Due diligence is one of the most time-sensitive use cases of expert sourcing. Often within a tight time constraint, due diligence requires a high level of specificity, detail, and precision. Getting too small an expert network or experts who are not perfect fits for the type of due diligence you need to conduct can result in uninformed decision making.
Traditional approaches to sourcing subject-matter experts operate within constraints. They are too tight for the specificity and speed needed for due diligence. Old-school expert networks rely on a limited pool of expertise that consists of vetted consultants who have signed up to be part of the network. Because the pool of possible people to connect with for due diligence is limited, companies run the risk of being given an expert who is not a perfect match . Worse, there’s no time to find a better one.
With the advent of automation and AI, however, some companies have moved beyond the expert network model. They now offer expert sourcing without limits or time constraints.
Expert Networks, A Wealth of Data, and Integrated Surveys
AI-powered knowledge sourcing platforms take a different approach than traditional expert networks. Rather than relying on pre-existing networks of consultants, an algorithm identifies the best respondents for any particular need. This ensures that you can get data and insights from people who precisely fit your needs. You don’t just the best fit within a closed network.
Algorithmic Definition of Experience
AI-powered knowledge platforms identify expertise through a two-pronged approach: the algorithm looks at both purported knowledge and experience in the field. Old-school networks define expertise in outdated ways: they define ideal consultants as those who possess knowledge, rather than experience.
Robust Due Diligence Data
AI-powered expert search engines can find experts through numerous databases around the world. As a result, it’s possible for companies conducting due diligence to get numerous experts for any given aspect of the due diligence, from customers, to distributors, to former executives. This ensures that data and insights sourced from experts are accurate and robust.
Qual-Quant-Qual Approach (Q3 Formula)
There are two sides to the coin when conducting due diligence. These are opinions from market participants (pain points, opinions on brands or products etc.) and quantitative insights (price points, tech specs etc.). The most effective way to get both aspects is through doing initial data capture with multiple experts in a given category, and then conducting deep-dive qualitative interviews with select experts from the initial pool. This ensures that you have a full picture of topic on which you’re conducting due diligence. It allows you to make the most informed decision possible. Traditional expert networks only allow for limited data and insights. Often, they cannot be verified by other experts because of their limited pool of possible consultants.
Scale, Speed, and Custom Targeting
By leveraging the power of AI, NewtonX can find precise matches for due diligence needs. We reach out to these people at three times the speed of traditional networks. Clients receive precisely as many experts in each category of due diligence as they ask for. That is, not just however many happen to be in a certain network. Additionally, NewtonX screens experts within 24 hours. This ensures that clients get the best stakeholders to give them the information they need for robust due diligence. This AI-powered custom recruiting, combined with human screening gives you the best possible expert or group of experts in the shortest possible time frame.
It doesn’t matter whether your due diligence requires speaking with customers, the head of procurement, distributors, or all of the above. NewtonX can find a precise match in even the most pressing of timeframes. Learn more about how NewtonX leverages AI to bring you the highest quality data so you can make decisions with confidence.