Techspert

Common mistakes to avoid when gathering expert insight

Written by Harri Lamden, Project Team Lead, 23 September 2019

As a Senior Associate at techspert.io, I ensure customers connect to the right experts using our AI technology. From matching a life sciences consultancy with a specialist in generalised pustular psoriasis to connecting a venture capital firm with key opinion leaders in the commercial market for genomic analysis reagents, the range is broad. Having provided support to customers on many projects, there are a few things I’ve picked up along the way when it comes to finding quality experts. 

This blog post highlights some typical pitfalls made when gathering expert insight with the aim to help customers get better results and ultimately to avoid loss of a pre-bid proposal, missing deadlines, and not getting a broad enough range of quality insights. 

Common mistakes to avoid when gathering expert insight

 

1. Searching for experts yourself

If your role includes having to find experts for primary insight, it’s highly likely that you work at a consultancy, a venture capital firm, or a market research company, to name a few. You’re often working on multiple projects simultaneously and have a range of responsibilities, such as project and team management, developing strategies to create value add for your end clients, navigating client relationships and communications, curating screeners, compiling discussion guides for expert calls and so much more. In short, you’re a busy person. With all these priorities demanding your attention, searching for experts isn’t necessarily the best use of your time. Let the expert network find you the specialists so you can focus on other areas to make your project succeed.  

2. Leaving the search for experts to the last minute

A lot of times customers fail to find the experts they need after conducting an extensive manual search and turn to techspert.io at the last minute to help them. Although we’re capable of delivering on tight turnaround times – thanks to our AI technology – rushed projects aren’t ideal. It can mean, especially for rare topics where not many experts exist, that your perfect expert might not be able to respond in such a short window and you then miss out on their phenomenal insight. You’ve also got to factor in the time required for approving experts and confirming the connections.

3. Screener questions that act as a barrier

Screeners are important. They help ensure that you get the precise experts you’re looking for. However, they become problematic when they’re long and complicated. A lot of the time the experts you want to engage with are incredibly busy and have demanding jobs. The last thing a top surgeon wants to do after being in theatre for 14 hours is fill in a lengthy, detailed screener in order to connect with the customer to provide insight. Your screener could be preventing you from engaging with specialists who are the best in their fields. Try and keep them short, requesting only the information you need to proceed with a connection. We recommend no more than six multi-choice questions that are quick to answer. 

4. Lack of flexibility

You’ve got to bear in mind that the experts you want to engage with may be located on the other side of the world to you, so it’s important to be flexible with your time. A connection at 2 PM might be great for you if you’re in Los Angeles but not so great for the expert who’s in France where it would be 10 PM.

5. Internal misalignment

Ideally, there should be one project lead who provides information to the expert provider to avoid any confusion. Realistically, this usually isn’t the case and many people are often involved in a project, but this isn’t an issue. The challenge emerges when people within a team have conflicting ideas on what they want and communicate mixed messages. Understandably, this can cause chaos. Before reaching out to a provider, ensure everyone on your team is on the same page.

6. Sitting on expert profiles

We know you have a busy schedule and that there are sometimes internal developments that stall the decision-making process but try to keep things moving along as much as possible, especially when it comes to approving an expert’s profile. At techspert.io, we send our customers data-backed expert profiles to review sourced by our smart AI technology. Once they approve the profile this triggers scheduling of the call. If a customer takes too long to approve a profile, especially if the project has a tight timeline, we run the risk of the expert losing interest or filling up their calendar and dropping off altogether. This will result in having to start the process of finding experts all over again. 

7. ‘We’ve always done it that way’ mentality

The expert network industry has been dominated by a few key players over the years and for this reason alone some organisations choose to work with them and overlook others. However, as the world’s first AI-driven solution to knowledge exchange, our platform does things differently by leveraging machine learning techniques to source and deliver a higher quality of specialists that precisely match your needs. So, don’t let ‘we’ve always done it that way’ mentality be your decision-maker. 

 

At the beginning of this blog post, I mentioned that I ensure our customers connect to the right experts using our AI technology. Based on a customer's criteria, this technology, powered by machine learning, searches the breadth of the internet to find the world’s leading specialists with unparalleled precision. Thus enabling techspert.io to match customers with quality experts whenever they need them. Finding experts to provide primary insight doesn’t need to be headache-inducing. By avoiding these mistakes and working with a quality expert network you're on track to get the insight you need.

 

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Topics: Best practice