The complexity of investments is increasing. The easy money – facebook, snapchat, youtube – has passed us by and the future is harder technologies. Every product class, from consumer packaged goods to SaaS, is getting more technical and employing more arcane methods to accomplish increasingly impossible tasks.
How are investors with good guts and general experience supposed to assess and then support portfolio companies in spaces like additive manufacturing or NLP?
That’s why Due Diligence was the first service line we launched when we left McKinsey. Our process is not an exercise in box checking. Rather, it’s a comprehensive and technically focused deep-dive into what makes an early-stage company tick. From the time our document checklist is completed to the delivery of the finished report takes just 10 business days, guaranteed – because the good deals don’t stick around forever. Wherever possible, we aim to tease out alignment with the rest of your portfolio to surface unfair advantages. The goal is to come away with a nuanced understanding of how this opportunity will fit into your overall investment thesis.
The best investors in the world invest in people, not companies. The challenge is figuring out, in a compressed time period, which people deserve your trust. Most VCs go on their gut based on phone calls and brief meetings with founders. Our process goes a step further, gathering data points from other investors in the target company, investors in previous exploits of the founding team, and former direct reports or colleagues of key team members. This is a lot of work, but it’s the only way to quickly build an informed mental model of how a team functions and how they’re likely to act in the future.
One of the challenges of conducting DD is that so much of the process is subject to information asymmetry benefiting the company, not the investor. Product evaluation is one of the few areas where we have the opportunity to reverse that asymmetry, gaining a deeper understanding of the target’s . This might take the form of code review at a software startup, or we might do a deep-dive into Intellectual Property if the company is targeting a licensing model. Even physical products can be subject to analysis in terms of their industrial design and manufacturing. By gaining this objective information, we’re able to analyze CEO
claims such as roadmap, timing, and technical capabilities in the context of a richer pool of data.
It doesn’t matter how great a team or product are if they are attacking the wrong space. We use a variety of proprietary tools to analyze the business landscape, looking for relevant competition as well as lessons from the graveyard. By assiduously rooting out confirmation bias, survivorship bias, and other common cognitive errors, we are able to more accurately place a given target company in their competitive space. A target that is a smart investment for one party, may not be for others. This is where we start to put the pieces together. Absolute returns, alignment with the rest of your portfolio, and risk tolerance all coalesce in the final analysis of whether or not to pull the trigger.
Jourdan has an old man’s wisdom alongside a young man’s energy. Though he is much younger, I often turn to Jourdan for the benefit of his clear thinking and his shockingly deep knowledge on many topics. I’m surrounded by smart people, but Jourdan is a singularity.