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Webinar: Automating and optimising the future

Nicholas Neveling 14 January 2021

Covid-19 dislocation has forced all businesses to reassess their technology infrastructure and look at new ways to lever data and systems to maintain business continuity and sustain profitability.

ON THE PANEL:

Axel Wehtje, partner, Park Square Capital

Chris Kindt, director, portfolio & data, Hg

Richard Lee, associate director, KPMG

Moderator: Mark Coronato, client development director, DealCloud

The collation and use of data have transformed the way businesses engage with customers, set out the strategy, and manage operations.

This has inevitably changed the way private equity firms assess deal targets, address portfolio management, manage their own teams, and report to investors. In a recent Real Deals webinar, held in association with DealCloud, the deal sourcing and fund management platform for the capital markets, a panel of experts shared their insights into how private equity firms are automating and optimising data for the future and embedding tech-enabled systems into the day-to-day.

Click here to listen to the full discussion

The session explored the current data strategies followed by firms, the purpose data serve within them, as well as how data has impacted dealmaking. Here are some of the highlights:

Reducing complexity and simplifying decisions

Axel Wehtje, a partner at Park Square Capital, said private equity firms have always turned to data to support decision-making, but that it is only recently that firms have really begun to look at ways of making data easier to collect, access, and interpret.

Wehtje said that data used to be locked up in large, complex spreadsheets, but that firms have since recognised the value of using software and data analytics tools to make data easier understand and use. This has seen the use of data expand across all aspects of managing a private capital franchise.

“Using data is just making things much, much easier,” Wehtje said. “We started with portfolio monitoring and valuations, then we moved on to tracking fund performance and really trying to do it on a KPI driven basis, and using data for that.

“The way we do business and the way we diligence companies continues to be the same, but if we can make it more efficient and facilitate decision-making by using data, we’ll give ourselves an edge.”

Setting a good example for portfolio companies… and learning from them

Chris Kindt, director of portfolios and data at buyout firm Hg, said his firm typically deployed up to 30 dedicated data specialists at any one time.

Around two-thirds of this resource was focused on supporting portfolio companies (around 30 of which are in the tech sector) to harness their own individual data potential, across business information and data warehousing, all the way through to artificial intelligence.

“The combination of data science and cloud infrastructure has been a real game-changer for us,” Kindt said. “We’re helping our portfolio companies to harness this, from how they run the operations, optimise commercial processes, handle cross sales and automate support processes, all the way through to actually monetising data and launching new propositions into their customer base.”

Kindt added, however, that the firm itself believed it was crucial to “drink our own champagne” and apply the same lessons to its operations.

“What kind of data tools can we use ourselves to optimise our own internal processes? That’s our second leg really, it’s about applying data science and proper systems and processes and cloud technology to make ourselves internally more data-driven. It’s across the full value chain here at Hg,” Kindt said.

How data strategy is reshaping M&A

Richard Lee, a director in KPMG’s M&A practice, said the focus in M&A lead advisory had evolved from simple, structured market data that was “pretty generic” to “capturing and democratising” institutional knowledge.

“A high volume adviser will see an awful lot of opportunities, but the insights and intelligence that come from all of those historically resided in individuals and small silos and team. It was shared through spreadsheets at best,” Lee said. “If you’re doing 100 deals a year, you’ve got 100 different spreadsheets with insights, trends, with information. Our strategy now is to basically try and coalesce and capture all of that, such that we can start to pull insights out of it.”

Codifying and collecting data in this way has given KPMG the ability to harness predictive analytics and differentiate its proposition.

How to build a data strategy from the ground up

The formation of a data strategy is challenging, as data is such a vast and fast-moving subject. The panel was able to outline key principles for making a start.

Wehtje said the process was one of “trial and error” and that failure was likely, but also a valuable learning opportunity. A data strategy also required upfront investment, but that it was important to have a clear idea of the desired end product and outcome before choosing systems.

“Ask what you really want out of a system; what you want the data to do. Then go and collect it,” Wehtje said. Kindt agreed that a strategy should be built up step-by-step and would involve trial and error. He advised adopting an approach of “small experiments”.

“You have to learn yourself what works, what doesn’t work. It also helps to get some small early wins and bring organisational engagement as well,” Kindt said. “When it comes to tools, you don’t have to buy the Rolls Royce that does everything in one go.”

Lee said it was helpful to start with a “bit of data discovery and classification at the beginning” then plan what you want to do and the tools you will require to deliver that.

Categories: Insights Webinars

TAGS: Data Hg Kpmg Private Equity Webinar

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