The attractiveness/advantage matrix (GE/McKinsey)

The Attractiveness/Advantage Matrix helps a diversified business compare its principal segments and decide where to invest, hold, harvest, enter or withdraw.

When to use it

• Use it whenever the organisation must evaluate and rebalance a portfolio of product-market segments.

Origins

The matrix emerged from General Electric’s portfolio-planning work with McKinsey and other advisers during the late nineteen-sixties. That programme also advanced the strategic-business-unit concept and the PIMS database, which ultimately represented ‘25,000 years of business experience’. Unlike simpler growth-share tools, the GE/McKinsey matrix combines several measures of market attractiveness with several measures of competitive strength.

What it is

The model answers two linked questions: how attractive is each segment, and how strong is the organisation’s position within it? Attractive segments in which the company holds a strong advantage are natural investment candidates. Weak positions in unattractive markets suggest harvesting or exit. Possible new segments deserve attention only if they are attractive and the company has a credible path to advantage.

The two dimensions are composites rather than single statistics. This makes the analysis richer, but also introduces judgement about criteria, scoring and weights.

How to use it

First define market attractiveness. Criteria should reflect the sector, but a useful starting set is:

• market size relative to other segments;
• forecast demand growth;
• competitive intensity, including entry barriers and other industry forces;
• average industry profitability; and
• market risk, including cyclicality, volatility and country exposure.

Size, growth and profitability generally increase attractiveness; intensity and risk reduce it. Check for double counting: growth influences rivalry, rivalry affects profitability and risk may already be reflected in returns. Choose weights deliberately. Equal weights are transparent, while a risk-averse organisation may assign more importance to the risk criterion.

Consider four current segments and one possible entry:

Market attractiveness: an example

Key to rating: 1 = Unattractive, 3 = Reasonably attractive, 5 = Highly attractive

Reverse the interpretation for competition and risk: a more intense or riskier market receives a lower attractiveness score. In the example, D ranks highest, followed by prospective segment E, while B is comparatively unattractive. The simple averages favour clarity; weighted averages may better reflect strategy if the rationale is explicit.

Next retrieve the competitive-position score developed in Rating competitive position and plot each segment. For example, A combines a competitive-position rating of 4.0 out of 5 with attractiveness of 2.8 out of 5.

The Attractiveness/Advantage Matrix: an example

Colour key

Current segment

1 Weak

2 3

Competitive Position

4 Strong

New segment

Note: Diameter of bubble roughly proportional to scale of current profit (except for E)

Sources: General Electric, McKinsey & Co. and various

The horizontal position shows competitive strength, the vertical position market attractiveness and the bubble size the segment’s approximate operating profit. Positions near the upper right support investment. Those below the lower-left diagonal point towards harvest or withdrawal. Middle-diagonal positions normally justify selective holding and close scrutiny.

In this example, A and C support steady development, D warrants investment, E merits deeper entry analysis and B is a candidate for harvest or exit. Use the result to ask which major segments generate the portfolio’s value, where a stronger position would matter most, whether promising adjacencies exist and which businesses no longer justify resources.

Top practical tip

Make every criterion, weight and score explicit, then test how robust the portfolio conclusion is to reasonable alternative assumptions.

Top pitfall

Composite scores can create false precision. Subjective definitions, weights and ratings may drive the recommendation more than the underlying market evidence.

Further reading

• Wind, Y., Mahajan, V. and Swire, D.J. (nineteen eighty-three). “An Empirical Comparison of Standardized Portfolio Models.” Journal of Marketing.
• Hax, A.C. and Majluf, N.S. (nineteen eighty-four). Strategic Management: An Integrative Perspective. Prentice-Hall.