Planning Market Share Growth in Mature Industrial Markets

0019-8501/98/$19.00PII S0019-8501(97)00094-1

Industrial Marketing Management

27

, 401–428 (1998)© 1998 Elsevier Science Inc. All rights reserved.655 Avenue of the Americas, New York, NY 10010

Planning Market Share Growth in Mature Business Markets

John A. WeberUtpal Dholakia

The study presents a decision support system, called pathmarketing analysis, which can help managers to utilize theirmarket knowledge and experience to develop more effectivemarket share growth plans in mature business markets.Through treating marketing mix elements in a hierarchicalfashion, the approach identifies key drivers of market sharechange and then uses this information to uncover, evaluate,and compare alternative opportunities for market sharegrowth. Also included is a structure for estimating the prospec-tive return on assets employed by alternative share growthstrategies. © 1998 Elsevier Science Inc.

INTRODUCTION

Energized by robust profits, cash hordes, low interestrates, and high stock prices, many chief executives todayare less concerned with trouble-shooting crisis after crisisand have more time to ponder the long-term futures oftheir companies. For many firms, such favorable finan-cial factors have resulted in an active search for newsources of growth [14, 44, 50, 73, 74]. Some have de-cided that acquisitions are the fastest and cheapest way tokeep their companies growing and viable. Reflectingsuch thinking, recent years have witnessed record strate-gic merger activity [58, 59, 62, 83, 119]. Other firms areconcluding the opposite and are divesting (e.g., AT&T,GM, Sears, Sprint Corp., Host Marriott, Novell, Melville,and many others) to make the parent company more nim-ble and responsive to competitive pressures and marketopportunities in core businesses [7, 47, 48, 122]. Yet othercompanies such as Procter & Gamble, 3M, Kraft, andRubbermaid are committed to emphasizing internal prod-

Address correspondence to Dr. J. Weber, University of Notre Dame,College of Business Administration, Department of Marketing, Notre Dame,IN 46556.

402

uct innovation as the primary avenue of growth, generat-ing hundreds of new consumer and industrial productseach year [1, 77, 111].

As important as growth opportunities through acquisi-tions and innovations are, they should not preclude com-panies from continually reassessing opportunities to

in-crease market share in already mature markets of thecompany’s core businesses

(e.g., [14, 63]). Reflectingthis realization, market share analysis continues as an im-portant part of marketing research and planning for mostfirms. For example, market share analysis was found tobe the second most common (behind industry analysis)of 36 market research activities of companies in one sur-vey [51]. This attention to share analysis may reflectwhat is generally regarded as a positive relationship be-tween market share and profits ([6, 18, 38, 63, 98, 104]exceptions noted [8, 24]).

CHALLENGES OF PLANNING MARKETSHARE GROWTH

Analysts have designed a number of approaches forthe express purpose of helping companies build marketshare in core businesses (e.g., [12, 17, 57, 82, 84–87,110]). Some of these schemes have focused specificallyupon mature markets [29, 39, 89]. Unfortunately, even intheir normative configurations, available approaches arenot very effective in projecting the explicit market sharechanges likely to result from implementing specificgrowth strategies. Complicating the challenge of project-ing share changes are a host of marketplace uncertainties

caused by changing demand patterns, new technologies,uncertain economic growth, dynamic public policy con-straints, and ever-changing strategies of competitors. Theinterrelationships among opportunities themselves andthe uncertain links between specific strategies and pro-spective share increases have further impacted the emer-gence of more effective share planning models. Reflect-ing these complexities, the objective functions of existingshare growth strategy valuation schemes tend to focusupon macro measures (e.g., shareholder value or overallcorporate profitability) rather than upon explicit microprojections of sales and market share increases (e.g., [6,9, 20, 27, 76, 90, 103, 106, 107, 120]).

Putting a formal structure around a difficult problemcan help to identify and clarify its most important com-ponents, thereby making the quest for problem solutionmore systematic, transparent, and manageable. The pur-pose of this article is to offer a conceptual contribution tothe formal structuring of market share decisions. Themodel presented is called path marketing analysis (PMAor PATHMOD). Through treating marketing mix ele-ments in hierarchical fashion, PATHMOD can help acompany to identify key drivers of market share change.This information can yield important insights for identi-fying share growth opportunities, deciphering the inter-relationships among such opportunities, projecting specificmarket share increases likely to flow from alternativestrategies, and for comparing the prospective return onassets employed by alternative share growth strategies.Through offering such benefits, the approach can poten-tially help managers to utilize their market knowledgeand experience to develop more effective market sharegrowth plans.

OVERVIEW OF PATH MARKETINGANALYSIS (PATHMOD)

This hierarchical planning model was originally pre-sented in the literature in its incipient form two decades

JOHN A. WEBER is Associate Professor at the University of Notre Dame, specializing in Industrial Marketing and International Business.

UTPAL DHOLAKIA is a doctoral candidate at the University of

Michigan.

Opportunities for increasing market share

in mature core markets are often overlooked.

403

ago by Weber [112–114]. It was initially referred to asgrowth opportunity analysis, later as gap analysis, and fi-nally, today, is called path marketing analysis (PMA orPATHMOD). Over the past 20 years, through trial and er-ror application with more than 200 groups of managersfrom 50 major industrial companies, the specific compo-nents (gaps) of PMA market profiles and the application ofthe approach to help plan share growth have been signifi-cantly modified, refined, and enhanced. A number of newuses for the framework have also been developed. Appen-dix A reviews the evolution of PATHMOD over time.

The essence of the PATHMOD framework presented isthat it treats marketing mix elements [65, 109] in a hier-archical manner (Figure 1A and B). The resulting formatis referred to as a PMA market profile. Each PMA mar-ket profile provides a compact visual and quantitativesummary of the share growth opportunities available fora company in a targeted segment. More specifically, aprofile summarizes growth opportunities (gaps) relatedto captive sales, breadth of product line, price position-ing, sales force size and effectiveness, alternative distri-bution channels, and promotion. Applying the frame-work for a specific target segment requires building twoPMA market profiles (Figure 1C)—one for the currentyear and a second for some future year (e.g., year 3),while assuming no new strategies by the company. Thetwo profiles are designated as PMA market profiles #1and #2, respectively.

Multi-Layered Segmentation as the StartingPoint for PATHMOD

Focusing marketing analysis and the development ofshare growth plans upon homogeneous market subsetsfacilitates understanding and adapting to market com-plexities and interactions. Therefore, following the rec-ommendations of other marketing planning schemes andanalysts, application of PMA begins with careful, multi-layered market segmentation [4, 13, 89]. One effectiveway to accomplish this is to overlay traditional macromarket segments with micro purchase influence segmen-tation (alternatively referred to as benefit segmentation)[28, 72, 115]. The planning team then selects one key tar-get market segment at a time for further analysis usingPATHMOD.

Identifying PMA Market Profile Gaps

To start building a PMA market profile, the planningteam estimates current annual industry sales (IS) and the

firm’s sales (FS) for the target segment. Next, the plan-ners try to explain all portions of the overall competitivegap (i.e., IS minus FS). As the explanations emerge, theytake the form of PMA market profile gaps (or, simply,gaps). The challenges involved in identifying individualgaps and estimating their size are considered in the de-scriptions of the individual gaps below. A full-scale ver-sion of the framework can accommodate several gaps ofeach type (e.g., several captive sales gaps, several prod-uct gaps, etc.). The compact example of PATHMOD pre-sented later in the study assumes a minimal number ofgaps of each type to clarify the treatment of how themodel can help to uncover, evaluate, and compare alter-native share growth strategies.

The first set of gaps together constitute the unservedmarket (USM). Each gap identified as part of the USMrepresents a potential share growth opportunity for whichthe company is

not

currently competing. Included in theUSM are four fundamentally different kinds of gaps:captive sales, product, price, and distribution gaps (asshown later, the promotion gap is treated as part of theserved market). The summary of the framework pre-sented in this article assumes the specific gap ordershown.

1

The logic for this order is included in the de-scriptions of the individual gaps. Importantly, recogniz-ing and including a specific gap does not in and of itselfimply that the company should pursue the related sharegrowth opportunity. Indeed, one important insight fromPATHMOD is to help the firm to prioritize alternativeopportunities (i.e., gaps) to decide which, if any, areworthwhile pursuing.

C

APTIVE

S

ALES

G

APS

. The first gaps to be estimatedare for captive sales. This gap refers to sales not availableto the company’s brand because of predetermined buyercommitments to competitive brands. Such commitmentsexclude simple brand loyalty and refer to phenomenasuch as long term contracts, compatibility requirements,specified requirements for brand choice diversity, or in-house allocations (e.g., General Motors reserving a cer-tain portion of its parts business for GM-owned affili-ates). Captive sales are included as the first gap in the

1

Because of the chain ratio or decomposition method used to adjust gapsizes as one moves down the hierarchy of opportunities (gaps), the order inwhich a specific gap appears in the profile does

not

affect the incrementalserved market and the potential new market share represented by that gap.Therefore, if logic dictates, gap order can be modified without affecting theimplications of the framework. Appendix B presents a two part caseexemplifying this.

405

profile because, if properly defined and estimated, thesesales are simply not available to the company’s brandover the relevant time horizon (see earlier footnote ongap order). The portion of industry sales remaining aftersubtracting captive sales from industry sales is referred toas current available market 1 (CAM1). As/if portions ofcaptive sales once again become available to generalmarket competition (e.g., as long-term contracts expire),those portions of industry sales move down in the profile,becoming part of CAM1.

P

RODUCT

G

APS

. Appearing next in the market pro-file and applying only to CAM1 are the product gaps.Buyers (or brand choice influencers) and marketing plan-ners alike have a tendency to consider some product-related purchase influence attributes in more tangibleform than others [35, 54, 116]. Therefore, for purposes ofbuilding PMA market profiles, it is useful to differentiatebetween tangible and intangible product gaps. Tangibleproduct gaps are typically easier to define and estimatethan intangible gaps. Tangible gaps refer to product di-mensions such as size, capacity, technology, range of op-eration, specific tolerances, or other concrete measuresregarding the physical, performance-related characteris-tics required by certain subsets of buyers. The size of atangible product gap is a best estimate of the proportionof industry sales accounted for by tangible product varia-tions not offered by the company, but insisted upon (i.e.,no substitutability) as per [15, 25, 36, 56, 99, 102, 108]by a definable subset of brand specifiers.

Empirical studies of the attributes which drive brandpreferences have shown that managers and buyers alike

tend to consider and express total product-related at-tributes such as quality, service, aesthetics, etc., in rela-tively intangible ways [45, 94, 101, 116]. This suggeststhat brand preferences are driven by composite judg-ments on several tangible benefits and/or overall judg-ments based upon general experience, rather than throughan active awareness and detailed knowledge of each tan-gible characteristic (e.g., [54, 55, 116]). Such attributesare potential intangible product gaps in the market pro-file. Specific intangible product gaps should be referredto by name in the profile (e.g., quality gap, service gap,quality/service gap, etc.). Intangible gaps can be difficultto define and tend to be overestimated on the first pass.Therefore, planners building initial PMA market profilesshould conservatively estimate specific intangible gaps,with residual industry sales allowed to temporarily filterdown further in the profile (to the served market—asconsidered below). More definitive estimates of the rele-vant intangible gaps can be generated over time throughfocused queries of sales personnel, distributors, and cus-tomers. See further discussion in the section addressingdata uncertainty.

If product gaps are properly identified and estimated,as precluding purchase regardless of price and distribu-tion availability, then a company cannot sell product lineelements for which it faces tangible and intangible prod-uct gaps. Thus, product gaps appear before price and dis-tribution gaps in the PMA market profile (see earlierfootnote on gap order). In this hierarchical scheme, resid-ual industry sales left after subtracting product gaps fromCAM1 yields current available market 2 (CAM2).

P

RICE

G

APS

. Price gaps appear next in the profile. Aprofile can have three different types of price gaps: a lowprice gap, a price/quality gap, and a composite of otherprice gaps (e.g., terms, discounts, special deals). Mostproduct markets include a segment of brand specifiersthat may always try to select the lowest priced brand,without regard to quality—either because the purchase isrelatively unimportant to the segment or because the

The essence of path marketing analysis (PATHMOD) is to treat marketing mix

elements in a hierarchical manner.

FIGURE 1.

(A): Traditional view of the marketing mix.(B): Alternative view: A PMA market profile presentsmarketing mix elements and related market sharegrowth opportunities in a hierarchical structure. (C):Two PMA market profiles are built for each segment.

406

market has matured to the stage where virtually all com-petitors are perceived by low price buyers as havingmore or less the same quality [89]. Newer market en-trants, particularly smaller firms, quite often create anddominate this low price segment, whereas many larger,well-established firms consciously choose not to partici-pate in this segment because of the unattractiveness ofthe low price image and low profit margins often affili-ated with this segment (for discussions of these and re-lated pricing principles, see [66–68, 75]). Industry salesaccounted for by the low price segment constitute a lowprice gap for any company not having a product entrycompetitively priced for this segment.

Other buyers may be price sensitive, but may also havespecific quality, performance, or service-related require-ments. Within the PMA framework, sales lost to compet-itive brands specifically because a company’s product isnot priced competitively within certain grades of theproduct line constitute a price/quality gap or value gapfor the company. Comparative price/quality disadvan-tages can occur at the low, medium, or high ends for aspecific product line. Other price gaps in the profile con-sist of sales captured by competitors not because of lowerpublished or actual base prices, but because direct com-petitors offer comparatively better terms, discounts, deals,or other special differential price incentives.

Regardless of price, a company cannot compete for theportion of industry sales already accounted for by captivesales and product gaps—if those gaps have been properlyidentified and estimated. At the same time, a firm neednot be concerned about distribution weaknesses (gaps)for portions of industry sales accounted for by captivesales, product gaps, or price gaps. Therefore, price gapsappear after captive sales and product gaps in the profile,applying only to CAM2, but before the distribution gapin the market profile (see earlier footnote on gap order).In this hierarchy, the portion of industry sales left aftersubtracting price gaps from CAM2 yields current avail-able market 3 (CAM3).

D

ISTRIBUTION

/A

WARENESS

G

APS

. For the portion ofindustry sales for which the company faces no captivesales, product, or price gaps (i.e., CAM3), the companycan still lose sales due to the target market’s lack ofawareness of the company’s competitive offerings. Forproducts where building brand awareness and getting thefirm’s competitive offerings considered are accomplishedwith a broad mix of strategies, sales lost because of lackof awareness can be characterized with the broad labelawareness gap. For many industrial products and ser-vices, sales force efforts and related distribution strate-gies are the primary tools used to build brand awarenessand to get the firm’s competitive offerings considered. Insuch instances, sales lost due to lack of awareness of thefirm’s competitive offerings (or failure to get the com-pany’s competitive brand offering on the comparativespreadsheet) can be appropriately characterized as a dis-tribution gap.

This distribution/awareness gap contributes the lastcomponent of the USM. An operational way to estimatethe size of this gap is to consider the proportion of CAM3accounted for by brand choice decisions where the com-pany’s brand is not considered as an alternative—i.e.,does not make the comparative spreadsheet (primarily dueto lack of distribution or awareness). Subtracting the dis-tribution/awareness gap from CAM3 yields current avail-able market 4 (CAM4—the same as the served market).

T

HE

S

ERVED

M

ARKET

, P

ROMOTION

G

APS

,

AND

S

HARE

OF

S

ERVED

M

ARKET

. CAM4 is alternatively referred toas the served market (SM).

2

The company is assumed tobe competing head to head (i.e., no recognized captivesales, product, price, or distribution/awareness gaps) forall portions of industry sales in the SM. Therefore, withinthe SM, portions of industry sales not captured by the

Gap order can be modified without affecting

the implications of the framework.

2

Although the term served market has been used elsewhere for some time invarious forms (e.g., in PIMS analysis [88], also variations in [3, 52]), inPATHMOD, as already shown, served market (SM) has a very specificdefinition and derivation (SM

5

IS minus CAM3 minus the distribution gap).

407

company make up a direct competitive gap. Industrysales thus lost to the firm can result from factors such asstrong brand loyalty to competitive brands, mispercep-tions about the actual product or price offerings of thecompany’s brand, or simply an indifference factor (i.e.,when two or more brands are perceived by specifiers asbeing equally attractive). The ratio of the firm’s ownsales (FS) over the SM is referred to as the share ofserved market (SSM). Efforts to increase SSM, therebyreducing the direct competitive gap, typically focus onrefining and/or expanding promotion efforts, includingstrategies such as advertising, sales promotions (directand trade shows), and promotion through the sales force.Therefore, this gap between the SM and the firm’s salesis labeled as a promotion gap in PMA market profiles.

General Perspectives on Estimating Gap Sizes

The process of estimating gap sizes for the PMA mar-ket profiles is facilitated if one thinks about the size ofeach gap only for the industry sales remaining after allprevious gaps have been subtracted from initial industrysales. For example, a firm should consider and calculateprice gaps only for portions of industry sales accountedfor by product line elements offered by the firm (i.e., forportions of industry sales for which the firm has no cap-tive sales or product gaps). Depending upon what as-sumptions are appropriate regarding the independence ofeach gap, a gap appearing lower in the market profilemay or may not apply equally to industry sales above andbelow that specific gap (see discussion regarding equalproportional dependence elsewhere in the article). Whenestimating gap sizes initially for any profile, a conserva-tive approach is recommended—favoring smaller gapsize estimates. As one gains more familiarity with theprocess of building PMA market profiles, and as relateddata inquiries expand, the accuracy of a firm’s profile

data quite naturally improves, thereby providing morecredible and useful strategic insights from the profilesover time.

3

For further discussion of alternative procedures for ad-dressing the challenges involved in identifying individualgaps and estimating their size, see the following sectionsof the article: Adjusting for Uncertain Data, ConsideringCompetitive Reactions, and A Decision-Support SystemOnly.

THE PATH MARKETING ANALYSISMODEL (PATHMOD)

Logic of PATHMOD

Once PMA market profile #1 (i.e., the current profilefor year 1) has been developed, the starting point forbuilding PMA market profile #2 (in 3 years, without as-suming new strategies) is to project industry sales forseveral years into the future (e.g., year 3). Gaps corre-sponding to those in profile #1 are then estimated for pro-file #2. The company’s gap size estimates for profile #2should assume no new strategies by the company, butshould fully incorporate specific assumptions concerning

A PMA market profile provides a compact visual and quantitative summary of share

growth opportunities.

3

For example, as a company gains experience with the approach andbecomes more confident in the quality of its data, the analysis can be expandedand refined to incorporate stochasticity. For example, opportunity sizes (gaps)can be considered as random variables, with probability distributions beingused to characterize expected opportunity size values in the base framework.Alternatively or additionally, the planning team can run simulations using riskanalysis software programs (e.g., @RISK [81]) to estimate the values of thevariables. A Bayesian learning model approach similar to those used to modelthe information integration process in marketing science [37, 79, 91] andconsumer behavior [96] can also be used to update and improve opportunitysize estimates over time. Furthermore, game theory can also be used tosystematically evaluate a wide range of potential competitive reactions in theanalysis—within the constructs of the hierarchical share planning framework.For further discussion, see Weber and Dholakia [118].

408

the ‘most likely future environment’ for year 3. Explicitprojection of the most likely future environment shouldcover likely transitions in customer demand patterns(e.g., different product variations, price trends, distribu-tion mode trends, etc.—i.e., gap sizes may change), tech-nology, the economy, and public policy.

4

It should alsoinclude specific assumptions concerning likely changesin competitive strategies (e.g., market entry or exit, spe-cific price increases or decreases, new sales force strate-gies, etc.—e.g., [40, 88]). Since profile #2 assumes nonew strategies by the company itself, anticipating and as-sessing strategic reactions of competitors to the company’sown potential strategies are not necessary until later.

Profile #2 (in 3 years while assuming no new strate-gies) serves as the quantitative base for estimating the in-cremental sales and market share likely to be associatedwith the company’s alternative potential strategies. InPATHMOD, therefore, a company’s alternative potentialstrategies are evaluated not against where the company isnow (profile #1), but, rather, against where the companyis likely to be in the future absent any strategy changes(i.e., against profile #2).

Profile #2 is subsequently overlain with assumptionsregarding alternative possible strategies by the company,as represented by the various gaps in the second profile.Thus, the sales and share implications of alternative strat-egies are determined in the context of the future environ-ment within which strategy implementation will actuallyoccur (i.e., starting with profile #2, rather than assuminga continuation of the current environment, as summa-rized in profile #1).

As shown in the complete example below, the firststrategy set to run through PATHMOD is the set of thecompany’s already planned strategies (i.e., all strategiesplanned before trying this approach). In the event thatsales and market share projected by PATHMOD fallshort of the company’s sales or share goals, the strategistcan then easily test alternative strategies and strategy setsto uncover one or more potential strategy sets that willenable the firm to meets its sales and share goals for therelevant target segment.

Default Version Of Pathmod:An Example

Table 1A–C presents the analytics of PATHMOD,whereas Figure 2 shows an example in its default config-uration. Once the logic and the inferences of the basicversion of PATHMOD have been reviewed, the treat-ment drops constraining assumptions. The scheme thenbecomes more flexible, providing more realistic perspec-tives for assessing prospective market share benefits re-lated to pursuing the full variety of share growth opportu-nities incorporated in the PMA market profiles.

Table 1A summarizes the notations used in subsequenttables. Table 1B shows the analytical derivation of PMAmarket profile #1 (year 1). As one moves down the pro-file, opportunity (gap) size estimates are adjusted down-ward in chain-ratio fashion, applying them only to themarket remaining after eliminating all opportunities pre-viously accounted for. The total USM reflects the ad-justed total of the captive sales, product, price and distri-bution opportunities. The SM is the residual of IS minusthe total USM. (As considered earlier, the promotion gapand related promotion opportunities are part of the SM,not part of the USM.) The SSM for profile #1 equals theratio of current FS over the current SM (i.e., FS/SM).

The same logic is used to estimate the makeup of mar-ket profile #2 (e.g., for year 3) in Table 1C—assumingno new strategies by the company, but incorporating theexplicit assumptions that the company has made regard-ing the most likely changes in the environment and invarious demand and competitive trends. In projectingmarket profile #2, the SSM for year 3 (SSM) is initiallyassumed to remain the same as SSM in year 1 (later on,this assumption is varied as SSM becomes a strategicvariable—discussed further below).

Figure 2 presents an example of a set of market pro-files (#1 for year 1; and #2 for year 3) for the designer in-fluence segment of the business letterhead stationerymarket. Note that the second profile (market profile #2—in year 3, assuming no new strategies) includes a projec-tion of the company’s sales and market share, while as-suming no new strategies by the company. This secondprofile not only lays out alternative sales and sharegrowth opportunities (in the form of the various gapsprojected for year 3), but also serves as the base for pro-jecting what specific potential new sales and marketshare are represented by each of these opportunities.

The focus of the interpretation of the projected profile(market profile #2) is to consider how to translate before/after potential changes in market profile #2 into prospec-

4

Regardless of how well-informed the company is when estimating thevarious dimensions of the most likely future environment, each dimension ofthe projection will have a degree of uncertainty. If desired, a firm can explicitlyrecognize and accommodate such uncertainties by casting market profile #2 ina contingency framework of estimated ranges, using traditional tools forcontingency planning under uncertain conditions (see discussion of “Adjustingfor Data Uncertainty” elsewhere in the article). Interested readers can also referto Weber and Dholakia [118].

409

tive increases in sales and market share. The key parame-ters relevant for the analysis are the sales response fac-tors (SRF) for the various components of profile #2. AnSRF is calculated in a slightly different way for each partof profile #2, with the various formulae appearing in Ta-ble 2A. To apply these SRF formulae for projecting pro-spective incremental sales and market share, the com-pany must first hypothesize implementing specific sharegrowth strategies (i.e., gap closures, such as closing partof the product gap, price gap, etc.).

To clarify how the SRF formulae are used to projecthypothesized gap closures into incremental sales, the ini-tial example (in Table 2B) includes the following as-sumptions:

• full strategy implementation by year 3;

• no lag between strategy implementation and full real-ization of incremental served market (ISM);

• share of incremental served market (SISM) in year 3equal to 100% of SSM in year 1;

• a focus upon incremental sales and share benefits foryear 3 only (versus a multi-year flow of new sales andshare); and

• equal proportional dependence among opportunities.

In the example (Table 2B), the approach calculates thevarious SRFs and then hypothesizes pursuing variousstrategic growth opportunities framed within market pro-file #2 (i.e., the projected profile, while assuming no newstrategies). The specific strategic opportunities tested are50% gap reductions by year 3—that is, 50% is used asthe constant ‘c’ when applying the SRF formulae from

TABLE 1ANotation Used in the Path Marketing Analysis Model

Market Profile #1 — Year 1IS

5

Industry sales in year 1 (in units — supplied by the manager).P

ij

5

Size of the jth gap of type i — as a % of IS in year 1 (estimated by the manager).L

ij

5

% of IS left in year 1 after considering the jth gap of type i (calculated by the model).G

ij

5

Adjustment to gap size P

ij

in year 1 while assuming equal proportional dependence (calculated by the model).

a

ij.i

9

j

9

5

Parameter of proportional dependence (0

#

a

ij.i

9

j

9

#

1) for year 1 in percent. Indicates the proportion of gap j of type i that is dependent on gap j

9

of type i

9

. These parameters are estimated by the manager.CAM1

5

Current available market 1 (industry sales minus captive sales gaps) in year 1 (% of IS remaining). CAM1 and all of the remaining variables below are calculated by model — except for FS, which is supplied by the manager.

CAM2

5

Industry sales minus captive sales gaps and product gaps in year 1 (% of IS remaining).CAM3

5

Industry sales minus captive sales gaps, product gaps, and price gaps in year 1 (% of IS remaining).CAM4

5

Industry sales minus captive sales gaps, product gaps, price gaps, and distribution gaps in year 1 (% of IS remaining).USM

5

Unserved market for year 1 as % of IS (

5

IS minus CAM4).SM

5

Served market for year 1 as % of IS (this is the same as CAM4 and as (IS minus USM).SSM

5

Share of served market for year 1 as % of IS (

5

FS/SM).FS

5

Firm sales in units for year 1 (supplied by the manager).MS

5

Market share for the firm in year 1 as % of IS (

5

FS/IS).

Market Profile #2 — Year 3, Assuming No New Strategies

IS

9 5

Industry sales in year 3 assuming no new strategies (in units — estimated by the manager).P

9

ij

5

Size of the jth gap of type i — in year 3 assuming no new strategies (estimated by the manager).L

9

ij

5

% of IS

9

left in year 3 after considering the jth gap of type i — assuming no new strategies (calculated by the model).G

9

ij

5

Adjustment to gap size P

9

ij

in year 3 — assuming equal proportional dependence (calculated by the model).

a9

ij.i

9

j

9

5

Parameter of proportional dependence (0

#

a

ij.i

9

j

9

#

1) for year 3 in percent assuming no new strategies. Indicates the proportion of gap j of type i that is dependent on gap j

9

of type i

9

assuming no new strategies. These parameters are estimated by the manager.CAM1

95

Current available market 1 (industry sales minus captive sales gaps) in year 3 (% of IS

9

remaining). CAM1

9

and all of the remaining variables below are calculated by model — including FS

9

(and, therefore, MS

9

as well).CAM2

95

Industry sales minus captive sales gaps and product gaps in year 3 (% of IS

9

remaining) assuming no new strategies.CAM3

95

Industry sales minus captive sales gaps, product gaps, and price gaps in year 3 (% of IS

9

remaining) assuming no new strategies.CAM4

95

Industry sales minus captive sales gaps, product gaps, price gaps, and distribution gaps in year 3 (% of IS

9

remaining) assuming no new strategies.

USM

9 5

Unserved market for year 3 as % of IS

9

assuming no new strategies (

5

IS

9

minus CAM4

9

).SM

9 5

Served market for year 3 as % of IS

9

assuming no new strategies (this is the same as CAM

9

and as IS

9

minus USM

9

).SSM

9 5

Share of served market for year 3 as % of IS

9 assuming no new strategies (5 FS9/SM9).FS9 5 Firm’s sales in units for year 3 assuming no new strategies (the firm’s sales for year 3 are projected by the model).MS9 5 Market share for the firm in year 3 as % of IS9 assuming no new strategies (5 FS9/IS9) (the firm’s market share for year 3 is projected

by the model).c 5 Constant or supplied variable (gap closure hypothesized).

410

Table 2A. Using a multiple of these and related variables(as shown in Table 2B), PATHMOD projects the specificnew sales and market share (in year 3) that are likely toflow from pursuing each opportunity tested. Note that inaddition to opportunities represented by the various 50%gap reductions, the example also hypothesizes and evalu-ates a small strategy-triggered increase (10%) in IS and amodest strategy induced reduction (10%) in the promo-tion gap (i.e., increased SSM). The percentage gap reduc-tion (50%), the year 3 planning horizon, and other specif-ics in this example are used for illustrative purposes only,and, in any actual application, would be adjusted asappropriate for different companies, strategies, and seg-ments.

REFINING PATHMOD

Having reviewed the logic and strategic inferences ofPATHMOD in its default form, the treatment now dropsthe default assumptions, yielding a more refined marketshare planning tool.

Refinements Regarding StrategicInterrelationships and the Assumptionof Equal Proportional Dependence

The default hierarchical share planning framework as-sumes that each subsequent opportunity (from top to bot-tom) in the market profile will apply on an equal propor-tional basis to all opportunities above it. This is referredto as the assumption of equal proportional dependence.For example, consider the case of a company that mar-kets vinyl siding to the builders’ choice segment of theUSA tract housing market. Assume that this companyfaces only two opportunities in its USM—a 10% coloropportunity (e.g., the opportunity to offer siding inshades of red) and a 20% distribution opportunity (e.g.,the opportunity to add distribution in the southeasternUnited States)—resulting in a USM of 28% [10% for thecolor opportunity plus 20% of the SM remaining after thecolor opportunity is eliminated from the SM, thus, [10%1 (20% 3 90%) 5 28%]. In this case, pursuing the coloropportunity would increase the SM by 8% (i.e., reducingthe USM from 28% to 20%). These calculations reflectand assume equal proportional dependence. Under these

TABLE 1BMarket Profile #1—Year 1 (assuming complete proportional dependence)

Components of theMarket Profile

Supplied VariablesEst. Gap Size (%)*

% of Market Left afterConsidering Gaps (%)*

Adjusted GapsSize (%)*

Industry sales (IS) 100%Components of the unserved market (USM)

Captive sales gap P11 (as % of IS) (100% 2 P11) 5 L11

L11 5 CAM1P11 5 G11

Product gapsTangible product gap P21 L11 2 (L11P21) 5 L21 L11P21 5 G21

Other product gap P31 L21 2 (L21P31) 5 L31

L31 5 CAM2L21P31 5 G31

Price gapsLow price gap P41 L31 2 (L31P41) 5 L41 L31P41 5 G41

Other price gap P51 L41 2 (L41P51) 5 L51

L51 5 CAM3L41P51 5 G51

Distribution gap P61 L51 2 (L51P61) 5 L61

L61 5 CAM4L51P61 5 G61

Remaining Calculated and Supplied Variables

Total unserved market (USM) 100% 2 L61

Served market (SM) SM 5 CAM4 5 L61

Components of the served market (SM)Promotion gap P71 5 a calculated residual 5 (SM 2 MS) P71 5 G71

Market share (MS) MS is supplied by the manager for year 1, but projected by the model for year 3(i.e., MS9 is projected)

Share of served market (SSM) SSM is calculated in year 1: SSM 5 MS/SM

*All supplied and calculated values shown in these exhibits are expressed as a % of industry sales.

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TABLE 1CMarket Profile #2—Year 3, Assuming No New Strategies (assuming complete proportional dependence)

Components of theMarket Profile

Supplied VariablesEst. Gap Size (%)*

% of Market Left afterConsidering Gaps (%)*

Adjusted GapsSize (%)*

Industry sales (IS9) 100%Components of the unserved market (USM9)

Captive sales gap P911 (as % of IS) (100% 2 P911) 5 L911

L911 5 CAM1P911 5 G911

Product gapsTangible product gap P921 L911 2 (L911P921) 5 L921 L911P921 5 G921

Other product gap P931 L921 2 (L921P931) 5 L931

L931 5 CAM2L921P931 5 G931

Price gapsLow price gap P941 L931 2 (L931P941) 5 L941 L931P941 5 G941

Other price gap P951 L941 2 (L941P951) 5 L951

L951 5 CAM39

L941P951 5 G951

Distribution gap P961 L951 2 (L951P961) 5 L961

L961 5 CAM49

L951P961 5 G961

Remaining Calculated and Supplied Variables

Total unserved market (USM) 100% 2 L961

Served market (SM) SM9 5 CAM4 5 L961

Components of the served market (SM)Promotion gap P971 5 a calculated residual 5 (SM9 2 MS9) P971 5 G971

Market share (MS) MS9 is projected by the model, as per SM9 calculation and the assumption that SSM9

for year 3 will remain unchanged from SSM for year 1.†

Share of served market (SSM9) In the default version of the model, SSM9 (year 3) is projected to remain unchanged from SSM (year 1).†

*All supplied and calculated values shown in these exhibits are expressed as % of industry sales.†SSM9 (year 3) is estimated by the manager from SSM (year 1) and, in the default version of the model, is projected to remain unchanged from year 1 SSM (i.e.,

SSM9 5 SSM). Multiplying the estimated SSM9 times the projected SM9 yields the market share projection for year 3 (MS9), assuming no new strategies. Thus,MS9 5 SSM9 3 SM9.

assumptions, opportunity order may at first look impor-tant visually (for example, moving the distribution op-portunity from the bottom to the top of the USM makes itappear larger), but is not analytically important (asshown in the example in Appendix B).

It is entirely possible, however, that there is no marketdemand for red siding in the southeast. In that case, thecolor and distribution opportunities would be indepen-dent and the USM would be simply 10% 1 20% 5 30%.Furthermore, in this case of complete opportunity inde-pendence, pursuing the color opportunity (i.e., addingshades of red) would increase the SM by the full 10%,rather than 8%, with this strategy yielding more potentialincremental sales and share than in the default case ofequal proportional dependence. The same potential re-finement can be applied to deal with variations in depen-dence among all opportunities in the market profiles.

PATHMOD can be extended to accommodate all situ-ations where the equal proportional dependence assump-tion is not realistic. This is accomplished by adding de-

pendency variables to the formula for each specificopportunity in the market profile. For opportunities lowerin the profile, more dependency variables have to beevaluated and included in the SRF formulae. An opportu-nity interdependency planning matrix can be used to di-rect deliberations concerning the explicit dependence ofeach opportunity versus all other opportunities. The ma-trix format is helpful for communicating this refinementas well as for assessing and expressing how a single an-ticipated competitive reaction can simultaneously influ-ence multiple opportunities in a market profile (see fur-ther discussion below under “Competitive Reactions”).Table 3A shows the analytical interpretation of this re-finement, including an example (Table 3B).

Adjustments for Variations in Strategic Timing

The primary purpose of PATHMOD is to help un-cover, evaluate, and compare specific new potentialshare growth strategies over the life of each would-be

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strategy. The default framework assumes that potentialstrategies evaluated would be implemented and fully op-erationalized over a single specified time frame.5 Fur-thermore, the default framework evaluates incrementalsales benefits for only 1 year (year 3). These strategictiming assumptions are seldom realistic because of pro-spective time variances in fully realizing and maintainingprojected ISM and share of incremental served marketSISM (e.g., [49, 92, 93, 105]). Table 4A reviews a num-ber of causes of timing variances in the realization andmaintenance of the projected ISM and SISM.

To address these timing complexities, variances instrategic timing can be incorporated in a flexible mannerin the model itself. Table 4B provides several examplesof fine-tuning the framework to adjust for unique timingcharacteristics of individual growth strategy alternatives.Note that the examples show variances in timing for bothISM and SISM. To arrive at appropriate timing parame-ters, strategic timing concerns would be specifically de-liberated and recorded during planning discussions re-garding each potential share growth strategy.

Adding Cost Dimensions and Estimating theProspective Return on Assets Employedfor Alternative Sets of Share GrowthStrategy Alternatives

Once incremental revenue projections for alternativepotential share growth strategies have been calculated us-ing the PATHMOD framework, a potentially importantsubsequent extension is to compare the projected revenue

flows with the cost flows related to each strategy. Thisinformation can serve as the basis for generating compar-ative projected rates of return on assets employed for thevarious strategies, thus providing further insights to aidin strategy choice and design.6

Incorporating cost flow estimates is fairly straightfor-ward, as summarized in the example in Table 5. The par-ticular configuration used in the example focuses uponincremental costs directly related to each strategy, pur-posefully omitting indirect costs. The example shows astructure for calculating the 5-year rate of return of eachstrategy, based upon the present value of revenue andcost flows projected for each strategy over that period. Infurther refinements, adjustments for uncertainties in costscan also be included, in much the same way as describedbelow for revenues.

Adjusting for Uncertain Data

Even a cursory review of the PATHMOD share plan-ning framework reveals that effective application re-quires an extensive array of data. Regardless of how wellinformed a company is, each estimated component of itsmarket profiles will have a degree of uncertainty. This istrue for the current profile (profile #1), for the projectedprofile when assuming no new strategies (profile #2), andwhen hypothesizing new potential strategies. Such uncer-tainties can be addressed by casting each parameter in-cluded in the market profiles as an estimated range ratherthan as a constant, finite variable. If this approach isused, then the principal outputs of PATHMOD (sales andshare projections and prospective return on assets em-ployed for each strategy) would also be expressed in

5As indicated above, in the default version, each strategy is fully implementedin year 3. Furthermore, the firm realizes full ISM and full share of incrementalserved market (SISM) immediately (i.e., SISM equals SSM now projected inprofile #2).

6Although the procedure does not address the varied conceptual andmethodological issues related to cost analysis in this logical extension (e.g., see[11, 26, 34, 43, 78, 80, 97]), PATHMOD does provide some insights forestimating the cost requirements of supporting individual planned strategies.For example, under certain conditions, the percentage increase in SM projectedby the framework for each hypothesized strategy can be used as a multiplier toestimate the indirect support costs that would be required to fully realize theprojected sales benefits of each strategy.

Variances in strategic timing can be incorporated within PATHMOD.

FIGURE 2. Example of a set of PMA market profiles(#1 & #2).

414

ranges, including most likely outcomes. As a result, thewidth and shape of the distributed range of outcomes forsales and share projections and prospective return on as-sets for each strategy would now represent a compositeof the specific distributions used to express the com-pany’s degree of uncertainty when estimating each pro-file component.

Incorporating uncertainty in this manner can be ac-complished by building the relevant market profiles on aspreadsheet and then using @Risk add-in software [81]to express inputs (i.e., gap estimates) as assorted data dis-tributions and outputs as distributed ranges (generatedthrough Monte Carlo simulation runs that are integral to@Risk). Although this refinement does not reduce theuncertainty of the results, it does integrate yet another di-

mension of managerial knowledge and experience intothe analysis of prospective share growth opportunities.Furthermore, with the subsequent results expressed indistributed ranges, the company can then not only makemore generally informed choices, but can also incorpo-rate its attitude toward risk (e.g., risk preference or aver-sion) when deciding upon its most appropriate mix ofshare growth strategies. For further discussion, see We-ber and Dholakia [118].

Considering Competitive Reactions

Whether or not a specific strategy accomplishes its in-tended objective may be heavily influenced by competi-tive reactions. Although evidence suggests that many

TABLE 2BExample of the Calculation and Use of Sales Response Factors for Projecting New Sales and New Market Share in PATHMOD (based upon the data in PMA Market Profile #2 in earlier exhibit)

Sales Response FactorsIncremental Sales Projections For Year 3

SRF9 3 C 3 P9 3 IS9 5

NewSales

New MktShareMS9 / L9 5 SRF

Industry sales 12.97% / 100.00% 5 12.97% 12.97% 3 10% 3 3 450 5 5.84 1.30%Unserved market

Captive sales Long-term contracts 12.97% / 90.00% 5 14.41% 14.41% 3 50% 3 10.0% 3 450 5 3.24 0.72%

Product gaps Missing colors 12.97% / 72.00% 5 18.01% 18.01% 3 50% 3 20.0% 3 450 5 8.10 1.80%Service 12.97% / 57.60% 5 22.51% 22.51% 3 50% 3 20.0% 3 450 5 10.13 2.25%

Price gaps Low price gap 12.97% / 46.08% 5 28.14% 28.14% 3 50% 3 20.0% 3 450 5 12.66 2.81%Price/Quality gap 12.97% / 39.17% 5 33.11% 33.11% 3 50% 3 15.0% 3 450 5 11.17 2.48%

Dist./Awareness gap: 12.97% / 29.38% 5 44.14% 44.14% 3 50% 3 25.0% 3 450 5 24.83 5.52%Served market SRF for Promo Gap 5 SM-MS 5 P71

Promotion gap 12.97% 16.41% 16.41% 16.41% 3 10% 3 450 5 7.38 1.64%Firm sales Total New Sales* 5 83.36 18.53%

*If all the strategies were implemented.Table 2A, B summarizes how the framework can help the strategist to project what new sales and market share are likely to result from implementing potential new

strategies suggested by the various gaps recognized in PMA market profile #2 (i.e., the profile projected for year 3, while assuming no new strategies by the company).

TABLE 2AFormulae for Sales Response Factors (SRFs)* in PATHMOD

Market Profile Component Sales Response Factor (SRF) Incremental Sales Year 3

Industry Sales Increase SRF01 5 SM9 * SSM9 5 MS9 SRF01 * c * IS9 Narrow Captive Sales Gap SRF11 5 MS9/L911 SRF11 * c * P911 * IS9

Narrow Tang. Product Gap SRF21 5 MS9/L921 SRF21 * c * P921 * IS9

Narrow Other Product Gap SRF31 5 MS9/L931 SRF31 * c * P931 * IS9

Narrow Low Price Gap SRF41 5 MS9/L941 SRF41 * c * P941 * IS9

Narrow Other Price Gap SRF51 5 MS9/L951 SRF51 * c * P951 * IS9

Narrow Distribution Gap SRF61 5 MS9/L961 SRF61 * c * P961 * IS9

Narrow Promotion Gap SRF71 5 L971 SRF71 * c * IS9 * 0.5

*These SRFs subsequently serve as the basis for projecting PMA market profiles components (including new firm sales) for year 3, assuming new strategies.

415

firms do not incorporate likely reactions of rivals into thestrategy planning process [19, 33, 121], such oversight isparticularly inappropriate in mature markets, where sharegains for one firm are likely to come directly from com-petitive rivals. Thus, analysis of competitive behaviorand prospective reaction should be an integral part of strat-egy assessment, especially in more mature markets [70,95]. Prediction of competitive response is complicated bymany factors, including its temporal dimension [16, 46],as well as the degree of competitor dependence, action ir-reversibility [23], market concentration, market growth,and degree of product standardization [22, 33, 88].

By providing a structure for dissecting the impact thatcompetitive reactions can have upon the effectiveness ofplanned strategies, market profile #2 within the hierarchi-cal share planning framework can provide insights forhelping to sort out conjecture concerning prospectivecompetitive responses. For each strategy hypothesizedusing the PATHMOD framework, competitive responsescan influence the size of any strategy-related ISM orSISM projected for the strategy. The challenge is to sortout these two potential influences.7

First, will the anticipated competitive reaction affect thetiming and the ultimate size of the gap closure anticipatedfrom the strategy? For example, if the planned strategy

involves filling out a product line, pursuing a low priceopportunity, or expanding distribution into a new geo-graphic area, will such strategies trigger one or more ma-jor competitors to introduce new product variations, intro-duce yet lower prices, or invigorate sales force efforts inthe affected geographic area? Any of these competitive re-actions would most likely reduce (or could even totallyeliminate) the gap closure anticipated by the companyfrom the prospective strategy, thus curtailing the ISM an-ticipated from the strategy. Such reactions are more likelyin mature markets, where, by definition, sales gainssought through attempted SM increases must usuallycome directly from competitors. The strategy timing ma-trix (Table 4B) can be used to help sort out and express theanticipated timing of the competitive reactions as well asthe timing of their impact on gap sizes and related ISM.8

Second, will the anticipated competitive reaction af-fect the timing and the ultimate SISM anticipated fromthe strategy? For example, consider the situation when aplanned strategy directly invades a portion of SM thathas traditionally been important to one or more majorcompetitors. In this instance, an affected competitormight well increase promotional response (through salesforce, promotion, direct customer promotions, etc.) in aneffort to preserve its historic share in those portions ofSM now being invaded. The strategy timing matrix (Ta-ble 4B) can be used to help sort out and express the antic-ipated timing of promotional reactions of competitors aswell as the timing of their impact on the planning com-pany’s SISM for each potential strategy. This analysis ofpotential competitive reactions should be an integral partof the discussions when considering what ISM and the

7To start the process, the company should identify the range of possiblecompetitive reactions to each strategy being considered, and should estimatethe probability that each reaction will occur. Reflecting those deliberations, thecompany should then explicitly identify the most likely competitive reaction.Subsequent projections are made with the assumption of the most likelycompetitive reaction. Contingency plans can be considered later for alternativepotential competitive reaction scenarios. Game theory can be used tosystematically evaluate a wide range of potential competitive reactions in thecontingency analysis—all within the constructs of the PATHMOD framework.To develop more substantive conjecture regarding prospective competitiveresponses to the company’s various alternative strategies, the planning teamhas access to insights from a number of theoretical bases [5, 19, 41, 70].Among the most useful is game theory as applied to strategy in general (e.g.,16, 21, 30–32, 53, 85–87, 95] and to competitive analysis in marketing inparticular (e.g., [40, 64, 69, 71]).

8When assuming away equal proportional dependency, it is possible thatcompetitive reactions could change the dependency variables of any relatedmarket profile gap as well, thus also affecting the size of strategy related ISM.Once again, the gap interdependency planning matrix (referred to earlier) canhelp to guide this inquiry and to sort out and express the likely impact ofanticipated reactions on the full set of individual gaps, and, in turn, upon ISMlikely to flow from the relevant growth strategy.

Adding costs to PATHMOD provides further insights for selecting and designing share

growth strategies.

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TABLE 3APMA Profile Opportunities without Assuming Equal Proportional Dependence: Formulae (i.e., Makeup of the Market Profile Assuming Variable Proportional Dependence)

GapsSuppliedVariables

% of Market Left afterConsidering Gaps

(5 Current Available Market) Adjusted Gaps

Industry Sales 100Captive Sales P11 (100 2 P11) 5 L11 P11 5 G11

Tangible Product Gaps P21 L11 2 (1 2 a21.11)P21 5 L21 (1 2 a21.11)P21 5 G21

P22 L21 2 (1 2 a22.11 2 a22.21)P22 5 L22 (1 2 a22.11 2 a22.21)P22 5 G22Other Product Gaps P31 • •

P32 • •Low Price Gap P41 • •Other Price Gaps P51 • •Distribution Gap P61 • •Total Unserved Market 100 2 L61

Served Market SM 5 L61

Promotion Gap P71 SM 2 FS 5 L71

Firm Sales FSShare of Served Market SSM 5 (F/S)

TABLE 3BAn Example of PMA Profile Opportunities Without Assuming Equal Proportional Dependence

With Equal Proportional Dependence

AdjustedGap SizeEstimates

(%)

Gap Interdependency Variables withEqual Proportional Dependence (%)Unadjusted

Gap SizeEstimates

(%)

CurrentAvailableMarket

CAM (%)1

cap2

size3

color4

lowP5

P/Q6

dist

1. Captive sales gap 10.0 90.0 10.02. Size gap 5.0 85.5 4.5 103. Color gap 12.0 75.2 10.3 10 54. Low price gap 15.0 64.0 11.3 10 5 125. Price/quality gap 5.0 60.8 3.2 10 5 12 156. Distribution gap 8.0 55.9 4.9 10 5 12 15 5

Unserved market 5 44.10Served market 5 55.90

With Variable Proportional Dependence

AdjustedGap SizeEstimates

(%)

Gap Interdependency Variables withVariable Proportional Dependence (%)Unadjusted

Gap SizeEstimates

(%)

CurrentAvailableMarket

CAM (%)1

cap2

size3

color4

lowP5

P/Q6

dist

1. Captive sales gap 10.0 90.0 10.02. Size gap 5.0 85.0 5.0 03. Color gap 12.0 75.0 10.0 5 124. Low price gap 15.0 65.3 9.6 25 5 105. Price/quality gap 5.0 61.7 3.7 10 5 5 106. Distribution gap 8.0 56.8 4.9 5 8 8 15 10

Unserved market 5 43.23Served market 5 56.77

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SISM are likely to be realized from all alternative sharegrowth strategies.

CAUTIONS & OTHER OBSERVATIONS

Adapting Gap Terminology to Best Suitthe Company

Whereas PATHMOD is proposed as a general frame-work to help structure the search for share growth oppor-tunities, broad variances occur among markets in termsof the types of market profile gaps (i.e., growth opportu-nities) that are likely to be encountered. This challengesthe notion that it is possible to develop a standard gap listand gap definitions that are inclusive and flexible enoughto apply to the broadest ranging markets. Thus, althoughthe list and definitions of gaps in the market profile (cap-tive sales, product, price, distribution/awareness, andpromotion gaps) are proposed as suitable for dealing withall markets, creative adaptation is required to capture re-alities of the share growth opportunities/gaps unique todifferent markets.

Share planners desiring to try the approach should notstray from the basic logic of the scheme (e.g., accepting

the default opportunity order and modeled interrelation-ships). However, they should adapt both the number andthe names of individual gaps (opportunities) to reflect theuniqueness of specific target markets and the preferencesof the company’s share planning team. Such adaptationsenable strategy planners to use concepts and terms withwhich they and the rest of the management team are al-ready familiar. This can facilitate comprehension, discus-sion, and use of this share planning framework in a mannerthat directly complements marketing planning conceptsand tools to which the company is already committed.

PATHMOD Is a Decision-Support System Only,with Its Usefulness Critically Dependentupon Key Inputs from Management

The methodology presented relies heavily upon mana-gerial inputs that must be arrived at without any direct aidfrom the model itself. For example, whereas PATHMODoffers a structured framework for presenting PMA mar-ket profile components (gaps) and their interrelation-ships, it does not tell the strategist what exact gaps to in-clude in a specific profile. Estimation of gap sizes,

TABLE 4AReasons for Timing Variance in Incremental Served Market (ISM) and in the Share of Incremental Served Market (SISM) Related toDifferent Strategies

Consider the following possibilities regarding time variance in the incremental served market (ISM).• Strategy Introduction Lags. Once an appropriate set of marketing strategies is determined, the individual strategies are usually not all introduced at one time. More

typically, new strategies are introduced in random or step-wise fashion in response to the firm’s priorities and strategic resources available, as well as the specific time and financial requirements of each strategy. Thus, realization of the full ISM anticipated from each strategy, even if projected accurately, may be delayed by late implementation .

• Time to Full Strategy Implementation. Some strategies take longer to fully implement than others. For example, strategies that focus on closing intangible gaps, as quality and service, can take considerably longer to fully operationalize than strategies designed to close more tangible gaps such as adding a new size or product variation.

• Strategic Tenure. Finally, incremental sales flows are likely to last much longer for some strategies than for others. For example, the benefits of closing a tangible product gap (e.g., adding specific colors) may be relatively short-lived, as market preferences quickly change and reduce or eliminate the ISM achieved through the strategy. On the other hand, reducing the distribution gap by selling through a new channel might result in very long-term ISM and related continuing sales and share benefits.

Also, consider potential time variances in the realization and maintenance of the projected Share of Incremental Served Market (SISM).• Time to Build Awareness. Achieving target market awareness takes longer for some strategies than for others, causing variance in the amount of time required to

fully realize the long-term projected SISM. For example, product quality improvements (i.e., narrowing a relatively intangible product gap) and distribution improvements (e.g., gaining immediate access to a new channel) may each bring immediate improvements in the served market. However, the target market may take considerably less time to become aware of the distribution improvement than the real quality improvement—with continuing misperceptions regarding product quality delaying full realization of the SISM projected for the new quality related ISM.

• Variations in Competitive Intensity and Reactions. The intensity of competition may vary in different portions of the ISM realized through different strategies. For example, capturing a “fair share” (e.g., a company’s current share of served market) of ISM realized through expanding distribution into a new geographic area where competitors are strong and firmly entrenched might take considerably longer than capturing a similar SISM when moving into a new geographic area where competitors are relatively weak and dispersed. Furthermore, even in intensely competitive markets, firms that have established market presence, often characterized by high brand awareness and preference, can usually achieve targeted SISM faster than newer, less well-known served market entrants. See further discussion in the “Considering Competitive Reactions” section of the article.

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TABLE 4BAdding Strategic Timing to the Market Share Projections: An Example

Market Share and Revenue Projections

Pursuing Share Growth Opportunities Related to:

Full-Term Market Share Projections

IndustrySales

1

CaptiveSales

2

MissingColors

3Service

4

LowPrice

5

PriceQuality

6Distribution

7Promotion

8

1. full-term incremental served market (SM9) 29.38% 29.38% 29.38% 29.38% 29.38% 29.38% 29.38% 29.38%3 3 3 3 3 3 3 3

2. full-term share of incremental served market (SSM9) 44.14% 44.14% 44.14% 44.14% 44.14% 44.14% 44.14% 44.14%5 5 5 5 5 5 5 5

3. full-term market share (MS9) 12.97% 12.97% 12.97% 12.97% 12.97% 12.97% 12.97% 12.97%4. gap size (P9ij) 10% 20% 20% 20% 15% 25% 16.4%5. full-term residual served market (L9ij)

(L9ij formulae are in Exh. 4c)100.0% 90.00% 72.00% 57.60% 46.08% 39.17% 29.38% 12.97%

6. full-term sales response factor 5(SM9/L9ij * SSM9) 5 (MS9/L9ij)

12.97% 14.41% 18.01% 22.51% 28.14% 33.11% 44.14% 100.0%

7. full-term strategy change assumed (5 constant c) 10% 50% 50% 50% 50% 50% 50% 10%8. gap size (P9ij) 10% 20% 20% 20% 15% 25% 16.41%9. full-term market share increase 1.30% 0.72% 1.80% 2.25% 2.81% 2.48% 5.52% 1.64%

(line 6 * 7 * 8)Three Strategic Timing Variables1. Timing variance of strategy phase in (constant c) (%)

c in Year 1 20 60 25 40 50 25 20 80c in Year 2 40 100 50 60 75 50 40 90c in Year 3 60 100 75 80 100 75 60 100c in Year 4 80 100 100 100 100 100 80 100c in Year 5 100 100 100 100 100 100 100 100

Strategy (constant c) realized (c 3 Pij) (%)c in Year 1 2.00 30.00 12.50 20.00 25.00 12.50 10.00 8.00c in Year 2 4.00 50.00 25.00 30.00 37.50 25.00 20.00 9.00c in Year 3 6.00 50.00 37.50 40.00 50.00 37.50 30.00 10.00c in Year 4 8.00 50.00 50.00 50.00 50.00 50.00 40.00 10.00c in Year 5 10.00 50.00 50.00 50.00 50.00 50.00 50.00 10.00

2. Timing variances in incremental served market(SM9) Realized (%)

SM ratio Year 1 50 30 60 40 25 20 80 40SM ratio Year 2 75 50 100 60 50 40 90 60SM ratio Year 3 100 70 100 80 75 60 100 80SM ratio Year 4 100 90 100 100 100 80 100 100SM ratio Year 5 100 100 100 100 100 100 100 100

New SM9 realized each year (SM ratio 3 SM9)SM9 Year 1 14.69 8.81 17.63 11.75 7.34 5.88 23.50 11.75SM9 Year 2 22.03 14.69 29.38 17.63 14.69 11.75 26.44 17.63SM9 Year 3 29.38 20.56 29.38 23.50 22.03 17.63 29.38 23.50SM9 Year 4 29.38 26.44 29.38 29.38 29.38 23.50 29.38 29.38SM9 Year 5 29.38 29.38 29.38 29.38 29.38 29.38 29.38 29.38

3. Timing variances in share of incremental served market(SISM9) realized (%)

SSM ratio Year 1 60 25 80 40 50 20 40 25SSM ratio Year 2 100 50 90 60 75 40 60 50SSM ratio Year 3 100 75 100 80 100 60 80 75SSM ratio Year 4 100 100 100 100 100 80 100 100SSM ratio Year 5 100 100 100 100 100 100 100 100

New SSM9 realized each year (SSM ratio 3 SSM9) (%)SSM9 Year 1 26.49 11.04 35.31 17.66 22.07 8.83 17.66 11.04SSM9 Year 2 44.14 22.07 39.73 26.49 33.11 17.66 26.49 22.07SSM9 Year 3 44.14 33.11 44.14 35.31 44.14 26.49 35.31 33.11SSM9 Year 4 44.14 44.14 44.14 44.14 44.14 35.31 44.14 44.14SSM9 Year 5 44.14 44.14 44.14 44.14 44.14 44.14 44.14 44.14

(Continued)

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trends, and dependency relationships are also left up tothe manager. Although specific quantitative perspectivesfor projecting strategy-related sales volume and revenuesdo flow from PATHMOD, estimates of the timing of rev-enue and cost flows must also come from the strategist,without insights (other than structuring) from the modelitself. Thus, PATHMOD is a decision-support systemonly, with its ultimate usefulness critically dependentupon the quality of managerial inputs. This is an impor-tant caveat, for as some market analysts suggest, one im-portant reason why structured planning schemes such asthis are not used more frequently is specifically becauseof difficulties in identifying and accessing relevant data[33, 42, 72, 121].

When initially developing market profiles, a well-designed share planning team may be able to developreasonably good estimates for profile components (gapsizes) in short order by drawing from its own collectiveexperience. A systematic plan can then be developed togradually improve key data over time (e.g., judgment-based parameter building, as argued for by Little [60,61]). For example, in most markets the company hasready access to informal networks of key brand specifiers(e.g., distributors and end users) that selected team mem-bers can query on a regular basis as a normal part of on-going business relationships. Through a formalized planto take the pulse of these specifiers as an integral part ofeveryday business, the team can gain better information

TABLE 4BContinued

Market Share and Revenue Projections



IndustrySales

1

CaptiveSales

2

MissingColors

3Service

4

LowPrice

5

PriceQuality

6Distribution

7Promotion

8

Results of Timing VariancesResultant timing variance in sales response factor (%) 5

(SM9/L9ij * SSM9) 5 (MS9/L9ij)Year 1 3.89 1.08 8.64 3.60 3.52 1.32 14.13 10.00Year 2 9.73 3.60 16.21 8.10 10.55 5.30 23.84 30.00Year 3 12.97 7.56 18.01 14.41 21.11 11.92 35.31 60.00Year 4 12.97 12.97 18.01 22.51 28.14 21.19 44.14 100.0Year 5 12.97 14.41 18.01 22.51 28.14 33.11 44.14 100.0

Resultant timing variance in market share increase from each strategy (%)

New Market Share from Each Strategy in Year 1: 0.08 0.03 0.22 0.14 0.18 0.02 0.35 0.13New Market Share from Each Strategy in Year 2: 0.39 0.18 0.81 0.49 0.79 0.20 1.19 0.44New Market Share from Each Strategy in Year 3: 0.78 0.38 1.35 1.15 2.11 0.67 2.65 0.98New Market Share from Each Strategy in Year 4: 1.04 0.65 1.80 2.25 2.81 1.59 4.41 1.64New Market Share from Each Strategy in Year 5: 1.30 0.72 1.80 2.25 2.81 2.48 5.52 1.64

Planners using PATHMOD should adapt the number and the names of individual profile

gaps to reflect the uniqueness ofspecific target markets.

420

TABLE 5Adding Revenue and Cost Dimensions and Calculating Projected Rates of Return on Investment for Alternative Market Share Growth Strategies

Market Share and Revenue Projections (from previous exhibit)



IndustrySales

1

CaptiveSales

2

MissingColors

3Service

4

LowPrice

5

PriceQuality

6Distribution

7Promotion

8

Full-Term Market Share Increase 1.30% 0.72% 1.80% 2.25% 2.81% 2.48% 5.52% 1.64%Timing Variance in Market Share Increase from Each Strategy

(from Previous Exhibit) (%)New market share from each strategy in year 1: 0.08 0.03 0.22 0.14 0.18 0.02 0.35 0.13New market share from each strategy in year 2: 0.39 0.18 0.81 0.49 0.79 0.20 1.19 0.44New market share from each strategy in year 3: 0.78 0.38 1.35 1.15 2.11 0.67 2.65 0.98New market share from each strategy in year 4: 1.04 0.65 1.80 2.25 2.81 1.59 4.41 1.64New market share from each strategy in year 5: 1.30 0.72 1.80 2.25 2.81 2.48 5.52 1.64

Converting Projected Market Share Increases into IncrementalRevenue Flows

New Sales Volume Flows from Each Strategy Incremental Unit Sales Flowing from Each StrategyIndustry Sales Year 1 425 0.33 0.14 0.92 0.61 0.75 0.11 1.50 0.56Industry Sales Year 2 450 1.75 0.81 3.65 2.19 3.56 0.89 5.36 1.99Industry Sales Year 3 475 3.70 1.80 6.42 5.48 10.03 3.18 12.58 4.68Industry Sales Year 4 500 5.19 3.24 9.01 11.26 14.07 7.95 22.07 8.20Industry Sales Year 5 525 6.81 3.78 9.46 11.82 14.77 13.04 28.97 8.61

New Sales Dollar Flows from Each Strategy (in $M), assuming[assuming a price of $100/unit (in constant year 1 dollars)](except for low price strategy - $80) (Low Price 5 $80/unit)

Year 1 $33 $14 $92 $61 $60 $11 $150 $56Year 2 $175 $81 $365 $219 $285 $89 $536 $199Year 3 $370 $180 $642 $548 $802 $318 $1,258 $468Year 4 $519 $324 $901 $1,126 $1,126 $795 $2,207 $820Year 5 $681 $378 $946 $1,182 $1,182 $1,304 $2,897 $861

Five Year Sales → $1,777 $977 $2,944 $3,135 $3,454 $2,517 $7,049 $2,4055-Year present value incremental revenue flow from each strategy

(assuming discount rate of 8%) $1,319 $721 $2,212 $2,311 $2,568 $1,810 $5,191 $1,783Adding Costs to the Analysis

New assets employed [investment required (in $M) for strategydevelopment, added capacity, and other strategy-related investment costs]

Year 1 $150 $100 $300 $500 $100 $150 $600 $300Year 2 $150 $100 $200 $400 $200 $150 $500 $200Year 3 $150 $75 $100 $200 $300 $100 $400 $200Year 4 $150 $50 $50 $200 $50 $50 $300 $200Year 5 $150 $0 $50 $200 $0 $50 $200 $2005-Year present value of new assets required for each strategy

(assuming discount rate of 8%) $599 $275 $599 $1,248 $539 $418 $1,658 $647Variable Cost (assumed here to only include Cost of Goods Sold,

with direct costs per unit estimated at $40)Year 1 $13 $6 $37 $24 $30 $4 $60 $22Year 2 $70 $32 $146 $88 $142 $36 $215 $80Year 3 $148 $72 $257 $219 $401 $127 $503 $187Year 4 $207 $130 $360 $450 $563 $318 $883 $328Year 5 $272 $151 $378 $473 $591 $521 $1,159 $3455-Year present value of total variable costs related to each

strategy (assuming discount rate of 8%) $527 $288 $885 $924 $1,284 $724 $2,077 $410

(Continued)

421

TABLE 5Continued

Market Share and Revenue Projections (from previous exhibit)



IndustrySales

1

CaptiveSales

2

MissingColors

3Service

4

LowPrice

5

PriceQuality

6Distribution

7Promotion

8

Total Costs (Present Value of New Assets Employed plus Present Value of Total Variable costs)

Year 1 $163 $106 $337 $524 $130 $154 $660 $322Year 2 $220 $132 $346 $488 $342 $186 $715 $280Year 3 $298 $147 $357 $419 $701 $227 $903 $387Year 4 $357 $180 $410 $650 $613 $368 $1,183 $528Year 5 $422 $151 $428 $673 $591 $571 $1,359 $5455-Year present value of total costs required for each strategy

(assuming discount rate of 8%) $1,126 $563 $1,484 $2,172 $1,823 $1,142 $3,735 $1,058

Calculating and Comparing the Return on Investment for Each StrategyReturn on Investment Comparisons

Total revenue minus total cost $192 $158 $728 $139 $745 $669 $1,456 $725Present value rev./Present value costs 32% 57% 121% 11% 138% 160% 88% 112%

per year 6% 11% 24% 2% 28% 32% 18% 22%Rank order of return → 7 6 3 8 2 1 5 4

Net Sales per Dollar of New Assets Employed(Net sales 5 NPV revenue 2 NPV variable costs) $1.32 $1.57 $2.21 $1.11 $2.38 $2.60 $1.88 $2.12

Rank order of return → 7 6 3 8 2 1 5 4

9A computer program with an integrated tutorial is available to facilitateinitial application of the default version PATHMOD. Please contact the author,if interested.

each operating period on key profile parameters. Treat-ments of data-related methodological challenges encoun-tered in formal data gathering exercises of this sort arereviewed elsewhere [2, 10, 100].

Until the time when the company is comfortable withthe quality of its estimates for the key data driving themodel, attaching uncertainty parameters to model inputsand outputs can help assuage management concerns aboutdata quality and cultivate more confidence in the frame-work. For example, even initial profile estimates can beexpressed in probability ranges, as per the previous dis-cussion of “Adjusting for Uncertain Data.” In this case,the goal of improving data estimates would be to tightenup each range to make modeled outputs more certain.

Analytics Versus Reality: An Operational Compromise

Whereas complexities such as opportunity indepen-dence, strategy timing variations, data uncertainty, andcompetitive reactions can be analytically integrated intothe path marketing analysis framework, attempting to in-corporate all of these extensions when initially trying toapply the scheme may be dysfunctional—yielding results

and inferences which can be cumbersome and difficult todecipher, communicate, and apply. This may defeat thepurpose of the approach, which is to try to add clarity tothe share growth planning process.

Thus, an important caveat for any company wishing totry PATHMOD is to use a phase-in approach. The com-pany should start by applying the default framework forthe company’s more important core business segments,then gradually expanding the application over time to in-clude more and more segments and product lines as fa-miliarity and confidence with the process grows. (Afterstarting with the default version, the various extensionsto PATHMOD described above can be added over timeas a company’s planning team becomes more familiarwith the process and as data quality improves.) In addi-tion to helping the company implement broader-basedapplication of PATHMOD over time, phased-in adoptioncan also help to reduce data quality concerns—as datachallenges can also be met on a phase-by-phase basis.9

422

SUMMARY AND CONCLUSIONS

Putting a formal structure around a difficult problemcan help to identify and clarify its most important com-ponents, thereby making the quest for problem solutionmore systematic, transparent, and manageable. The pur-pose of this article has been to offer a conceptual contri-bution to the formal structuring of market share decisionsby outlining path marketing analysis as a new decisionsupport system for market share planners.

By linking key drivers of market share change in a hi-erarchical framework, the approach outlined can provideinsights for uncovering share growth opportunities, fordeciphering the interrelationships among such opportuni-ties, for projecting specific market share increases likelyto flow from alternative strategies, and for estimating theprospective return on assets employed by alternativeshare growth strategies. Through such benefits, the schemerepresents a potentially valuable new tool for helpingmanagers to better utilize their market knowledge andexperience to develop more efficient and productive mar-ket share growth plans. Ultimately, the value of the ap-proach presented depends upon whether the methodol-ogy does indeed provide a better understanding of marketshare drivers and whether application of the process canhelp companies make better share growth strategy decisions.

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APPENDIX A

Evolution of the Path Marketing Analysis Model

The model described was originally presented in theliterature in its incipient form two decades ago by Weber[112–114]. It was initially referred to as “growth oppor-tunity analysis,” later as “gap analysis,” and finally, to-day, is called path marketing analysis. Over the past 20years, through trial and error application with 200 groupsof managers at over 50 major industrial companies, thespecific components (gaps) of PMA market profiles andthe application of the approach to help plan share growthhave been significantly modified, refined, and enhanced.A number of new uses for the framework have also beendeveloped.

Changes and Refinements of the Model Since Its Original Inception

1. Application of the process is now initiated with bene-fit segmentation.

Application of the approach now begins by overlay-ing traditional macro segmentation with micro benefitsegmentation. Carefully focusing the analysis uponrelatively narrowly defined, homogeneous marketsubsets (benefit segments) facilitates identifying andestimating the size of the different gaps (i.e., sharegrowth opportunities) comprising the market profiles.This segmentation process not only helps in identify-ing, estimating, and interpreting profile gaps [116] butalso helps to clarify the strategic insights flowingfrom the market profiles developed.

2. The approach is now targeted specifically for theanalysis of industrial products in mature markets.

Whereas the framework was originally developedprimarily for application in consumer good markets,the approach has been found to appeal most to compa-nies marketing industrial products in mature markets.Thus, although utilization of the approach can stillyield insights for uncovering and evaluating sharegrowth opportunities for products and services in var-ious industries and stages of the life cycle, the mostimportant modifications and refinements have beenmade in response to the unique challenges faced bycompanies marketing industrial products in maturemarkets.

3. Market profile gap definitions and derivation havebeen significantly modified and refined (new gapsversus old gaps).

Through in-depth discussions and trial and error ap-plications with 200 groups of managers at over 50companies over a 20-year period, many changes andrefinements have been made in the definitions andderivations of the gaps comprising the market pro-files. The definition and estimation of all gaps in theprofile have been refined considerably. A number ofnew gaps have been integrated into the structure tomake the overall framework more complete and moreuseful. More details on the new gap definitions andderivation procedures are presented in the article.Summarizing, these changes and refinements includethe following:

• Usage gaps eliminated. Previously, three usagegaps appeared in the middle of the market profile[114]. Because the process is now intended pri-marily for analyzing mature markets, the revisedframework eliminates usage gaps altogether, thusomitting the consideration of industry sales growthitself as a strategic variable. (Although no longer aprimary use of the model, companies still interestedin using the approach to analyze their market posi-tions and opportunities in immature markets canstill view industry sales as a strategic variablewithin the scheme by adding usage gaps to the topof the market profiles—see [112–114].)

• Captive sales gaps added. After identifying and es-timating industry sales and firm sales for the tar-geted segment, the first gap the strategist now con-siders and estimates is a potential captive sales gap(i.e., sales locked in by competitors over the rele-vant time horizon due to long term contracts, in-house buying commitments, or similar factors).

• Product gaps refined. Next, the planner now differ-entiates between and estimates two different typesof potential product gaps (tangible and intangibleproduct gaps).

• Price gaps refined. Following this comes the con-sideration and estimation of three types of potentialprice gaps (low price and price/quality gaps, and anadditional potential price gap related to deals anddiscounts gap).

• Distribution/awareness gap changed to assess sharegrowth opportunities specifically in business-to-business markets. After this, a distribution/aware-ness gap is identified and estimated using a varietyof procedures that have been developed for assess-ing the unique potential weaknesses (and related

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share growth opportunities) of distribution for busi-ness-to-business products. The new distribution/awareness gap contrasts sharply with the originalmodel, in which this gap incorporated concepts andmeasures appropriate only for assessing distributionof consumer products—i.e., gaps due to weak-nesses in retail coverage, intensity, and merchandis-ing exposure. A variety of new procedures havebeen developed for generating better quantitativeestimates of companies’ distribution weaknesses(gaps) in business markets.

• Direct competitive gap changed into a promotiongap and refined into a more strategically integralcomponent of the market profile framework. The fi-nal gap in the market profile, formerly treated as asimple residual (referred to as the direct competi-tive gap), is now a strategically oriented componentof the profile. That residual is now comprised ofthree separate subgaps (gaps for brand loyalty, mis-perception, and indifference), collectively calledthe promotion gap, since all three of these subgapsare typically addressed most effectively with strate-gies incorporating strong promotion components.

4. The model now incorporates explicit definitions ofgap interrelationships and interdependencies.

The original framework did show how viewing cur-rent weaknesses in the form of ‘gaps’ in a hierarchicalmarket profile can provide perspectives on the rela-tive size of alternative sales growth opportunities[114]. However, it provided only general, descriptiveperspectives for using the framework to estimate whatspecific new sales and market share are likely to beassociated with the alternative gaps incorporated in amarket profile. In the new model, all gap interrela-tionships and gap interdependencies are detailed. Thisenables the strategist using the model to identify pro-spective incremental sales related to each potentialopportunity (gap) in explicit, quantitative terms—instead of in only general, descriptive terms, as underthe original framework. This advance, in turn, yieldsimportant inputs for planners trying to develop an op-timal set of marketing strategies for each of the com-pany’s various product lines and markets.

5. The starting application of the new formulation of themodel is designed specifically to help a company de-termine whether its current set of planned strategieswill enable it to realize its sales and market sharegoals. The model then lays out and facilitates assess-

ing alternative strategic scenarios from which thecompany can choose to enhance its chances of realiz-ing its goals. To provide this perspective, three mar-ket profiles are now developed, instead of one, as un-der the original model.

Under the original framework, only one marketprofile was developed for each product market. Thatprofile was for the current year and gave the firm a snap-shot view of its current weaknesses (gaps) and oppor-tunities. Current gap sizes were the key analytical pa-rameter used in projecting the sales likely to resultfrom closing or narrowing any of the gaps. This pre-sumed a static environment over the planning horizon,essentially ignoring the consideration of potentiallyimportant transitions in factors such as customer de-mand patterns, competitive strategies, technology, theeconomy, or legislative constraints. Thus, in the origi-nal framework, new sales from alternative potentialgap closures excluded the systematic consideration ofpotentially important environmental discontinuities inthe marketplace over the relevant planning horizon.

Under the new framework, the company starts theanalysis by explicitly reviewing its current sales andmarket share goals as well as its current set of plannedstrategies for the targeted product market. The com-pany then uses the approach to assess the likelihoodthat the firm’s stated sales and market share goals willbe met if the company implements its current set ofplanned strategies. This evaluation of current strate-gies is accomplished by developing and interpretingthree sets of market profiles for the relevant segment.The process in accomplished in the following manner.

• The first profile, for the current year, provides thecompany with a snapshot view of relative impor-tance of its current gaps (opportunities), with gapinterrelationships and interdependencies explicitlydefined.

• The company then projects the most likely environ-ment for the near-term future (e.g., three years), fo-cusing upon identifying likely environmental changesthat could affect the company’s sales or marketshare in the relevant product market segment. Fac-tors that could influence the makeup of the firm’sfuture market profile (i.e., gap sizes) are then pro-jected. Among the environmental changes that thecompany should consider as it explicitly projectsthe most likely environment for the relevant seg-ment are potential transitions in customer demand

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patterns, competitive strategies, technology, theeconomy, or legislative constraints.

• A second market profile is then developed for a fu-ture year (usually in 3 years), while assuming theprojected most likely environment, but assuming nonew strategies by the firm. Developing this secondprofile starts by projecting of overall industry salesfor the segment (for year 3). Potential changes inthe gaps that the company faces in its current pro-file are then considered—reflecting transitions inthe environment, but assuming no new strategies bythe firm. The resultant projected profile (in 3 yearswhile assuming no new strategies) subsequentlyserves as the quantitative base for evaluating alter-native planned and unplanned strategies, and esti-mating the incremental sales and market sharelikely to be associated with each. In the new frame-work, therefore, alternative strategies are evaluatednot against where the company is now, but, rather,against where the company would be in the futureabsent any strategy changes.

• The third market profile is then developed to over-lay the second profile with assumptions regardingalternative possible strategies and strategy sets, asrepresented by the various gaps in the second pro-file. Thus, in the new model, sales and share impli-cations of alternative strategies are determined inthe context of the future environment within whichstrategy implementation will actually occur—ratherthan assuming a continuation of the current envi-ronment, as in the original model. The company’scurrently planned strategies (i.e., all strategies plannedbefore trying this new approach) comprise the firststrategy set run through the model.

In the event that the analysis suggests that the com-pany’s current set of planned strategies will not en-able the firm to meet its previously stated sales orshare goals, the framework now enables the user toquickly evaluate alternative strategies and strategysets to uncover potential strategies that will enable thefirm to meets its sales and share goals for the segment.See the next point and the article for additional specif-ics on evaluating alternative potential strategy sets.The article also includes a complete example.

6. More refined perspectives for quickly assessing theimpact that alternative potential sets of strategies arelikely to have upon company sales and market share.

Because gap interrelationships and interdependen-

cies have now been made explicit (reviewed above), asales response factor (see formulae in article) is nowdefined for each strategic opportunity (gap) identifiedin the projected market profile. As a strategy is hy-pothesized (i.e., hypothesizing a gap closure—eitherpartial or total), its impact upon prospective companysales and market share is immediately apparent. Byusing joint sales response factors, alternative combi-nations of strategies (strategy sets) can also be readilyevaluated. Generating and reviewing the projected re-sults of alternative strategy sets is facilitated by usingthe auxiliary spreadsheet-based computer programnow available for the path marketing analysis model(PATHMOD). This computer program enables theuser to hypothesize any combination of possible strat-egies (gap closures) and immediately observe the im-pact on company sales and market share. Overlayingthe computer program with a version manager add-inthat is now an integral part of most spreadsheet soft-ware programs further facilitates reviewing, assess-ing, and recording alternative potential strategy sets.

7. Additional refinement that enhances the benefits ofthe new hierarchical share planning model.

In addition to the changes and improvements withinthe model itself, as reviewed above, application of themodel has now been enhanced in a number of impor-tant ways to make its application more realistic anduseful for strategy planners. Because the formulationsof gap interrelationships and gap interdependencieswere not explicit in the original model, none of thesenew extensions were possible. Some of the improve-ments now incorporated in the application of the newframework are listed here and discussed in the paper(including examples).

• assessment of incremental sales flows over time(rather than for only a single year), including presentvalue analysis;

• accommodation for alternative variations in poten-tial strategic timing when assessing the potentialimpact of alternative strategies;

• consideration of competitive reactions;• capabilities to adjust projected results for uncertain

data estimates; and• for share planners interested in gaining insights vis-

à-vis strategic optimization, incorporation of strat-egy cost flows and integrative benefit/cost calcula-tions of the prospective present value return (ROI)for alternative sets of growth strategy alternatives.

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8. New applications and uses for the extended model.Through application of the extended hierarchical

model with management teams from many differentcompanies over the years, a number of new potentialuses for path marketing analysis have evolved.Among others, these have included the use of the ex-tended and improved framework to help corporate de-cision-makers in the following areas:

• for assessing and planning synergistic marketingbenefits between acquisition partners [117];

• for determining appropriate levels and growth ratesfor marketing and promotion budgets;

• for directing, valuing, and determining the appro-priateness of alternative potential market researchstudies designed to improve the certainty of marketdata estimates [118];

• for developing more focused and effective product,price, distribution, and promotion strategies (i.e.,through the enhancement of the techniques nowused for identifying and estimating the size of vari-ous gaps in market profiles—e.g., better quantita-tive estimates of companies’ distribution gaps).

None of these additional potential uses are explicitlyconsidered in the current study.

APPENDIX BOpportunity Order Does Not Affect Strategic Implications in Path Marketing Analysis

Because of the chain ratio method used to adjust gap sizes, as one moves down the hierarchy of opportunities (gaps), the order in which a specific opportunity appearsin the profile does not affect the incremental served market (ISM) and the potential new sales represented by that opportunity. Therefore, gap order can be modified,if logic dictates, without affecting the primary implications of the hierarchical share planning framework. The table below presents a two-part case exemplifying this.In this example, the distribution opportunity appears in its normal position (after the price opportunity, on the bottom of the unserved market) in one case and at thetop of the profile in the other case. Hypothesizing a strategy to pursue the distribution opportunity (i.e., reduce the distribution gap by one-half in the example) resultsin the same projected ISM in both cases.

The Incremental Served Market Generated by Each Strategy Does Not Change with Alternate Gap Orders

With No StrategiesUnadjusted Gap

Size EstimateAdjusted GapSize Estimate

With Strategies toCut Gaps by 1/2

Unadjusted GapSize Estimate

Adjusted GapSize Estimate

Example #1: With Distribution Gap on Bottom of Unserved Market

1 captive sales gap 10.0% 10.0% 1 captive sales gap 5.0% 5.0%2 size gap 5.0% 4.5% 2 size gap 2.5% 2.4%3 color gap 12.0% 10.3% 3 color gap 6.0% 5.6%4 low price gap 15.0% 11.3% 4 low price gap 7.5% 6.5%5 price/quality gap 5.0% 3.2% 5 price/quality gap 2.5% 2.0%6 distribution gap 8.0% 4.9% 6 distribution gap 4.0% 3.1%

Original unserved market 5 44.10% Resulting unserved market 24.62%Original served market 5 55.90% Resulting served market 75.38%

Example #2: With Distribution Gap on Top of Unserved Market

1 distribution gap 8.0% 8.0% 1 distribution gap 4.0% 4.0%2 captive sales gap 10.0% 9.2% 2 captive sales gap 5.0% 4.8%3 size gap 5.0% 4.1% 3 size gap 2.5% 2.3%4 color gap 12.0% 9.4% 4 color gap 6.0% 5.3%5 low price gap 15.0% 10.4% 5 low price gap 7.5% 6.3%6 price/quality gap 5.0% 2.9% 6 price/quality gap 2.5% 1.9%

Original unserved market 5 44.10% Resulting unserved market 24.62%Original served market 5 55.90% Resulting served market 75.38%

Planning Market Share Growth in Mature Industrial Markets

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