Profit Impact of Marketing Strategy - A Critique of PIMS

A Critique of PIMS

Clearly, it could be argued that a database operating on information gathered in the period 1970 - 1983 is outdated. However data continues to be collected from participating companies and PIMS argues that it provides a unique source of time-series data, the conclusions from which have proven to be very stable over time.

It has also been suggested that PIMS is too heavily biased towards traditional, metal-bashing industries, such as car manufacturing; perhaps not surprising, considering the era in which the majority of the surveys were carried out. In reality, as of 2006, the 3,800+ businesses contained within the database includes data from the consumer, industrial and service sectors.

It is also heavily weighted towards large companies, at the expense of small entrepreneurial firms. This resulted from the data collection method used. Generally only larger firms are prepared to pay the consulting fee, provide the survey data, and in return have access to the database in which they can compare their business with other large businesses or SBUs. Mintzberg (1998) claims that because the database is dominated by large established firms, it is more suitable as a technique for assessing the state of "being there rather than getting there". (page 99)

A serious theoretical criticism has also been mentioned. An empirical correlation does not necessarily imply cause. There is no way of knowing whether high market share caused the high profitability, or whether high profitability caused the high market share. Or even more likely, a spurious factor such as product quality could have caused both high profitability and high market share.

Tellis and Golder (1996) claim that PIMS defines markets too narrowly. Respondents described their market very narrowly to give the appearance of high market share. They believe that this self reporting bias makes the conclusions suspect. They are also concerned that no defunct companies were included, leading to "survivor bias".