Critique of theory Underpinning GE Matrix

Portfolio analysis provides management with information on aspects such as entry into new markets, allocation of scarce resources to business units and liquidation of units that destroy an entity’s value (Nipper, Pidun & Rubner 2011; Kotler et al. 2005, p. 60). One of the models developed to help managers in portfolio management is the Mckinsey/ General Electric matrix. Although GE matrix offers a more comprehensive approach compared to predecessors such as BCG matrix, it has drawbacks such as vulnerability to manipulation and failure to recognize the role of external markets in financing business expansion (Kotler et al. 2005; Nipper, Pidun & Rubner 2011). This paper offers a critique of the theory behind Mckinsey matrix and discusses its suitability for evaluating Yahoo Inc.’s product portfolio.

Critique of Theory behind GE Matrix

Mckinsey/GE matrix arose from Mckinsey & Company’s analysis of General Electric’s wide product portfolio in the 1970’s. It is a two-dimensional nine-block matrix used to evaluate a business unit’s value to the entity (Pidun et al. 2011; Peters 1993). One of the dimensions evaluates industry attractiveness whereas the other evaluates the strength of the business unit (Peters 1993). Each of the dimensions has three rating levels – high, medium and low. A business with a high rating on industry attractiveness and a high rating on investment implies that the entity should invest its best resources in such an entity (Peters 1993; Kotler et al. 2005, pp. 62 – 63). The decisions concerning business units/products falling on other sections of the grid are as represented in figure 1 in the appendix.

The GE matrix and its growth-share matrix predecessors are outcomes of extending financial-portfolio theory to product management. Financial portfolio theory argues for the balance that an entity should maintain given the investments’ return/risk analysis (Cardozo & Smith 1983). A prudent investment strategy combines high risk-high return and low risk-low return investments (Markowitz 1952). Extending the application of financial theory to product management, are findings such as those by Cardozo and Smith (1983) indicating that product lines and business units have similar characteristics to financial investments; i.e. products with a higher risk have higher returns. Such risk and return concept is translated into growth and share terms, a high growth and a high share product/unit being recommended for more investment of an entity’s resources (Day 1977; Pidun et al. 2011). However, various aspects highlight the limitations of growth-share matrices in informing strategic decisions.

One of the criticisms of growth-share matrices is oversimplification of complex strategic decisions of multi-unit entities. Use of few proxies e.g. market growth and relative market share as the sole proxies to quantify market attractiveness and competitive position have been argued to affect the reliability of such models in informing strategic decisions (Nippa, Pidun & Rubner 2011). GE matrix attempts to address this by incorporating multiple factors in constructing its indices. GE matrix thus offers more information about a unit compared to models such as the BCG matrix (Wind, Mahajan & Swire 1983).

A second criticism relates to underlying assumptions of growth-share matrices. Most significant assumptions relate to the concept of market share. For market share to represent relative performance, the models assume a similarity in overhead costs and experience curves for all competitors; hence, the position of each competitor on the experience curve corresponds to the competitors’ position in the market (Day 1977, p. 31). However, various aspects such as differences in technological endowment among competitors influence the cost structures (Day 1977). Thus, a unit’s poor performance may be due to its relative disadvantage in investment in technology rather than its potential to enhance business outcomes. Accordingly, the criticism in this regard has been that the matrices do not examine a unit’s risk, competitive expectations and capabilities adequately (Devinney & Stewart 1988).

The GE matrix also enhances vulnerability to misapplication – inappropriate or inadequate application – by managers. The wide scope of interpretation for measures included in the GE matrix’s indices could lead to managers manipulating the measures to indicate a favorable position for their unit (Nippa, Pidun & Rubner 2011; Pidun et al. 2011; Day 1977). Alternatively, managers could misinterpret or casually apply the generic recommendation exhibited by the matrix (Pidun et al. 2011). This leads to ill-informed strategic decisions that may result into substantial business losses in future where the entity divests from a unit that is a victim of inappropriate application.

Finally, GE matrix, as other growth-share matrices, disregards the role of external markets in generating funds for business expansion (Nippa, Pidun & Rubner 2011). The matrix opines that resources freed from divesting or harvesting low-rated units are used to invest in high-rated products (Wind, Mahajan & Swire 1983; Day 1977). Accordingly, the matrix disregards the importance of using external markets to fund growth into new markets. Such growth may be necessary for products that are performing poorly due to saturation in one market but have potential in new markets.

Various aspects limit the application of GE matrix in Yahoo business. For instance, most of the entity’s segments are interrelated in that they use a similar approach (displaying of advertisements) to generate revenue for the entity. Accordingly, determining aspects such as the specific market share for each of these sections is challenging. Existence of entities that operate in the ads market whose traffic does not appear in the ranking by tracking entities such as Alexa, for instance limit the determination of the market size for ads.

Conclusion

GE matrix is provides a better tool for accessing product portifolio compared to BCG matrix by incorporating various components in its metrics for industry attractiveness and business strength. However, it has drawbacks such as its susceptibility to misapplication, assumption that fail in some scenarios, and its disregard of external sources of financing. Further, the application of the matrix is limited in entities such as Yahoo where the products offered are interrelated. Accordingly, use of GE matrix should be to complement rather than replace strategic decision-making process.

References

Cardozo, RN & Smith, DK 1983, ‘Applying financial portfolio theory to product portfolio decisions: an empirical study’, Journal of Marketing, vol. 47, no. 2, pp. 110 – 119, viewed 1 April 2012, < http://www.jstor.org/stable/1251498>.

Day, GS 1977, ‘Diagnosing the product portfolio’, Journal of Marketing, vol. 41, no. 2, pp. 29-38, viewed 1 April 2012 < http://www.jstor.org/stable/1250631>

Devinney, TM & Stewart, DW 1988, ‘Rethinking the product portfolio: a generalized investment model’, Management Science, vol. 34, no. 9, pp. 1080-1095, viewed 2 April 2012 <http://www.jstor.org/stable/2632071 >.

Kotler, P, Wong, V, Saunders, J & Armstrong, G 2005, Principles of Marketing, 4th European edn., Pearson Education Limited, Essex.

Markowitz, H 1952, ‘Portfolio selection’, Journal of Finance, vol. 7, no. 1, pp. 77-91.

Nippa, M, Pidun, U & Rubner, H 2011, ‘Corporate portfolio management: appraising four decades of academic research’, Academy of Management Perspectives, November, pp. 50 – 65, doi.org/10.5465/amp.2010.0164

Pidun, U, Rubner, H, Krühler, M & Untiedt, R 2011, ‘Corporate portfolio management: theory and practice’, Journal of Applied Corporate Finance, vol. 23, no. 1, pp. 63 – 76.

Peters, J 1993, ‘On product and service management,’ Management Decision, vol. 31, no. 6, pp. 49 – 51.

Wind, Y, Mahajan, V, Swire, DJ 1983, ‘An empirical comparison of standardized portfolio models’, Journal of Marketing, vol. 47, no. 2, pp. 89-99, viewed 02 April 2012 < http://www.jstor.org/stable/1251496>

Appendix

Portifolio management decisions based on GE Matrix

Business Strength
Market attractiveness High Medium Low
High Deploy best resources(Green) Build Share(Green) Invest with care(Amber)
Medium Defend Share(Green signal) Monitor(Amber) Niche(Red signal)
Low Harvest(Amber) Divest or harvest(Red signal) Direct(red signal)

Source: Peters, J 1993, ‘On product and service management,’ Management Decision, vol. 31, no. 6, pp. 49 – 51.

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