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Applying advanced analytics to accelerate value creation in M&A

Advanced analytics techniques can enable better decision-making for merging companies.

Optimizes organization design, culture, talent management, and advanced analytics across multiple geographies and sectors through complex merger integrations to help executives capture value to drive synergies and growth.

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.

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