Reflections on the Dry Powder podcast
It’s not so long ago that AI and data science were at the top of every CEO’s Christmas toy list!
After all, they promised flashing lights. Extendable wings. And glitz. (Think Buzz Lightyear.)
Yet, the truth is that these early innovations were often more ideas and buzz, than value adding in the business context.
But this is changing.
Data science and machine learning now offer radically new ways of working: optimising and automating processes, unearthing new insights, and predictive analytics. More importantly, data science is adding measurable economic value to many businesses - both traditional & digitally sophisticated.
So, it’s no wonder that private equity investors are assessing & deploying advanced analytics to lift performance & IRRs, alike.
Take Hg, who has been at the forefront of software & technology investing for two decades. Our clients & partners know that we are avid fans of their strategies – particularly their extensive use of data science across the PE value chain.
In this recent Dry Powder podcast, Hg’s managing partner, Matthew Brockman, talks to Hugh MacArthur, partner and global chairman of Bain & Company private equity practice. The 2-part interview is an investing masterclass, offering fascinating insights into the defensive characteristics data-fuelled businesses.
Here are my takeaways:
💡 Businesses are likely to accelerate their adoption of software in this high-interest rate / low-labour availability market as they seek greater automation and workflow – processes by machines – to substitute for high-cost labour.
💡 All businesses are facing margin compression; passing on increases (wage or pricing) of 3-4% isn’t enough. A behavioural shift is required to achieve the 8-9% increase required. This mindset change is totally new for most PE investors who, for 10-20 years in Europe and the US, haven’t had to manage investments in high-inflation environments.
💡 AI and data science are turning from concepts & ideas, to practical workplace applications - especially in customer service, sales support, and prioritisation. Many PE shareholders are now asking the question: How can we use the information captured within our portfolio company’s sales, CRM, and product management systems to enhance development and improve performance. These systems are a rich source of potential insights - especially when combined. Even for a sophisticated investors like Hg – investing in mature software companies – it is rare to find businesses that are already developing and gaining economic value from these potential insights.
From a DataDiligence perspective, we believe all these factors add considerable impetus to the need for data due diligence during deal assessment (buy and sell-side) for ALL companies (not just SaaS). Plus elevate the rationale for developing a structured data strategy to frame the economic opportunities of data.