the impact of activity-based costing on managerial decisions at insteel industries

The Impact of Activity-Based Costing onManagerial Decisions at Insteel

Industries—A Field Study

V.G. Narayanan and Ratna G. SarkarHarvard Business School

Boston, MA 02163

In this field-based study, we interview top- and middle-level managers atInsteel Industries and conduct statistical analysis of firm-level data in orderto shed light on whether activity-based costing (ABC) provides new infor-mation to managers and whether activity-based management (ABM) signifi-cantly influences product and customer-related decisions. We find that afterthe ABC analysis, Insteel undertook a number of process improvements thatresulted in significant cost savings. Additionally, Insteel displayed a higherpropensity to discontinue or increase prices of products and discontinue cus-tomers that were found comparatively unprofitable in the ABC study. Thuswe provide empirical evidence that ABC influences both strategic and oper-ational managerial decisions.

1. Introduction

In this paper, we provide empirical documentation of the effect ofactivity-based costing (ABC) information on product- and customer-related decisions made by managers in a company.

Cooper and Kaplan (1998) argue that when an entity implementsABC, it reaps at least two important benefits. First, its entire operationis scrutinized in great detail and its performance analyzed and bench-marked against best practices. Employees are encouraged to be criticalof the status quo and to suggest improvements. This critical analysis,they argue, can result in process improvements that promote moreefficient use of resources and hence reduce costs. Cooper and Kaplan

A previous version of this paper was titled, “ABC at Insteel Industries.” We wouldlike to thank the Insteel Industries management for generously providing us with theirtime and complete access, and Dave Conrad for the data. We also thank Stan Abraham,Sarah Eriksen, and Gregg Friedman of the Harvard Business School for their researchassistance; and Eric Noreen, Naomi Soderstrom, the seminar participants at the HarvardBusiness School, Pennsylvania State University, and the April 1999 NBER conferenceon Organizational Change and Performance Improvement, Santa Rosa, California, andEd Lazear, the discussant at the conference, for their comments.

© 2002 Massachusetts Institute of Technology.Journal of Economics & Management Strategy, Volume 11, Number 2, Summer 2002, 257–288

258 Journal of Economics & Management Strategy

call this operational activity-based management. Second, ABC informa-tion may enable a firm to change the mix of products produced andcustomers served, allowing it to focus on making profitable productsand serving profitable customers. Cooper and Kaplan call this strategicactivity-based management.

There are a number of teaching cases and other such anecdo-tal evidence of ABC improving managerial decisions. Likewise, thereare many other cases where ABC has no influence on managerialdecisions, presumably because of organizational resistance to change.To our knowledge, there has been no systematic, statistical investiga-tion of whether ABC really influences managerial decisions. An ABCanalysis may fail to have any impact on a firm for two reasons:

1. It may not reveal any new information to the managers, who intu-itively know already what an ABC system formally captures.

2. It is conceivable that outside consultants are hired to do an ABCanalysis, but decisionmakers in the firm do not accept the ABCnumbers, which often differ significantly from traditional cost num-bers. Effective follow-up to the ABC analysis may require man-agerial decisions and actions significantly different from the statusquo, resulting in organizational change and upheaval, to whichmanagers may be resistant.

In this study, we interview top and middle managers at Insteeland conduct statistical analysis of firm-level data in order to shed lighton whether ABC provides new information to managers and whetheractivity-based management (ABM) significantly influences product-and customer-related decisions.

We find that after the ABC analysis, Insteel undertook a num-ber of process improvement actions that resulted in significant costsavings and displayed a higher propensity to:

1. Discontinue products that were found comparatively unprofitablein the ABC study products.

2. Increase price of products that were found comparatively unprof-itable in the ABC study.

3. Discontinue customers that were found comparatively unprofitablein the ABC study.

The changes to the portfolio of customers served were similarto but not as striking as the product-mix and pricing decisions. Thisfinding is consistent with senior managers’ intuition that product-leveldecisions can be made faster than customer-level decisions.

The next section reviews the literature. Section 3 provides thecompany’s background and cost structure and discusses its decision

The Impact of Activity-Based Costing on Managerial Decisions 259

to use ABC analysis. Section 4 describes ABM at Insteel and analyzeswhether the ABC analysis had an impact on their operations and mar-keting decisions. Organizational issues are highlighted in Section 5.

2. Literature Review

Surveys of company practices in the US and abroad show that for atleast several decades overhead costs have been allocated to products.Likewise, surveys of company pricing practices document that compa-nies typically use fully allocated product costs, rather than short-termvariable costs, to set product prices. For example, Govindarajan andAnthony (1983) surveyed pricing practices of Fortune 1000 industrialcompanies and found that 83% of them use full cost, rather than vari-able costs, for their pricing decisions. See Horngren et al. (2000) for asummary of a number of surveys on cost allocation practices in US,Australia, Ireland, Japan, and the UK as well summaries of surveysthat ask managers to rank the importance of full cost relative to vari-able cost in their pricing decisions. The pervasive use of full costs,as opposed to short-term variable costs or marginal costs, in pricingdecisions runs counter to the prescriptions of microeconomics thatfirms should set prices in a way that equates marginal revenues withmarginal costs plus opportunity costs (shadow prices) of constrainedresources.

Many theoretical papers try to explain this paradox and identifyconditions under which using full costs for product pricing willmaximize firm value or at least serve as a good heuristic. Hansen andMagee (1993) show that under specified circumstances, the sunk costof capacity approximates the optimal opportunity cost of capacity.Johnson and Kaplan (1987), Cooper and Kaplan (1987), Zimmerman(1979), and Demski and Feltham (1976) suggest that sunk costs couldbe a crude proxy or surrogate for the externality costs and opportu-nity cost of resources. Balachandran and Srinidhi (1987) use queuingtheory to model uncertainty and show that a fixed charge (over andabove marginal costs) needs to be applied to achieve an optimum useof service centers in the presence of uncertainty in demand. Fixedcharges help relieve congestion of service centers and reduce delaycosts to the firm. Whang (1989) considers information, incentive, andcongestion effects of cost allocations and shows that cost allocation,in contrast to marginal-cost pricing, induces users to reveal theirtrue values and achieves ex post efficiency in allocating purchasedcapacity. Cooper and Kaplan (1987) argue that managers rely on fullcosts, rather than marginal costs, because they view product portfolioand pricing decisions as long-term decisions. Under that viewpoint


all long run costs are variable and constraints are less likely to bebinding, and full costs will serve as a proxy for long-run marginalcosts. Govindarajan and Anthony (1983) reject the notion that man-agers are trying to maximize profits and appeal to Herbert A. Simon’ssatisficing model to explain the use of full costs as opposed to variablecosts in pricing decisions.

Traditionally, all overhead was allocated to products based onvolume drivers such as labor hours, machine hours, or number ofunits produced. Over the last decade, a new way to allocate overheadcosts to products, called activity-based costing, has emerged. Recent sur-veys indicate that 15% to 20% of companies have adopted ABC andan equal number are considering adopting it (see Horngren et al.,2000). The term “activity-based costing” was first used in John DeereComponent Works (see March and Kaplan, 1987).

Under both traditional costing and ABC, overhead costs are as-signed to cost objects such as products and customers in a two-stepprocess. Cost of resources such as rent, utilities, depreciation, andindirect labor are first assigned to cost pools using resource drivers.For example, rent is assigned using floor space, while depreciationis assigned using book value of assets. Under traditional costing,cost pools were often departments (e.g., machining, assembly, andfinishing), whereas under ABC, cost pools include not only depart-ments but also activities such as inspecting incoming materials, mov-ing materials, and performing setups. Costs are allocated from costpools to cost objects using cost drivers. Under traditional costing,cost drivers were typically volume drivers such as machine hoursand labor hours. Under ABC they include not only volume drivers,but also activity drivers such as number of inspections, moves, andsetups. ABC recognizes that it is cheaper to produce products in largerbatches than smaller batches. For example, under ABC setup costsare assigned to a batch whenever a setup is performed, independentof the batch size. Likewise, product design and engineering costs areincurred independent of the number of batches and units of a productproduced. Thus under ABC, managers must track separately expensesthat are required to produce individual units, to process batches, todesign or maintain a product, and to keep a manufacturing facility upand running. See Figure 1 for a graphical representation of an ABCsystem.

Robin Cooper and Robert Kaplan have written several cases andarticles about the design, implementation, and benefits of ABC sys-tems (see Cooper and Kaplan, 1988, 1991). The theory of a hierarchy ofcosts—unit-, batch-, product-, and facility-level costs—was proposedin Cooper (1990).


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The theory of ABC (that overhead costs were related to non-volume drivers, such as batch- and product-level drivers) was firstempirically tested by Foster and Gupta (1990). They analyzed cross-sectional data from 37 facilities of an electronics company and did notfind evidence that overhead costs were related to nonvolume drivers.Since then, however, a number of papers have found evidence of over-head costs being positively correlated with nonvolume drivers (seeAnderson, 1995; Datar et al., 1993; Banker and Johnston, 1993; andBanker et al., 1995).

Another stream of literature addresses the question, “Do ABCimplementations succeed in providing better information to man-agers and improving decisions?” Shields (1995), Roberts and Silvester(1996), Anderson et al. (1997), Anderson and Young (1997), and Fosterand Swenson (1997) have used surveys of companies implementingABC to understand what factors explain the success or failure of ABCimplementation efforts. These studies have identified the level ofteam commitment, management support, and quality of other infor-mation systems as some of the factors that affect the success of ABCefforts. Our interviews and surveys of company management supportthe findings of these studies and suggest that other factors such asmarket forces and compensation structures also play a significantrole in the ability and willingness of an organization to implementABM. These issues present themselves as leads for future work in theempirical investigation of ABC implementations.

In this paper, we complement the earlier surveys on ABC imple-mentations by focusing on decisions made within one company afteran ABC study. Using statistical analysis and interviews, we documentwhether the ABC system affects product- and customer-related deci-sions at that company.

3. Research Site: Company Background andProduction Economics1

Since the 1950s, Insteel has operated as a manufacturer of pre-cast concrete products for the construction industry. The companyentered the wire business in the early seventies, when it beganmanufacturing welded wire mesh in response to a shortage of thisconcrete-reinforcing product. Over the years, it has broadened itsproduct offering and extended its manufacturing capabilities beyondthe mesh business, expanding into a range of higher-value-addedproducts. Currently Insteel Wire Products (IWP), a subsidiary of

1� This section of the paper is drawn from Narayanan and Sarkar (1998).


Insteel Industries, Inc., manufactures and markets concrete reinforc-ing products, industrial wire, bulk nails, collated fasteners, PC strand,and tire bead wire. The company’s primary markets are the construc-tion, home furnishings, appliance, and tire manufacturing industries.Headquartered in Mt. Airy, North Carolina, the company currentlyoperates eight manufacturing facilities serving markets nationwide.Annual sales revenues are about $300 million.

This paper studies the managerial and organizational issuesrelated to ABC at the Andrews, South Carolina, plant of InsteelIndustries. Four product lines are produced at the Andrews plant:steel wire of different gauges (called “bright wire” or “industrialwire” in the trade), galvanized wire of different gauges, wire mesh,and nails. In 1996, about 477 individual products were spread acrossthese four product lines. However, 20% of the products accounted for85% of Andrews’s annual revenues of about $60 million. Likewise,20% of Andrews’s customers accounted for 95% of all sales.

The steel and galvanized-wire product lines are produced toorder; the other two product lines, nails and mesh products, are pro-duced to stock (about 20 days’ inventory). While other Insteel plantsalso produce wire products, all of Insteel’s nail products are manu-factured at the Andrews plant, in Nail Mill A (commodity nails andsinkers, a large-volume, nondifferentiated product line) and Nail MillB (pallet nails, manufactured to tight tolerances on diameter, heading,and threading specifications).

The primary raw material is hot-rolled steel rod, purchased inlarge rolls of about 4000 pounds from both domestic and foreign sup-pliers. Wire drawing, which is the first production stage, is commonto all of Andrews’s products and generally operates at capacity. SeeFigure 2 for a graphical representation of Insteel’s production process.

Prior to 1996, Insteel did not have a sophisticated cost system.The price per ton of steel rod, the basic raw material, was closely

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monitored. This price was used to estimate the material costs of allof Insteel’s products—by multiplying the weight of the product bythe price of steel rod. Although freight was billed as a separate coston each invoice, customers were charged an average freight charge oneach shipment, independent of the actual destination. Price quotationswere based only on the weight of the product and estimated freightcosts.

In 1996, after years of product and customer proliferation, Insteeldecided to implement an ABC system. Insteel’s management recog-nized that the consumption of overhead resources had increasedsubstantially and varied significantly over its product and customerportfolio. Wishing to limit the upheaval caused by a change in thestatus quo, and also to maximize the possibility of enthusiastic adop-tion, Insteel’s management selected the Andrews plant as its first ABCsite. The plant had had a history of good communications betweenplant management and workers and supervisors, it had minimaloperational overlap with other plants, and its manager, Bill Sronce,was an enthusiastic champion of the process. He communicatedthe objective and the process of the ABC study to all employees ofthe plant. Dave Conrad, the director of cost management, was alsoassigned full-time to the project. He worked in close coordinationwith the consultants to implement the technology, analyze the data,and train Insteel’s staff in the ABC methodology.

At Insteel, the ABC team took their first ABC snapshot of oper-ations at the Andrews plant in the summer of 1996 with the assis-tance of a big-six accounting firm. The ABC team analyzed Andrews’soperations and identified 12 business processes. Within each businessprocess, a number of activities were identified—a total of 146 activi-ties. Next, 426 employees were surveyed to estimate how they allo-cated their time to different activities. All overhead resources werethen collected in 80 cost pools and assigned to cost objects such asproducts and customers (some cost pools included multiple activities).This assignment was done by selecting cost drivers that link the per-formance of activities to demands made by individual products. Forexample, the cost of the material-handling activity was assigned toproducts based on the number of moves for that product, on theground that it is the number of times raw materials and work-in-process is moved that causes material handling resources to be con-sumed, rather than the weight of materials moved. See Table I forexamples of unit-, batch-, product-, and customer-level activities andthe cost driver associated with each activity.

This cost allocation exercise resulted in Insteel’s first ABC analy-sis and its first ABC database (essentially a set of linked Excel spread-sheets and Access databases), maintained by the ABC team. Cost of


TABLE I.Cost Hierarchy, Activities, and Cost Drivers at

Andrews and Mt. Airy, 1996

Cost Hierarchy Cost (MM) Activities/Cost Pools Cost Driver

Unit cost 15�5 Cleaning house Tons cleanedProduction Pounds produced

Batch 1�4 Material handling Number of movesChangeovers Number of changeovers

Product 0�2 Pricing & advertising Number of products

Customer 8�9 Invoicing Number of invoicesSelling products Sales calls

goods sold was tabulated by products and customers and brokendown into six major cost categories as described below. A secondABC snapshot was developed in the summer of 1997, by which timeInsteel had its own staff group collecting the data.

Insteel classified cost data into the following broad cost cate-gories:

• Material costs: Cost of steel rods and other materials used in produc-tion. These costs were assigned to products and customers based onpounds produced and sold, respectively.

• Conversion costs: Overhead resources consumed in converting steelrod to finished wire or nail products. This category includesunit-level costs (such as plant labor), batch-level costs (such aswire-drawing setup resources), plant-level costs (such as plantmanager’s salary), and product-level costs (such as the costs ofspecial wire-drawing dies for particular products). Each componentof conversion costs was allocated to products using an appropriatecost driver.

• Customer costs: Overhead resources consumed in serving specialcustomer needs such as the packing and loading costs, order-processing and invoicing costs, cost of postsales services, andcarrying cost of receivables. Customer costs were traced to eachcustomer and allocated to products based on quantity of eachproduct purchased by that customer.

• Capital costs: Cost of capital related to product- and customer-specific assets. Assets were first allocated to products and cus-tomers. A weighted average cost-of-capital charge was then appliedto these assets and then charged to the corresponding product orcustomer. For example, accounts receivable were identified with


individual customers. A cost-of-capital charge was then applied,based on the days of sales outstanding for that customer.

• Freight costs: The actual freight charge incurred by Insteel to makeeach delivery. This freight cost is in contrast to the average freightcost number that had been used in the actual pricing and billing.

• Corporate overhead costs: Overhead resources incurred at the corpo-rate office level (managerial salaries, information systems, financialservices, etc.). These costs are allocated down to the Andrews plantaccording to its share of total company assets, or its share of totalcompany revenues. Allocation to products is based on quantity ofproduct manufactured, and to customers is based on percentage ofsales revenue.

4. Activity-Based Management at Insteel

Insteel managers indicated that the new ABC system influencedoperations and also product portfolio, product pricing, and cus-tomer portfolio decisions. The effect of ABC on operations (processimprovements) appears to be its first benefit. Process improvementinitiatives are unique and small in number and cannot be analyzedstatistically. We rely on anecdotal evidence, interviews, and reviewof internal reports to document process improvements in the sub-section below. Product- and customer-related decisions, on the otherhand, are a few hundred in number, and we examine empirically therelationship between price/mix decisions and the ABC in Section 4.2.

4.1 Operational ABM: Process Improvements

Internal reports at Insteel prepared in 1996 and 1997 documentthe use of ABC information for process improvements. The firstABC study, in 1996, reveals that the 20 most expensive activitiesaccounted for 87% of Andrew’s total physical and people resourcecost of $21.4 million. Within the top 20 activities, almost $5 millionpertained to quality-related activities such as reactive maintenance,management of by-products and scrap, and preventive maintenance.Analysis of the top 20 activities also revealed that material-handlingcosts, including freight costs, consumed $4.6 million. Activities werefurther classified into value-added and non-value-added or resource-draining activities. Nearly $4.9 million was spent on resource-drainingactivities such as reactive maintenance, management of by-productsand scrap, moving materials and resources, processing returns andclaims, reworking products, managing customer complaints, andhandling warranties, claims, and returns. These activities, within the


20 most expensive activities, were targeted for cost reduction andprocess improvement.

The 1996 ABC reports also list improvement opportunities andidentify teams of senior and middle managers responsible for eachbroad opportunity. For example, separate teams were formed for man-aging quality costs, material handling, and preventive maintenance.

As a part of the 1997 study, Insteel followed up on the processimprovement opportunities identified in the 1996 study. The companyestimates that within a year of the first ABC study, $1.8 million hadbeen saved in quality costs, mainly through a reduction of scrap andreactive maintenance costs. Freight costs were reduced $555,000 in ayear in the Andrews plant alone. Resource-draining activities werereduced from 22% of activity costs to 17%.

Insteel focused on freight because delivering products to cus-tomers showed up as the most expensive activity following the1996 ABC study. It represented 16% of the total people and physicalresources cost at the Andrews plant. We believe that prior to the ABCstudy this cost would not have been apparent, because it would havebeen billed to the customer. As a part of the ABC study, Insteel startedtracking freight cost per pound shipped. This directed attention toways in which these costs could be reduced. In 1997, by changingthe layout of boxes within each truck, the Andrews plant was able toship 7400 pounds more per truckload than in 1996. This representeda 20% reduction in freight expense, from about $31/ton to about$25/ton. Subsequently, all of Insteel’s other manufacturing facilitiesalso converted to heavier loads, emulating the results achieved atAndrews. The resulting savings were significant in comparison withInsteel’s after-tax income of $4.2 million in 1996.

Customers were billed for freight in 1996 based on an averagerate agreed upon for each customer. For example a customer maywant goods shipped to three different locations during the next year.Let’s say the three locations are at distances of 100, 200, and 300 miles,and the customer says that it plans to ship 50%, 30%, and 20% of thevolume to the three locations, respectively. Then the average freightwill be based on 170 miles (�5×100+�3×200+�2×300). However, somecustomer who agreed to an average shipment of 170 miles would endup shipping more goods to the 200- and 300-mile locations but getbilled for a 170-mile shipment. While this was a genuine estimationerror with some customers, others might have intentionally misstated(biased downward) the expected shipping distances when the averagerate was agreed upon, hoping that Insteel would never follow upto check whether the promised average shipping distances were infact close to the actual ones. The customer profitability reports, which


matched the billed freight charge with the actual freight cost, revealedthis pattern of discrepancy.

When Insteel realized after the 1996 ABC study how much theywere actually incurring in quality costs, they put in place a teamresponsible for probing deeper and understanding better what wascausing the quality costs to be incurred in the first place and for sug-gesting steps to reduce them. Insteel realized that certain foreign sup-pliers of rods were lower in price but supplied poorer-quality rodsthat caused breakdowns in Insteel’s manufacturing process. The lowerprice of those suppliers did not compensate for the quality costs.Insteel switched to higher-quality rod suppliers. Insteel also realizedthat smaller-diameter wire products are more likely to break and dis-rupt the manufacturing process. Insteel migrated its product mix tomore large-diameter wire products. Such initiatives led to reductionin quality costs from $6.7 million in 1996 to $4.9 million in 1997.

It is hard to estimate how much of these savings would havebeen realized had Insteel not conducted an ABC analysis. From inter-views with Insteel managers and sitting in on senior managementmeetings, it appears that the activity analysis gave them an appreci-ation of the scope and quantified the magnitude of the improvementpotential, thereby allowing them to prioritize among various processimprovement possibilities. In the opinion of the senior management,the ABC system also helped them keep track of the savings and ensurethat the promised payback was actually realized.

The plant manager reported that no other initiatives, such astotal quality management (TQM) and just-in-time (JIT), were beingintroduced or practiced in the plant simultaneously with the adop-tion of ABC. Applying our past experience with at least ten ABCimplementations and our visits to more than a dozen JIT/TQM plants,we observed certain factors at Andrews that lead us to believe thatthe process improvements were indeed the result of the ABC study.Under JIT or TQM, process improvements are undertaken by trained,motivated, and empowered employees. Data about the manufacturingprocess is collected, displayed, and shared with and by the workers,either through charts and diagrams or via computers on the plantfloor. Workers are cross-trained and wage contracts are redesignedto encourage teamwork and creative problem solving while workingwith reduced buffer inventories, smaller lot sizes, and tightly coupledworkstations. Continuous process improvement is then a byproduct ofworker-level initiatives.

In contrast, in an ABC study, potential process improvementsemerge from the cost data analysis when certain activities show upas being disproportionately expensive. Teams of managers usually


prioritize these improvement opportunities according to cost andthe available skill set and then coopt the workers in implementingthe most important changes. This was the nature of the operationalchanges we observed at Insteel. For example, plant floor workers,most of whom have only a high-school education and on-the-jobtraining on specific machines, were asked to improve monitoring ofthe feed wire and the frequency of machine maintenance to reducedowntime, and this resulted in lower scrap and reactive maintenancecosts. There was also some reduction in finished-goods inventorylevels motivated by the imputed carrying cost, but it was not accom-panied by reduced lot sizes or reduction in work-in-process inventoryon the plant floor, which typically occurs in a JIT implementation.Hence, we are inclined to believe that the process improvementsreported in this paper were largely driven by the findings of the firstABC study, which highlighted for the managers the inefficient use ofcertain overhead resources at Andrews.

ABC-induced process improvements raise two questions:

1. Of all the cost reduction opportunities, why were quality andfreight costs chosen for cost reduction?

2. Couldn’t these costs have been reduced without an ABC study?

It’s hard to answer these questions definitively, but we find a stronganalogy to these questions in Rosenberg (1976)� Rosenberg seeks tounderstand why some cost-reduction technologies are undertaken andnot others, and why the cost-reduction technologies introduced tendto reduce capital rather than labor. Rosenberg identifies several fac-tors, such as disruptions caused by war and threat of strikes, andterms these factors focusing devices because they direct the firm’s atten-tion to particular cost-reduction opportunities. Clearly ABC served asa focusing device at Insteel by providing cost data by activity ratherthan by department, directing attention to the top 20 activities, andby labeling some of them as resource-draining activities.

4.2 Strategic ABM: Product- andCustomer-Related Decisions

ABC data is typically used for making product-line decisions suchas discontinuation of unprofitable products, changing prices, andintroduction of new products similar to existing profitable products.In this section, first we conduct simple univariate statistical analysesto test the effect of ABC information on product-line decisions. Wealso conduct a multivariate probit analysis of product-level decisionsand interpret these results in the light of interviews with Insteelmanagers.


4.2.1 Univariate Analyses of Product- andCustomer-Related Decisions.

4.2.1.1 Impact of ABC on Product Portfolio

Hypothesis 1: Products found to be unprofitable in the 1996 ABCanalysis are more likely to have been discontinued in the followingyear than products found to be profitable.

Products may also be discontinued at a particular plant forvarious reasons, such as changes in customer requirements, generalchanges in particular market segments (for example, a downturn inthe home-building industry), changes in availability of raw materials,and shifting of production to other plants. Likewise, ABC numbersmay not influence product portfolio decisions if managers do notbelieve the numbers or if most of the overhead costs are fixed andirrelevant for product portfolio decisions.

We can observe order patterns for various products during theyear before ABC and the year after ABC. We count a product as dis-continued if it was sold in 1996 but not in 1997. We cannot tell forsure why a product was discontinued. It may be that customers whoused to order that product no longer source with the company, orthat those customers did not place an order for that product in yearfollowing the ABC study, but may do so later on. Thus our defini-tion of discontinuation includes products that are merely dormant.The company may take longer than a year’s time to decide whetherto discontinue a product. The company may have raised prices onunprofitable products rather than discontinue them.

First we conduct a simple χ 2 test to examine whether unprof-itable products, as per the 1996 ABC study, are more likely to be dis-continued (defined as zero sales in 1997, the year following the firstABC analysis) than profitable products [see Table II(A), columns Aand B]. To ensure that inferences, if any, are correctly attributable toABC numbers rather than the old gross-margin-based cost-accountingsystem, we repeat the χ 2 tests for product profitability measured bygross margin per pound, where gross margin is defined as sales lessmaterial costs. Since all but one of the products have positive grossmargins, we split the sample into above-the-median and below-the-median gross margin per pound to see if the two samples exhibitdifferences in the proportions of products that are continued and dis-continued [see Table II(A), columns C and D].

We see from columns A and B of Table II(A) that 80% of prod-ucts found profitable in the 1996 ABC study were also sold in 1997(i.e., they were continued products), versus 62% for those that were


TABLE II.Frequency Distribution of Products

Description A B C D

(A) By 1996 Profitability and 1997 Availability for Sale

No. of products sold in 1996 and1997 (“continued products”) 193 (80%) 123 (62%) 161 (73%) 155 (70%)

No. of products sold in 1996 but 48 (20%) 76 (38%) 59 (27%) 65 (30%)discontinued in 1997(“discontinued products”)

Total 241 (100%) 199 (100%) 220 (100%) 220 (100%)

(B) By 1996 Profitability and 1997 Price Changes Relative to 1996

No. of products sold in 1996 and 112 (58%) 52 (42%) 81 (51%) 83 (53%)also in 1997 for which prices weredecreased in 1997 relative to 1996

No. of products sold in 1996 and also 81 (42%) 71 (58%) 77 (49%) 75 (47%)in 1997 for which prices were increasedin 1997 relative to 1996

Total 193 (100%) 123 (100%) 158 (100%) 158 (100%)

(C) By 1996 Profitability and 1997 Price Changes or Availability Relative to 1996

No. of products sold in 1996 and also 112 (46%) 52 (26%) 81 (37%) 83 (38%)in 1997 for which prices were decreasedin 1997 relative to 1996

No. of products sold in 1996 that were 129 (54%) 147 (74%) 139 (63%) 137 (62%)discontinued or for which prices wereincreased in 1997 relative to 1996

Total 241 (100%) 199 (100%) 220 (100%) 220 (100%)

A: number of products found profitable in the 1996 ABC study; B: number of products found unprofitable in the1996 ABC study; C: number of products above or equal to the median 1996 gross margin per pound; D: number ofproducts below the median 1996 gross margin per pound.

unprofitable in 1996 ABC study. The χ 2 test statistic is 17.984 (p =0�001), indicating that the likelihood of continuing a profitable prod-uct, where profitability is measured by the 1996 ABC numbers, is sig-nificantly higher, and lending considerable support to Hypothesis 1.Analysis by product lines, namely nails and wire products, leads tosimilar results.

Columns C and D of Table II(A) indicate that 73% (70%) of prod-ucts with 1996 gross margin per pound above (below) the medianwere continued in 1997. The χ 2 test statistic is 0.404 (p = 0�525),indicating that the likelihood of continuing a more profitable product


is not significantly different from continuing less profitable product,when profitability is measured by gross margin per pound.2

Thus, it appears that product continuation discontinuation deci-sions are more closely associated with ABC profitability numbers thanwith gross margins. Although a higher proportion of unprofitableproducts seem to have been discontinued after the ABC analysis,the company can expect to improve overall profitability only if theresources and capacity freed from not producing these unprofitableproducts are redeployed in selling more of existing products or inoffering new products. Alternatively, these resources can be elimi-nated, thus removing the costs associated with these resources. Thecompany has chosen the former strategy, and just in the 1996–1997period, after its first ABC analysis, it introduced about 40 new nailproducts and over 100 wire products.

In the nail product group it focused largely on high-value-addedspecialized products such as pallet nails, which require precisionmachining and cutting-edge packaging technology. Since nails aremanufactured only at the Andrews facility, the company could movequickly on these findings, and by early 1997 it had installed new man-ufacturing capacity for some of these products [see Narayanan andSarkar (1998) for a description of one of these initiatives]. Decisionsand actions related to wire products are intertwined with capacityand utilization issues at other plants, and are therefore harder tocharacterize.

An interesting question is whether the new products introducedare more likely to be profitable for Insteel than the old products,and whether their degree of profitability is higher. Unfortunately weare unable to follow this issue up. There have been changes in thedatabases used to store and analyze the cost information, and in par-ticular, the product categories and codes have changed in a way thatdoes not permit us to map product codes between 1996–1997 and thepresent.

Another potential explanation for the product discontinuationdecision runs as follows: Products go through a three-step processending in their discontinuation. First they are healthy and profitable.Then volume slows down and they become unprofitable. Finally, theyare discontinued. This three-step process could have been happen-ing at Insteel for several years and could be independent of the ABCstudy. This would be the case if ABC profits were just a proxy for vol-ume declines that were demand-driven rather than an active choice by

2� Results are virtually identical when profitability is measured by gross margin perdollar of sales.


TABLE III.Correlation of Change in Sales Volume with Cost

and Profit Variables

Correlation withChange in Volume Sample

Variable from 1996 to 1997 p-value Size

Cost per pound in 1996 −�067 �237 316Cost per pound in 1997 −�028 �622 316Profit per pound in 1996 −�026 �641 316Profit per pound in 1997 �011 �847 316Change in cost per pound from 1996 to 1997 −�015 �786 316Change in profit per pound from 1996 to 1997 �015 �795 316

managers acting on ABC information. We could test this alternativeexplanation if we could go back and compute the ABC profitability ofproducts in 1995 and examine whether the product continuation deci-sions in 1996 are related to 1995 ABC profits. Unfortunately, Insteel didnot do an ABC study for 1995, so this data is unavailable. Instead, wetry to see if product volume changes are correlated with ABC profits.

ABC profits could be mechanically correlated with volumechanges. For example, if volume declines for a product and overheadcosts of that product are fixed, then the overhead costs would bespread over fewer units and the product would appear less profitable.As the volume kept declining, the product would appear more andmore unprofitable till it was finally discontinued—not because theproduct was actually unprofitable, but because it was not in demand.3

Table III reports correlations between the volume changebetween 1996 and 1997 and product costs and profits in 1996 and1997. We have 316 observations corresponding to products that weresold both in 1996 and in 1997. We find no significant correlationbetween the volume change and product costs or profits in either1996 or 1997. Correlations between percentage change in volume from1996 to 1997 and product costs and profits in 1996 and 1997 weresimilarly insignificant. We spoke to Insteel’s management to help usinterpret these results. It turns out that very few resources at Insteelwere product-specific, and declining volumes in particular productswere made up by increasing volumes in other products. Hence, itdoes appear that product discontinuation decisions were related to

3� Such a mechanical relationship between product profitability and volume can beavoided if firms use capacities rather than actual volume to allocate costs. However,Insteel did not do that and is thus a good candidate to expect such a relationship.


the ABC initiative at Insteel rather than an apparent relationshipbetween volumes and ABC profits.

4.2.1.2 Impact of ABC on Product Pricing. We next analyze whetherInsteel’s pricing decisions were affected by the 1996 ABC study. Prod-ucts found to be unprofitable in the 1996 ABC study are likely to bemore costly to manufacture, on average, than previously thought byInsteel. Likewise, products found to be profitable in the 1996 ABCstudy are likely to be less costly, on average, than previously thoughtby Insteel. Based on this assumption, we formulate the followinghypothesis:

Hypothesis 2: Prices of products found to be unprofitable in the 1996ABC analysis are more likely to have increased in 1997 than prices ofproducts found to be profitable.

Since we cannot observe prices of discontinued products, firstwe limit the test of Hypothesis 2 to continued products—i.e., thosethat were sold in 1996 and in 1997. If certain products were discon-tinued by raising prices, it will bias our tests against finding supportfor Hypothesis 2. We conduct a simple χ 2 test to examine whetherprices of unprofitable products, as per the 1996 ABC study, are morelikely to have decreased in 1997 than prices of profitable products [seeTable II(B), columns A and B].

To ensure that inferences, if any, are correctly attributable toABC numbers rather than the old gross-margin-based cost system, werepeat the χ 2 tests for product profitability measured by gross mar-gin, where gross margin is defined as sales less material costs. Sincealmost all products have positive gross margins, we split the sam-ple into above-the-median and below-the-median gross margin perpound to see if the two samples exhibit differences in the proportionsthat have price increases and decreases [see Table II(B), columns Cand D].

We see from column A of Table II(B) that 58% of products prof-itable as per the 1996 ABC study, and sold in 1997, were sold ata lower price in 1997 than in 1996. However, column B shows that42% of the products unprofitable in 1996 and sold in 1997 were soldat a lower price in 1997 than in 1996. The χ 2 test statistic is 7.469(p = 0�006), indicating that the likelihood of decreasing prices for aprofitable product is significantly higher, and this lends considerablesupport for Hypothesis 2.

We see from columns C and D of Table II(B) that 51% (53%)of products with 1996 gross margin per pound above (below) themedian were sold at a lower price in 1997. The χ 2 test statistic is 0.051


(p = 0�822), indicating that the likelihood of price increase for a prof-itable product is not significantly different from that of an unprofitableproduct, when profitability is measured by gross margin per pound.4

From Table II(A) we know that products found unprofitable inthe 1996 ABC study are more likely to be discontinued than profitableproducts. It is conceivable that Insteel discontinued products by rais-ing their prices to a level that would take them off the market. Forcompleteness, we include in discontinued products those for whichprices were increased in 1997 and run the analysis once again. Theresults are shown in Table II(C). Naturally, relative to Table II(B) onlythe second row of Table II(C) has increased frequencies, and the find-ings are considerably stronger: From columns A and B of Table II(C),74% of ABC-based loss-making products faced price increases or dis-continuance, vs. 54% of profit-making products (χ 2 = 19�3, significantat less than 0.01%). In contrast, the gross-margin-based frequency dis-tributions in columns C and D show almost no difference betweenhigh- and low-gross-margin products (χ 2 = 0�04 with p-value 0.84),further strengthening our findings in support of Hypothesis 2. Thus,it appears that 1997 product pricing decisions are more closely asso-ciated with ABC profitability numbers than the old cost-accountingsystem’s gross-margin-based numbers.

4.2.1.3 Impact of ABC on Customer Portfolio. Next, we analyzecustomer-level data to test whether the evidence broadly shows thatthe sales force acted on these customer-level findings of the ABCanalysis. Defining customers who appear in the 1996 and the 1997data as continuing customers, and 1996 customers that dropped outof Insteel’s 1997 customer list as discontinued customers, we formulatethe following hypothesis on customers:

Hypothesis 3: Customers found to be unprofitable in the ABC studyare more likely to be discontinued in 1997 than customers found tobe profitable.

Within the nail product group, we have 1996 and 1997 infor-mation about the total revenue from a customer, the total productcost, customer cost, and freight cost, and the net profitability of thecustomer. The data we have on wire customers needs additionaldecomposition before it can be used for a test of this hypothesis;hence we restrict attention to customers for nail products. The resultsare summarized in Table IV. Unlike the product-level data used in

4� The results are virtually identical when profitability is measured as gross marginper dollar of sales.


TABLE IV.Frequency Distribution of Nail Customers by

1996 Profitability and 1997 Purchases

No. of Nail Customers in 1996

Description Profitable Unprofitable

No. of customers that purchased from 66 (66%) 20 (53%)Insteel in 1996 and 1997 (continuing customers)

No. of customers that purchased from Insteel in 34 (34%) 18 (47%)1996 but not in 1997 (discontinued customers)

Total 100 (100%) 38 (100%)

Table II, we do not have the materials cost by customer and areunable to estimate gross margin by customer. Hence we are unableto perform gross-margin-based tests for customer continuation-discontinuation decisions. We see in Table IV that 66% of customerswho were profitable in 1996 were continuing customers in 1997, ver-sus 53% for those that were unprofitable in 1996. The χ 2 test statisticof 2.1 is significant only at the 15% level.

Compared to multivariate tests, univariate tests are simpler andprovide more economic intuition. However they are not informative ofmarginal effects. To understand the marginal effect of ABC data aftercontrolling for volume and gross margins, we turn to multivariateprobit analysis.

4.2.2 Multivariate Analyses of Product and Customer-Related Decisions. The results of the univariate analyses aboveindicate that taken separately, ABC profitability explains product mixand pricing decisions more than gross margin does. To some extent, italso seems to affect customer mix decisions. But ABC profits and grossmargins are correlated, and our χ 2 tests, by treating the independentvariables as categorical, ignore much of the variation on the profit andgross-margin levels. Hence, the question arises, “Would these findings[in support of Hypotheses 1, 2, and (weakly) 3] hold if we analyzedthe relationship between the mix/price decisions and the levels ofeach type of profitability, while controlling for the other?” Addition-ally, we would want to control for the volume of business that a prod-uct or customer brings in: if a large-volume product or customer isrevealed to be unprofitable, the company is likely to make a greatereffort to retain these strategic products and customers and to workwith them to convert them to profitability in the long run. Such prod-ucts and customers would also make larger relative contributions to


fixed costs, and this would also cause Insteel to be reluctant to dis-continue the product or fire the customer. Since volume is also relatedto profitability, the hypothesis we wish to test is then

Hypothesis 4: The higher the 1996 ABC profits, the higher the 1996gross margins, and the greater the 1996 share of volume of a product(or customer), the higher will be the 1997 probabilities of continuingto sell a product, of lowering product price, and of continuing to sellto a customer.

To test this hypothesis, we conduct probit regressions of the deci-sion to continue a product or raise prices against 1996 ABC profit perpound (ABC PrPP96), 1996 gross margin per pound (GMPP96), andshare of volume of product sold in 1996 (LBS PCT96). Table V givesunivariate statistics and correlations for these variables: panel (A) isbased on all 440 products that were sold in 1996, panel (B) is basedon 316 continued products (those that were sold in 1996 and 1997),and panel (C) is based on the 138 continued nail customers. As men-tioned in the section on univariate tests, we do not have gross-margininformation for customers. We note that for products GMPP96 is neg-atively correlated with LBS PCT96, indicating that Insteel was sell-ing a larger relative volume of lower-gross-margin products. Not sur-prisingly, GMPP96 is positively correlated with ABC PrPP96. At theproduct and at the customer level, sales volume is not significantlycorrelated with ABC profitability.

Relying on our earlier definition of continued products and cus-tomers, but recognizing that discontinued products may only havebeen rendered dormant by high prices, in one of our tests we combinediscontinued products and those that experienced a price increase.Specifically, we conduct probit analyses of four decisions and reportthe results in Table VI:

• The decision to continue selling a 1996 product in 1997 (probit 1).• The decision to raise 1997 price on a continued product (probit 2).• The decision either to raise 1997 price or to discontinue a product

in 1997 (probit 3).• The decision to continue serving a 1996 nail customer in 1997 (pro-

bit 4).

Probit 1 (which is overall significant at the 0.01% level, asindicated by the likelihood-ratio statistic) indicates that ABC profitsand share of volume are positive and significant determinants ofthe decision to continue selling a product. Gross margin, although


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insignificant, negatively influences the decision to continue sell-ing a product. This finding lends further support to our test ofHypothesis 1 [Table II(A)]. Probit 2 is overall insignificant, and theindividual coefficients are insignificant. Treating price increases andproduct discontinuance as inseparable in the data, probit 3 (whichis overall significant) indicates that the higher the ABC profits, thelower is the propensity to raise price or discontinue a product. Finally,probit 4, which is significant, indicates that share of volume is theonly determinant of the decision to continue to serve a customer.5

The coefficient on ABC profitability, although positive as predicted,is not highly significant (p = �154), and this is completely congruentwith the weak results we obtained for the influence of ABC numbersin the test of Hypothesis 3 (Table IV). The lower sample size for thecustomer-related tests, compared to product related tests, could alsobe responsible for the lower significance levels.

Table VI also provides the marginal effect of each variable on theprobability of affecting activity-based management decisions. Overall,a change within the interquartile range of ABC profits per pound(from $0.26 per pound to $0.39 per pound in the entire sample of 440products) reduces the probability of discontinuance or price increaseby about 3%. The most dramatic marginal effect is that of a customer’sshare of volume: a change within the interquartile range (from 0.06%of total pounds to 0.50% of total pounds) raises the probability ofretaining the customer by almost 42%. This is strong evidence of theimportance of large customers to Insteel’s business.

Overall, our univariate tests provide some evidence of activity-based management, particularly the management of product mix andprices. The multivariate tests provide evidence of ABM and show thateven after controlling for gross margins and volume-related signifi-cance, ABC profitability had an influence on product mix and pricingdecisions, but not (as much) on customer portfolio decisions.

We discussed our findings with Insteel’s plant mangers, salesmanagers, and CFO. There was a general consensus that armed withthe ABC information, discontinuing an unprofitable product or dis-couraging its purchase was one of the early initiatives undertakenwith respect to Andrews’s products. Next, production and sales ofhidden-profit products were ramped up. For example, in Narayananand Sarkar (1998) we document their aggressive move into palletnails. The ABC analysis had also highlighted the high cost of the dies

5� The results of probit 4 are the same whether volume is defined as total poundsof products sold to a customer in 1996, or total dollar sales to that customer. For consis-tency across the four probit analyses, we use product or customer pounds (as a fractionof total pounds sold for all of Andrews).


that wear out in the wire drawing process and, hence, the greater rel-ative profitability of large-diameter wire. The sales force tried to pushthese large-diameter wire products more aggressively after the ABCproduct cost information was made available to them.

When we asked them why they had been unable to act moredecisively with respect to customers, they pointed out that consolida-tions and vertical integration within the industry during the periodof interest limited Insteel’s ability to jettison customers shown tobe unprofitable in the ABC analysis. Specifically, they pointed outthat some of Insteel’s most profitable customers had been bought byInsteel’s competitors, which were integrating forward into the valuechain. The loss of that profitable business in 1997 meant that Andrewswould have excess capacity if it fired more customers. The plant wasbetter off retaining some large unprofitable customers who coveredtheir variable cost and made a positive contribution to fixed cost.

4.3 Impact of ABM on Insteel’sFinancial Performance6

It is hard to isolate the financial impact of ABM on Insteel’s overallperformance, and the evidence that we provide on that impact willbe only suggestive, for the following reasons:

1. While we have provided evidence consistent with Insteel takingseveral product- and customer-related decisions based on ABCinformation, the effect of these decisions on the bottom line maynot be felt for a few years yet. Also, those effects may be con-founded by other changes at Insteel, such as the purchasing anddivesting of businesses.

2. The ABC project was piloted in the Andrews plant at Insteel in 1996and 1997 and was subsequently rolled out to the other plants atInsteel in 1998 and 1999. Our data analysis in the preceding sectionsis confined to the Andrews plant. Financial data for Insteel as awhole in the 1996–1999 period would not reflect the performanceof just the Andrews plant.

3. Several industry-level factors would have affected Insteel’s finan-cial performance.

Given the above limitations, we present financial information thatseems to support Insteel’s senior management’s feeling that ABC hashad a positive financial impact. Average and median gross margins

6. More detailed information on Insteel’s financial performance is available from theauthors upon request.


(sales, less all costs, including materials, conversion, and customer-and facility-level costs, but excluding allocated corporate overheads)of Insteel’s plants improved after the introduction of ABC. For exam-ple, the gross margins at the Andrews plant improved from 8.28% in1995–1996 to 11.26% in 1998–1999.

To control for industry-wide factors we compared the financialperformance of Insteel with that of other firms with four-digitSIC code 3310. Since Insteel introduced ABC into its non-Andrewsplants only in 1998, we can think of the financial performancein 1999 as being post-ABC. We examined return on equity (netincome/owner’s equity), return on assets (operating income beforeinterest expense/total assets), and stock returns. Insteel outperformedindustry median numbers under all three metrics in 1999, whereasit had lagged behind the industry median under all three metrics in1996. For instance, the Insteel’s returns on assets in 1996 and 1999were 2.91% and 5.95%, whereas the industry medians were 5.38% and5.09%, respectively. While by no means conclusive evidence, theseupward trends in gross margins and returns are compatible with themanagement’s perception of ABM having a positive financial impactat Insteel.

5. Organizational Issues7

The adoption of ABC at Insteel developed from a project in one loca-tion in 1996 to a company-wide initiative in 1999. Interviews withthe management indicate that they consider this effort to have beensuccessful in improving the bottom line despite the cost of analysis,implementation, and managerial energy invested in the effort. Judg-ing from our own observations at Insteel and five other companies,readings of case histories of similar projects, and input from Insteelmanagers, we can say that worker involvement, intensive communi-cation, and commitment from the sales force and upper managementwere the key determinants of the perceived success of this project.

5.1 Worker Involvement and Communications

The ABC initiative was seeded in a controlled setting—the Andrewsplant. The plant had a successful history, and plant management wasenthusiastic and supportive. Those managers spent a great deal oftheir time communicating the goals of the project and getting buy-in

7. This section is based upon our visits to Andrews, participation in meetings, tele-phone conversations, and the management interviews (transcripts available fromauthors).


for the intensive interviewing and data-gathering process. Before thefirst interviews, the plant manager addressed two main worker con-cerns: job loss and compensation. He assured the workers that theplant, operating at capacity, would continue to do so and there wasno threat of layoffs. Most of the workers participated in profit sharing,and the plant manager strongly emphasized that the data gatheredfrom them as a part of the ABC study would help Insteel becomemore profitable and this, in turn, would increase each worker’s take-home pay.

The ABC interview team consisted of the plant industrial engi-neer, the area supervisor, one consultant, and the accountant in chargeof the ABC project. The plant manager was also actively involved inthe early interview rounds. The aims of the project were reinforcedat each interview, and workers were encouraged to suggest changesto the activity dictionary and the drivers used in the ABC study.Although the interview team had sufficient data by the time half theworkers had been interviewed, during that first round they pressedon and interviewed each and every worker on company time. Thiswas done to ensure that everyone felt included and had a chance todiscuss their concerns.

We attended one of the plant-floor meetings where the results ofthe first ABC analysis and its implications were shared with a smallgroup of about 15 workers. The mood was upbeat, and the work-ers asked a number of questions. Product and customer profitabilityresults were shared with the workers. They were shown that “small”(small-diameter) wire was unprofitable and specialty nails were veryprofitable. Since they generally preferred to work with “heavy” (large-diameter) wire, which suffered fewer breaks during production, thewire-products outcome was welcome news.

Similarly, since the Andrews plant is the sole producer of nailsfor Insteel, they understood that nail production would not be dis-placed, but the mix would change slightly in favor of specialty nails.Specialty nails require more stringent quality standards, but betterfeed wire is used as input, and this results in fewer line problems.There were also a subset of workers keen to work on the more sophis-ticated product line, on modern, automated machines, and this wasan opportunity for them to upgrade their skills.

5.2 Reaction of Managers

Sometimes different managers reacted differently to the same ABCdata. When the study revealed that mesh products were unprofitable,the plant manager was keen to shut down the mesh machine in the


plant. But the senior management felt that mesh production was inthe long-term interests of Insteel. The company had its beginnings inthe agricultural and construction mesh business, and upper manage-ment was reluctant to drop mesh. The mesh-products sales manager,who had been a long-time employee, made significant efforts and suc-cessfully improved the profitability of mesh products within one year.She organized more efficient loading of trucks with rolls of mesh andrenegotiated prices with key customers.8

We observed the greatest enthusiasm for ABM among Insteelmiddle managers, who acted quickly in gathering up the low-hangingfruit of the first ABC analysis, i.e., identifying and implementing pro-cess improvements with a quantifiable payback. Quick wins wereshared and celebrated with all associates (a term that includes plant-floor workers). This helped generate and maintain momentum forthe project when changes related to product mix inevitably causedupheaval in the plant. John Calcagni, the sales manager for industrialwire products pointed out that the ABC approach was the first toolthat allowed them to model the effects of labor, product mix, and cus-tomer demands—i.e., factors other than volume—on profitability andfinancial performance, and it could also be used to guide and justifyproduct and customer-mix changes made by the sales force.

5.3 Sales-Force Reaction

In volume-based businesses, it is usually difficult to motivate a salesforce to stop pushing certain products, and is even harder to get themto “fire” unprofitable customers. Our analyses suggests that the Insteelsales force was quite effective in discontinuing unprofitable products,albeit less so with unprofitable customers. Although compensationwas not highlighted in our discussions with Insteel managers, it issignificant that Insteel’s sales-force compensation is composed mainlyof straight salary. This means that they are usually willing to givea new sales strategy a try even at the risk of losing some volume.While the motivational effects of such a wage scheme are debatable,we observed a high level of conviction and enthusiasm for the marketactions suggested by the ABC analyses among the sales managers.

Many of the unprofitable products were the only ones purchasedby unprofitable customers. In such cases, the salespeople intuitivelyrecognized that those customers had been opportunistically buyingthose products from volume-driven Insteel, and that other US com-petitors had stayed away from those product-customer combinations.

8� Mesh products, which are only four in number, are not included in our productor customer portfolio analyses.


For many of these products, prices were raised drastically, and thecustomers were thus encouraged to leave. Some products were notoffered at all in 1997, and customers were encouraged to substituteother Insteel products.9 One of Insteel’s largest customers, “walked”in the face of raised prices and discontinued purchases after the 1996study, but recently, having tried other sources, has become an Insteelcustomer again. This, the sales force feels, is vindication for their newABC-based strategy.

5.4 Resources and Commitment fromUpper Management

Finally, the ABC initiative was given a high level of visibility withinInsteel’s upper management. This translated, in part, to adequatelevels of financial support, computing resources, and managerialattention during the early project phases (we attended some ofthe monthly ABM meetings where all of the top management wasbriefed). While the use of outside consultants had been discontinuedby 1998, more staff and IT resources were added to the ABC project.All managers (including ex-employees) in production, sales, andfinance consider the ABC project at Insteel a success. At the currenttime, almost four years after the start of the ABC initiative, a fullrollout to all plants has been implemented, supported by a new Ora-cle ERP relational database system.10 Automated data collection andanalysis on a monthly basis provide real-time feedback to managersas they implement new market strategies and pursue operationalimprovements.

The analyses from the new system are now being used to ratio-nalize operational capacity across the plants. Some of the productdecisions made on a local plant level early in the ABC study havebeen revisited, and those most closely involved with the ABC projectfeel that the initiative should have been rolled out earlier to the otherplants.

6. Conclusions

In this study we sought to understand the impact of ABC on man-ager’s product pricing, product portfolio, and customer portfoliodecisions.

9� Note that in our empirical analyses, both of these types of products would becounted as “discontinued” products.

10� This system change has also led to a complete overhaul of their product andcustomer codes and a consolidation of their activity dictionary. This has made new,post-1997 data hard to compare with the data used in this study.


Interviews with managers and our statistical analysis lend sup-port to the hypothesis of changes in managerial decisions at Insteelfollowing the ABC study. The rationalizing of the product portfolioand pricing decisions appears to have been influenced by the ABCstudy. Customers are now billed for freight in a more direct way. Thecompany has made several process changes attributable to the ABCstudy. It has introduced new product lines. However, the rationalizingof the customer portfolio, although initiated by the company, cannotbe statistically detected. These strategy changes will, we suspect, bereflected in the data in the future.

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