A Blog by Jonathan Low


Jul 24, 2019

How Leaders Use Analytics To Add Value and Retain Talent In M and A

There are many good reasons why between 70% and 90% of mergers and acquisitions fail to achieve their operational and financial goals.

Inability to effectively analyze market opportunity, asset value and, especially, talent base are frequent deficiencies. Advanced analytics are now providing means by which leaders can optimize their strategies. JL

Lena Koolman,Ali Korotana and colleagues report in McKinsey:

“Good assets poorly run” is the phrase used when describing an acquisition target. The assets may be physical like machinery (or intangible) like employees. Companies that don’t undertake retention efforts can lose 70% of their senior managers in the first five years after a merger, twice the attrition rate for companies that haven’t undertaken deals. Whether acquiring new capabilities to keep pace with competition or expanding to meet the needs of customers, leaders often have limited information about the skills required in the new markets. Mergers are distracting and can disrupt a company’s business. Amidst the chaos, analytics can accelerate timelines.
When a company makes an acquisition, the CEO and steering committee embark on a path to integrate the businesses in a “glitchless” manner, hopefully creating value, retaining talent and aligning cultures to form an effective company. The long-standing and well-documented integration approach works, but it often takes many months or even years to complete the integration.
To ensure value creation is accelerated and sometimes increased, acquirers can more rapidly integrate by applying advanced analytics techniques already used in organizational transformations. In applying these techniques, they can more easily manage vast amounts of information coming from merging companies. More effective and timely use of data enables better decision-making, which allows organizations to meet tight deadlines for integrating functions and processes inherent in every deal.
We examined potential gains in 200 companies that applied analytics to solve pressing business problems, focusing on those likely to crop up during M&A. We determined whether advanced analytics could help merging companies in four activities: (1) improving talent management, (2) accelerating time to impact, (3) developing predictive capabilities, and (4) increasing asset effectiveness. Here are a few of our insights:
Improving talent management
Acquiring companies may have little information about the workforce they inherit, including what roles and employees are creating value and what skills are required to compete. That may cause talent gaps in critical areas.
Using advanced analytics, companies can move beyond traditional talent acquisition, development and retention strategies. In a recent acquisition of a technology company by a conglomerate, online publicly available professional networks were scraped to identify behavior indicating a higher chance for talent flight and targeted talent retention measures implemented. In addition, having identified the top 10-20 critical roles required to drive the new combined organization’s performance objectives, advanced analytics could be used to ensure the right talent holds those roles. Without the right talent, a company’s strategy will be significantly impeded.
Accelerating time to impact
Mergers are distracting to all involved and can disrupt a company’s business. Advanced analytics can help companies improve some of their most important operations and business processes. Even amidst the chaos of a merger, advanced analytics has the power to accelerate timelines.
For example, in many industries merging companies have extensive, costly product development pipelines. Data analytics can weed out weaker product development candidates more rapidly by estimating expected effectiveness results across merging entities. The combined entity can then allocate its R&D spending more effectively soon after close. Accelerating product development timelines by a few months can be worth significant value, especially in markets where innovation is critical.
Developing predictive capabilities
Before a deal closes, top management has limited insight into many of the most important aspects of their target. Such knowledge gaps may compromise forecast accuracy and inhibit their ability to make fact-based decisions.
Advanced analytics can sort through the confusion to obtain better insights—and one area in particular where this is needed during an integration is customer retention. In one case, a retail bank was experiencing increased churn following a merger. Using advanced analytics, it was able to identify the underlying drivers of churn, create targeted retention strategies and reduce the churn rate by 20 percent.
Increasing asset effectiveness
“Good assets poorly run” is the phrase often used when describing an acquisition target. The assets in question may be physical assets like machinery and factories but could also include employees or functional groups.
Applying advanced analytics, asset effectiveness is taken to a level unachievable with traditional levers. One chemical company used advanced analytics to improve high variability in throughput and low overall output. After assessing 40 million data points, the company developed a model that enabled a 20-30 percent increase in output and an estimated EUR 30 million benefit. These levers today still often go unused when merging entities.
Tried-and-true strategies for merging companies will get the job done, but introducing advanced analytics into the equation will likely accelerate and increase value creation. We examine in the next post examples where advanced analytics was applied to talent management during mergers, creating real value.
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:
Talent acquisition
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.
Talent retention
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.


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