Rapid, Robust Screening of Potential M&A Targets: AI Shows the Way

In my last M&A blog, I spotlighted how advanced analytics can accelerate and optimize acquirers’ due diligence activities. But the need for greater speed and efficiency kicks in at an even earlier stage of the merger process. In fact, it plays a vital role right from the outset. Find out how cutting-edge artificial intelligence (AI) can handle the heavy lifting during the shortlisting phase – helping you slash costs and rapidly pinpoint more, higher-quality M&A targets.

The Challenges of M&A: Yesterday and Today

Whether you’re looking to hone your company’s competitive edge by adding digital assets or by enhancing more conventional capabilities, one of your first tasks in any M&A project will be to draw up a list of candidates. Of course, the challenges of shortlisting – from identifying promising companies through to ranking them – are nothing new. What has changed in recent years is that these tasks now have be performed faster than ever before.

Traditionally, prospective acquirers have called in investment bankers to prepare painstakingly researched lists of potential acquisitions. That’s good news for the bankers, but expert services of this kind carry a hefty price tag. So, it’s hardly surprising that businesses are increasingly seeking solutions that can accelerate their shortlisting process and cut associated costs.

Shortlisting Can Make or Break Deals

While the heavy-duty number-crunching of the due diligence phase is rightly regarded as key to successful mergers, it’s worth remembering that shortlisting also plays a pivotal role. Recent research by McKinsey has revealed that some 10% of large-scale M&A deals are canceled each year – with mismatched expectations regarding synergies contributing significantly to these failures.

One way of sidestepping issues of this kind is by increasing the number and quality of shortlisted targets. To align expectations with reality, companies need to formulate unique evaluation selection criteria derived from their unique acquisition strategy and apply these to planned acquisitions. What’s more, they must create a robust shortlist by screening possible candidates from both a market and investment perspective. But how can they do this without driving up costs?

AI Meets M&A

The answer is provided by state-of-the-art artificial intelligence (AI). During the shortlisting phase, sophisticated statistical algorithms can sniff out not only key terms but also important trends and patterns inherent in mountains of data. This enables companies to quickly and easily categorize large lists of targets in line with their specific criteria.

AI solutions of this kind can automate a substantial portion of the shortlisting process. By eliminating the need for time-consuming manual activities and costly external experts, they radically reduce potential buyers’ spend in the run-up to a merger and free up internal resources to focus on analyzing outputs. But that’s not all: They also promise to deliver significantly better target lists. So, just how do they achieve this?

 

When it comes to scrutinizing targets over time, AI algorithms have many clear advantages over traditional approaches. By supporting real-time tracking of potential acquisitions, for example, they give acquirers a multi-dimensional perspective, enabling them to better assess how companies are likely to respond to shifts in their business and economic environment, providing an invaluable basis for sound shortlisting decisions.

Pinpoint Trends in Vast Data Volumes

Another major advantage of AI is its power, which allows companies to delve far deeper into the wealth of data now available on targets and the markets in which they operate. Though computer-assisted trend analysis has been around for some time, the advent of AI has made it possible to bring together and evaluate multiple correlated data sources and discern patterns that would be far from obvious in individual datasets. What’s more, AI does this far faster than humans could ever hope to.

Traditional approaches also fall short of the mark when it comes to gauging the potential of small, private targets. Here, too, consolidated datasets coupled with integrated analytics and AI can help companies spot possible acquisitions faster and more efficiently than would otherwise be possible. Research by Accenture puts the associated time-savings at between 50 and 60%.

Leverage AI to Chart Your Course to Successful Deals

In today’s rapidly evolving business environment, M&A is essential to maintain and enhance competitive edge. But all too often, poor target selection puts paid to budding deals. State-of-the-art AI can help you quickly and easily master your shortlisting challenges, paving the way for successful mergers and acquisitions.

If you’re considering a merger and are looking for tools that can accelerate and enhance your target selection, AI could be just what you’re after. Feel free to reach out to me, if you’d like to find out more about how this tech can support your M&A endeavors.

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