Expert networks facilitate connections between third-party businesses that need specialized expertise and experts available for hire. These networks are usually equipped with valuable information, data, advice, expertise, and insights outside the general knowledge base. They provide expert resources and subject matter experts to C-suite professionals, founders, and other executive decision-makers in organizations.
A brief history of expert networks
Termed by Yankee Group’s Mark O’ Connor, the phrase ‘expert networks’ was first used in his presentations when he introduced his report, Knowledge Management: People and the Process in 1997.
In April 1999, the Yankee Group, a consulting and technology firm, published a white paper ‘A Knowledge Perspective: The Knowledge Management Product and Service Domain. In December 1999, they broached on “important tools of the trade” in their publication ‘Knowledge Evolution’. They encouraged clients to utilize expert networks within and beyond the organization to employ their expertise across a broader range of business contexts and processes for more refined decision-making.
In the 1950s, industry analysts and investment research were the only kinds of experts. The 1980s saw rapid industrialization and growing global trade which gave rise to management consultants. Post the 2008 recession, there has been a new brand of experts on demand. First-generation expert networks used internal databases and phone directories, just like conventional recruitment firms did. In the early 2000s, a marquee industry grew to enable expert connections outside the confines of a company and its limited networks.
Types of expert networks
The expert network landscape is classified into three broad categories:
Four big players lead the expert network industry. GLG (the Gerson Lehrman Group, Inc.), Boston Consulting Group, Bain & Company, and McKinsey & Company. Today the expert network industry market size tops $1.3 billion, with double-digit growth year-on-year. Other nascent competitors like AlphaSights and Third Bridge are competing at the heels.
The regional leaders have a secure position in their respective geographies. Expert Powerhouse, for instance, has been a big player in Germany. There’s also Infomineo with a strong foothold in Dubai, and Avvnue in the US.
There are over a hundred smaller expert networks that serve specific geographies, industry segments, or operate on different business models. They are particularly fast-growing, some with a distinct positioning. Dialectica, for example, is based on a traditional expert network model. CleverX and Prosapient are more automated platforms in the recruitment delivery niche.
Expert network business model
1. Sourcing model
Expert network companies may source expert professionals from their internal database or a custom recruiting method or both. Custom recruiting for specific projects has become popular with the rise of job-application and networking platforms like Linkedin.
2. Revenue models
Also known as the pay-per-use model where the expert networks invoice the client for every hour or minute of expert consultation based on the credit price of the expert. Transactional revenue models are good for generating direct revenue. Consumers may be attracted to the simplicity and the availability of various expert resource options in this model.
As a traditional concept, a lion’s share of the industry runs on the subscription model where clients pay for a pre-decided number of credits at the beginning of every contract year or month that they can use on every expert consultation. The network bags the difference between the subscription fees collected and the hourly rates paid out. This model generates great revenue if the company is mature. On the other hand, maintaining a high subscriber rate is key to profiting from this model.
3. Operating models
Beyond, revenue and sourcing, different expert networks have unique internal operations. Each operating model is unique and has its merits. And there is room for multiple players to thrive in this industry.
Standard expert networks
Standard expert networks are dependent on the intelligence, savviness, and flexibility of junior employees to find the right experts. It takes hours of manual work, research, and scanning through career databases. Internal databases are built based on the previously used experts who may be contacted again in the future.
Machine-driven expert network
CleverX, Xperti, NewtonX, Prosapient, Techspert.io, and Atheneum overcome the bottleneck of associates looking for experts and automate this process. Scraping from a multitude of data sources like directories and professional sources is not simple. Machine learning helps make sense of large datasets and come up with a comprehensive solution to scrape relevant data that is comprehensive, detailed, and up-to-date. These lists may be further refined with a good human-vetting process.
Expert Q&A Networks
Expert question and answer portals like Answers.com and Quora to get answers to questions vetted from experts. But these sites are not as esoteric and are best suited for matters that are not pressing and do not need confidentiality terms sealing them. They may also almost always cater to B2C audiences. It is rare to find secrets of trade as most of this information might already be available on the internet. The upside may perhaps be that one may have it explained by someone familiar with the lingo of the industry that one is looking for.
Customers get to browse for experts or gig workers to hire in DIY marketplaces. At the core of the gig economy are such platforms that apply algorithms to match client requests to experts who are on board. Upwork is an example. These platforms aim to provide highly specific knowledge workers on-demand to clients.
Crowd-funded expert calls
Slingshot Insights is an example of a crowdfunded expert network. Standard model expert networks often use open expert calls when there’s no need for confidentiality clauses and a need for better-crowdsourced wisdom and insights from other researchers on the conference line.
Trends in the expert network industry
Three primary trends pervade the knowledge expert industry.
1. The stratification of consultants and consulting as a service
The expert industry is a labor-intensive space and revenues are deeply steeped in billable hours. The bigger the value, the bigger the bills one can invoice. In a post-COVID and digitized world, knowledge workers and experts are being further categorized into two primary groups. One, the strategic ones, worth the high price, and two, the gig workers who make up the expert resource category that charges hourly rates.
2. Digital delivery and remote working models
The rise of remote and hybrid working models related to technologies is no doubt a norm. This is a great opportunity for tech platforms to set up processes to bridge gaps in work processes and methodologies. This needs to go beyond video conferencing and disrupt consulting offerings like no-code software and artificial intelligence to create new digital operations.
3. Scalable business models with value pricing
If clients can pay for skills, expertise, and information goods on Upwork, SlideShare, or CleverX, why would they need a consulting firm that bills them annually? The standard business model is based on leverage. Senior partners depend heavily on MBA freshers who can make big bills for them. Conventional expert networks stand the risk of losing the market share to younger challengers. Frameworks, tools, templates, and other information goods will be commoditized as free resources on the internet. Different brands of expert networks must reinvent themselves from offering Gantt chart answers to solutions that will last beyond the engagement itself.
How to hire the right expert?
Before you hire an expert, you might want to predetermine the service level your project or organization needs. A few things to consider:
Do you have a dedicated account or project manager for your niche industry? Hew professional are they and what is their level of expertise?
Is your brief well-articulated and simple to understand?
What is the turnaround time for these projects and the speed of execution?
Compliance and Quality check
Information goods and resources are foundational to the expert network and knowledge industry. And compliance is equally important for any transaction.
1. Compliance terms for expert professionals:
Simple instructions and a clear how-to knowledge base for training and before the engagement starts.
Terms and conditions of contracts.
Regular background checks.
2. Compliance terms for clients and third-party companies:
Compliance monitoring tools and technologies.
Project compliance terms and custom controls.
A compliance department or a legally vetted process.
3. Compliance terms for enablers and expert networks:
Regulatory compliance (e.g. GDPR protocols and data security measures)
Employee opt-out terms if the expert network has a policy in place for experts working full-time elsewhere.
Summing up expert networks
On the demand side of things, the global value chains are becoming even more complex as companies branch out into niche segments. The supply segment is also thriving as expert professionals make themselves more and more available on online career directories, and are more open to gigs. Both companies and expert professionals have made themselves at home working 100% remotely and trusting each other regardless of their different time zones. Remote work tools, mechanisms, and self-service gig-based recruitment platforms will see enormous growth in 2021.