PIMS is a statistical model that investigates the relationship between strategic variables and profitability of companies. It was the result of the initiative taken at General Electric in the 1960’s under the leadership of Sidney Schoeffler.
This model relies on empirical data across various industries to study the impact of various strategic variables on profit volumes of organisations. It was a major breakthrough in the field of marketing studies in that it relied on a verifiable method of empirical analysis using regression techniques as opposed to bald conceptual frameworks not supported by hard data from the industry. The model is an endeavour to generalise the strategic determinants of profitability without disregarding the peculiarities of a given market terrain.
The PIMS study lends predictability to strategic decision making. It relies on ROI as a key criterion of strategy choices. The most important aspect of the model is the variables it uses in analysing the impact on profitability of strategic decisions. The nature and number of variables used in the analysis is an on-going development. They can be broadly divided into 2 types: Market related variables and non-market related variables (1).
Market related variables include aspects such as market share, relative market share, pricing, product quality etc. Non-market variables include factors such as R&D expenditures, investment intensity, technological development, labour productivity (2).
Some of the key findings of PIMS are that High market share leads to high profitability. This has been the most studied finding of the PIMS project and has been confirmed in subsequent studies (3).
The model also reports a positive correlation between product quality and profitability as also between employee productivity and profitability. As regards, capital intensive initiatives, it finds that capital intensive strategies are characterised by low return on investments (4). A normative implication of this finding is that labour productivity ought to be the focal point for strategic decisions as opposed to heavy investment in machinery or technology.
While the generalisation afforded by the vast database of the PIMS project is attractive and indeed useful, it must be taken with a pinch of salt. One general criticism of the PIMS model is that the model fails to make any clear distinction between causal relation and co-incidence. However, this criticism seems to disregard the essential nature of empirical analysis on which the model relies. However, there is some merit to the apprehension that confusion between causal relation and mere co-incidence can be misleading (5).
Another important criticism is the multi-colliniarity of the variables. It means that the variables used may affect each other and hence are not independent. This problem is widely acknowledged to be implicit in the model (6). However, notwithstanding the limitations, the robust database on which the model rests is certainly of great value in strategic decision-making. The model coupled with sharp awareness of market peculiarities is still a critical source of input for managers.
1. Schnarrs, ‘Marketing Strategy: A Customer driven Approach’ The Free Press (1991)
2. C W Roney, ‘Strategic management Methodology’ Praeger Publishers (2004)
3. See: Szymanski et al: ‘An analysis of Market share-Profitability Relationship’ J. Mark (1993) 1-18
4. Ghemavat & Caves, ‘Capital Commitment and Profitability: An empirical analysis’ Oxfor Economic Paper, New Series Vol. 38, Nov 1986 (94-108)
5. John O’Shaughnessy, ‘Explaining Buyer Behavior: Central Concepts and Philosophy of Science Issues’ OUP (1992) [32]
6. See: Challenges and Perspectives in using PIMS Methodology to explain the success of marketing strategy in business’ available at http://www.scielo.org.mx/pdf/cya/n234/n234a5.pdf