Why skills strategy fails

It’s an all-too-familiar tale. An organization needs to change or transform in order to survive. However, they do not know what skills their people already have, which means they also don't know which skills they need to 'buy'.  

Even IF they do know which specific skill gaps they need to close, they are finding it increasingly hard to do so. Talent is either thin on the ground, concentrated in a few places, or in some cases simply non-existent.

In the meantime, as change continues at a rapid pace and as new technologies [and related jobs] emerge, we see increasing numbers of people within companies whose current skill-set will be redundant within the foreseeable future.  

The specific twists and turns of this tale may differ from one organization to another based on sector, geographical location, etc., but they usually converge at the same point:

A situation where there are jobs to be done, but not enough skilled people to do them.  

Data from most developed countries suggest this is the case, and all the indicators point to this problem getting worse as AI-powered digital transformation continues to disrupt one industry after another in ways that were unimaginable even just a decade ago.

It's worth noting that many people have been predicting for years that while a significant number of blue collar jobs will be automated and eventually replaced by machines, the net result is likely to be more jobs, not less.  

However, from an organizational perspective, it's obvious that the shortage of a skilled workforce means that it becomes more difficult to be able to deliver their products or services properly. So what we see increasingly are gaping wounds at the very heart of the enterprise, which, left unattended, eventually necessitate major life-saving surgery.  


Why is skills strategy so hard?


How do we avoid this type of scenario? How do we turn these potential horror stories into more positive ones? In my opinion, the only solution is to proactively re and up-skill people. When performed on a large scale, this process also lends itself to strategically looking at which capabilities you want to develop as an organization.

This seems logical enough on a conceptual level, but it immediately raises our first challenge because skilling at scale is often easier said than done. The problem is compounded by the fact that our formal education system is simply not designed for it. Which in turn brings us to the core of the issue many companies are only now coming to terms with:  

Organizations can no longer rely on the education sector to deliver skilled people to the workplace. To quote Nick Van Dam, ex-CLO at McKinsey, the "workplace has to become a learning place."

And now to the second, equally pressing challenge; one that will be sadly familiar to most learners- current practice is still very much focused on the classic model of training.  

Yes, COVID-19 may have brought about some (long-overdue) changes to the way corporate L&D functions, but in many cases these were done as a short-term fix and too many companies have now reverted to type as their people return to offices.

The issue of course, is that apart from being expensive, traditional models simply don't scale. We might be able to get 'bums on seats' but the point of an L&D function is not to run a cinema.  

Aside from enrollment figures and completion, how do we determine what the return actually is when it comes to training sessions? How do you verify someone has actually mastered the skills needed for a new role? How do we differentiate between theoretical knowledge and the capability to apply this on the job?  

These are the questions that need careful consideration, and the answer to too many of these questions is : It's on the roadmap.

The goal should be job readiness and performance improvement, not just knowledge acquisition- which is part of the reason why the formal education system is broken.


How do we address the skills challenge?


In my experience, the only way to do achieve this goal successfully is through a holistic approach, focused on creating a learning ecosystem. This ecosystem is not exclusively about the tooling, as many organizations often think. Nor is it just about stitching a collection of learning systems together.

A true learning ecosystem concerns a variety of different actors, partners in learning strategy and culture, learning content and programs and learning systems and infrastructure. It is important that all these partners are supported by data-driven insights. You cannot set up sustainable reskilling within your organization without insight into data.

Ah yes, data. That other oft-repeated word. Was it the new gold or the new oil? It's difficult to keep track. But whatever it is, it's impossible to talk about skills without data. So it becomes critically important to be able to collect the right data and more importantly: interpret that data in the light of reskilling.  

Which brings us back to that common language we talked about earlier. A skill framework or ontology lends structure to the knowledge and skills of your people, the role they perform and the strategic capabilities that your organization needs.  

When done right, it creates a foundation for harmonizing various initiatives; for example between recruitment on the one hand and talent and leadership development on the other. After all, it all uses the same skill framework.

So we've seen how skills can form the basis for data-driven reskilling. But that means that you have to think about how you implement skills at all levels.  

At a strategic level, it affects your workforce planning, but also your performance conversations and overall learning culture. Learning content must be standardized and classified based on skills. Learning and leadership programs need to be restructured based on skill profiles.  

And at the learning system level, employees must be able to create skill profiles, set skill goals, make skill gaps transparent and receive timely and relevant recommendations.

Once you have done this and are able to store that data, you can use it to further steer building your strategic capabilities. You then have insight into which skills are located where in your organization, you can see where the most important skill gaps are when it comes to executing on your strategy, and you can see which skills people are developing and which skills are lagging behind. But it also makes it easier to plan targeted interventions to stimulate the development of certain skills.


The centrality of skills for modern talent strategy


In today's world of work, it is important that you are able to grow your people in both vertical and horizontal directions. Vertical progression is the classic form. You develop from junior to medium to senior, and then on to lead, manager, manager of managers etc.  

We're now seeing that horizontal progression is more and more common. Many young people are also specifically looking for this. For example Joanna may have joined a bank as a KYC analyst, then became a scrum master, then front-end developer and now is a data scientist. Many like Joanna don't want to stay in one position for too long, but learn many different skill sets before growing further vertically.  
                                             


So where once there was a corporate ladder, now there is a lattice. This not a new concept, as this article from Deloitte in 2011 shows. But a combination of factors in the past decade, including changes in organizational structures, workforce demographics, technological advances and more recently a post-Covid realignment has meant that the corporate landscape is fundamentally altered.  

In fact, more than ten years ago companies were experimenting with remote working and were surprised by the results. One example provided by Forbes is of the telecommunications provider Frontier Communications where they let 30% of the call center agents work remotely, often from home. What they found was that 25% were more productive and had double the retention rate of agents who worked in the company's traditional call centers.

The debate around office / remote work may well rage on for a while longer, but what is clear is that organizations need to grapple with these challenges and find win-win solutions together with their employees.  

Focusing solely on the needs of the organization, or being wedded to old models that are no longer fit for purpose, will only lead to them losing their talent in large numbers, like what we saw a couple of years ago with ‘Quiet Quitting’.

This is the context in which the talent marketplace platforms are entering the scene. But as with most things, simply implementing a technology solution is not going to get you to where you want to be.

Unless the system finds a proper place within your wider Learning Ecosystem, your skills frameworks are owned and maintained by L&D and you have the right kind of learning assets to serve up to people, all the AI in the world won't solve the problems around talent deployment, development, or acquisition.

Ultimately, what you need is a specific mechanism that consists of three critical components. If you want to increase the skill mobility of people, they need to know what their current skill set is and how big the gap is from a desired new role. The ability to determine someone's skill level is critical. Finally, you also want to give people the opportunity to bridge the gap by helping people to develop the required skill set as effectively as possible.

Fedor Hagenaar

Fedor
CEO & Founder

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