Analyzing Merger and Acquisition Opportunities: A Role for Intellectual Capital

One of the critical unanswered questions in knowledge management (KM) and intellectual capital (IC) studies is an empirical link to improved organizational performance. Everyone who works in the field is probably convinced that identifying, cataloguing, and then better managing knowledge assets will benefit a firm. But efforts to empirically demonstrate this relationship have been mixed, at best, and demonstrate a decided lack of agreement on approach, variables, and, ultimately, the true meaning of the results. This paper begins to address these issues and, indeed, establishes that a firm's level of intellectual capital may very well be correlated with financial performance. Moreover, the relationship is less statistical than experimental, so with a big enough data set, the approach could infer causation. Making an identifiable strategic decision based on objective intellectual capital data, executing the strategic decision at a distinct point in timer, and incorporating pre- and post-event financial data can be defined as a field experiment with high external validity. It's a different approach to some of the previous approaches that attempt to draw statistical correlations at a point in time, but the longitudinal structure avoids some difficulties with previous empirical work looking demonstrate the link between IC and financial performance. The specific approach of the study is obtaining IC metrics from firms announcing a merger & acquisition action (here, Tobin's q). Those metrics identify firms of interest to later collect financial results, specifically marketing capitalization, both pre- and post-merger. The results demonstrate that specific IC circumstances can predict financial outcomes, essentially locking in the knowledge asset and financial performance relationship. Further research is necessary to uncover the details of that empirically demonstrated relationship. But establishing the empirical is a key result for the full disciplines of both IC and KM. It essentially demonstrates why we all work and believe in these fields. The methodology can also prove extremely useful for practitioners, specifically as an investment strategy. Consequently, this paper explains the investment approach as that is easiest to understand. The results, making an investment decision based on pre-M&A metrics and evaluating its success, are both positive and significant. And, again, as an experiment rather than a statistical demonstration of correlation, have a more substantive conclusion. Again, the results are important for the investment community as a financial strategy and, ultimately, for the KM and IC community as a demonstration of the importance of the fields to the financial performance of the firm.