Deloitte M&A focus on: Analytics
Utilizing data analytics in post-deal integration
The increasing use of data analytics has made it a powerful tool throughout the merger and acquisition (M&A) deal lifecycle. The insights gained from data provide for a deal-making advantage, especially during the integration stage. Discover how analytics may help unearth potential risks and hurdles to successful integration and post-deal execution.
- How data shapes post deal details
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- About the survey
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How data shapes post-deal details
By Anna Lea Doyle, principal, Deloitte Consulting LLP
The rising use of technology-driven data analytics has altered the merger and acquisition (M&A) deal-making marketplace. We have seen how insights gleaned from deep data can help identify targets, confirm assessments of financial conditions and predict business trends.
Responses from our recent survey, “Deloitte M&A focus on: Analytics,” showed that two-thirds (68 percent) of corporate leaders surveyed use data analytics as part of their M&A analysis—and 64 percent say they have increased their use of analytics significantly or somewhat. Use of M&A data analytics has risen steadily in recent years and more than eight in 10 respondents see data analytics becoming increasingly important to M&A activity in the future.
But increasingly, deal-makers are turning to analytics to help unearth potential risks and hurdles to good integration and post-deal execution. For example, we have seen the use of automated natural language processing to assess the intellectual property of an acquisition target, and to cross-reference those findings with other databases. This aids an acquiring company in evaluating the stability of the intellectual property of an acquisition target, and can help avoid potential litigation or regulatory pitfalls.
Another application is the use of analytics to clarify the nature of various contracts and legal arrangements that exist between an acquisition target and its clients, suppliers, and others. A page by page review of such documents used to take hundreds of expensive man hours. Today, with advanced digital analytical tools, such a review can be done automatically, and provide instant awareness where critical terms of any contract, such as indemnification, may not align.
Another powerful application is the use of deep data to analyze the talent pool of a potential target. In fact, using analytics to better understand the target’s workforce and compensation structure is the second-most frequent application of data analysis, according to our survey, with 55 percent of respondents saying they had used it for that purpose.
It’s not hard to understand why in an economy, where talent is often the most significant asset of any organization, it is critical for any deal maker to understand who is working, who is managing, and who poses the greatest likelihood of leaving after a deal is consummated.
Advanced analytics open a window into any workforce, helping to reveal critical demographic features, patterns of employment, and potential risk factors. The potential for talent flight is often overlooked in a transaction, but thanks to analytics, that risk can be better understood and possibly accounted for in advance talent management strategies.
Also valuable are insights into how the acquisition target will mesh with new owners and managers. While deep data will not reveal whether two corporate cultures will clash, they can often reveal if the ratio of managers to employees is out of proportion, or if the compensation structure of either firm is far different than the other.
We have seen, at times, that an acquirer would be taking on an organization whose pay scale was noticeably higher than its own. The result would have been deeply challenging: The acquirer would have either had to raise its labor costs noticeably, or take the target’s wage scale down. Neither option is easy to do, and, without the advanced warning revealed by the use of analytics, both could have dramatically changed either organization.
Considering the potential risks of a transaction involving a mismatch of organizational cultures and workforces, this kind of analysis can be essential. It is no surprise that the largest players in the M&A marketplace (those with five billion or more in revenue) regard data analytics as a core component of their approach—58 percent said so, and an additional 19 percent said data analytics plays a role in select areas of their M&A activity.
Our view is that interest will likely increase as organizations recognize that a mismatch on talent—among many potential risks—can potentially destroy much of the value of a transaction, often no matter how well conceived. We expect analytics to have that same value in an increasing number of areas of the M&A marketplace in coming years.
About the survey
In December 2015, we surveyed 500 corporate leaders at large US companies about analytics. Those surveyed were at the director level or above at companies with at least $10 million dollars in revenue.
View the full survey results on SlideShare.
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