Profile: Phillipe Laval, Jolt Capital
The Drawdown (TDD): You founded Evercontact and Sinequa before joining Jolt Capital almost six years ago, what prompted the change?
Philippe Laval (PL): I have known Jolt’s founder Jean Schmitt for quite a long time, we were classmates back in engineering school and have kept in touch since then.
When I merged Evercontact with a US-based company, he approached me and told me he needed someone to build software for his new PE firm. Being an engineer at heart, I really didn’t want to become an investor and at the time I told him I could be an external consultant at most.
Jean talked me into joining him on an offsite brainstorming session. Eventually it dawned on me that it would be like starting up a new embryo-company within Jolt’s womb. And Jolt quickly became a fantastic opportunity to learn new things, face new challenges, and assemble a great team with a shared vision.
TDD: What made Jolt decide to create the role of CTO?
PL: We don’t want our investing partners to be fenced off from the market, with junior analysts filtering raw information and acting as gatekeepers.
Having said that, it’s impossible for the partners to screen every bit of possibly relevant information. That’s why Jolt Capital created the role of CTO and appointed me to design and build our software platform Ninja. It’s a way to make sure our partners have the best of both worlds: a comprehensive access to quality data and a toolbox to carefully curate the information.
TDD: How would you assess the role of CTO in the private equity landscape?
PL: In the beginning, there were none. You had system administrators setting up the operations or the email systems. But in a digital economy, whatever the industry, a CTO is mandatory.
As a CTO in a private equity firm, I fulfil three different functions. The first one is of course, to provide technical expertise to the team on topics within my range of skills.
The second one has to do with digitalization. Email systems, cybersecurity issues, archiving documents, and much more. Take capital calls or reporting for example: I can help our middle and back office with robot process optimization and ease their workload. We are talking about large amounts of money and heavily regulated processes, so the final say should stay with a human, but we can free up lots of time with data automation tools.
The third part of my duties at Jolt, arguably the most interesting, is ‘investment target hunting’. Setting up tools to fuel a proprietary deal flow and to assist the investment process and the in-portfolio operations. We have decided to build those pieces of software in-house. I’d also like to hammer this thing home: the CTO of a PE firm should spend time and share space with the investment partners. Had I been shut off from the heart of the investing team, Ninja would never have blossomed the way it did.
TDD: Why are you building the software in-house as opposed to outsourcing?
PL: We’re developing the tool as we go along. Looking back at the first five years, there were a lot of things we thought would be smart to implement, and they turned out to be useless. When you outsource, you need to have a clear idea and give explicit guidelines on what it is that you want. We know where we want to go but cannot decide the path beforehand.
There’s another reason that is linked to our investment philosophy. If you subcontract your design, the secret sauce behind your algorithms will likely be used for other clients. When the automobile industry relies on the same OEMs, all cars end up looking similar. At Jolt we like to be the only financial investor on a given deal because competition drives up the price, and we want the right price for both Jolt and the entrepreneurs, not beauty contests and price wars.
TDD: How do you see data in private equity?
PL: From what I see and hear from our peers, there are several problems. Firstly, data is messy. It’s usually user - or company- generated and you’ll need a lot of technical acumen to use it in a meaningful way, to go beyond the analytical.
Secondly, if you buy it, it's … expensive! And most private equity teams are not equipped to deal effectively with these massive amounts of data. That’s why you need to hire a data science team, to build a software, or to get consultants who are going to help you extract insights.
Another challenge is getting everyone to use the tools you’re building, buying, or licensing. Private equity is a people’s business, and professionals used to work with just a phone and their Rolodex. Having to transition to a single software managing all the interactions for you can be counterintuitive. When I started designing Ninja, I realised that with no built-in CRM it would not be used daily, and in turn we would then fail to capture some of the crucial interactions.
But now everyone is using the platform constantly, it’s become our ‘super-app’. Over the last five years we’ve been able to curate a corpus of more than 25,000 European investment deals, and to fine-tune a model which suggests deals to partners, with a current 80% success rate, out of the two million companies presently tracked by Ninja.
TDD: What will your next twelve months look like?
PL: There are three specific areas we want to focus on. Firstly, we want to better understand entrepreneurs, document their background, analyse their career paths, and take this data into account when orienting the strategy of our portfolio companies.
Secondly, sustainability. We want to feed our Ninja platform with quality ESG data, despite the difficulty to find it at scale. You can get indicators such as carbon footprint but what I am really after is a way to grade and rank a large number of companies.
And thirdly, we are starting to have enough data to produce theme-based market reports. We can fully map the investment landscape on a sector-based approach: number and distribution of active investors, job creations, key technologies, patents dynamics, you name it. And because we think we can get additional insights from our peers, we are ready to share these reports widely.
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Shielding your Data
With the collection of data, protecting it has now equally moved to the forefront of everyone’s mind. Laval shares his insights into the development: “A few years ago, it wasn’t really on anyone’s radar. You changed your password every six months and that was it. Now, we’re seriously tackling this. There’s strict guidelines, penetration tests, and we hire staff with security backgrounds while using more and more external cybersecurity tools.”
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