Empowering the Future Workforce, Part 1: Mapping the Skills Landscape
We’re in the midst of another Industrial Revolution—and while we can expect great things to come from technological advances (like increased automation), we’re going to need to work collectively to prepare ourselves for the changes that are to come. We can rest assured, however, that newer, more efficient jobs are on the horizon. Soon, we’ll start to liken the workforce transformations of today to those of the 18th century Industrial Revolution, when we witnessed the now obvious transition of certain roles like carriage drivers to taxi drivers (and now, rideshare app drivers). But before we can realize all the good, productive outcomes from a revolution, we must admit that change is not easy.
In this next Industrial Revolution, led by the perforation of AI into every industry, how can we actively ease the transition for organizations and their people? Let’s consider this: the automation we are familiar with today often replaces menial tasks, which in turn alters the value that certain roles bring to an organization. In the near future, however, we may start to see AI’s responsibilities shift from objectively placing doors on a car frame to subjectively selecting the best product from a bin with almost infinite combinations of shape, size, texture, color or weight.
What this means is that the AI Industrial Revolution will impact every role across every industry, but not necessarily equally. While some roles will only see a shift in certain automatable tasks, others with a higher percentage of repeatable tasks will experience more disruption. In order to fully grasp the extent of the impact on various roles and industries, we first need to understand the skills landscape.
Governments, non-profits, educational institutions and businesses alike are all going to have to play a part in global reskilling and upskilling initiatives. As AI continues to mature, the private sector will need to be more deliberate and strategic in building skills within their people if they want to achieve desired business growth.
As your organization embarks on a journey to map out your unique skills landscape and drive actionable insights, be sure to consider the following capabilities: a unified view of skills, the measurement of proximity of different skills, and continuous monitoring of new skills.
A Single View of Skills and Capabilities
Even in mature HR organizations, it’s a heavy lift to implement a skills framework that provides insights into which roles require which skills, who has which skills, and which skills are needed from an organizational standpoint. Many teams are only able to complete this sort of work for a relatively narrow scope.
There are natural barriers around hierarchies, languages, and intensive specializations, which make it difficult to capture a cohesive picture of skills within an organization. Many traditional and even new skills technologies struggle to get past these barriers, only providing pieced together fragments of skills mappings.
However, there are also next-gen solutions, which sit on massive sets of data gathered from public, private, and academic sources to aggregate a global pool of any term that could be used to represent a skill. From there, Natural Language Processing, analysis, and eventually AI structure these terms into unique "nodes" that can ingest synonyms across global languages to represent skills evenly across the organization. Similar to the world of finance, where we convert the balances of different accounts into a single view to make decisions, this is like creating a single skills balance sheet to understand how to invest for the future.
Gaps and Importance of Proximity
Most of the ink in the future of skills is spilled on gaps: what skills do people have now and what skills are they lacking for the future. With this narrow view, the work ahead of us looks incredibly daunting. In order to have a better understanding of skills evaluation—and achieve more impactful results—it’s critical that we consider proximity and adjacency.
Take, for instance, clinical research and market research. Intuitively, the names tell us there are commonalities and fundamental differences between the skills required to perform in these areas. These two skills have a correlated distance, or a proximity, to one another. They also have skills that cluster or are closely adjacent to them. But how much is the same and what exactly is different? The clusters surrounding those skills and their own distances from similar skills help provide that key insight into creating a pathway from one set of skills to another.
Instead of proximity, many solutions focus on hierarchy in organizing sets of skills. Why? Understandably, to help ease human navigation and use. But of course, more advanced solutions also unlock the power of understanding the relationships between skills, as well as the distance, and that is critical to maximizing effectiveness of HR initiatives.
Future-Proofing Your Skills Inventory
Another important concept when considering the new skills revolution is the context of the roles they impact. There are, what we call, "deep roles," which are very specialized in certain areas that may rapidly change and adjust. These roles will see their skill sets change in concurrence with technology. For instance, highly specialized roles in Natural Language Processing will need to have at least an awareness of new technologies and techniques as they are announced to maintain relevance in the market.
Supporting these scenarios and the many in between is very difficult for humans to do. That’s why new generations of intelligent skills engines have emerged to actively crawl the web looking for job postings, resumes, blogs, training videos, and other public and private data. These tools help us understand how the global skills economy is shifting. Eventually when there is enough data to be confident of a new skill, the skill is mapped into individual roles to keep workers in those roles competitive with equally dynamic training recommended to help skill them.
Why These Criteria
There’s no doubt we will continue to see innovation in the skills department as upskilling remains a top business and talent priority. With that, there will be many criteria to consider when evaluating the tools needed to support the future workforce. The outcome will be a single up-to-date dashboard of skills across the business that sets the organizations up for success as they plan for the future.
With these criteria in mind, organizations can have a clearer picture of how to invest in their people development. The driving force that gets us from today to tomorrow is skill-building. This development takes time, and it's successful when it’s pinpointed and personalized. With the sheer volume of employees and their nuanced roles, we have to prepare to fill the 95 million jobs of the future quickly and efficiently.