A New Approach to Portfolio Matrix Analysis for Strategic Marketing Planning

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A NEW APPROACH TO PORTFOLIO MATRIX ANALYSIS
FOR STRATEGIC MARKETING PLANNING
1

2

Vladimir Dobrić , Boris Delibašić
Faculty of organizational science, vdobric@fon.rs
2
Faculty of organizational science, delibasic.boris@fon.rs
1

Abstract: Portfolio matrix is probably the most important tool for strategic marketing planning, especially in the strategy selection stage. Position of the organization in the portfolio matrix and it’s corresponding marketing strategy depends on the aggregation of values of relevant strategic factors. Traditional approach to portfolio matrix analysis uses averaging function as an aggregation operator. This approach is very limited in realistic business environment characterized by complex relations between strategic factors. An innovative approach to portfolio matrix analysis, presented in this paper, can be used to express complex interaction between strategic factors. The new approach is based on the logical aggregation operator, a generalized aggregation operator from which other aggregation operators can be obtained as special cases. Example of traditional approach to portfolio matrix analysis given in this paper clearly shows it’s inherited limitations. The new approach applied to the same example eliminates weaknesses of traditional one and facilitates strategic marketing planning in realistic business environment.

Key words: Portfolio matrix analysis, strategic marketing planning, logical aggregation, aggregation operator.

1. INTRODUCTION
The portfolio matrix analysis is widely used in strategic management [2, 3, 6]. It offers a view of the position of the organization in its environment and suggests generic strategies for the future. Some of the most frequently used portfolio matrices are the ADL (developed by Arthur D. Little), the BCG (Boston Consulting Group) and the GE (General Electric) McKinsey matrix. Other models that can be considered as versions or adaptations of the original GE McKinsey matrix are the Shell directional policy matrix and McDonald’s directional policy matrix (DPM) that is used in this paper.

The application of any of these portfolio matrices can be, roughly, divided into two stages: the first stage, which includes the analysis of the business position of the organization, and the second stage in which the strategies that should be used in future are recommended based on the estimated position. The difference between aforementioned matrices lies in number and meaning of factors used in the analysis process as well as in the number and generality of recommended strategies. It is common for all the portfolio matrices that the position of the organization in a portfolio matrix is based on estimated values of two factors: the one describing external environment (market attractiveness in DPM) and the other describing inner characteristics of the organization compared to the major competitors (business strengths/position in DPM). On the basis of portfolio matrix analysis , a generic marketing strategy is recommended based on an organization’s position in the portfolio matrix.

In the portfolio matrix analysis, values of two factors describing external and internal environment are estimated as aggregations of values of strategic factors influencing respective environment. The choice of the most adequate aggregation functions depends on the condition in which organization operates, i.e. an aggregation functions describing external and internal environment should have a behaviour which models organization’s external and internal environment conditions respectively. In the traditional approach to portfolio matrix analysis, weighted arithmetic mean is commonly used as an aggregation function. This aggregation operator describes an averaging behaviour, thus, it can be used to model business environment in which high and low values of strategic factors average each other. In the realistic business environment strategic factors can interact in a more complex...
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