Recent merger and acquisition activity is at an all-time high and shows little sign of slowing down. While the right acquisition can unlock value and innovation, identifying the wrong target organization or failing to retain talent post-acquisition can scuttle any hope of merger success.
Whether acquiring new capabilities to keep pace with the competition or expanding to meet the needs of your customers, leaders often have limited information about the skills required in the new markets or segments, and whether their acquisition target has the right talent bench.
Using advanced analytics enabled by greater computing power, executives can leverage a wide range of data when considering and undergoing a merger, including information from external sources previously overlooked because they lacked the capacity to collect, clean and analyze. Here’s how advanced analytics can help in talent recruitment and retention:
In one recent merger, a conglomerate acquired a technology company to build its Internet of Things capabilities. During the merger, it used advanced analytics in three stages.
In order to attract additional high-tech talent to make the deal pay off, it applied analytics to publicly available data for employees at companies with a strong IoT presence to determine what skills were essential for success.
Then, the company analyzed the local talent pool outside the company to determine how many people had the skills required for critical positions. This revealed that it would need to attract 85 percent of local hires to fill essential roles—a difficult if not impossible task.
The company used advanced analytics a third time to determine which colleges could provide talented entry-level employees to fulfill long-term demand and build up their talent pipeline. These talent insights and resulting strategy would be impossible without advanced analytics.
An IT services company took a similar approach when identifying the right company to acquire, given its desire to strengthen its presence in a complex, high-growth and high-margin area of the IT services market.
Many of its target companies were small and opaque—making it unclear which was best positioned for the future. However, the company used analysis to compare LinkedIn profiles of staff from target companies to talent from successful competitors.
This method allowed the acquirer to notice key differences in background, skillset and experience level between their target organizations’ account managers and those at successful companies in the space.
The company therefore focused on companies with a high presence of skills correlated with success as M&A targets. After completing an acquisition, this work also enabled a clear and targeted retention strategy, focused on those employees crucial to drive deal rationale and protect deal value.
It’s not enough to identify the best employees and hire them—companies also must retain them, and that’s challenging during a merger when many staff begin looking for new jobs because they fear change or don’t see a future with the new business.
In our experience, companies that don’t undertake extensive retention efforts often lose up to 70 percent of their senior managers in the first five years after a merger—about twice the attrition rate for companies that haven’t undertaken deals.
With advanced analytics, companies can create more targeted retention plans using external data to provide important clues. For instance, data scientists could analyze LinkedIn profiles to determine how often current employees are updating their information or to measure the level of detail in their profiles. Employees with recently updated profiles, or those who include very lengthy descriptions of their skills, are most likely looking for jobs.
As recent M&A activity and acquisition premiums hit historical highs, we see new opportunities to use the power of advanced analytics to drive larger and accelerated impact in delivering value creation post-acquisition.