In a private setting at the Royal Automobile Club, Holland Mountain and Kelp hosted a panel discussion on the future of data-driven deal sourcing.
The discussion featured insights from:
- Chris Conradi, Chief Digital Officer at FSN Capital.
- Christopher Vilhelmsen, Head of Investment Consulting at Holland Mountain.
- Douglas Trafelet, Managing Director at Kelp.
Together, the panel explored the trends and technologies reshaping the way private equity firms approach deal sourcing.
The journey to today
Historically, deal sourcing in private equity was driven by opportunity, entrepreneurial instinct, and relationships. The shift towards a more data-driven approach has been supported by CRM systems, which aim to capture and institutionalize the knowledge and networks traditionally held by individuals. This transition has enabled firms to retain insights long-term, beyond the tenure of specific team members.
While financial data analysis has long been part of deal teams’ toolkit, competitive advantage increasingly lies in non-financial data—such as sentiment analysis from reviews and the wealth of insights available through LinkedIn.
One of the biggest challenges is the enormous volume of potential data to analyze. As a result, deal teams have continued to expand, with highly skilled – and highly costly – professionals often dedicated to manual data aggregation.
With the rise of AI, many viewed it as a solution to these challenges. While AI certainly introduces efficiencies, it is not a silver bullet.
Using Technology in Deal Sourcing Today
So, what are the current technological approaches to deal sourcing? During the panel, speakers highlighted three main strategies that firms should explore:
- Combine CRM with a data warehouse: Many firms attempt to use solutions like Salesforce paired with Snowflake. However, this approach often falls short due to the lack of robust master data management.
- Develop in-house solutions: Some firms, such as EQT with its “Motherbrain” platform, have built proprietary solutions tailored to their needs. While effective, this route is extremely costly and requires a commitment to software development – a path most firms are hesitant to take.
- Adopt specialized off-the-shelf tools: Another option is to use dedicated deal-sourcing tools, such as Kelp, which are purpose-built for this function and offer a more accessible, ready-made solution.
Measuring Success: Efficiency vs. Effectiveness
The success of these tools should be measured by increased effectiveness, not just by speed. To gain a true competitive edge, firms must leverage technology to uncover insights that others can’t access.
- One significant advantage FSN Capital has achieved is vastly improved search capabilities. Traditional data filtering methods have clear limitations, especially since industries and sectors are categorized too broadly. Companies are often tagged under a single category, though they could belong to multiple sectors in practice.
- Using Kelp, FSN Capital was able to automate the creation of one-pagers for 28 million tracked companies – an impressive gain in efficiency, though not necessarily in effectiveness.
- To enhance effectiveness, FSN Capital implemented a highly innovative approach: creating a one-pager for a hypothetical (or “fake”) company, then using it as a benchmark to compare against the 28 million companies. This technique helps them identify companies they might otherwise miss with traditional methods.
Other Potential Game Changers
The panel discussion also highlighted additional opportunities that could significantly enhance deal-sourcing effectiveness:
- Automated SWOT analysis: Automating the creation of SWOT analyses for target companies can help improve the quality of a deal team’s outreach and pitches.
- Analyzing missed deals: There’s increasing interest in analyzing deals that were passed over, though this remains challenging due to the sheer volume of opportunities.
- Capturing spoken information: New tools are emerging to capture spoken information, such as insights from podcasts that discuss specific companies or sectors.
- Quicker deal elimination: An advantage of current tools is the ability to “kill” deals faster, saving time by not pursuing unpromising leads. However, this brings an element of caution, as there’s always uncertainty around what could have been missed.
- Using LLMs for website translation: A true game changer for FSN Capital was using a large language model (LLM) to translate the websites of millions of tracked companies into English, bypassing Google Translate. This innovation has saved FSN Capital millions in translation costs.
Driving Deal Team Adoption of New Technology
A recurring question from the audience was how to encourage deal teams to embrace new technology to improve effectiveness. Chris Conradi shared a particularly successful approach used at FSN Capital.
The strategy involves identifying “SPOCs”—single points of contact—within each team. Selecting a sociable individual for this role is key. These SPOCs are thoroughly trained on the new system and then tasked with demonstrating its benefits to their teammates, fostering a smoother and more organic adoption process.
Other ideas mentioned during the panel for encouraging adoption included:
- Getting team members excited about the new tool by focusing on the benefits rather than getting bogged down in technical details
- Bringing team members along from the start to create a sense of ownership
- Embedding the tool into business-as-usual activities by making it a core part of regular meetings, reports, and deliverables
Ultimately, firms can strike a balance between incentives and accountability to ensure consistent adoption.
What About AI?
To effectively leverage AI in deal sourcing, firms require a large volume of high-quality data and the capability to integrate information from multiple sources on target companies.
As Chris Conradi noted, “A year ago, experts predicted that AI was going to totally change the world by now. In reality, it is slower than expected. A few groundbreaking use cases, but not many.”
Ultimately, AI should still be a last resort. If a problem can be solved with a proven algorithm, it’s often better to use that approach over AI.
The key takeaway for AI in deal sourcing is consistent with other AI-driven initiatives: to achieve meaningful benefits, firms must first ensure they have access to a high-volume, high-quality, and well-structured dataset.
Concluding thoughts
The potential to source deals more effectively with a data-driven approach is growing, and the partnership between FSN Capital and Kelp serves as a strong example of its impact.
While AI may take time to fully transform the deal sourcing process, firms should begin building robust data-driven deal sourcing capabilities now to stay competitive and start uncovering opportunities that others may miss.
