M&A Strategy: using Machine Learning, Natural Language processing and analytics already today
There is ongoing discussion surrounding the utilization of technologies such as machine learning, natural language processing, and analytics in the context of mergers and acquisitions. However, there is a noticeable lack of information regarding the specific timing and methods for implementation in this field. In this blog you will learn which of these technologies are already being used by tools for M&A strategy.
I have extensively researched a total of 40 tools specifically designed for M&A strategy purposes. Each tool's technology has been meticulously categorized to align with various essential tasks involved in mergers and acquisitions.
Analytics
Analytics involves the systematic exploration of data to extract insights and patterns that can inform decision-making. Through the use of statistical analysis and computational techniques, analytics enables organizations to uncover valuable information hidden within large and complex datasets. It plays a crucial role in various fields, such as business, finance, healthcare, and marketing, by providing valuable insights that drive strategic actions and improve outcomes.
The accompanying visual representation vividly portrays how analytics are used.
Natural language processing
The next destination on our journey through the realms of technology and innovation is the fascinating field of natural language processing. It takes text from documents and computes using that text, e.g. to find critical clauses in contracts. Here is the histogram of NLP technology across M&A strategy tasks.
Machine learning
Machine learning, a subset of artificial intelligence (AI), involves the use of algorithms to enable computers to learn from and make decisions based on data without explicit programming. It encompasses various techniques such as supervised learning, unsupervised learning, and reinforcement learning, playing a crucial role in powering many modern technologies and industries. Here is the distribution:
Analytics has seen widespread adoption across M&A strategy due to its ability to derive valuable insights from data. In comparison, natural language processing (NLP) is just gaining traction in some M&A tasks for text analysis tasks, albeit to a lesser extent than analytics. On the other hand, the utilization of machine learning techniques remains relatively limited, with only a few tools using it.
