The top four tech priorities on every CTO’s mind
Over the past six months or so, I’ve had meetings with 57 different PE firms, mostly with technology leaders or management-level professionals who have responsibility for the investment process and, often, the firm’s broader technology strategy and operating model. I took this opportunity to reflect on what I’ve observed and to share some thoughts.
Here’s a breakdown of the data
45% were UK firms, with the rest being HQ in Nordics, DACH or Benelux, as well as 10% US. The majority of firms invest in the mid-market and/or growth. I spoke with just three VC firms, one of which had set the goal to be the “world’s most data-driven VC”. 23% of the 57 firms had already built an application which centralises their data for proprietary investment scoring. Within this cohort, many were now considering how to integrate Generative AI and the use of natural language in their applications. Of the remaining 44 firms, 57% are currently in active exploratory mode for new technologies and AI or LLM-driven efficiencies, not just limited to origination but across different aspects of the investment cycle, although deal sourcing was a common priority. The remainder were either very bank-focused in deal sourcing, and/or too small to be thinking about modernising their operating model and/or investing in a partner like Filament Syfter.
Common themes
I analysed notes from every single meeting and pulled out four main themes:
1: Identifying quality companies early
Identifying great businesses early means a PE firm is more likely to build a trusted relationship with management/founders, and an understanding of that business, before competitors. “The goal is to build relationships earlier and faster” as one Managing Partner of a US growth fund shared.
Being less dependent on advisors and doing more direct deals was also something I heard many times. “We want to get in touch long before investment” shared a data scientist at a B2B European software investor.
Exclusivity and bilateral situations are naturally the most desirable outcomes, but even when there is an advisory process, stacking the odds in your favour as a ‘preferred partner’ usually means starting conversations very early. When I asked one investment manager about losing deals, he replied, “We may get outbid, but we don’t want to get outsmarted.”
Finding great companies and staying ahead of competitors are, of course, interlinked. “Competition is our biggest challenge,” declared one Investment Director. In the age of so much information, finding something unique is increasingly difficult, and the chances are high that other investors have also identified the same company. This is all the more reason why the use of advanced technology is going to be so important, and why it pays to combine data in order to create something proprietary.
2: Relationship management
But it’s not just about building a great target identification engine. The importance of the nurturing phase was unanimously agreed. To my surprise, this has remained a fairly basic workflow based on periodic reminders, versus the notion of always leading with value, and at the right times. One head of origination explained how, ideally, they’d like to treat top targets like portcos themselves to create as many ‘right-to-win’ situations as possible over time. It became clear that this strategy is positively correlated with pipeline conviction and predictability, though of course not the only variable.
3: AI working groups and a crowded vendor landscape
Many of the firms have set up working groups to explore the possible benefits of different AI tools and services. There are lots of tools that will accelerate business processes across the investment cycle. Whether they be generalist LLM tools that will combine insights from the web with internal knowledge bases, or some of the tools that have been verticalised for private equity, such as generative-AI driven platforms that enhance due diligence, or pitch presentation, there is a lot to think about and it can be overwhelming for PE buyers to know where to prioritise. One truism, of course, holds: despite the obvious efficiency gains to be had from ever-evolving SaaS tools, the playing field will always level itself quickly with adoption; the key is unlocking something proprietary to fully gain a market edge.
4: Data centralisation
“Our operational goal is to centralise technology,” shared one executive, a strategy echoed by an encouragingly growing number. A CRM manager at one of the most respected global software investors explained the top-down shift from C-suite towards centralising data sources across the firm, and positioning itself for “more intelligent-driven processes” in the not too distant future.
Other firms simply saw the need to unify fragmented data sources as a first step in thinking about their total investable universe holistically, versus clunky and individualised ways of working that involve a myriad of different types of desk-based research and static lists, so long as there is flexibility in architecture for longer term aspirations.
By Joshua Berman,
Enterprise account executive, Filament Syfter