4326235(1)

© Academy of Management Journat1982, Vol.25, No. 3, 510-531.

Strategic Attributesand Performance inthe BCG Matrix—A PIMS-Based Analysis ofIndustrial Product Businesses^DONALD C. HAMBRICKIAN C. MacMILLANDIANA L. DAYColumbia University

This paper empirically explores the performance ten-dencies and strategic attributes of businesses in the fourcells of the Boston Consulting Group product portfoliomatrix. Businesses differed in their performance andstrategic attributes, according to the two dimensions ofthe BCG matrix—product life cycle stage (growth rate)and market share.

Most discussions of business-level strategy fall into one of three groups.First are normative propositions about which strategic actions make senseunder different conditions. These prescriptions typically are set forth byseasoned observers of organizations (Andrews, 1971; Glueck, 1976; Katz,1970), but, so far, creation of these ideas has substantially outpaced em-pirical tests of their validity. A second category of literature is empiricallybased, but aimed at demonstrating universal "laws" of strategy. Findingson the pervasive positive effects of market share (Chevalier, 1972; Schoef-fler, Buzzell, & Heany, 1974) and the experience curve (Boston ConsultingGroup, 1968) are primary examples. The third group also is empirical butconcludes that so many contingent factors exist that strategy must be high-ly situational (Hatten, Schendel, & Cooper, 1978). In the latter vein,Hofer (1975) set forth what he considered to be a manageable list of 20contingent factors (narrowed down from 54) that affect strategy for

The authors gratefully acknowledge sponsorship by the Strategy Research Center, Columbia Uni-versity Graduate School of Business, and generous support from the Strategic Planning Institute,Cambridge, Mass. Thomas Lenz, William Newman, Max Richards, Sidney Schoeffler, and MichaelTushman made helpful suggestions on earlier drafts.

510

1982 Hambrick, MacMittan, and Day 511

mature businesses. All possible combinations of these (assuming only twovalues per variable) result in over a million possible configurations.

What is needed are empirically based "mid-range" theories about busi-ness-level strategy. As Bourgeois noted, "The solution is for the re-searcher to abstract a smaller number of more encompassing conceptualcategories with a broader range of generalizability" (1980, p. 29). Thispaper pursues that advice by focusing on only two key contingent varia-bles—the product life cycle and market share—and identifying their i'ela-tionships with different strategic attributes and performance. The term"strategic attributes" is preferred to "strategic action" because this essen-tially is a cross-sectional study in which an array of strategic variables, in-cluding those that are controllable only in the longer term (e.g., capital in-tensity, productivity) are examined.

In the literature on business-level strategy, probably no constructs havebeen deemed more significant than market share and the product lifecycle. However, there is little empirical research treating these as contin-gent factors. The choice of these two constructs has the added advantagethat, taken together, they form the framework for a widely known modelfor analyzing corporate strategy—the Boston Consulting Group (BCG)product portfolio matrix (Henderson, 1979). (Purely speaking, the verticaldimension of the BCG matrix is "market growth." For most products,growth rates closely correspond with certain stages of the life cycle. Theconceptual distinction is that each stage typically is attributed with charac-teristics in addition to growth rate, for example, customer adoption ratesand the nature of competition. The emphasis here on life cycle stage is notinconsistent with BCG's strict emphasis on market growth.) If both theproduct life cycle and market share have major significance, and if manyfirms actually conceive of businesses along these two dimensions, then thisstudy has the potential for generating empirically strong and manageriallymeaningful results.

Two broad questions are addressed in this paper:1) How do businesses in the four cells of the BCG matrix tend to differ

in their performance on various key criteria (profitability, risk, cashflow, market share change)?

2) How do businesses in the four cells of the BCG matrix tend to differin their strategic attributes?

A third research question, which follows from the first two, is addressedin a companion paper (MacMillan, Hambrick, & Day, 1982).

3) Which strategic attributes are associated with the various perfor-mance measures in each cell of the matrix?

Theoretical Review

Business-Level Strategy

The distinction between corporate-level strategy (what businesses to bein) and business-level strategy (how to compete in a given business) is

512 Academy of Management Journal September

established (Hofer & Schendel, 1978; Vancil, 1976). This study focuses onbusiness-level strategy, which is of interest to strategic units (typically divi-sions) in multibusiness firms, or to single business firms. Although busi-ness-level strategy centers on the concept of "competing," it is importantto stress that it encompasses all the functional areas of the business. Op-tions in operations, marketing, distribution, R&D, finance, and personnelall determine the business's basis for competing.

Contingency Theories

Contingency models, in which the appropriateness of certain actions aredeemed contingent on particular given conditions, abound in the field oforganizational theory (Ford & Slocum, 1977). Relatively little progress hasbeen made in investigating contingent models of strategy. Hofer (1975)made an eloquent call for such research, and he also provided his own no-tions of what types of relationships might exist. However, since his paperappeared, essentially all empirical investigators of business-level strategyhave had goals other than identifying and testing contingencies (Hatten etal., 1978; Lenz, 1978; Miles & Snow, 1978). A notable exception is Harri-gan's (1981) research on factors affecting the appropriateness of differentstrategies in declining industries.

It is not clear which contingent variables will lead to the strongesttheory. Hofer (1975) lists 10 to 20 variables (depending on life cycle stage)in several categories: market, consumer, industry structure, competition,suppliers, macroenvironmental, and organizational characteristics. Hofersurmised about the importance of each variable within its category but didnot suggest an overall priority. He did propose that "the most fundamen-tal variable in determining an appropriate business strategy is the stage ofthe product life cycle" (1975, p. 798).

Product Life Cycle

The concept of the product life cycle is well established (Fox, 1973;Hofer, 1975; Levitt, 1965; Wasson, 1974). Although scant empirical re-search has been done on the life cycle, theorists have set forth an abun-dance of prescriptions about which strategic behaviors lead to success ateach stage.

For the early stages (introductory and growth), theorists generally layemphasis on strategic actions aimed at gaining a strong competitive foot-hold, such as aggressive pricing, building capacity, heavy marketing ex-penditures, and product R&D. For the later stages (maturity and decline),the emphasis is on extending/expanding the product category and seekingefficiencies via adding channels, broadening the product line, vertically in-tegrating, avoiding price cuts, and so on (Clifford, 1971; Fox, 1973; Hen-derson, 1979; Wasson, 1974). Again, these prescriptions have been basedmore on seasoned observation than on systematic research.

1982 Hambrick, MacMillan, and Day 513

There are common threads, but there also are various prescriptive in-consistencies among life cycle theorists. For example, Wasson (1974) callsfor cost cutting accompanied by price cutting in the maturity stage, where-as Fox (1973) encourages price maintenance. Clifford (1971) claims that"vigorous" advertising and sales efforts are crucial in the growth stage,yet Patton says that "marketing steps to the center of the stage" duringthe maturity stage (1959, p. 12). Not only are there unresolved differencesamong theorists, but there also are confusing stances within giventheorists' prescriptions. For example, Wasson encourages mature busi-nesses to seek new markets, product expansions, product improvements,and cost reductions. This array of suggestions is so encompassing as toleave the strategist with little sense of priorities, or any sense of what mightactually work.

Market Share

Market share was selected as the second contingent factor in this study,on the rationale that market share has been demonstrated empirically tobe a key factor affecting the performance of business units. Although it ispossible for businesses to have (or buy) more market share than is optimal(Fruhan, 1972), the weight of evidence indicates that high share businesseshave significantly higher earnings than do low share businesses (Chevalier,1972; Schoeffler et al., 1974). Hofer (1975) endorses the importance ofmarket share by listing it as dominant among all the organizational attri-butes he would include in contingency models for all except brand newbusinesses.

Very little systematic research has been conducted on different strategiesfor different share positions. Bloom and Kotler (1975), drawing on anec-dotal evidence, counseled high share companies to evaluate the risks (pri-marily regulatory and public pressure) of their dominant positions and toadjust their shares in light of those risks. Conversely, Hamermesh, Ander-son, and Harris (1978) outlined strategies for low share businesses. Basedon anecdotes, they offered these suggestions to underdogs: conduct nar-rowly targeted R&D; limit growth; diversify cautiously; and recruit astrong-willed, hands-on chief executive. These authors' prescriptions havean intuitive allure, yet they are neither precise nor systematically derived.Foremost, there is no indication why they have any more applicability tohigh share (or low share) businesses than to others. A recent, more syste-matic study by Woo and Cooper (1980) identifies discrete clusters of highperforming, low share businesses, and it contrasts them with clusters oflow performing, low share businesses and high performing, high sharebusinesses. Their paper is a step toward more accurate understanding ofissues associated with market share.

Combining the Two Dimensions: The BCG Matrix

The choice of the product life cycle and market share as the two contin-gent variables has an added attraction. When combined, they form the


framework for the BCG's product portfolio matrix (Henderson, 1979).Although the matrix has limitations (Hofer & Schendel, 1978), it is widelycited in academic and popular discussions of strategy. Other more refinedportfolio matrices, such as those used by Arthur D. Little (Patel &Younger, 1978), Royal Dutch Shell (Robinson, Hickens, & Wade, 1978),and General Electric (Taylor, 1976) generally are consistent with the BCGframework, because they all incorporate an "attractiveness" dimension(broader than, but encompassing, life cycle) and a "competitive position"dimension (broader than, but encompassing, market share).

There is not unanimity as to what the dividing points on the two dimen-sions of the matrix should be. BCG favors 10 percent real market growthas the point of distinction between high and low market growth. Thegroup views market share in terms of the ratio of the share held by thebusiness relative to the share held by its leading competitor. A ratio of 1.0,indicating highest market share, is commonly considered the dividing linebetween high and low share. BCG also states that a ratio of 1.5 is neces-sary to claim and exploit true dominance in a market (Hedley, 1977). Inthe absence of systematic data on alternatives, the present study relies onthe 10 percent market growth rate and 1.0 relative market share as thedividing points in the matrix.

Although a great deal has been written about the BCG matrix (and lessso about other portfolio matrices), the emphasis has been on how to allo-cate resources among the four cells and what kinds of performance pat-terns to seek for each. High share/low growth businesses (Cash Cows), forexample, should be managed for maximum generation of cash, and thatcash should be directed to newer, higher growth businesses (Wildcats andStars). Low growth/low share Dogs are seen as serious cash drains thatshould be promptly harvested, liquidated, or divested.

No systematic evidence exists about whether the performance tenden-cies of businesses in the four cells actually allow or warrant these prescrip-tions. No information exists about the strategic tendencies of businesses inthe four cells. The goal of the present paper is to fill these voids in part. Indoing so, it will form the backdrop for a companion paper on the relation-ships between strategic attributes and performance for each of the fourcells.

At this stage, it is not appropriate to set forth all plausible hypotheses.However, two broad propositions may be stated: (1) Businesses in thefour cells will differ systematically in their performance (including in theircash flow tendencies as argued by BCG); (2) Businesses in the four cellswill differ in their strategic attributes. Previous literature which shouldcontribute to more specific hypotheses has been speculative, imprecise,and even contradictory. And the range of strategic variables and perfor-mance measures to be examined make an inventory of hypotheses un-wieldy. Thus, the approach will be to treat this as an exploratory study toenhance understanding of a widely recognized but little-documented, stra-tegic framework.


Method

The PIMS Data Base

The data used in this study were drawn from the Profit Impact of Mar-ket Strategies (PIMS) project, an ongoing study of environmental, strate-gic, and performance variables for individual business units. About 200corporations submit data annually on a total of about 2,000 of their busi-ness units. Each business, often a division, is a distinct product-marketunit. For a technical summary of the PIMS data base, see Schoeffler(1977).

Anderson and Paine (1978) provide a comprehensive critical review ofthe PIMS data base. Most of their concerns are about how the PIMS datahad been statistically analyzed and presented in previous studies. Al-though they raise limited concerns about the quality of the data, they gen-erally acknowledge the data base to be of high quality and reliability. Twofactors that previous critics have not noted especially commend the data.First, PIMS staffers help each business interpret and answer the questions,thus assuring a high degree of data comparability. This feature is missingfrom conventional questionnaire studies. Second, each company pays asubstantial sum to participate in PIMS, and the software is oriented suchthat their ability to derive meaningful conclusions from the data is particu-larly a function of the accuracy of their own data. The businesses wouldappear to have a commitment to thoroughness and accuracy that is miss-ing in most survey studies. No conventional tests of the reliability of thedata base (e.g., test-retest, multiple respondent consistency) are known tohave been conducted.

The data base does have some limitations, including those noted by An-derson and Paine. Foremost, the businesses in the data base cannot beviewed as typical of business units in general. On average, the participat-ing businesses probably are more sophisticated, more dominant withintheir markets, and more effective in general than the total population ofbusiness in the United States.

Categorizing the Businesses

The study reported here is based on the most recent four years of PIMSdata for businesses that manufacture industrial products. Further re-search, in progress, will extend the analysis to the consumer product sec-tor.

The businesses in the sample were classified into the four cells of theBCG matrix according to their life cycle stage (market growth rate) andrelative market share. PIMS respondents indicate the business's life cyclestage by answering this question: "How would you describe the stage ofdevelopment of the types of products or services sold by this business dur-ing the last three years?"


— Introductory stage: Primary demand for product just starting togrow; product/services still unfamiliar to many potential users

— Growth stage: demand growing at 10 percent or more annually in realterms; technology or competitive structure still changing

—Maturity stage: Products or services familiar to vast majority of pro-spective users; technology and competitive structure reasonablystable

— Decline stage: Products viewed as commodities; weaker competitorsbeginning to exist.

Responses to this straightforward categorizing question were used in theanalysis. A more elaborate index for measuring life cycle stages fromPIMS data has been shown to yield strikingly equivalent results (Christen-sen, 1977).

The data base has relatively few businesses in the introductory and de-cline stages, so the study included only those in the growth and maturitystages, a total of 1,028. Even though the label "life cycle" is being used,the classification is fully consistent with BCG's view of this as the "marketgrowth" dimension, because part of the PIMS definitional distinction be-tween a growth business and a mature business is a real growth rate in pri-mary demand of 10 percent.

Relative market share is defined as the ratio of the unit's market sharerelative to the share of its leading competitor (using a four-year average).A relative market share figure of greater than 1.00 is considered high rela-tive market share; 1.00 or below is classified as low relative market share.The average relative share for the entire sample is 1.30 (supporting thespeculation that PIMS businesses are relatively dominant), and the stan-dard deviation is 1.68, indicating that the businesses are not too heavilyclustered around the 1.0 dividing line. The four subsamples are portrayedin Figure 1.

Figure 1The Subsamples of Industrial Products Businesses Studied

Growth

Product RealLife GrowthCycle 10% Year

Mature

StarsN=114

Cash CowsN=315

WildcatsN=181

DogsAf=418

High 1.0 Low

Relative Market Share

Variables

Two types of variables are distinguished in this study—strategic at-tributes and performance. Environmental variables are not included.


As uncontrollables, they amount to additional contingent factors thatmust be systematically treated in future studies.

The PIMS data base includes data on dozens of strategic attributes.Only variables that have been prominent in previous PIMS findings or inother strategy studies (e.g., product quality, capital intensity, capacityutilization) were included in this study.

The strategic attributes, as grouped for analysis and discussion, are asfollows:

Expense StructureManufacturing/revenueProduct R&D/revenueProcess R&D/revenueSales force/revenueAdvertising and promotion/revenueCompetitive DevicesSales from new productsRelative sales from new productsRelative pricesRelative direct costsRelative imageRelative servicesRelative advertising expensesRelative promotion expensesRelative sales force expenses

Resources and Resource UsageInvestment/revenuePlant and equipment newnessCapacity utilizationCapacity/market sizeSales/employeeWorking Capital ManagementReceivables/revenueInventory/revenueDomainRelative product line breadthRelative customer type breadthRelative number of customersCustomer fragmentationVertical IntegrationValue/added revenueRelative integration backwardRelative integration forward

The definitions of the strategic attributes can be obtained from the au-thors. In all cases, four year averages were used. Four performance mea-sures were examined:

(1) Return on investment (ROI) (average of last two years): Pretax netincome minus allocated corporate overhead costs, as a percent of averageinvestment including fixed and working capital at net book value.

(2) Cash flow on investment (CFOI) (average of last two years): After-tax income (estimated at 50 percent of pretax income) minus changes innet investment, as a percentage of average investment.

(3) Return per risk (RPR): Average ROI divided by the variability ofROI (calculated as the sum of the absolute differences between the four-year average ROI and each year's ROI).

(4) Market share change (MSC): The change (annualized via leastsquares) in this business's average share of the market (expressed as a per-centage of the market) for the four-year period.

The rationale for using two-year averages for ROI and CFOI bears pri-marily on the analyses to be reported in the companion paper (MacMillanet al., 1982) and will be discussed there. The two-year vs. four-year time-frame has little effect on the tendencies reported in this paper.

518

Method of Analysis

Academy of Management Journal September

Reporting of means, with two-way analysis of variance, was used toidentify any tendencies for the four types of businesses to differ in theirperformance or strategic attributes, either according to life cycle stage ormarket share. Zero-order correlations among performance measures foreach cell also are reported.

Results and Discussion

Performance Across the Four Ceils

This study empirically corroborates the primary theme espoused by theoriginators of the BCG matrix (see Table 1): namely, the four types ofbusinesses have significantly different tendencies to consume or generatecash. The average Wildcat has a negative cash flow (-2.67 percent) ["re-quires large cash inputs that it cannot generate itself" (Henderson, 1979,p. 164)]. The average Star essentially generates as much cash as it uses (.74percent) ["may or may not generate all of its own cash" (Henderson,1979, p. 166)]. Cash Cows are net cash generators (10.10 percent) ["gen-erate large amounts of cash" (Henderson, 1979, p. 164)]. These results arepreinterest charges (which are not reported in the PIMS data), and so mustbe regarded as suggesting patterns rather than absolute figures.

The results present a somewhat more positive view of Dogs than that ex-pressed by Henderson, who said that a Dog gives "no cash throwoff. Theproduct is essentially worthless, except in liquidation" (1979, p. 164). TheDogs examined in this study had average net positive cash flow on invest-ment of 3.4 percent, while holding their market shares. This cashflow ratefrom Dogs is more than is required to meet the cash needs of the average

Table 1Performance Levels of Businesses

in the Four Cells of the BCG Matrix(Means Reported, with Standard Deviations in Parentheses)

Performance Measure

Return on investment

Cash flow on investment

ROl/ROI variability(return per risk)

Market share change

*p< 05•*p< 001

Wildcats(N= 181)

20.55(24.53)-2.67

(18.79)2.37

(3.53).39

(1.76)

Stars(N= 114)

29.58(22.59)

.74(18.26)

3.96(5.20)

.72(2.97)

Cash Cows(N=315)

30.00(22.67)10.01

(17.03)4.57

(4.15).38

(2.30)

Dogs(N=418)

18.48(21.68)

3.41(16.17)

2.80(4.68)

.14(1.55)

2-Way Anova(Main Effects)

Life Cycle MarketStage Share

«*

** «*

** «*

* •


Wildcat (-2.67percent). If one assumes that the absolute size of the aver-age Dog is larger than the typical Wildcat (often fledgling operations),then the absolute cash throw-off from some Dogs may be sufficient tofund two or more promising new ventures. It also should be noted that thestandard deviation of CFOI for Dogs is 16 percent, indicating that someDogs generate substantial amounts of cash. And the modest correlation(r=-.O7) between CFOI and Market Share Change (Table 2) for Dogs in-dicates that cash flow can come other than through "harvesting." It ap-pears that Dogs outperform the expectations placed on them by BCG. In-stead of focusing solely on harvesting or liquidation strategies for Dogs,researchers should start dealing more positively and creatively with thistype of business (e.g., Hamermesh et al., 1978; Woo & Cooper, 1980).

Consistent with previous PIMS findings, ROI (reflecting accrual prof-its, not cash flow) was higher for high share than for low share businesses(Buzzell, Gale & Sultan, 1975). There were no significant ROI differencesacross the two life cycle stages. Specifically, Stars (29.58) and Cows(30.00) were roughly equal in outperforming Wildcats (20.55) and Dogs(18.48) on the ROI measure.

When ROI is adjusted for risk (4-year ROI variability), differencesacross the four cells reflect both the profitability of high market share andthe profit stability of maturity. Cows score highest (4.57), due to theirdominance in relatively stable markets. Stars follow (3.96), due to theirdominance, but in turbulent markets. Dogs are next highest (2.80). Wild-cats are lowest (2.37), reflecting their moderate profitability and unsettledmarkets. These results support the established concept that growth busi-nesses are more uncertain than mature businesses. They also reemphasizethe soundness of carefully tending mature businesses—including Dogs.

Market share change was one of the performance measures examined.As expected, there were indications of greater share increases in thegrowth businesses than in the mature businesses, reflecting both the rela-tively entrenched positions in mature industries and the presumed charterof mature businesses to seek primarily cash, not share. Also, high sharebusinesses tended to gain more share than did their low share counter-parts. Apparently, "the strong get stronger." Yet, there is no indicationthat businesses attempt to gain or succeed in gaining truly large share in-creases. In absolute terms, the average share increases are modest (highestis .72 percent for Stars), as are the standard deviations (highest is 3.0 per-cent for Stars). A quest for a 5 percent to 10 percent share increase appar-ently is unusual, unrealistic, or both.

The results (Table 2) also shed light on the tradeoffs presumed to existbetween performance measures, particularly cash flow and market sharegain. Nil correlations between these two performance measures suggestthat no real tradeoff exists (except for Stars, for which r=-.27, p < .01) orthat unaccounted factors may be masking indications of such a tradeoff.The results also indicate nil relationships between ROI and share changefor each cell. It is beyond the scope of this paper to identify circumstances


Table 2Relationships Among Performance Measures

(Pearson Correlation Coefficients)

Wildcats (N= 181)

ROICFOIRPRMSC

Stars (N= 114)

ROICFOIRPRMSC

Cash Cows (N = 315)

ROICFOIRPRMSC

Dogs (N= 418)

RDICFOIRPRMSC

ROI

.68**

.45**

.13

ROI

.61**

.39**-.15

ROI

.61**

.38**-.04

ROI

.57**

.39**-.06

CFOI

.54**-.07

CFOI

.53**-.27*

CFOI

.46**-.07

CFOI

_.45**

-.05

RPR

-.03

RPR

-.07

RPR

-.12

RPR

-.02

MSC

MSC

MSC

MSC

—*p<.01

**p<.O0l

or strategies that will allow market share and cash flow or profits to in-crease together. Factors such as the magnitude of an attempted share in-crease, competitors' strategies and goals, and product differentiation nodoubt are among those that future research should include as moderatingvariables in studying tradeoffs between profits and share changing. Thepresent results suggest that a tradeoff may not always exist. The findingsalso raise questions about the extent to which managers should be relievedof profitability or cash flow goals when they also are charged with gainingshare.

Strategic Attributes of the Four Cells

The results indicate a host of significant differences in the strategic attri-butes of the four types of businesses. Some of the attributes, including al-most all those expressed in terms "relative to competitors," varied pri-marily according to market share. Several others varied according to lifecycle stage. Still others varied according to both dimensions of the matrix.

Care must be taken in trying to interpret the attributes as either causesor effects of the business's position in the matrix. For example, it will beobserved that high share businesses have relatively broader product linesand customer types than do low share businesses. Because the data arecross-sectional, there is no way to disentangle the extent to which broadproduct/market bases precede, accompany, or follow market dominance.

1982 Hambrick, MacMitlan, and Day 521

Future longitudinal treatment of the PIMS data base could yield such in-formation.

Resources and Resource Usage

It comes as no surprise that high share businesses have substantiallymore of their markets' production capacity than do low share businesses(Table 3). High share businesses also utilize their capacity at a higher ratethan do low share businesses, probably reflecting the leaders' relative easein securing orders to fill capacity. The lower utilization rates of low sharebusinesses indicate that those businesses either built capacity in earlierdays when they held or anticipated higher shares or built capacity recentlyas part of a plan to gain share. That plant and equipment newness (netP&E/gross P&E) varies according to the product life cycle, but not ac-cording to market share, suggests that low share businesses typically havenot engaged in recent capacity buildups, but rather they simply do nothave the market power to fill earlier built capacity the way a high sharebusiness can.

Table 3Strategic Attributes of Businesses


Resources and Resource Usage

Strategic Attributes

Capacity/market

Capacity utilization

Plant and equipmentnewness

Investment/revenue

Sales/employee

Wildcats(N=181)

20.37(16.37)73.36

(16.88)59.24

(15.80)63.93

(36.12)63.22

(44.29)

Stars(N=114)

56.61(25.85)75.28

(15.60)58.93

(14.09)60.05

(27.66)63.92

(39.50)

Cash Cows(N=315)

52.03(25.96)78.09

(14.23)50.58

(14.26)51.35

(24.72)55.37

(36.49)

Dogs(N = 418)

21.27(15.40)75.14

(16.04)51.40

(14.84)56.06

(27.33)59.06

(40.68)


Life Cycle MarketStage Share •

***

• *•

***

*** **

*p<.05**p<.Ol

***p<.OOl

Mature businesses have higher capacity utilization rates than do growthbusinesses. This may reflect the relative stability and equilibrium that ex-ists in mature industries (as indicated by relative market share stability asdiscussed above), and perhaps also an efficiency orientation in maturebusinesses.

Because the numerator of investment/revenue (capital intensity) is mea-sured in terms of net investment, it is not surprising that growth businesses


have higher scores on this attribute than do mature businesses. Growthbusinesses, on average, have newer, less depreciated assets [the correlationbetween plant and equipment newness and investment/revenue was .34(p>.01) for the entire sample, indicating a strong relationship betweennewness and capital intensity]. The high capital intensity figure for growthbusinesses also may reflect their presumably smaller revenue bases overwhich they must spread investment. The disguised dollar figures in thedata base prevent any test of this speculation. To some extent, the findingof high capital intensity for growth businesses runs counter to conven-tional thought of businesses becoming more capital intensive over time, ascompetition shifts to a volunie or efficiency orientation.

The high sales/employee figure for growth businesses, compared to ma-ture businesses, suggests that mature businesses have not dramatically re-placed labor with capital assets. The higher employee productivity figurefor growth businesses may be partly attributable to the relatively strongerpricing structure that exists in growth businesses (gross margins in growthbusinesses average 30 percent, compared to 27 percent in mature busi-nesses—a significant difference at the .05 level), which inflates their reve-nue figures. Or Parkinson's Law may be operating: mature businesses arechoked with people (presumably administrators/stafO who, on average,generate relatively little salable output.

Capital intensity is less for high share than for low share businesses.This may reflect the smaller revenue bases of the low share businesses, or itmay suggest that low capital intensity provides flexibility and market re-sponsiveness which, in turn, can lead to high market share.

Working Capital Management

Wildcats have a significantly higher receivables/revenue ratio than doany of the other types of businesses (Table 4). This may reflect their at-tempts to attract customers via liberal credit terms. This relatively



Working Capital Management


Receivables/revenue

Inventories/revenue

*p<.Ol**p<.OOl

Wildcats(N= 181)

17.62(11.77)20.90

(11.71)

Stars(N=114)

15.62(8.80)18.61

(10.54)

Cash Cows(N=315)

15.15(7.47)19.87

(10.59)

Dogs(N=418)

15.13(8.89)22.01

(11.45)



*•

1982 Hambrick, MacMittan, and Day 523

mundane way of competing as a low share business apparently is not thenorm for Dogs. A possible explanation is that rigid credit norms build upover an industry's life cycle, discouraging unusual credit practices.

An indicting explanation for the relatively high inventories held by lowshare businesses is that these businesses are less adept at managing their in-ventories, which in turn raises the question of whether they are more poor-ly managed in general. Their low shares could prompt such a speculation,but the data from this study do not necessarily support it. Another, morecharitable, explanation for the high inventories held by Wildcats and Dogsis that they attempt to compete, using those inventories for ready delivery.This is another example of a relatively mundane competitive device, aimedat what Katz (1970) would call "going for the crumbs"—those customersin which the dominant players have little interest.

Expense Structure

This study also included an examination of the expense structures ofbusinesses, or how they add value (Table 5). Results indicate differencesprimarily according to life cycle stage, and less so by market share.



Expense Structure


Manufacturing/revenue

Product R&D/revenue

Process R&D/revenue

Sales lorce expenditures/revenue

Advertising and promo-tion expense/revenue

Wildcats(N= 181)

26.31(12.06)

2.63(2.66)

.87(1.24)6.48

(4.17)1.02

(1.15)

Stars(N=II4)

25.08(9.99)2.76

(2.51)1.10

(1.32)5.45

(4.21).85

(.93)

Cash Cows(N=315)

28.45(11.50)

1.68(2.08)

.53(.81)4.99

(4.15).71

(.92)

Dogs(N=418)

28.30(11.33)

1.76(2.28)

.52(.84)5.32

(4.35).81

(1.07)



•*

*•*

**•

** *

*p<.05**p<.Ol

***p<.001

Growth businesses tend to spend proportionately more on what mightbe called "future-oriented" expenses, that is, product R&D, processR&D, advertising, and sales force, than do mature businesses. Three fac-tors may be creating this difference. First, managers of growth businessesmay tend to view their businesses as having longer, brighter futures thando the managers of mature businesses, and thus they are more willing to

524 Academy of Management Journat September

incur costs that will have an impact only in the future. This is not a con-vincing rationale. Sales force and advertising expenses presumably havesome important near and current term payoffs even for mature businesses.A second possibility is that many of these mature businesses are beingmanaged for cash throwoff, according to BCG prescriptions, and there-fore nondirect expenses are minimized. A third interpretation stems fromthe semifixed, rather than variable, nature of most of these "future-oriented" expenses. Thus, in growth businesses, which may have smallerrevenue bases than mature businesses, these expenses take on dispropor-tionate magnitude when expressed as a percentage of sales. This line ofreasoning also may explain why low share businesses (with relatively smallrevenue bases) have higher sales force and advertising expenses than dohigh share businesses.

Mature businesses add more value through manufacturing than dogrowth businesses. This is an indication of the relative emphasis of maturebusinesses on the "core technology" (Thompson, 1967) or "engineering"(Miles & Snow, 1978) aspects of the business rather than on the "domain"or "entrepreneurial" aspects. In light of this emphasis, it could be ex-pected that mature businesses would spend a relatively heavy amount onprocess R&D, in an attempt to make their throughout functions even moreefficient (Utterback & Abernathy, 1975). As already observed, the oppo-site is true. Mature businesses, on average, spend about half as much oftheir sales dollars on process R&D as do growth businesses. One explana-tion is that organizational structures, climates, and technological orienta-tions either foster R&D in general, or they do not. That is, product R&Dand process R&D tend to go hand in hand. This speculation pales in lightof the only moderate correlation (/•= .24, p > .01) between the two types ofR&D expenses for the entire sample.

Another possible explanation for the relatively low process R&D expen-ditures by mature businesses is that these businesses are being managed forcash throwoff in industries with severe price competition, such that evenexpenditures on process R&D are viewed as profit detractors.

Domain

The term "domain" is used as Thompson (1967) did, to refer to the ar-ray of products and markets a business stakes out for itself. Because thernain domain variables in the PIMS data base are expressed in terms rela-tive to the competition, no differences were expected across stages of thelife cycle and, in fact, none were observed (Table 6).

Differences in the domain breadths of low and high share businesseswere significant. Stars and Cash Cows reported more relative product linebreadth, customer type breadth, and relative number of customers thandid their low share counterparts. Because this is a cross-sectional study,there is no way of determining whether a broad domain is a means of gain-ing share, or whether domain broadening is an activity typically pursued




Domain


Strategic AttributesWildcats(N= 181)

Stars(N= 114)

Cash Cows(N=315)

Dogs(N=418)

Life CycleStage

MarketShare

Relative product linebreadth^

Relative customer typebreadth

Relative number ofcustomers

Customer fragmentation

1.81(.81)1.81(.62)1.47(.65)

12.91(10.32)

2.39(.75)2.28(.65)2.35(.81)

13.94(12.14)

2.42(.72)2.29(.66)2.47(.69)

13.33(11.51)

1.85(.75)1.89(.59)1.68(.74)

13.54(11.53)

^For the sake of brevity and interpretability, means and ANOVA results are reported for ordinalvariables. A display of response distributions and chi-square statistics for the ordmal variables doesnot suggest different patterns or conclusions.

»p<001

by businesses that have already achieved dominance in a segment of a mar-ket. What is clear is that the low share businesses tended toward "marketconcentration" (Hofer & Schendel, 1978) or "focused" (Abell, 1980) stra-tegies. They concentrated their efforts either because they recognized theirweak positions or were constrained by their weak positions.

There were no significant differences across the four cells in theamounts of customer fragmentation, the variable that taps the extent towhich the business avoids relying on a few key customers. It could havebeen expected that Wildcats, in particular, would have a small set of cus-tomers with which they were establishing themselves. And, in fact, thecustomer fragmentation score for Wildcats is the lowest (though not sig-nificantly) of the four types. On average, though, none of the types has ex-traordinarily more or less customer fragmentation than the others.

Vertical Integration

Just as high share businesses have broader domains than low share busi-nesses, so do they also tend to be more vertically integrated (Table 7).Their value added/revenue figures are higher than for low share busi-nesses. And they indicate significantly more vertical integration (bothbackward and forward), relative to their competition, than do low sharebusinesses.

As with domain breadth, there is no way of knowing from these datawhether vertical integration is a cause or an effect of high market share. Areasonable speculation is that high share businesses tend to integrate ver-tically to perpetuate their growth and that they integrate because their




Vertical Integration


Value added/revenue

Relative V.I. backward

Relative V.I. forward

*p<.05**p<.OQl

Wildcats(N=18I)

56.13(16.58)

1.83(.60)1.89(.52)

Stars(N= 114)

61.14(13.63)

1.98(.62)1.97(.50)

Cash Cows(N=315)

59.57(14.19)

2.04(.60)1.99(.49)

Dogs(N=418)

54.77(14.84)

1.78(.59)1.92(.47)


Life Cycte MarketStage Share

•*

*

scale of operations makes it relatively difficult to be assured of outsidesupplies in the quantities and at the prices they desire (Williamson, 1975-Kreiken, 1980).

Competitive Devices

In examining the tendencies of the four types of businesses to use vari-ous competitive devices, some striking differences are observed (Table 8).Understandably, growth businesses have higher sales from new productsthan do mature businesses. (Businesses in all four cells claim to have, onaverage, higher sales from new products than their competitors. This canbe reconciled only by returning to the earlier contention that the PIMSbusinesses are likely to be more aggressive, and hence perhaps more proneto new product activity, than are their non-PIMS competitors.) Wildcatshave the highest new product sales, and Dogs the lowest. This may reflecta kind of self-fulfillment of the BCG doctrine, in which Wildcats arevie\yed, either by their own managers or their parent firms' strategists, ashaving the potentially longest and most rewarding horizons of any of thefour types, and thus most deserving of a new product orientation. Dogs,typically viewed as having no promising future (Henderson, 1979), areviewed as not warranting the outlays associated with new products.

High share businesses indicate the relatively low direct costs that shouldaccrue to them due to their accumulated experience (Henderson, 1979;Hofer & Schendel, 1978). The typical prescription for high share busi-nesses in the growth stage is for them to drive costs down and to price atdiscouragingly low levels. However, the Stars in the data base had relative-ly high prices, perhaps reflecting that they already were established leadersinstead of struggling for leadership. More broadly, it warrants noting thatboth Stars and Cash Cows are reaping double benefits from their marketpower: relatively low costs and relatively high prices.




Competitive Devices


Sales from new products

Relative sales from newproducts

Relative prices

Relative direct costs

Relative product quality

Relative image

Relative services

Relative advertisingexpenses

Relative sales promotionexpenses

Relative sales forceexpenses

Wildcats(N= 181)

18.66(20.69)

4.01(11.80)103.20

(7.02)104.30

(7.68)22.03

(29.18)3.21(.86)3.27(.80)2.19(.99)2.39(.93)2.76

(1.01)

Stars(N=1I4)

18.16(20.73)

2.08(10.19)105.00

(7.40)99.52(8.38)45.12

(29.77)4.06(.71)4.00(.83)2.75

(1.11)3.03

(1.07)3.09

(1.04)

Cash Cows(N=315)

7.31(12.97)

.79(6.21)

104.30(6.37)

100.20(7.13)34.25

(28.56)3.96(.78)3.83(.82)2.82(.96)2.99(.89)3.12

(1.02)


Dogs Life Cycle Market(N=418) Stage Share

7.82 *(13.68)

.50 *(7.08)

102.70 *(5.13)

103.20 *(6.93)17.64 • *

(25.38)3.26 •(.81)3.28 •(.79)2.29 *(.93)2.51(.86)2.79(.93)

Stars and Cows apparently command their high prices through a broadarray of superiorities. They claim to have higher average product quality,image, and services than their low share competitors. They claim to spendrelatively more on advertising, sales promotions, and sales forces thantheir lesser adversaries. All of these measures are ordinal and somewhatimpressionistic, so there is some likelihood that the market leaders falselyattribute to themselves strength in all categories (Nisbett & Wilson, 1977).Still, some of the apparent differences are substantial, and they tend tosquare with expectations. Businesses with various strengths would be ex-pected to gain market share and, once dominant, they would be expectedto reinforce and add strengths with the slack generated from market lead-ership (Cyert & March, 1963).

Conclusions

This paper has attempted to test and extend the BCG product portfoliomatrix. The primary theme of BCG—that the four cells of the matrix havequite different tendencies to generate or consume cash—has been cor-roborated. Significant differences among the four cells on other perfor-mance measures—return on investment, return per risk, and market sharechange—also were observed. Thus, each of the four types in the matrix—

528 Academy of Management Journat September

Wildcats, Stars, Cows, and even Dogs—contributes in its own way to thebalanced performance of the corporation. Of particular note is the findingthat the average Dog has a positive cash flow, even greater than the cashneeds of the average Wildcat. BCG's schematic (Henderson, 1979, p. 165)portraying optimal cash flows could be revised, as in Figure 2, on the basisof these results.

Figure 2Cash Flows Within the BCG Matrix

Stars

t>6gs

BCd Prescription (Henderson, 1979) ^Revised, based on study •»-

The results do not support BCG's advice that Dogs should be promptlyharvested or liquidated. This should come as a relief to many managers,because more and more of their industries are maturing and because allbut the market leaders qualify as Dogs. What is needed is creative, positiveresearch and thinking about how Dogs can be managed for maximum longterm performance.

Another key, tentative conclusion to come from the study is that busi-nesses may not always face sharp tradeoffs between share building andcash flow or profitability. Only among Stars was there an inverse relation-ship between market share change and any of the measures of returns.Otherwise the relationships were nil, suggesting that multiple, seeminglyincompatible objectives can be pursued in tandem. More research isneeded on the circumstances that favor such "well-rounded" effectivenessand on the internal features that can promote or stymie it.

The four types of businesses differ markedly in thf ir strategic attributes.Some attributes (e.g., R&D expenses, plant and equipment newness) varyaccording to life cycle stage. Some (e.g., domain breadth, vertical integra-tion, relative marketing expenditures) vary according to market shareposition. Still others (e.g., capacity utilization, sales/employee) vary ac-cording to both dimensions.

What emerges is an expanded understanding of the strategic profile ofeach type of business:

Relative to the other cells. Wildcats tend to have low capacity utiliza-tion, new plant and equipment, high current asset levels, high capitalintensity, high R&D expenses, high marketing expenses, narrow do-mains, heavy new product activity, high direct costs, and competitivedevices that lag Star competitors on all fronts.

1982 Hambrick, MacMiltan, and Day 529

Stars tend to have new plant and equipment, high capacity utilization,high R&D expenses, broad domains, high sales per employee, highvalue added, and superiority on a number of competitive devices.

Cows tend to have very high capacity utilization, dated plant and equip-ment, low capital intensity, low sales per employee, low R&D andmarketing expenditures, broad domains, and superiority on essen-tially all competitive devices examined.

Dogs tend to have dated plant and equipment, medium capital intensity,high inventory levels, low R&D expenses, moderate marketing ex-penses, narrow domains, low value added, and competitive devicesthat lag Cow competitors on all fronts.

Overall, there is a clear indication that businesses differ in their perfor-mance and strategic attributes, according to their life cycle stages and mar-ket shares. The importance attached to these two key constructs by Hofer(1975) and others appears not to have been ill-placed.

This paper sheds empirical light on an important, but heretofore ill-documented strategic framework, but it also raises many questions. Forexample, would consumer products or service businesses yield findingsdifferent from the industrial businesses studied here? Would a sample ofnon-PIMS businesses yield similar findings?

The only contingency variables included were life cycle stage and marketshare. Many others have been suggested in the literature (Hofer, 1975). Ifbusinesses were subdivided further within the four BCG cells according toadditional contingent factors (e.g., concentration rates, frequency of pur-chase, or advertising intensity), what new findings would emerge? Thepresent study should serve as a springboard for adding contingent factorstoward the goal of full scale contingency models as advocated by Hofer.

The cross-sectional nature of this study poses an obvious problem. Howbusinesses move among the four cells of the matrix or how their strategicattributes tend to change as they move from cell to cell has not been exam-ined. This shortcoming highlights a key opportunity for future PIMS re-search. The data base has been in existence long enough that some longitu-dinal analyses should now be possible.

Empirical analysis of the BCG matrix has long been overdue, as haveanalyses of many other normative and conceptual devices in the field ofstrategy. This paper has corroborated and extended the published ideas ofthe Boston Consulting Group. It serves as an important backdrop to anaccompanying study of the relationships between strategic attributes andperformance in each of the four cells (MacMillan et al., 1982).

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Donald C. Hambrick is Associate Professor, Graduate Schoolof Business, Columbia University.

Ian C. MacMitlan is Associate Professor, Graduate School ofBusiness, Columbia University.

Diana L. Day is a doctoral student at the Graduate School ofBusiness, Columbia University.

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