More Success Than Meets the Eye: The Case of M&As in the High-Tech Industry

Abstract

Mergers and acquisitions are staples of the business landscape. On a global basis, companies engage in tens of thousands of deals each year, collectively valued in the trillions of dollars. At the same time, decades of research, predominantly grounded in the finance literature, predicts most deals will fail. These competing ideas of high transaction volume and high failure rate lead researchers to wonder why managers would continue to engage in these deals knowing most are predicted to fail. While some might argue agency theory issues are the answer, the problem is the commonly used assessment measures (e.g., CAR and ROA) are unreliable when trying to determine the success or failure of individual transactions. M&A are complex transactions that may take years to develop value and require a multi-faceted approach for assessment. Using an inductive, theory-building, case study methodology the overarching focus of this study asks, “How does the use of multiple acquisition success measures help to identify M&A success.” This research develops a random sampling of 50 completed Cisco Systems acquisitions and determines and then compares the CAR, ROA, and managers’ subjective assessment outcomes for each transaction. Primary and secondary objectives and insights concerning cultural fit and talent retention are also found. An additional sample of 600 acquisitions from twelve highly acquisitive firms is developed and CAR results for each transaction, each firm, and the whole sample are determined. I organize this research effort into two studies. The first considers limitations of the commonly used academic measures of acquisition assessment and the second considers how a strategy-focused, multi-faceted or holistic approach to acquisition performance assessment might produce a more reliable measure of acquisition success. During the second study I obtain due diligence checklists and primary data through practitioner interviews. The research produces several important findings. The CAR results are not statistically significant and cannot be used to provide an assessment of the sample acquisitions. CAR, which is often used to predict the effect or influence of a piece of information on stock price, is not an effective measure of the success or failure of an individual acquisition transaction and the oft-cited statistics are not an accurate representation of M&A success rates. ROA has limitations in highly acquisitive firms, especially when the acquiring company is larger than the target firm. These findings support the argument by other researchers that suggest the need for another measure and that overreliance on a single success measure produces unreliable results. Additionally, this research offers new insights regarding practitioner assessment criteria, when assessment criteria are developed, and how practitioners assess these deals. More specifically, practitioners determine acquisition assessment criteria during corporate strategy discussions or when developing the business case for a deal. These new insights reinforce the need for a holistic, ex-post assessment to effectively determine M&A success or failure.