Creating a 'Discovery Market' for talent search with AI

In Brisbane, Australia, the ‘‘Sunday’’ Discovery Market' draws thousands of people each weekend. This sprawling marketplace offers shoppers an opportunity to explore exceptional treasures, including books, toys, coins, artifacts…it is simply filled with options and choices!

Drawing inspiration from the ‘Sunday Discovery Market’ in these pandemic times, we can think of creating staffing models or solutions using AI (Artificial Intelligence) to address mounting employee layoffs and internal talent deployment in companies.

The thinking process is simple. In India alone, the Deccan Chronicle reports that around 6.6 million white-collar professionals lost their jobs after the coronavirus lockdown, washing away all employment gains made since 2016. So, let us visualize creating an AI-driven ‘’Discovery Market’’ to address individual, corporate, and rising social problems due to the loss of jobs from the pandemic. The concept of ‘’Discovery Market’’ is based on the social change which we are experiencing in the face of COVID-19. It can provide an opportunity for competing and non-competing companies to co-create algorithm-powered both, internal and external ‘matching market’ platform to harvest available talent.

Applying AI in talent search and deployment

It is interesting to note what Yuval Noah Harari once said: “Non-conscious but highly intelligent algorithm may soon know us better than we know ourselves”.

In this context, we can examine the various dimensions of AI in context of its application in talent search and deployment.

• Firstly, how AI can enhance collaboration among competing and non-competing companies. COVID-19 has brought to the forefront the interconnectedness, interdependencies, and vulnerabilities of the complex systems that make the modern social systems run. This global health crisis is a human, economic, and social crisis, in which we must make our motto ‘Human Life First’. And in that context, it must be possible to create a ‘Discovery Market’ to save job losses, heading off the severe social problems that might otherwise result.
• Secondly, how AI can support internal and external talent search and deployment of resources within the company on projects to support business growth.
• Thirdly, how AI can support managers in decision making for the selection of internal resources and their redeployment.
• Finally, how the ‘Robo-Advisor’ concept can power the ‘matching market’ platform.

Further, using the predictive power of AI, employees will be able to accurately understand what part of their work can be replaced by technology and how to stay ahead of curve, and what tools they need to drop that are no longer adding value to their career progression.

The forms of 'Discovery Market'

By keeping AI at the core, we can create an alternative staffing framework considering two major driving forces: the company's goals and employees’ well-being. The success of the framework relies on two important considerations. Firstly, managers should ideally be less possessive over their teams. Secondly, the company should actively encourage and promote a culture where employees move around functions or teams to gain hands-on experience in new environments, handling some fresh challenges as part of constant renewal. The structure of this ''Discovery Market'' is simple. Firstly, a good number of opportunities or openings should be available in the ''Discovery Market'', just as the variety in the real Brisbane ‘Sunday Discovery Market’ that inspires it. Secondly, the ''Discovery Market'' should be able to provide managers a wide range of talent choices for selecting the best fit. The choices may come from internal sources or external sources—from competing or non-competing companies. Lastly, the ''Discovery Market'' should be sufficiently automated for transparency, accuracy, and speed. Two types of ‘’Discovery Market’’ may be proposed.

‘Discovery Market’ 1: where access is open to competing and non-competing companies for talent search and deployment.

In pandemic times, competing and non-competing companies may be invited to come on board and have access to the ‘Discovery Market’ with the sole objective of minimizing layoffs and job losses, and harvesting the right talent. In this marketplace, employees who are likely to be displaced from their present company will be provided access to the job opportunities made available or displayed by the participating companies.

The viability of this ‘Discovery Market’ depends on transparency around the roles that are available, and the skills required to fill them. It also depends on timely updates to the job board displaying opportunities, possibly on a weekly basis. Further, on this platform, both employees and managers should be allowed to rank their choices of roles, and they must do so accurately. AI can then pair them using an algorithm to arrive at a good match between employees to roles based upon their choices, and of course those of their managers. 

This platform will also be armed with a bias-free ‘Robo-Advisor’ which would be available for both, employees and managers, to consult the bias-free ''Robo-Advisor'' to validate the role match results generated by the system.

‘Discovery Market’ 2: where access is exclusively for internal talent search and deployment (not open to competing or non-competing companies) and both managers and employees can use this platform for talent search and deployment.

This version of the ''Discovery Market'' will encourage employees to enthusiastically network with managers across the business, in order to understand emerging opportunities and the requirement of new skills.

For this ‘’Discovery Market’’ to remain relevant, new opportunities or openings would have to be placed every quarter. Otherwise, it will be quite similar to the first version. The success of both types of ‘’Discovery Market’’ relies on firstly, stakeholders’ trust in the system. Employees should be able to feel that they have adequate control over their deployment or finding relevant roles. They should also feel that they are able to get one of their top 3-4 choices whenever they move internally.

Furthermore, for either type of ‘’Discovery Market’’ to succeed, managers should ideally be less possessive over their teams. The company should also actively encourage and promote a culture where employees move around functions or teams to gain hands-on experience in new environments, handling some fresh challenges as part of constant renewal.

A major cultural shift

The main advantage of a ‘’Discovery Market’’ system is increased ease of moving employees through competing and non-competing companies by reducing ‘frictions’, namely, Cost, Time, and Geography. AI can be successfully used to power the ‘Discovery Market’ to facilitate uncovering the talent available within and outside the company, but this level of collaboration among competing and non-competing companies will require a major cultural shift. 

With this application, AI can be used to connect people and create a win-win situation for companies, employees and their managers, and collectively for the society at large.