Competitive food manufacturing: Evidence from the 1994 competitive manufacturing survey

Competitive Food Manufacturing: Evidence from the 1994 Competitive Manufactur ing Survey

S. Andrew Starbird Narendra Agrawal

Despite accounting for 10% of the US gross domestic product from manufacturing in 1991, the US food manufacturing industry hus been, for the most part, neglected in the strategic management literature. In this article we use a survey of over 225 food manufacturing firms to explore the relationship between manufacturing strategy and competitiveness in this important industry. Specijically, we examine the relationship between manufacturing objectives, manufacturing policy adoption rates, manufacturing performance, and financial performance. Our results suggest that many food manufacturing firms fail to fully exploit manufacturing’s potential contributions to customer satisfaction and that they frequently adopt manufacturing policies that have little or no effect on manufacturing performance. Firms can use the results presented in this article to benchmark their performance relative to the best firms in the industry. 01996 John Wiley & Sons, Inc.

In 1993 the Institute of Agribusiness at Santa Clara University inaugurated the first in a series ......................................................

Requests for reprints should be sent to S.A. Starbird, Leavey

School of Business, Institute of Agribusiness, Santa Clara Univ., San-

ta Clara, CA 95053.

of biannual surveys designed to identify and re- port on sources of competitiveness in the US food manufacturing industry. Our primary objective is to identify the contribution made to firm competitiveness by specific manufacturing policies, procedures, strategies, and goals. There are three mo- tivations for this project. First, manufacturing’s overall contribution to customer satisfaction and firm competitiveness is poorly understood and often overlooked. Authors such as Hil1,l and Skinner3 have suggested that manufacturing can contribute to customer satisfaction in many ways in addition to simply delivering an inexpen- sive product. They argue that firms can use manufacturing to differentiate their product on the basis of attributes like rapid and reliable delivery, high quality, o r a customized order capability. In this study we explore the extent to which food manufacturing firms emphasize these alternative manufacturing objectives. Second, advocates of popular, contemporary manufacturing policies (e.g., just in time, computer-aided manufacturing, materials requirement planning, etc.) often make sweeping claims regarding the contribution of their systems to firm competitiveness. Empirical studies that sustain or discredit these claims are conspicu-

............................................................................................................... The authors are with Santa Clara University

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Agribusiness, Vol. 12, No. 6, 525-539 (1996) 0 1996 by John Wiley & Sons, Inc. CCC 0742-4477/96/060525-15

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Starblrd and Agrawal

ously absent from the management literature. In this study we test whether these promises of broad improvements in manufacturing and financial performance are justified in the food manufacturing industry. Third, past research into manufacturing strategy and competitiveness either ignores the food industry o r combines the food industry with other unrelated subsectors of the economy, For example, in the biannual survey performed by the manufacturing round table at Boston University, information from food manufacturers and processors is combined with consumer packaged goods.4

The strategy development and implementation process depicted in Figure 1 served as the concep- tual framework for the development and inter- pretation of the survey. We assume that competitiveness can be measured by financial performance and that it is a function of customer satisfaction. We also assume that manufacturing contributes to customer satisfaction in a number of important and specific ways. As represented in Figure 1, the first step in satisfying the customer is, of course, identifying the customer’s needs and requirements. The second step is to translate the customer’s requirements into reasonable and at- tainable manufacturing objectives. Finally, the

I Customer Requirements I

Manufacturing Objectives

1 Manufacturing Policies and Procedures ~

I Manufacturing Performance I

Financial Performance

Figure 1. The strategy development and implementation process.

firm must choose manufacturing policies and procedures that contribute to achieving the firm’s manufacturing objectives. If the firm chooses manufacturing objectives that are consistent with customer needs and adopts manufacturing policies that truly contribute to the firm’s objectives and correctly implements those manufacturing policies, then it will experience superior manufacturing and financial performance. On the other hand, if customer needs are not fully understood, if the firm7s manufacturing objectives are inconsistent with customer needs, or if the firm’s manufacturing policies do not contribute to manufacturing objectives, the process breaks down and the firm’s competitiveness will deteriorate.

According to some authors,l~5~“ a common reason for the collapse of the system represented in Fig- ure 1 is that firm strategies become “unfocused.” A focused strategy is one in which manufacturing objectives match customer needs. Because customer requirements and expectations change continuously but manufacturing strategies tend to be stationary, it is natural for the two to diverge over time. Unless the firm continually revisits its strategic objectives, it is only a matter of time before it will lose the competitive edge.

The firms that participated in this survey were asked questions about each step in the strategy development process. From their responses, we can determine which policies and procedures contribute to firm competitiveness and which do not. The results presented here can be used by industry participants to determine which manufacturing methods lead to improved manufacturing performance and which do not, compare their performance and practices to other firms competing in the food industry, and gauge their position with respect to the most successful competitors in the food industry.

The paper is composed of five sections. In the next section we provide a statistical profile of the firms that responded to our survey. We discuss manufacturing strategy and the linkage between customer satisfaction and manufacturing performance in the second section. In the third section, we distinguish the “high performance” firms from the remaining firms and identify the traits that they have in common. We draw several conclu-

526

Food Manufacturing Survey

sions and point out a number of management implications in the last section.

Participant Profile

In late 1993 we sent a 10-page questionnaire to 3120 US food manufacturers. The questionnaire required 194 individual responses to questions regarding the firm’s demographics, manufacturing performance, financial performance, customer requirements, and manufacturing policies. We re- ceived 228 usable surveys, most of which were completed by company presidents, CEOs, or general managers. The titles of the respondents are listed in Table I.

Our sample consists of firms representing every state and every type of agribusiness in the United States today. The firms that participated in the survey are relatively small in terms of annual sales, number of plants, and number of employees; but they also have broad product lines and impressive rates of growth. The mean value for a number of important business statistics are presented in Table 11. All of the subindustries under Standard Industrial Classification (SIC) code 20, Food and Kindred Products, are represented by the firms in our sample. In Table I11 we show the percentage of participating firms in each of the SIC subindustries. Nearly a quarter of the partici-

“able I. Tit le of Survey Respondents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Title . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . President, CEO, or General Manager Owner or Chairman of the Board Division, Area, or Plant Manager Manager, Director, or V P of

Operations CFO, Treasurer, Controller, or V P

of Finance Production Manager or V P of

Marketing Executive V P Other

. . . . . . . Percent . . . . . . .

58 9 7

11

3

7

2 2

~ ~ ~

b b l e 11. Selected Business Statistics for Participating Firms.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mean

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sales Per Year ($ Million) 17.4 Market Share (70) 28 Pretax Profit as 70 of Sales 17 Growth Rate in Sales, Per Year 18

4 Number of

Products 14 1 Plants 2 Vendors 74 new products in the last 5 years 25

Indirect Labor Employees 42

R&D Expense as 70 of Sales

Direct Labor Employees 94

pating firms are classified as “miscellaneous.” Mis- cellaneous products include prepared foods, cof- fee, peanut butter, honey, and many other food products that do not fit conveniently into the other categories. Over 20% of participating firms make canned and frozen fruits, vegetables, and specialty products. The oils and oil seed products subindustry has the fewest number of participants. Subindustry-specific business statistics can be found in Starbird and A g r a ~ a l . ~

Most of the participating firms serve several dif-

Table Ill. SIC Subindustry of Participating Firms.

Subindustry (SIC Code) Percent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Processed Meat and Poultry (2010) 11.4

Canned & Frozen Fruits, Vegetables, 22.4

Flour and Other Grain Mill Products 7.0

Bakery Products (2050) 9.6 Sugar and Confectionery Products 8.3

2.2

Miscellaneous (2090) 22.8

Dairy Products (2020) 11.0

& Specialties (2030)

(2040)

(2060) Oils and Oil Seed Products (2070) Beverages (2080) 5.3

*527


Table IV. Sales to Different Customer Groups for A l l Participating Firms.

Customer Group Percent

Government 2.0 Individual Consumers 8.0 Remanufacturers 14.0 Retailers/Distributors 48.0 Food Service 22.0 Wholesale Clubs 4.0 Other 2 .o

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ferent customer groups. In Table IV we show the percentage of sales to the major customer groups for all the participating firms. Only 8% of the participating firms’ sales are directly to consumers. Most sales are to retailers, distributors, and food service organizations. This fact is important in determining the needs and requirements of the customer. Food manufacturers who sell directly to consumers often have different manufacturing objectives than food manufacturers selling primarily to distributors, retailers, and food service firms.

The majority (52.7%) of the participating firms operate a batch process as opposed to a job shop, assembly line, o r continuous process (Table V). This is not a surprising statistic because the participating firms tend to have broad product lines (see Table 11). Batch operations are more common when the same facilities are used to produce many different products.

The average manufacturing performance of the participating firms is presented in Table VI. We divide the manufacturing performance statistics into four categories: cost control measures, inven-

Table L Process Tyipes Used by Participating Firms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Process Type Percent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Batch Process or Operations 52.7 Continuous Flow Process 28.3 Assembly Line 14.6 Custom Job Shop 4.4

Table VI. Manufacturing Performance Statistics for Participating Firms.

.................................................... Manufacturing Performance Statistics Mean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cost Control Measures

Manufacturing cost as Yo of sales Overhead as % of manufacturing

Value-added/employee/year ($ 000)

Investment in inventory as Yo of all

Finished goods inventory turns per

cost

Inventory Control Measures

assets

year Process Control Measures

Machine utilization (%) Labor utilization (Yo)

Throughput time (days) Manufacturing lead time (days)

Delivery Performance Measures

. . . . . .

51.3 16.0

42

30.2

49.5

57.3 76.5

24.8 16.7

tory control measures, process control measures, and delivery performance measures.

Based on the information in this section we can say that the participating firms represent a broad cross section of the industry; they tend to be small firms with attractive rates of growth and pretax profit; and most sell directly to distributors, retailers, or food service firms.

Manufacturing Strategy and Performance

In this section we examine the translation of customer requirements into manufacturing objectives, the relationship between manufacturing objectives and the adoption of manufacturing policies and procedures, and the effect of manufacturing policies on manufacturing performance.

Customer Requirements and Manufacturing Objectives

Customers purchase products in order to satisfy manufacturing-related and nonmanufacturing- related customer requirements. Manufacturing-

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related customer requirements include fast delivery, reliable delivery, high quality, low price, the ability to customize orders, and an innovative design. Because satisfying these customer requirements depends upon manufacturing performance, we refer to these customer requirements as manufacturing “deliverables .” Manufacturers must determine the importance of these different deliverables to their customers and prioritize their manufacturing objectives accordingly.

In our survey participants used a 7-point scale to indicate the importance of alternative deliverables to the firm’s customers and to indicate the emphasis on those deliverables in the firm’s manufacturing strategy. In Figure 2 we show the difference between the deliverable’s rating in terms of customer requirements and the deliverable’s rating in terms of the firm’s manufacturing strategy. The difference between the ratings is statistically significant at a 10% level of confidence for all deliverables except quality. Fisher’s randomization test with a continuity correction was used to determine statistical significance (see Snedecor and Coch- ran,8 p. 132). Evidently there are significant inconsistencies between the needs of the market and the emphasis of the manufacturing strategy. The respondents indicated that fast delivery and customization are more important to customers than their manufacturing strategy implies, and that low price, reliable delivery, and innovative design are more important in the manufacturing strategy than customer requirements warrant. It is important to note that these ratings were gener- ated by the manufacturers themselves and not by the manufacturer’s customers, so the ratings associated with customer needs may include some bias.

Hill1 suggested that the discrepancy between customer requirements and manufacturing objectives is due in part to the discrepancy between customer requirements and the basis for evaluating managers’ performance. Even when fast delivery and customization capability are recognized as important factors in customer satisfaction, these deliverables are rarely taken into account when evaluating a manager’s performance. Evaluation systems should be based on the manufacturing deliverables that contribute to customer satisfac-

tion, and managers should be rewarded for delivering what the customer wants.

The inconsistency illustrated in Figure 2 indicates that some firms in the sample are pursuing an unfocused manufacturing strategy. In unfocused firms, manufacturing is not contributing all that it can to customer satisfaction and firm competitiveness. This situation leaves oppor- tunities open for firms that can identify the manufacturing deliverables that are important to their competitor’s customers and then emphasize those deliverables in their manufacturing strategy.

In this section we examined the relationship between customer requirements and manufacturing objectives in the participating firms. In the next section we determine whether there is a relationship between manufacturing objectives and the manufacturing policies and procedures that are adopted by the participating firms.

Manufacturing Objectives and Policies

Food manufacturers and processors have a seem- ingly endless supply of new and improved manufacturing methods from which to choose. Methods like materials requirements planning (MRP), just in time (JIT), and others have been sold to manufacturers as the solution to their problems and the source of competitiveness. We believe that these policies, methods, procedures, and philosophies only contribute to firm competitiveness if they support the achievement of manufacturing objectives that are directly related to customer satisfaction.

In our survey, we examined the adoption of several classes of manufacturing policies to determine which policies are most popular in the food manufacturing industry, how manufacturing objectives affect the adoption of manufacturing policies, and how the adoption of manufacturing policies affect manufacturing performance. We considered process design policies, process control policies, vendor relations and certification policies, capacity management policies, benchmarking, and product development policies. In Table VII we present the rates of adoption for several specific manufacturing policies in these categories.

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"able VII. Adoption of Manufacturing Policies by Participating Firms.

.................................................

Ilanuiacturing Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Process Design Policies

Flexible manufacturing systems Group technology Automation Robotics

Process Control Policies CAM Receive JIT deliveries Make JIT deliveries MRP

Vendor Relations Policies Number of vendors Vendor certification program Vendors involved with product

Vendors informed of production

Vendors informed of demand

Vendors informed of quality level

Subcontracting used for extra

Overtime used for extra capacity Benchmarking

Quality Productivity Profitability Manufacturing process Procurement policy Distribution strategy

No. new product introductions in last 5 years

No. products CAD

design

schedule

forecasts

Capacity Management Policies

capacity

Product Development Policies

Percent Adopting

. . . . . . . . . . . . . . .

48.7 16.7 36.4

3.9

16.7 41.7 55.3 26.3

748 33.3 32.5

42.1

47.4

64.5

16.2

64.5

64.5 46.5 50.0 46.1 25.4 35.1

258

1418 14.5

aThese are absolute figures, not percentages.

The rates of adoption shown in Table VII imply several things about the food manufacturing industry. First, when compared to other industries such as the automotive and electronics industries,

we find that the food manufacturing industry has lower adoption rates for the more popular manufacturing p o l i c i e ~ . ~ ? ~ Second, no policy enjoys unanimous or even near unanimous adoption by the food industry. The most popular policies are used by less than 65% of the firms and are related to quality. The least popular are the technologi- cally advanced, capital-intensive methods such as robotics, computer-aided design (CAD), and computer-aided manufacturing (CAM). Third, there is a discrepancy between the percentage of firms making JIT deliveries and the percentage of firms receiving JIT deliveries, Because more firms make JIT deliveries, food manufacturers may be holding the inventory that would have been, in the past, held by customers or suppliers. Finally, there are relatively low levels of vendor involvement in decision making, which is inconsistent with trends in other industries.

For the firm to be competitive, adopted policies must help the firm achieve its manufacturing objectives, which must be consistent with customer requirements. To determine whether or not this is the case, we need to determine whether there is a relationship between the firm's manufacturing objectives and the adoption o r avoidance of specific policies and whether the specific policies have any effect on manufacturing performance.

In Table VIII we summarize the results of our statistical analysis of the relationship between manufacturing objectives and the adoption or avoidance of particular policies. We used multiple analysis of variance with type I11 sum of squares and a 10% level of confidence to determine whether or not an objective had a significant impact on the adoption of a policy or procedure [SAS process GLM with option multiple analysis of variance (MANOVA)].lO Our analysis indicates that there is a strong relationship between manufacturing objectives and the adoption of specific sets of manufacturing policies. For example, when low cost is the objective, firms tend to adopt CAM and robotics, inform vendors of production schedules, and benchmark productivity, profitability, and manufacturing processes. When innovative design is the objective, firms adopt flexible manufacturing systems and group technology, they involve vendors in product design issues and inform vendors of de-

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Table VIII. Manufacturing Objectives and Manufactnring Policy Adoption or Avoidance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Manulacluring Objectives

Hanufacturing Policy/Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Process Design Policies Flexible manufacturing systems Group technology Automation Robotics


Vendor Relations Policies Vendor certification program

. . .

Conformance Reliable Fast Custom Low Innovative Quality Delivery Delivery Orders Price Design

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

+ - + + -

+ +

+

Vendors involved with product design Vendors informed of production - + Vendors informed of demand forecasts - + Vendors informed of quality level

Subcontracting used for extra capacity Overtime used for extra capacity

Productivity + Profitability - + Manufacturing process - +

+

schedule

+ Vendor concentration

Capacity Management Policies + +

Benchmarking Quality

- Procurement policy Distribution strategy

CAD Product Development Policies

+ -

New product introductions + + Broad product line + + +, adoption; -, avoidance.

mand forecasts and quality levels, and they tend to carry broad product lines and introduce new products more rapidly than other firms.

We also found that certain objectives lead to the avoidance of specific sets of policies. When conformance quality is the objective, firms avoid policies like JIT, MRP, and CAD. These policies are often put forth as methods for reducing cost and im-

proving delivery, objectives that can conflict with an emphasis on high quality.

The adoption or avoidance of many of the policies seem to be unaffected by manufacturing objective. This result is disturbing because it implies that managers do not understand how these policies contribute to manufacturing objectives o r that these policies have no effect on achieving manufac-

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turing objectives. Managers need to carefully scru- tinize the potential contribution of manufacturing policies before making any investment. Only policies that make specific and clearly understood contributions to the firm’s objectives should be considered.

Manufacturing Policies and Manufacturing Performance

Do manufacturing policies have a significant effect on manufacturing performance? To answer this question we have to determine whether the policies have a significant effect on any or all of the manufacturing performance measures described in Ta- ble VI. As in the preceding section, we used MANOVA with type 111 sum of squares and a 10% level of confidence to determine whether the adoption of a specific policy significantly influences manufacturing performance (SAS process GLM with option MANOVA).l0 We found that for many of the manufacturing policies there is no statistically significant correlation between the adoption of the policy and manufacturing performance. Some firms did well and others did poorly, regard- less of whether or not they adopted a specific manufacturing policy. The policies that have no statistically significant effect on manufacturing performance are listed in Table IX. The policies

Table IX. Manuiactnring Policies with No Effect on Manufacturing Performance.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flexible manufacturing systems Receiving JIT deliveries Vendor involvement with product design Informing vendor of quality level Subcontracting Benchmarking

Quality Productivity Profitability Distribution strategy

Offering a broad product line

that have a statistically significant positive effect on manufacturing performance are listed in Table X, and the policies that have a statistically significant negative effect on manufacturing performance are listed in Table XI. Some policies show up in both Tables X and XI because they have a positive effect on some measures of performance and a negative effect on others. We found no policies that have a widespread general effect, either positive o r negative, on manufacturing performance.

There are three explanations for the lack of statistically significant correlation between manufacturing policies and performance. The first explanation is that in some cases poor performance drives policy adoption. For example, benchmarking has a nonexistent or negative effect on performance in nearly every case. It seems more likely that poor performance causes firms to adopt benchmarking rather than benchmarking, a relatively nondisruptive and benign policy, causing the poor performance. This may be the case with other policies as well.

The second explanation is that some firms may be incorrectly implementing their manufacturing policies. To have a positive effect on performance, the correct policy must be implemented and it must be implemented correctly. For example, if a firm adopts a JIT manufacturing policy but fails to reduce setup times or coordinate with suppliers, then the effect on manufacturing performance may be negative. A negative or nonexistent effect may be due to the incorrect implementation of a policy that should have a positive effect when correctly implemented.

The third explanation is that the expectations associated with adopting these policies are exagger- ated. For example, total quality management (TQM) is often touted as a manufacturing “philos- ophy” that will lead to improvements across a broad spectrum of performance measures. Our results indicate that none of the policies we examined will solve all of manufacturing’s problems, but some policies can make a specific contribution to manufacturing performance. This result high- lights the importance of critically evaluating potential manufacturing policies in terms of manufacturing objectives.

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Table X. Manufacturing Policies with Positive Nffect on Manufacturing Performance. I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I Manufacturing Policy Performance Effect I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Automation Robotics Make JIT Deliveries Inform Vendors of Demand Forecasts Vendor Concentration Benchmark Procurement Policy Rapid Product Introduction

Increase machine utilization Increase labor utilization Decrease throughput time Increase labor utilization Increase value-added per employee Decrease overhead Decrease throughput time

The lack of a clear relationship between manufacturing policies and overall firm performance motivated us to identify the common characteristics of the best performing firms. In the next section we identify the common characteristics of high performance food manufacturers.

High Performance Food Manufacturers

The financial performance of any firm is dependent upon many manufacturing-related and many nonmanufacturing-related factors. For example, financial performance in the food industry is a function of regional and international economic factors. Without collecting and including these factors in our analysis, an accurate assessment of the relative contribution of manufacturing to financial

performance is difficult to make. We can, however, identify the best performers in our sample by separating them from the remaining firms in order to see whether they have any characteristics in common. Although we cannot conclude that these common elements are fully responsible for the superior financial performance, we may be able to identify the characteristics that do not have any effect on performance.

We define the high performance firms as those that have a growth rate in sales that is above the median growth rate for all firms (10% per year) and a profit as a percent of sales that is also above the median profit rate for all firms in the sample (also 10% per year). Only about 23% of the firms can be classified as high performance under this rigorous definition. In Table XI1 we present a side by side compari-

Table XI. Manufacturing Policies with Negative Effect on Mannfacturing Performance. I 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I Manufacturing Policy Performance EIPect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Group Technology CAM MRP Vendor certification program Inform vendor of production schedule Overtime for extra capacity Benchmark manufacturing process Benchmark procurement CAD

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Increase throughput time and lead time Increase throughput time Decrease inventory turnovers Increase lead time Decrease machine and labor utilization Increase lead time Decrease labor utilization Increase investment in inventory and increase throughput time Decrease inventory turnovers

Rapid product introduction Decrease value-added per employee


Table XII. Comparison of High Performance Firms with Remaining Firms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

High Performance Firms Other Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sales Per Year ($ Mil1ion)a 6.3 21.8 Market Share (%) 30.0 27.9 Pretax Profit as % of Salesa 29.6 13.0 Growth Rate in Sales, Per Yeara 32.3 13.0 R&D Expense as Yo of Sales 7.6 3.2 Number of

Productsh 61.5 157.5 Plants') 1.4 1.9 Vendors 55.5 78.9 New products in last 5 years 30.5 25.6

Indirect Labor EmployeesJ 16.7 56.1 Manufacturing Costs as Yo of Sales 49.1 52.1 Overhead as Yo of Manufacturing Costs 15.8 17.0 Value-Added/Employee/Year ($ 000) 65.7 36.8 Investment in Inventory as Yo of All Assets 30.1 28.6

Direct Labor Employeesa 29.3 111.2

Finished Goods Inventory Turns Per Year 40.3 57.5 Machine Utilization (Yo) 56.3 59.5 Labor Utilization (Yo) 76.4 77.6 Throughput Time (Days) 11.9 24.1 Manufacturing Lead Time (Days)<. 8.4 18.8

"Significantly different at 1%. ')Significantly different at 10%. "Significantly different at 5%.

son of the high performance firms with the remaining firms. We used a simple t test (SAS procedure TTEST)IO to determine whether the performance of the high performance firms is significantly different than the performance of the re-

maining firms. We found a statistically significant difference in the sales, number of products, number of plants, number of employees, and, of course, in profit and growth rate. We found no significant differences in customer groups served

Table XIII. Emphasis on Manufacturing Objectives at High Performance Firms. .............................................................................................................

Percent Emphasizing in Manufactnring Strategy Mannhcturing Objectives High Performance Firms Other Firms

High Product Quality 94.9 94.7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Reliable Delivery a 79.5 90.2 Fast Delivery 46.2 57.1 Custom Ordering 35.9 39.1 Low Price 69.2 74.4 Innovative Design 38.5 28.6

'Significantly different at 10%.


Table XIV. Importance of Customer Requirements at High Performance Firms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent Ranking Important to Customers

Fustomer Requirement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . High Product Quality Reliable Delivery Fast Delivery Custom Ordering Low Price Innovative Designa

High Performance Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3 76.9 61.5 61.5 28.2 23.1

Other Firms . . . . . . . . . . . .

85.7 82.7 73.7 55.6 37.6 12.0

'Significantly different at 10%.

by the high performance firms nor in the subindustry represented by the firms. As shown in Ta- bles XI11 and XIV, we found only minor differences between the groups in terms of strategic objectives and customer requirements. We also found few differences between the adoption of different manufacturing policies by the two groups. Only the use of automation, informing vendors of quality level, and the use of CAD were different between the two groups (Table XV). The high performance firms use less automation, do not inform vendors of quality levels, but are more likely to use CAD when compared to the remaining firms. Because product innovation is important to the customers of the high performance firms, the in- creased use of CAD seems appropriate.

the high performance firms and the remaining firms cannot be attributed to differences in the manufacturing policies they have adopted, the subindustry in which they are competing, the customer groups they are serving, the requirements of their customers, or their emphasis on a particular manufacturing objective. This result suggests that financial success is not dependent upon the requirements of the market being served or upon the objectives emphasized by the manufacturing division. Firms have the same potential for success whether they are selling canned vegetables to food service companies or dairy products directly to consumers. The common characteristics of the high performance firms appear to be related to

The difference in financial performance between

size and focus. The high performance firms have significantly less sales, fewer products, fewer plants, and fewer employees and they deliver significantly faster than the competition. The best performers can adapt faster and better to changes in the market and in customer requirements.

Conclusions

The results of our analysis led us to several conclusions regarding competitiveness in the food industry.

Many Firms in the Food Industry Have Unfocused Manufacturing Strategies

In many of the firms participating in the survey, there are critical inconsistencies hetween customer's needs and strategic objectives. Firms must re- alize that manufacturing can only make a significant contribution to customer satisfaction if customer requirements are understood by and communicated to manufacturing. In some cases, manufacturing must be willing to trade performance in traditional dimensions, like cost, for performance along dimensions more closely related to customer needs, like customization and delivery reliability. The firms participating in our survey underemphasize delivery speed and customization capabilities and overemphasize cost control.

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Table XV. Adoption of Manufacturing Policies and Procedures by High Performance Firms. I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percent Adopting

Manufacturing Policy High Performance Firms Other Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Process Design Policies

Flexible manufacturing systems Group technology Automation Robotics


Vendor Relations Policies Number of vendors Vendor certification program Vendors involved with product design Vendors informed of production schedule Vendors informed of demand forecasts Vendors informed of quality level

Subcontracting used for extra capacity Overtime used for extra capacity

Benchmarking Quality Productivity Profitability Manufacturing process Procurement policy Distribution strategy

Number of new product introductions in last 5 years Number of products CAD

Capacity Management Policies

Product Development Policies

...........................

43.6 20.5 23.1 0.0

18.0 51.3 51.3 28.2

568 38.5 38.5 41.0 46.2 56.4

23.1 69.2

74.4 48.7 53.9 46.2 30.8 29.0

318 628 33.3

. . . . . . . . .

51.9 15.0 40.6

4.5

21.8 40.6 57.1 27.1

798 38.4 35.3 48.9 54.9 72.2

17.3 72.9

69.2 51.1 57.1 52.6 26.3 36.8

268 15S8

11.3

aThese are absolute numbers, not percentages.

Manufacturing Objective Influences Adoption of Manufacturing Policies

ing the appropriate objective, or that they are adopting policies that enhance their manufacturing performance.

The participating firms adopt or avoid large sets of manufacturing policies based on their manufacturing objectives. The high quality objective leads to the avoidance of several cost control policies, and the low cost objective leads to the adoption of several efficiency enhancing policies. It is not clear, however, that f m s in the food industry are adopt-

Most Manufacturing Policies and Procedures Have Little or N o Eflect on Overall

Competitiveness

When manufacturing policies have any effect, it tends to be a specific effect on one or two perfor-

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Starbird and Agrawal

mance measures rather than a general effect on all performance measures. Only five out of the 25 manufacturing policies that we examined have an unambiguously positive effect on at least one measure of manufacturing performance (two policies have both a positive and negative effect). Ten policies have a negative effect on a single measure of performance, and 10 have no effect at all. This result may be due to firms adopting the wrong methods or implementing the methods incorrectly. Either way, this result calls into question the value of some of the more popular new manufacturing policies, procedures, methods, and philosophies. In spite of the wide-ranging promises associated with many manufacturing policies, the evidence suggests that no manufacturing method can solve all of manufacturing’s problems.

The Best Performing Firms are Smaller and More Focused

The best performing firms are smaller, and have lower annual sales, fewer employees, fewer plants, and fewer products. Better financial performance is not significantly influenced by subindustry, customer groups, or the adoption of manufacturing policies. One explanation for this result is that smaller firms, perhaps niche players, can respond quickly to the changing needs of customers and outperform the rest of the industry. An important implication of this result is that every firm, re- gardless of product or market, has the potential to achieve superior financial performance.

Implications

The preceding conclusions have several implications for the management of food manufacturing firms.

Manufacturing Needs to Focus EfSorts on Contributing to Customer Satisfaction

Managers need to understand what their customers want and how manufacturing can contribute to customer satisfaction. Firms that make this con- nection will be more competitive.

Manufacturing Policies must be Carefully Evaluated

Manufacturing managers must carefully evaluate manufacturing policies before adopting them, and they must rigorously question any promise of dra- matic sweeping improvements in performance. The evidence suggests that a new manufacturing policy is as likely to have a negative effect as it is a positive effect on manufacturing performance. Manag- ers must assure themselves that the policy they are considering has a positive effect on the performance measure that is important to them.

Manufacturing Strategy Must Evolve as Marketplace Evolves

The marketplace is evolving continuously. What the customer needed 5 years ago is probably not what the customer needs today. Manufacturing must not only track these changes in customer needs, but they must also work with marketing to predict the needs of the future.

Long-Term Manufacturing Goals Must Reflect Long-Term Market Trends

It takes much longer for the manufacturing division to change its capabilities than for the firm’s customers to change their requirements. If the firm wishes to remain competitive it must predict and act on shifts in the basis for customer satisfaction long before these changes are realized.

The objective of this project was to enhance overall food industry competitiveness by identifying the effect of manufacturing policies, procedures, strategies, and goals on firm performance and competitiveness. We used the results of a survey of 228 food processors and manufacturers to derive summary statistics, test these relationships, and draw conclusions. It is our hope that firms will use the results presented here to determine which manufacturing methods lead to improved manufacturing performance and which do not, to compare their performance and practices to other firms competing in the same subindustry, and to gauge their position with respect to the most successful competitors in the food industry.

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Documents

Competitive food manufacturing: Evidence from the 1994 competitive manufacturing survey