The Skills Conundrum

Ian Cook / Posted On: 11 November 2021 / Updated On: 2 December 2022 / International Thought Leaders / 154

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The Skills Conundrum



The promise of skills

Everywhere you turn these days there is a buzz about skills. Somewhat like Bitcoin, skills have been cast as the new “currency” in HR.  However skills are not a new concept, over the 30 years of my career there have been 2 prior “skills waves”.  These were driven by disruptive market events, which led to the need to re-align people with new ways of work and new ways of doing business.

 

At the heart of today’s buzz around skills has been the rapid, and continued need, to match people with work. This matching process has changed dramatically because our new business climate means the work being done is so different than a job title alone will not work to match candidates to open positions. Add to this the scarcity of talent caused by an overall reduction in the size (and willingness?) of the working population. And you get a situation where certain businesses are losing out on revenue due to a lack of people. This is driving urgency into new ways of matching people to work. The new way of matching is to leverage the skills associated with individuals as well as the work to be done.


The opportunity for enabling people and work to find each other through a skills-based approach is deeply exciting. This is especially true when you consider how much of the economic harm that is the outcome of poor diversity, is caused by opportunity going to those with the right job title, previous employer, or educational background. At its theoretical best, skills create a playing field that is level, merit-based and agile - bringing opportunity and growth to everyone willing to invest in, and champion their talents.

 

The Skills Conundrum

And yet for all of the compelling business drivers and wondrous potential to unleash human capability, there is a conundrum at the heart of the application of skills to business which makes its widespread adoption and uses fraught with challenges. Those who are looking to realize the potential of skills, and are willing to make the right investments, are better placed than ever before to succeed. Those who are following the skills rainbow, on the assumption it leads to a pot of gold, are in for a shock.

 

To understand why this is true we need to unpack the conundrum that is at the heart of any organizational work involving skills.

 

Challenge 1: Skills have no inherent value

The value in skills is not in the information itself. The plethora of skills that can be attached to each individual, or job, quickly becomes so overwhelming it is just noise. The tangible value from skills data comes from how this information can be used to solve for a few specific business challenges. Ask any CFO if they would invest $100k to understand the skills of their labor force, the likely answer is no. Ask them to invest $100k to ensure the right people are assigned to projects which must succeed to generate the promised revenue growth and this answer changes. Getting this work funded is challenge.

 

Challenge 2: Off-the-shelf skills standardization is limited

Whilst a number of skills ontologies/taxonomies exist, most of them are limited in their application. The challenge with any standardization approach is that it, almost by definition, removes important areas of nuance or insight which may actually be differentiating. Ontologies are derived from existing data and need sufficient volume to create a standard. If what your business is doing is new, or unique, then the differentiating skills related to your work are unlikely to show up in any standard ontology. There is no quick way to build the standards which fully meet the needs of your business.

 

Challenge 3: Skills without standardization are impossible!

This is where the conundrum starts to truly bite. The value in skills comes from being able to match people to work. To do this successfully you need standard skills data that describe the job/work, and also describes the person who can perform the work. These two sets of data combine to detect matches, gaps, and adjacencies, enabling people to be recommended for work, or work to be recommended to people. (Work typically done by complex scoring algorithms). But without the money, or the opportunity to develop a standard that aligns to your business, you cannot perform this matching work. You cannot deliver the value which makes this work valuable.

In summary, the Gordian Knot of skills that many PA leaders are working to unravel comes down to the following. There is a core need to generate some form of standardized skills model, to support a number of skills matching use cases. Existing off-the-shelf ontologies only cover 80% of the business skill requirements and costly data science work is required to complete the missing 20%. Even if you get this work done, and the money is spent, you still only have an outcome that is not interesting to the business. The PA work only creates the conditions for a solution, rather than solving an actual problem.

 

Threading the skills needle

There are numerous ways that organizations are attempting to work through, and around, this conundrum. Let’s take a look at each of these to understand if and how progress may be made.

 

Employee curated skills

In a recent group discussion, about 60% of the participants were following this approach. They all owned new HRIS systems, which came with a “skills” module. The capabilities of this module allow employees to create, share and validate their own skills profiles. The more advanced ones are underpinned by an ontology so that you don’t end up with 2million unique text entries!!

 

Sounds good right?  Here is a free way to capture and standardize skills - all we have to do is ask employees.  Employees operate very much like a CFO when it comes to their time, they invest it where they think it will give the biggest reward, or avoid the biggest pain. Completing a skills profile, skills for skill's sake, do not fit into this category. Whilst there are mechanisms and practices by which self-reported skills data can be grown, the history of this work indicates that this practice can be successful on a project basis, but that the investment of human time and energy to keep the skills maintained typically falls off once the immediate pain has been resolved.  There is always something more urgent.

 

Outsource a piece of the problem

Another avenue that has seen rapid adoption, and early success, is to outsource not just the skills component of the business issue but to outsource the whole transactional problem to be solved. Internal talent marketplaces are examples of “skills in action” products. The technologies, and their providers, take care of the full end-to-end process of understanding people, understanding work, facilitating the opportunities for change, and re-alignment, all driven by skills at the core. For any organization looking to foster employee-centric growth and mobility, they are a sound investment.

 

The conundrum kicks in when you need to move on to business issue 2. Whilst your internal talent marketplace is building talent mobility, how do you use the same data to drive your next workforce skills project? The core data may be accessible and may overlap to some extent with your next challenge. However, it is almost guaranteed that the workforce you are designing to compete in new markets or tackle new business models does not contain the skills or skills combinations that will create a competitive advantage for you.

 

So what to do? Opt into a different 3rd party vendor, and use their tools for this business workflow, or go back to the CFO to ask for money to build your own bespoke ontology? This is a very real scenario, a contact of mine was recently asked to integrate data from 2 outsourced skills tools, as well as some employee curated content, to solve for a new employee development initiative. When each ontology can be over 50,000 items, and no proven crosswalk between different standards exists, even the most capable people analytics professional is likely to balk at the work to value ratio involved here.

 

Build your own ontology

The capabilities and technology exist which make it viable for an organization to build its own ontology. It is not a cheap undertaking. Assume at least one or more data scientists for 6-12months to create it. It is also fraught with “expert” risk. I have heard of two organizations that lost their data scientist just as the skills ontology work was coming to fruition. The knowledge to execute and maintain the project walked out in the head of those people. So the risks of building your own ontology are not purely technical.

 

Where to now?

If working with skills is starting to feel daunting, you are likely wondering how to balance hype with progress! And it would be disingenuous to promise there is an easy button that ensures a smooth escape from this conundrum. However, there are guiding principles that can substantially raise the likelihood of delivering results and more importantly ensure you avoid the vortex of wasted time and energy that is often the result of such a massive hype cycle.

 

For your consideration here are my rules of thumb.

 

No dollars, no dice!!

Attempting to do more from the edge of the desk has done more damage to the credibility of HR than anything else. If you are being asked to work on skills-based projects, then you need to determine the willingness of the business to invest upfront. It will take money. Let’s start and see how we go is not a viable strategy. If there is no willingness to invest, then the only work to do is research that proves no one has had a skills success without adding either technology or people. Investing to solve this problem is essential.

 

One ontology to rule them all

To truly unleash the power of skills in solving the myriad of business problems to which they can be applied, you need a single ontology that can drive all the associated tech. But you don’t need to build it all. The two options are to partner with a 3rd party who can custom build and maintain an ontology for you - data science on demand. Or rent a core ontology from a 3rd party and fund the work that augments this with the special 20% that is differentiating to your business. Integrating this work into the project stages of solving a specific business problem will make it much easier to get funding. Making it part of a business fix is more likely to lead to funding, than positioning it as a standalone piece of work. When it comes to funding optics is everything.

 

Shrink the business problem space

Success will come through focusing on a specific population, delivering a specific piece of work, with a clear impact on business objectives. We undertook a re-skilling project at Visier developed around enhancements and automation to certain aspects of our key roles. For our size of the organization (500EE) the work volume required to successfully deliver a project which affected 20 people was manageable.  Trying to run two at the same time would have guaranteed that both failed! When approaching any form of business problem involving skills the key is to make it as small and business-focused as possible!

 

Don’t forget the ethics

In amongst all the cool AI and funky vector math associated with skills capture, analysis, and recommendation, it is easy to lose sight of the reality that behind all the data is a living, breathing, human being. Done badly, skills matching has the potential to damage individual opportunity, and systematize invisible bias into your processes. If you are building this yourself then my recommendation is to lay down specific ethical guidelines that everyone on the project is committed to. If you are working with a 3rd party then a commitment to transparency and constant validation are the start points for a good relationship. “Trust us, it just works” as a response from any vendor, is your sign to walk away.

 

The promise is likely worth the squeeze

Being a leader in the people analytics space is rarely easy. The practices, insights, and community-engaged in this area have, and will continue to re-shape, the dynamics of people and work. I have been privileged to see many of these stories unfold, where organizations moved from finance first decisions to people-centric decisions and made more money in the process. The ability to effectively use skills to navigate crucial business processes and facilitate growth for everyone is enormous. Whilst there is no rainbow to follow, doing the right work, properly funded, and with shared awareness of the trade-offs, will lead to big rewards. Better still these rewards are in both the social and financial aspects of the business.

 

The post "The Skills Conundrum" was first published by Ian Cook here https://www.linkedin.com/pulse/skills-conundrum-ian-cook/

 

About Ian Cook

Broad experience in driving organizational growth working both as an external consultant and through internal leadership roles.

The strong and varied business background includes consulting roles, sales roles, operational management and executive leadership. I am recognized as a capable people leader.

Specialties: Strategic planning and developing metrics
Leading transformational change
Product innovation


Ian Cook
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