In the 2011 film Moneyball, Jonah Hill – playing Yale-educated sports analyst Peter Brand – tells baseball coach, Brad Pitt, “I believe there’s a championship team of people we can afford because everyone else underrates them.”
Thanks to AI, the same may soon be true of private-equity deal-making.
Moneyball’s story centres around Billy Beane, the general manager of the Oakland Athletics, who needs to assemble a competitive team for Oakland's limited budget of 41 million dollars. Brand shows him how – instead of trusting the gut instincts of Oakland’s hard-bitten but fallible human baseball scouts, trust something else instead – data.
Unlike San Francisco Bay baseball scouts, most PE dealmakers are already evangelists for data-driven insights. So, it’s hardly surprising the industry continues to embrace AI at speed.
As Financier Worldwide points out, “Acquirers are expanding their use of AI and related technologies, deploying everything from ML (Machine Learning), augmented intelligence and natural language processing (NLP) to advanced analytics. AI and ML offer acquirers a number of advantages across the deal spectrum, including greater insights into target selection.”
In Private Equity News, VC-legend John Moulton agrees, “AI is already being used in due diligence, portfolio company monitoring, risk discovery and management and increasingly in deal sourcing.”
It is, perhaps, in this Moneyball-style identification of acquisitions that its impact will become most profound. As every dealmaker will be able to ask themselves a PE version of the question Pitt does in the movie. In essence – who are the companies that everyone else is not seeing because they don’t properly understand the opportunity.
And, through the strategic use of AI, be able to answer it.
Moulton again, “Portfolio companies can use AI tools to analyse industry trends and spot opportunities as they emerge. Immense quantities of press reports, social media content and flows and old-fashioned financial data can be correlated, weighed, and cross-checked using AI tools in a way that is otherwise practically impossible – better decisions generally follow.”
Initially, thinks Financier Worldwide, “AI and ML are generally expensive to implement, so larger, better capitalised firms are more likely to take advantage.” But, in the longer term, as competition drives machine-learning entry costs down, AI may even the playing field, favour the Davids, over the more risk-averse Goliaths.
Because all AI can do is discover. It still takes something machines do not possess – a little human courage, to ultimately decide. And, as the Moneyball story clearly demonstrates, “finding value in players no one else can see,” is not for everyone.
Exactly the same thing will continue to prove true for the acquisition of companies. It will still take some old-fashioned human bravado to make that nail-biting final call. No matter what the algorithms are telling you.