in terms of speed, accuracy, control, improvement in purchasing and the elimination of out—of—stock items. TLe problem of attracting manpower to this area is vital. Perhaps programmers will have to work for the Cente's on a regional basis or through the Steel Service Center lrnztituite. Warehouse Operation Centers have to take more cognizance of the effect that pro—production processing has had on their physical diatribution systems. A study should be made to determine Just how each Center goes about programming their orders on the various machines. Production control departments should check all orders, allocate them to various machines, and publish schedules which show the time each order was set up to be worked on each machine. Under this system, there would be a schedule for each machine for every day. 1M0 ltd%)rmai,ioh :d)out,(wrd(wn; czall interested organizations within the Center, i.e., traffic and sales. Each part of the Center would then be aware of the status of all orders, and could work their jobs acc(n%iingly. Pre—production processing also means new machinery ter t.h<> Ciw1tr:a:‘.ting. There are cases where Centers buy material they (‘unhnt Hell bt'itzilme HH‘ price is .1 ow. Some Centers fail t~ look at all cf the total cost ramifications of i nhourui rout l' 11;); . A study might be made regarding location theory as it applies to the Service Center industry. Most Centers are located in the heart of metropolitan areas; however, there is a trend toward the location of new distribution centers on the reltways outside large metropolitan areas, where over—the-road shipments can get in and out quickly. duch a study Would also have to include the affect of labor, both blue-collar and white—collar, on the location of Centers. This labor problem could mean split facilities with the office being located in the suburbs and the plant in the center city. All of the physical distribution ramifications of such split facilities should be studied very closely. One final area needs to be mentioned. This is dis- tribution cost. There should be more work done in develop— ing some information about the cost of performing the distribution functio.s. This cost analysis does not have to be elaborate or be done every day, but Centers should have some idea of their distribution costs. This informa— tion should be available not so much to be used as a basis 11:5 for pricing, hut as a managerial tool. It ‘s most diffi— cult to make intelligent management decisions regarding physical distribution if the Center has no idea of the co ts of the alternatives. Development of these costs, particularly in light of improved data processing, is not the horrendous task that many Centers make it out to i)“. Metals Service Centers have set up excellent facilities for effectively distributing metals. With improved technology in the areas of order processing, transportation, materials handling, storage and inventory control, the Metals Service Center should become an even bigger factor in the distribution of metals. Increased efficiency by Cente s within the next decade should enable the Centers to rise to heights unmeasured in the early stages of warehouse development. 3) I) U - E .‘-. JDICES 1146 APPENDIX A THE DATA COLLECTING INSTRUMENTS 1147 o T E E L S E R V I C E C E N T E R I N S T I T U T E 5H0 Terminal Tower (216) 2Ul—3U68 Cleveland, Ohio “Ull3 Robert G. Welch, President The current doctoral student being sponsored by SSCI is Peter Lynagh who is doing a study of distribution patterns in the metals service center industry. So that he can gather data and observe service center operations, we have helped him select a number of companies to visit. Yours is one of those selected. Sometime in the near future, Peter will contact you to set a mutually convenient time for him to visit. He will want to first gather some general information about your company. Then, he wants to talk with you briefly and with the people in your company who are responsible for the assembly, pack- aging and delivery of orders. Everything he learns will be treated confidentially and will not be used in any manner which would permit identification with your company. Your welcoming Peter and your cooperation in helping him get the kind of information he seeks will contribute in a major way to the validity of his work and in helping to produce a dissertation which is meaningful to the industry. Sincerely, Robert G. Welch 1.14 8 iJATVl SIHLET7 All information will be held in strict confidence. Once thi:3 is twaturwnxl, 51 d—rnunbcn° wil i bC‘ZlSSlfiflled, {ind tJie cover sheet destroyed. 1149 150 Q Hwt Sales: Less than a million One million but less than five million Five million but less than ten million Ten million or more Net profit before taxes as a per cent of net sales: 8% and above 6% but less than 8% 11% tnlt ltnss idiari 6% 8% but less than 4% Less than % Total number of people employed: Number employed: lnside salesmen Outside salesmen Office clerical Schedulers Warehouse Processing Packing and shipping Transportation Management Do you specialize in any types of metals? Yes No if answer was yes, please list the special types, and the approximate percentage of the annual sales volume which is accounted for by those special types: Approximately how many items do you keep in inventory? What is the dollar value of inventory on hand? 191 What method do you use to determine the value? What % of your orders are pre-processed? What % of your orders are shipped direct from stock without any additional work? What % of your orders are shipped direct from stock without any work but cutting to length? Approximately how many accounts do you service? Describe briefly the geographical limits of your market. What % of your orders are delivered in the metropolitan area where your plant(s) is/are located? Sq. feet of space in your operation Sq. feet of space in office Sq. feet of inventory space Sq. feet of pro—processing space _ Sq. feet of packing and shipping (TfltflleY (lhhl(flih J. Number of items shipped per year ;’. 'foteLl aruiual.'tordulqe ‘Jkl 0 Number of days worked Number of shifts each day A. Number of employees eacn shift ). Basic jobs done by each shift: Shift ] Shift 2 Shift 3 6. Are your employees unionized? Yes No 7. Company policy on customer service: (N 0. Minimum charge per order: 9. What does it cost to: (Per item or per order) a. Process an order (from receipt until it goes to the warehouse) b. Schedule selection and transportation 0. Select the order and transfer it to shipping d. Packing e. Loading f. Transportation: Per Mile Per CWT Per Ton l0. ll. 15. 17. 153 [Mi yrnl maid? morufiy prmnxessirwgz 3. Cutting Yes No b. Slitting Yes No c. Burning Yes No d. Shearing Yes No C. Others Yes No 1F NO ABOVfi: Why do you do it? -. .— Who does your purchasing? ho vou lease or own your equipment? Lease (1 Why do you prefer this method? Own Who makes the investment decisions? Who makes the investment decision on materials handling? Dollar value of money invested in: a. Transportation EQ b. Material Handling c. Pre—Processing 15“ l8. Paperwork available: Company Annual Report P & L Statement Order Blank Inside Sale Work Sheet Company Stock List Balance Sheet Transportation Ton. Rept. Truck Trip Tickets Others (Jhiflii: PiMJCtRSSJiJH l. Apyn%)xinmmxc nununer of‘<>rderm; haiuiled iai orme day: a. By Telephone b. By Mail c. Other 9. Check below the time period when a majority of your orders arrive: 8-lO AM 1-3 PM 10—12 AM 3—5 PM After 5 PM i. What is your inventory control procedure? A. Do you check orders for credit purposes? Yes No *— lf Yes, what is the procedure for checking credit? 5. What is the average time it takes to process an order, i.e., from the time it arrives by phone until it reaches the warehouse? S(b)Pastest time you can process an order: 6. What % of your daily orders are Will Calls? 7. What percentage of your daily orders require special handling (non—standard delivery date, needs naterial today, rush, hot)? ‘l 10. ll. l5. l6. 17. IBM th(, nuik<3s tin: (Jvr:i:yl4uxrltnice (n1 ycnir pnuesern; jcfl) a.-— Nhat do you consider to he the major advantage your company has over its competitors? (Pleas .K one below) Pritx3 13:1 1635 Product Quality Efficient Delivery Service Strmum; Prodiuu; Line Variety in Product line Others: Explain What do you consider to be the major advantage your top competitor has over your company? (Please check one below) Price Sales Product Quality Efficient Delivery Jervice Strong Product Line Variety in Product Line Others: Explain Given identical physical products, do you feel that one 3.8.0. can handle an order better than another? Yes No Do you feel 5.8.C.'s have been successful in their efforts to sell customers on letting the Center bear the cost of carrying inventory? Yes _ No Do you feel that the increase sale of imported steel has injured the competitive position of your company? Yes N 0 ‘— ———.— in terms of delivering the right product to the customer as quickly as possible, how would you rate your company as campared with your top competitors? '1 l a 3 H , Hell Below Below About the Same Above well Above W [ht/,7) Wluuwv, in ymuir Ufillfltnl, do Huhat delays iilthaliverirugzni order occur? LHNJuI‘ PITHJCSLZngj Scheduling LlelLWEtiIut Parking & Shipping l‘r'alrlrtlicii't.l 12g; how important do you feel quick, e ficient delivery service h; to ycuuclxnnpany's (unstomers? 1L 2 3 I l ”wry important important Of Mild Importance Unimportant 5 Very lhlimptdumint what do you consider to be the most important aspect of quick, efficient delivery service? Order Processing Scheduling Selecting Packing & Shipping Transportation ho you feel top management in your company overstresses customer service? Yes No Understresses customer service? Yes No What would you consider the most frequently lodged complaint customers make about S.S.C.'s? Price Sales Pr*oclu<:t Lula lilzy inefficient Delivery Service Small Product Line Other n V '1. V“" - r. “Mull/in b .m. w sAnPtt ULNTLHS Allllfl‘lu’l‘lixl Ell" yfllilic i3 167 AldfilC/’tifll'13u ElliNlTZ'BO {lifllddfi Cbflyfhtflj The male] used in this thesis describes, verbally, W i be. if a F4 ibutios system as it snou sample Center perfectly matched the model, then that Center was given three points. if the sample Center was the antithesis of the model, then that Center was given zero poi.u.:. The i xllouirutrneasuremnnit systmnn shows tfluc basis for the allocation cf points for each physical distribu- tixlrl i'a«:t()r'. Vor each factor, points were allocated based on an ideal. in some cases, the Center was not performing accord— ing to the ideal, but what they were doing was appropriate for their particular organization. For example, a computer order entry system would be inappropriate for a very small, single-unit Center. ln such cases, the allocation of points was based on what was appropriate for the individual Center. Order Processing 1. How the order arrives at the Center 3 Paints - QD—lOO% by telephone 2 " — 80-89.9% by telephone l " - 70—79.9% by telephone 0 " — Less than 70% by telephone 160 “low or lhe incoming orders throughout the day ‘i Points ') H r, J H U H ljrfxlit, clue _) Point. 1‘; "3 H O H lletlnwi of‘ ?) Poilits ’_‘\ H r ‘ H l, i‘ H l‘.Xl.Qlli; ()1. ) 3 Points ’3 H (.l 1 H () H Speed in % Points 1) H 1 H O H 0 Even distribution throughout the day One time period punching Two time period bunchings no knowledge of the time when orders arrive I 4- YD L C ‘ ',.' ';»‘ ‘ K 1‘ ‘ "A “\ 1" lll. hairllirg: ll. The affect of pre-production processing on scheduling 5 Points — do affect a " — Affec s some operations l ” — Affects all operations 0 " — an reply l3. luw3r‘ I, ~ ‘ (- -' 4‘ 1 ‘- -. - r, ‘ r‘ :7- ‘ - ‘— -. C'ill‘ x; "' .'.(,‘~_ L, DI wfilnl) lift, uflig-‘ph Cl «AL; OIlC LIJJHC ’ " — lama: orders aIT?.fillpde at tnr; time i " - inlippimng occtnn: thrcnnnlout tune day 0 " - No reply lY. Tran-k lawidirnj by chfliverds 3 Points - Less than 25% a " — 45% — M9.9% l " — 5(% - 7M.9% U ” - 75% or more 19. warree at will-call business g Points — Less than 5% of the outbound tonnage P ” ~ 5% — 9.9% of the outbound tonnage l " — lb; — ll.9% of the outbound tonnage t ” — l5% or more of the outbound tonnage £9. Causes of shipping delays ” Points — Uncontrollable from a physical distri— bution standpoint, e.g., mechanical breakdown, pre—production processing and special packing ” » Fairly uncontrollable, e.g., poor personnel and poor transportation equipment 1 " — Fairly controllable, e.g., poorly assembled orders and lack of handl- ing equipment U ” — Uontrollable factors, e.g., lost material and poor shipping space J’O. ‘darwehtnise «co:rts 3 Points — Lower one-third P - Middle one—third l " - Upper one-third ”' " he not know their cost Cf) l7? 'i‘rfins p o 1" ta t i on ?l. scheduling of orders for transportation prior to selection Points ~ Yes ') H __ __ i H _ a " _ _ Us. Use of daily transportation routes 5 faint: - haily schedules set up and used 3 ” — acme sohedules used l " — Schedules between company facilities only 0 " - Ho daily schedules 0 a4. Outbwund tonnage R loints — r T5% via private transportation ’\ \i d l g I? \ 2 ” ~ 5u% — ?M.9% via private transportation l " a 95% - “9.9% via private transportation 0 ” — Less than 25% via private transporta- tion 2“. heason for the use of private transportation ’ \ Points — setter delivery service ! J ' - Kore control over operations, flexibility l ” — Poor common carrier service 0 " — Lower cost 35, Method of purchasing private transportation fleet < Points - Lease with legitimate justification 2 " — own with legitimate Justification l " — Lease with poor justification 0 ” — Own with poor justification 36. Weight per truck 3 Points — Top one—third \ 2 ” - Middle one-third ” — Lower one-third O " — No information available 'Ji} " . QJ y—o Number of ') l’HlliL.) ) H l H t) H t H J H {} H number of a reintu H H l {l ” ”ltur if ) D a ' .-. ’4, l (J 1. 1’1 t/ L H H ‘l H O H hegree of 3 Points ) H l H U I! 173 st(nis [mar tufiip Lovnjni, orM2—tlrirtl Middle one—third Highest one—third No information available 5 tfip Elites: one—third Riddle onentnird Lower one—third pa) lnlfimwnati(ni:ivaiijnile trips mide per day by drivers Less than 33% make more than one trip per day 33% — 60.9% make more than one trip per day ('73, p N \ o ,1 ,__ if f. 1 r r U{,u alml hiipler {mine IerE?‘tnar1<3ne trip per day No information available 1. the drivers' daily trips Seldom make the same trip every day Sometimas make the same trip every day Very often make the same trip every day Always make the same trip every day unlcnrlirmjliorna by thciverfs Less than 25% done by drivers 25% — “9.9% done by drivers 50% — 7U.9% done by drivers 75% or more done by drivers Determination of customers' receiving facilities 5 Points 9 H ( J H d ” Written questionnaires sent to customers Salesmen check out customers' facilities Depend on information from drivers No procedure to check customers' facilities Lu. avg u.) {T\ l‘ \l 1714 Control checks on drivers Contrwd_f 'zick—Jniul 3 Points — Juy—outs and mill purchases 2 " — Mill purchases only 1 " --lfiuy—OLHx3 only 0 " - Na back-haul Transportation costs should be 3 Points - Lower one-third 2 " Middle one-third l " Upper one—third 0 " No cost information minimized Al‘l’l‘l 34' l) i X A 'i‘ l xngw'm '11 U1 N ,1_ Ill l. \ $4 V J Ix [4 .1 ‘ A . Via I. .lv . 175 STATldTiCAL COMPUTATIONS Appendix C contains a series of tables detailing the computations used in Chaoters 5 and 6. There were three statistical tests used in these chapters. First, a t-test Was used to see if the mean score of the sample was signif— icantly less than the score of the normative model. The fknwmila tuwxi was: t=£§£fl.l Q Second, a comparison was made between two sample means. The formula used here was: _ ’ 2 X “h, .. _ 1 Z . - (f‘ .L l t — 3“”, S— — - CW 7?— r“— . oil-iq Xl'X2 \Lle 142 Third, a chi—square test was used in Chapter 6: 1Details can be found in: John E. Freund and Frank J. Williams, Modern Business Statistics, (Englewood Cliffs, N. J.: Prentice-hall, Inc., l9583, p. 233. 2Details can be found in: Frederick E. Croxton and Dudley J. Cowden, Practical Business Statistics, (Englewood Cliffs, N. J.: Prentice-Hall, Inc., 19607 Chapter 23. jDetails can be found in: Quinn McNemar, Psychological Statistics, (New York, N. Y.: John Wiley and Sons, Inc., 19607 Chapter 13. 176 ‘1) r I L). 3'? a U) Trans- -arehouse Y i4 Order ‘ I Tota' “ran. ortat' p 'H r"! S: (U (\j \C v N if (V 1; Sample X(Points) Centers (‘\ (D (\J (“J r~~ ON (I) (\l 17 U) (\l wl (M \L ) rd 13 12 11 \i 3 t i (7\ ( \J :T L\ 2r 0 ) [\‘ (Ki \O O\ is~ F J Lifi‘x KO [\._ l(\ r l (\J r‘d 50 r- on 9 q l \ C) .— 4 l l \ (\J (\J Lfl (T\ Lf‘l \i) [6‘1 .0 J 32a (1) v i O‘\ U .) C \J [\ 177 ")\ ( ) U- ) m L O r i I) ("d 'm a (U (\l r1. 1‘1 (If) i. \J [7‘ 2704 C) L. Ll'\ ! O [_\J ( "J [1“ r4 rd (.3 C.) C r—4 H v—d (\1 (Y3 MW ‘0 f\\- \O (\l l. l \ v.) m 13 16 16 3364 Cl) 729 225 \. D LIN (U Lf\ (\J (V) L‘f\ Li \ \D (‘0 \O LIN (\J’ ‘O HNM?U\\OL\CXDO\O H 2500 50 61 73‘ (V) 0:) 32M H00 0‘) ('1 \0 O‘\ r“! 1U r_.{ f"! 3721 li’\ (\J C‘) \O U \- (‘0 16 15 14 (\J H 900 57 3249 30 140 (\l LIN (XI WW (.4 :r m CD 28 30 256 32M \0 r“! KE) O\ H 3721 61 900 ON \0 n—l 13 16 ll 13 11 CC) [x~ 28 32 UBH 32“ (\l ("\l \.(_) II\ (\J 61 3721 102b r~l 121 169 121 M356 2209 \O \0 L1 \ r—i 361 3a 100 1 .L M7 676 26 :rmxozxooox r-lr-ir-dt—lr-‘ir-i Trans- Warehouse Order :--l (d 1) 1’-) l;-+ C H (*3 3-4 (7) L14 {1() (1)- r-iG) (\l (\J X N (:24 ~l—) Cl) (1;) O\ :'\J (V) In m [=- r—i KC) r-i (“'1 19 (\J Lfl C) {\J L'.\ (\J 0’) LG LE \ -T‘T 0,) (I) (\J 16 15 r—4 (‘1 U\ (\J (\J D \D L."\ 256 16 U\ 01 Cd (‘x J M900 7734 (‘1 U r—i (“J Ln r4 . 4. I , 196 l H [\. #4 (V) i "a CC: Cl 3 r4 (\J Lfl C\ (\J (Y) (‘J 676 (\I 6 369 178 “) 23'5971-369C _ L: 1 s=\l J ’3 c. 15.375-30 , 4. lo K D = 3.606 I . U 99-U.06 = -19.894>—2.069 C) l! -“?.U ZX = 369 C‘. 5971 XX“: 179 O‘\ m ‘ (n l 10 1| 3 I Ux { ‘0 0\ II C O 'I O“. t 3| ' (fr) 0‘. II ° Ch ' ‘ Lf‘\ 10 CH CH 3 i 6“ (7‘1 \{D ' . :1 In To - f) C m «M O\ . [\ . . . (\J 0 Ch [1 l - o 1 Q“ (\J "7 (\J I) ‘l 7‘") r—i ' o o I. 1 Ch I A (O 2* ";‘ i- ll (\l ‘1 ll L1“ I i ll - m ll .l :T \O m l m (\1 | :r :r l O\ .—7 \O :U l: 0“ II I ' ," ll (Y1 (Y0 0 ON (77 H IcJ ox b~m . 1‘ O \ ° C) ' . [\ - H {I :3 :4- FG :1 or: L0 ll dim Ian . b~m Icm I": \O in (h Ch r4 H CA - o (\1 Q N o O\ U) ’ ;3- ‘O . (‘n :1- [\ . I (\1 . O‘\ . (J ' FYI . \C) rd . KO ' "‘ ’7 H! | ”-7 (\l ‘ II II II II I O) .1 3 (f) 0 ll '6 <1) :1 c e S l .3 $' l #4 o ' o c C) ‘ S: (”J | l (U -,-—4 ' ' ‘ .I: L; *4 H ° ' (\J Li". 0‘ 0.1 O\ O\ m I Q) \0 C\ 1“» ‘k 4—) [\- 0\ r4 7 U) . ‘eg on J\ ~r Ll - 03 n :3 KO C‘) - ° -C‘ O \0 rd ° :1] I Q r-—{ (Y‘. O\ .——1 (Y . \I"- Q 01 L0 :: b-l ‘ ,C (O m g 0) II II II II II H C II II II ‘1: . Sc CK CU F4 1 a1 Ix »: :< L l :3: v~1 *3 6? r7; Dd yd Es. I>< :1 U0 4 -17>-2.069 -u.737-u.9 = XX = 6H3 2x2= 17,779 Total Sample r“! ST LI’ (\J n ( (“i If (‘1 b——- :9 U) [xi 0) UN I‘r'< 111 U 06) 1.90 I>< U) 1411 XX 2- 8M,9H1 XX 181 TAHLH l6.——bifference between the Mean Number of Points gtcormul on (huler ldchessiing of‘lhnall_zand lxirge (knaters. ._.. ._ _._ . -._ ..—w —.._._- ..._..-- ..-. __ — 0--.- _......._-- .-_.._ Small Large —«_-—a—. _. ._ . q - fl-.' _-._ 2—77- __.—..._.. -m k .- Sample 3 9 Centers X(Points) X“ X XL 1 13 169 11 121 n :2 119 15 225 3 17 269 17 289 M 20 900 13 169 5 16 256 16 256 6 . 15 225 15 225 7 in 196 16 256 :1 14 196 11 121 9 13 169 . l3 169 10 11 121 ° 23 529 ‘11 17 ' 289 16 256 12 - _ ' 15 _ 225 13 ‘ . ' 26 ‘ 676 162 215m 7 207 3517 i] = 1u.727 . i, = 15.923 .3w1 = 2u5u—1622e11 = 68 N1 = 11 n, = 12 Sw2 = 3517—207 13 =221 S = R S = 2 S : ‘ _ .wl 6- W2 2 1 w 289 1 1“. 'f‘-—*- s— — = + —e = ' 2 12' = . X1_Xq J289(11 15) U2. 01-2 1 48 C" I H .11" -\ F J H~d ° I H \fl KO {‘3 L/‘v ll H8. —.80< -2.069 182 'wnamc 17.——Difference Between the Mean Number of Points Scored on Warehouse Handling of Small and Large Centers. Sample Small 2 Large 2 Centers X(Points) X X X l 17 289 17 289 2 14 196 16 256 i 17 289 18' 324 4 17 289 16 256 5 15 225 20 400 6 16 256 12 144 1’ Iii :524 P2 1484 H 16 256 18 ’24 9 18 324 19 361 10 10 100 19 361 ll 14 196 11 121 12 1 16 256 3 23 529 172 2744 227 4105 . 1722 N1 = 11 N? = 15 8wl = 27uu——TT— = 56 Y] = 15.636 X? = 17.46 2 H -, , _ Sw- - 4105—227 =1u1 ow]: 5n hwp= 141 2 13 ——" Sw = 197 $71-25: .,197(%—1- + —i—_—) = 1 3 = -1.40< —2.069 Fail to Reject 183 TABLE 18.--Difrerence Between the Mean Number of Points Hunred on Transportation of Small and Large Centers. _._-. ...-'_._.. ._. ....--» M—v—o- ——.—..——. .—..- _ _ _—_..,.fi_. ._._ .. ___..._.—..—.. “www .‘.—.... H, Small Large .nimple 2 2 Centers X(Points) X X X 1 17 289 24 576 2 28 18a 19 361 3 19 361 24 576 u 15 225 2a 576 5 2/ 729 25 625 6 24 576 30 900 7 18 321 28 78M 8 ' 28 78M 32 102“ 9 30 900 3“ 1156 10 26 676 31 961 11 39 1521 28 78M 12 3a 1156 13 39 1521 271 7169 372 11000 N1 = 11 N2 = 13 X1 = 2u.6u X2 = 28.62 SW1: H93 Sw2= 355 3w =7169_31l: = 7169-6676 = 193 k 1 11 37°2 3wq=11,ooo——j§—-= 11,000—1o,6u5 = 355 SW = 8&8 _ 1 1 _ - S§1_i2— J8M8111,,i nuetl . 193 o s 0-H (O—E)2 (O—E)2£E Table 10 10 11 1 1 .091 10 10 0 0 7 10 3 9 .900 13 11 2 4 .364 8 8 0 7 7 O 0 11 7 4 16 2.286 3 8 5 25 3.125 3 2 1 l .500 3 2 1 1 .500 1 2 1 1 .500 1 2 1 1 .500 3 4 1 l .250 2 3 1 1 .333 3 3 0 o 6 3 3 9 3.000 104 'PAHLH 24.--Cont1nued. o 6 0—0 (0-13)2 (0-E)2%E Table 11 3 5 0 0 3 3 0 0 3 3 0 0 4 3 1 1 .333 2 2 0 0 3 2 1 1 .500 4 1 2 4 2.000 0 2 2 4 2.000 4 7 3 9 1.286 2 6 4 16 2.667 10 6 4 16 2.667 10 3 9 1.286 1 4 16 3.200 7 4 3 9 2.250 3 4 1 1 .250 6 4 2 4 1.000 7 4 3 9 2.250 4 3 1 1 .333 2 3 1 1 .333 1 4 3 9 2.250 7 4 3 9 2.250 3 3 O O 0 3 3 9 3.000 2 3 1 1 .333 2 x =30.29 195 TABLE 24.——Continued. ._ .. ._ _.-.. *,.__ .1 ".1- __. - P- —. .__.2..__.- _.__......_ -.—. _-. M... _. ._..—.._—..._... ____._. _.._ -F-v~—~- M.. 0 0 O-E (o—E)2 (o—E)2+E Table 12 8 8 0 0 11 8 3 9 1.125 9 8 1 .125 4 8 4 16 2.000 5 4 1 1 .250 5 4 1 1 .250 3 4 1 1 .250 3 4 1 1 .250 4 6 2 4 .667 1 6 5 25 4.167 6 6 0 0 12 6 6 36 6.000 5 3 2 4 1.333 3 3 O O 3 3 0 0 0 3 3 9 3.000 2 2 0 0 2 2 0 0 1 2 1 1 .500 4 2 2 4 2.000 2 x =2l.92 196 TAMLH 24.—-nontinued. 0 L O—E (0—13)2 (o—E)2eE Table 13 15 12 3 9 .750 8 11 2 9 .818 9 11 . 4 .363 13 11 2 4 .363 7 F’ 1 l .125 11 8 3 9 .500 9 8 1 1 .715 5 8 3 9 1.125 2 4 2 4 1.000 < 4 1 .250 4 4 0 0 5 4 1 1 .250 BIBLIOGRAPHY 197 BIBLIOGRAPHY Books Ammer, Dean 8. Material Management. rev. ed. Homewood, Illinois: Richard D. Irwin, Inc., 1968. Boril, Louis C. Packaging Engineering. New York: Reinhold Publishing Corporation, 1954. Borsodi, Ralph. The Distribution Age. New York: D. Appleton and Company, 1929. Bowersox, Donald J. "Changing Channels in the Physical Distribution of Finished Goods." Readings in Physical Distribution Management. 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