A Fresh Approach to Narrowing the Skills Gap
It's fairly easy for people in small businesses to keep track of everyone’s skillset. When a project comes along, figuring out which employees can contribute and what skills should be brought in from outside the company is a fairly straightforward endeavor.
But scale that scenario into an organization with tens or hundreds of thousands of employees distributed around the world, and it gets quite difficult to pinpoint potential contributors. The gap between needs and available resources can be thought of as white space, a void to fill. White space becomes apparent when projects languish for lack of skilled support or when there is a need for new skills that could be fulfilled by identifying those individuals who have them.
White space is a significant concern as it leads organizations to hire services or additional staff and assume the costs associated with those choices. Compounding the expense is the tendency for large organizations to keep existing employees “on the bench,” waiting for the right opportunity for their skills. Cisco's Connected Futures Report confirmed this trend, reporting that 93% of IT and business executives can’t find the people they need, a talent gap that holds back business transformation.
Create a Digital Marketplace to Fill Skills Gaps
A highly effective alternative is possible in the digital workplace, in the form of an online digital marketplace for the organization. With a system like this, a project leader can simply publish a definition of upcoming work. The platform then automatically generates a structured recommendation, providing a list of people on staff ranked in order of their suitability to the task considering not only skills but availability, proximity, familiarity with the client, performance rankings of previous managers, and a myriad of other relevant traits.
Such a system can leverage the same information used to enable nano-personalization of user experiences throughout the digital workplace, as well as external data sources, such as skills posted on a public LinkedIn profile, to narrow the list to the best candidates. This approach means you'll optimize the productivity of your existing employee roll before considering costly additional resources.
Related Article: Why People Search: 3 Use Cases
How the Gig Economy Can Fill the White Space
Of course, there are times when skills do not exist within an organization, due to scarcity or because the specialized need is temporary. The rise of the gig economy means more skilled professionals are simply not available for hiring as staff. According to CNBC, “If the gig economy keeps growing at its current rate, more than 50% of the US workforce will participate in it by 2027.”
For many companies, this is an opportunity. A recent article in Forbes said, “40% of companies expect that gig workers will become an increasing part of their workforce.” Ultimately that means that some specialized skills such as data engineering can be difficult to find and expensive to employ. Companies need a marketplace system that can act as a portal/search engine to find the best people outside the organization to fit such short-term needs. Connections between the marketplace system and operations areas such as human resources and finance further automate the onboarding process of these resources.
It is early days for implementing the digital marketplace approach, but already we're seeing signs of its appeal. While it may not yet be time to use this technique for basic workforce needs, high demand areas such as artificial intelligence (AI), natural language processing (NLP) and data engineering are best filled by gig workers. These skills come at a very high cost, but organizations are realizing they only need access to this skilled work for a limited time.
Related Article: The Pros and Cons of Hiring a Fractional CTO
A New Approach to the Gig Economy
This is a new way of thinking about the gig economy. A gig for an Uber driver might be measured in 20-minute intervals of rides, but a skilled gigger in AI might expect to work on a project for six to nine months. The gig is also more complex. A data engineer’s gig needs to include time to train and become familiar with the environment. Businesses looking to take advantage of gig workers need to give careful thought to the success criteria, as well as intervening gate criteria, that will signal progress and define the engagement’s endpoint.
These measures will be very specific to the project. For example, if a gig worker is focused on natural language processing, the business needs to consider how to measure success. Did the individual make measurable improvements to the chatbot? Along the way, were they able to make sense of user behavior and understand the persona of individuals? How long did that take? If the project is in analytics, perhaps the metrics for success relate to gaining an understanding of customer engagement and evaluating their experience.
Companies need to be thoughtful and specific as they explore this new gig environment for filling the white space in their skills requirements. Having a strong idea of what a successful hand-off will look like is essential because, like an Uber driver, the gig specialist will be driving off down the road without a rearward glance.
Related Article: Understanding the Tech Skills Gap
About the Author
Kalyan “KK” Kumar is the corporate vice president & CTO, IT services of HCL Technologies and the company’s business line leader for Global Cloud Native Services and DRYiCE products and platforms. He also leads the Service Line for Global Infrastructure Services.