How primary insights fuel investment decision-making
By David Holden-White, co-founder & managing director of techspert.io – Investors have long sought data from primary research to get an edge in their decision-making. Whether gathered through surveys, focus groups, panels or qualitative interviews, insights from individuals with lived experience of the relevant problems, markets, technologies and services, are hugely valuable. They offer a way of uncovering the intangibles, those moments that can’t be quantified solely on data. They augment and extend an investor’s own knowledge and experiences.
They also provide companies with a real competitive advantage. Most investors will have access to the same pool of data, whether it’s financial reports or app downloads, but for those looking to get into new opportunities ahead of the competition, they need insights that aren’t readily available or accessible.
That’s why finding and connecting to the people with the right insights on a particular market is critical. Being able to tap in the minds of these experts is the fuel for successful investment decision-making.
The profile of that expert will vary depending on the sector and what the investors need to know. Investors looking at funding new pharmaceutical products, for instance, may need to call on scientists and physicians experienced and familiar in the conditions the medicines intend to treat. These specialists can help investors understand the need for the product, its viability and through that, the market opportunity.
That’s all well and good, but how do investors find the right experts in the first place? And how do they determine whether their expertise matches their needs?
There is no clearly defined formula. Even in pharma and biotech where there are abundant trusted accreditations and peer-reviewed publications, these are only relevant if the subject-matter precisely matches the need. Therefore, determining whether the expert is right for the project in question is rarely straightforward, and finding them in a timely manner is challenging.
Digitalisation and the fact that so many of us live our lives online makes it easier to confirm an individual’s knowledge and credentials. At the same time, the proliferation of platforms with low barriers to entry means we’re living in an age of information overload, where true insight and original thinking can easily be drowned out.
Then there’s the issue of subjectivity. Even experts are only human, with the same biases as the rest of us. Investors need to ensure they are speaking to a diverse mix of opinion so as not to risk missing critical insights. There’s a tendency, once an expert is found, to use them again and again, but this ultimately only provides a narrow viewpoint. This is true in any walk of life, even in scientifically rigorous fields such as drug discovery.
Expert networks offer one way of finding the right people. They have been around for a couple of decades, ever since people realised that they could sell access to digitised contact books. While business models have evolved since then, fundamentally these networks offer investors an opportunity to tap into the minds of industry leaders. However, whether traditional vendor or more recent entrant, they will primarily rely on either a database curated manually through research and/or expert self-reporting of skills, or searching and messaging across LinkedIn, relying on job history as a proxy for expertise.
Neither approach solves the core challenge of matching expertise precisely to needs and onboarding experts in an efficient way. Instead, they are over reliant on outdated curated lists and data that doesn’t provide the granularity of real-time, global expertise matching needed.
Another issue is that some networks are populated by the same faces, on the same issues, which would struggle to address the issue of subjectivity. Plus, they are by their very nature limited in how specific they can be. In sectors such as life sciences, as energy and industrials, on a given subject there may only be a handful of true experts in the world. If they don’t participate in panels then it’s going to be hard to access that knowledge.
A solution may lie in technology. Artificial intelligence (AI) can be deployed to rapidly sort and analyse data and online content, whether articles, papers or posts, grant information or position announcements, and identify potential experts that meet the needs of an investor.
Such technology can drastically reduce the time spent finding knowledge leaders, while still providing a broad and diverse spread of expertise. It goes beyond simply highlighting the latest information and gives investors access to the minds behind the material, providing a gateway to previously hidden insights.
What’s more, technology sees beyond borders, meaning that investors are no longer restricted to those experts in their region, time zone, or cultural affiliation. It also automates the process of contacting them – once a match has been made, the experts can be engaged automatically, rather than needing time to be spent manually LinkedIn messaging and waiting for replies.
Finally, it would take out the guesswork, matching the specific needs of the project to the exact expertise of the subject matter specialist. By giving investors access to AI-sourced experts, this technology acts as a route to, rather than the ultimate source of, knowledge. What AI can do is rapidly find the needle in the haystack of knowledge, facilitating access to expert insights that can be fed into the due diligence process that will ultimately underpin investment decisions.