There’s a renewed focus on enhanced and intelligent decision-making in the world of business today, powered by Artificial Intelligence (AI). But this could spell trouble for traditional expert panels. Graham Mills, Co-Founder & Managing Director of techspert.io, addresses this in a new guest spotlight.
Giving decision-makers access to the right knowledge and expertise has become big business. The knowledge economy as a whole, covering everything from management consultancies, market research and conferences, to in-house research functions and expert networks, is worth hundreds of billions of dollars.
One area of the knowledge economy that is growing rapidly is expert networks. The idea, of being able to connect with subject matter experts through a one-off or subscription model fee, emerged at the beginning of the 21st century when companies realised they could monetise access to contacts by creating panels of experts. Over the years, the sector has developed to a point where investors, corporates and professional services firms rely on expert networks to help gain insights directly from people who understand specific markets, products, and technologies. In short, these networks give businesses intelligence their competitors don’t have.
A Boom Time for Expert Networks
The popularity of expert networks is booming as corporates and investors seek more external expertise to inform increasingly complex product and investment decisions. In addition, as more companies gather insights in this way and gain an edge in their decision making, it drives competitors to need the same level of information to keep up.
Yet what are these companies actually buying when they engage in an expert network? Are they accessing the full breadth of knowledge available on any given subject? Or are they paying to speak to a panel made up of a select few who, while undoubtedly experts, ultimately only provide limited viewpoints?
Historically, the answer is the latter. Expert networks were built on panels of specialists who would agree to take part and companies would pay to access them.
Why Expert Panels Are Out of Date
This has a number of drawbacks. First, these panels are based primarily on either a manually maintained database that relies on research and/or experts self-reporting their skills, or, more recently, searching and messaging across LinkedIn, with job history used as a proxy for expertise. Neither approach solves the main issue of matching knowledge precisely to needs and onboarding experts in an efficient way. Instead, they rely on curated lists and data that are hard to keep relevant and up to date. More importantly, this approach doesn’t provide the needed granularity of real-time, global expertise matching.
Second, 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. To understand a particular market opportunity or risk, there may only be a handful of true experts in the world that have the right insight to unlock the most valuable decisions. This will be particularly true in sectors such as life sciences, and energy and industrials.
Quite simply, if these specialists don’t participate in panels, then we don’t have access to their knowledge. The proliferation of social networks, for instance, has given rise to a whole host of digital opinion leaders in pharma and life sciences – specialists who both share and build their knowledge as much through online interactions and engaging with communities as through more traditional methods. With panels rooted in analogue ways of working, what is the likelihood that this new breed of expert is involved?
A data science-led approach to identifying, matching and engaging with experts will mean that companies can get access to untapped knowledge and insights quickly.
Co-Founder & Managing Director, techspert.io
A Gateway to Hidden Insights
What’s needed is a way for you to traverse the expertise landscape effortlessly, connecting with the right experts without the need for prior sign-up or human processing. A data science-led approach to identifying, matching and engaging with experts will mean that companies can get access to untapped knowledge and insights quickly.
It’s an approach that uses AI 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 a business or 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 just highlighting the latest information and gives access to the minds behind the material, providing a gateway to previously hidden insights. What’s more, companies 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 decision-makers 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 business decisions.
A New Ecosystem for Knowledge Exchange
Knowledge will always be key to effective decision making. As such, having the ability to access that knowledge is critical. Traditional panels of experts are already dated, slow, and not fit for purpose in a digital-first world. A data-led approach that uses AI to find, match and engage experts, feeding their insights into businesses, will be at the core of the new ecosystem for knowledge exchange.
ABOUT OUR GUEST WRITER
Co-Founder & Managing Director, techspert.io
Graham is Co-Founder and Managing Director at techspert.io, where his role involves leading the company’s commercial functions. A scientist by training, Graham completed his PhD in pancreatic cancer chemoresistance at the University of Cambridge, having further worked scientifically in R&D at Genentech and Avidity Biosciences. His commercial experience comes from roles in venture capital at both Johnson & Johnson’s corporate venture fund as well as Seroba Life Sciences, all of which preceded his most entrepreneurial endeavours, both as co-founder of smoking cessation startup Abdicare, followed by Biotechspert, which has evolved today into techspert.io.