Future vision of M&A automation

I would like to present the future vision of M&A strategy. Well, to be honest, it is a vision of the near future since we will only leverage technologies that exist today but are not used for M&A strategy at the moment.

Let us assume the vision gets implemented in a solution called StrategyBot. StrategyBot uses a library of successful strategies and business models. It also leverages machine learning and generative market model computing. Here is an outline of the functionalities of StrategyBot. Enjoy.

Real-time M&A strategy

StrategyBot´s data are provided in realtime, and the functionality of StrategyBot automates most of the tasks of the M&A strategy phase. Hence, it can provide evaluation and creation of strategies in real-time. It will provide updates of the strategic position of a company and propose appropriate strategic actions on an ongoing bases. All is based on on realtime data of the company, its markets, suppliers, customers, partners, competitors. Here´s how it works.

Determine the status quo of the buyer and getting ready for M&A strategy planning.

StrategyBot works on the basis of a dataplane and creates an initial status of the buyer company. It assembles, aligns and connects data from different data sources like the company´s ERP system, market data, data about competitors, partners, channels patents etc. to create a unified view of where the company stands. It also integrates data about customers and customer sentiment.

Drafting the growth strategy

You set a growth goal, e.g. a certain increase in revenue of 45 percent over the next two years. StrategyBot diligently analyses a variety of potential areas for growth and strategically proposes actionable steps based on a comprehensive set of data regarding the company, its customers, relevant economic outlook data, and competitive dynamics within the industry. Through a thorough examination of the scalability of the company’s business model, its operational model, and various distribution channels, StrategyBot offers well-informed recommendations and measures designed to effectively reach the established goals and objectives.

If there are limitations to reach the goals organically, genetic algorithms are used to determine strategic moves that are needed within or outside of the company to reach the goal. Should StrategyBot proposes an inorganic move.

Evaluating the inorganic growth strategy

Again, StrategyBot effectively leverages a large amount of data collected about the successful execution of various strategic moves. By combining this information with advanced genetic algorithms and machine learning techniques, it is able to select and meticulously detail out the strategy that is most likely to succeed. Essentially, it provides insights into which forms of growth are realistically possible based on the current status and performance of your company.

Finding and selecting the right target

In a next step, StrategyBot diligently checks thousands of companies operating within adjacent markets, as well as those in remote sectors, while also exploring entities both up and down the entire supply chain. Through this extensive analysis, it determines their overall willingness to be acquired and identifies various strategic approaches for how to effectively acquire the company. t predicts the likelihood for a deal to succeed.

Summary

As an M&A professional, you should be aware that the singularity of massive AI-based automation is upon us. The technology exists, it just has to be applied to the M&A process. So, the race is on and we will see who will get there first.

This relates to my new book “Automation of Mergers and Acquisitions“.

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