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There is a future where, at your job, you’ll be given a test every day. 

The test will be short (there is work to do after all) and it will be variable. Yours will not be the same as your teammate’s. The questions will be adaptive (they will get harder as you get them right). Adaptive testing, after all, is much better for true results.

I realize this may sound like torture to some. Testing every day? Questions getting harder until I get them wrong? Yikes.

The good news is that there is gold at the end of this testing rainbow: a direct and customized learning plan made just for you, focusing on exactly what it is you need to learn, and, eventually, tools with how to learn it best (that’s where your local learning and development team of the future will come in).

The other good news is that, through the data gathered from this, truths will emerge. Who is good (or bad) at what? New people analytics models will start to infer what jobs you’d be a great fit for and talent teams will see who’s truly ready for a promotion or internal mobility.

The organizations of the future will have a very real idea of who is the best fit for certain roles and levels. We’ll be able to hire based on these skills instead of just years of experience or the luck of a promotion to fill an open role.

Indeed, the age of AI that is upon us will open up new frontiers in skills assessments and understanding organizational skills gaps.

Not every company will employ what I described above, but it’s almost certain to me that the future has more assessments and a move away from judging employees from once- or twice-yearly performance reviews.

Here, I’ll outline why I think our current skills assessment methods are inadequate and why we’ll see innovations like I described above in the future, knowing just how important skills are to the modern organization.

Why Employee Skills Assessment Matters

Skills have become big business. As Josh Bersin breaks down here, building out skills matrices and competency models has been an organizational obsession for the better part of the last decade.

Organizations are racing to re-establish people practices like a company’s hiring process or training methods around a skills-first approach.

Just last week, Karin Kimrough, the Chief Economist at LinkedIn, and other HR professionals went to Congress to talk about the value of a skills-first approach to the professional world of the future.

As it’s been put, skills are the “currency of the future”. We know that they matter and will continue to matter.

In an economy increasingly reliant on thought leaders and workers and less on manual labor, it is our cognitive abilities that increasingly determine our value. It is the sum of these abilities that underlie a business’s value.

Skills, in short, are a building block for our human capabilities and thus our place in the professional world.

And the numbers prove this. The soft skills training market alone is estimated to be more than $47 billion and, since skills are estimated to change dynamically in the coming years, this will only grow.

Put short, the obsession with skills—their place within job descriptions, job performance, and job productivity—is here to stay.

But Bersin points out that all this work has probably just put us at the starting line, and that learning programs and companies are probably the furthest behind. 

We want to be skills-forward, to think of jobs, roles, and pay levels in terms of what people are capable of instead of college choice or simple years of experience, but we’re not quite there yet. 

The Current State Of Organizational Employee Assessment Strategy

I do think we’re a few years out from the vision I laid out above, so it’s worth looking at where we are today.

Many organizations have done a great job of building out competency models, running skill gap analysis, and laying a foundation for building future skills in their learning management systems.

The best ones achieve this by working backward. They start with the idea of what skills they want to create or upskill in the first place (among their population).

It’s crucial to start a skills assessment strategy by working backward. Just don’t dwell at this stage too long. I’ve seen companies take years honing and tweaking competency maps and models only to fall short on actually testing or assessing the assessment tools. 

In this great article, Forbes contributor Allison Dulin Salisbury makes the case that, in our drive to have perfect skills data, we’ve lost sight of the bigger question of how having this information will drive positive change.

Maxwell Wessel, Chief Learning Officer at SAP, adds to this sentiment, “In reality, most of our organizations are facing big changes that require us to be thoughtful around the 5-10 skills we really need to build at scale. Getting that thinking done, and then getting into the real workforce change, is so much more important than getting the skill definition perfect.”

So, once you can have a target set of competencies or skills, you can start assessing. This is easier said than done, of course. And it’s also why we haven’t made great strides in the last decade in measuring skills, especially so-called “soft” ones.

As it stands today, organizations use a variety of skill assessment approaches. I’ll list those out here and discuss my critique of each, showing why we’ll need to be more innovative to uncover the truth of our real talent. 

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Methods of skills assessment

Hard skills exams

Perhaps the easiest of all assessment types, these are used for testing for skills where questions have specific and clear solutions.

Hard skills exams give you a clear sense of how much someone knows about statistics or laws, but you need to assess early and often to really uncover this and, if these aren’t adaptive, you’re asking folks who may be experts already to waste time assessing themselves. 

Workera, a new startup, is aiming to disrupt this with better testing (see the section below on adaptive assessments) and by giving employees a customized learning plan based on their scores.

Soft skills exams 

Only a few Talent teams have tried moving toward soft skill exams to measure talent, but it will be more popular in the coming years. The challenge now is defining these skills and the content you want to test on.

What is the “right” way to measure communication or collaboration? Right now, we don’t have that definition and I don’t think we’ll ever have an objective one. Instead, organizations will design their own approach to these—based on their product, values, strategy, etc—and can then test on it. 

For now, very few are doing this and relying mostly on performance reviews to understand their talent at large

Case studies & hands-on experience

These are a good workaround to feeling like you’re burdening folks with a culture of assessment. 

After all, learning should be fun and interactive (often forgotten about for adults). So companies are innovating with simulations and case studies and seeing how folks react, respond, and show their strengths. 

However, these are not always the actual skills employees need on-the-job and the grading or assessment parts of these can often be specific to the task at hand instead of broad to fit a whole skill set.

Performance Reviews 

Probably the most used form of employee assessment and yet they, and the very idea of subjectively judging a skill set, provide a loose base to evaluate folks on. Let’s chat about a bit more in the below section.

Performance Reviews And Subjective Skill Sets

Of course, most companies are still going to revolve a lot of skill measurement initiatives around performance reviews. 

Since this is established practice at companies, many use this opportunity to ask managers, peers, and employees themselves to weigh in on their own skills and career development. 

This then ties into things like promotion, bonuses, and compensation, and becomes a kind of jockeying for whoever can tell the best story about their growth.

There are obvious flaws here. One is that, typically, this only happens once or twice a year at best. The second is the obvious subjectivity of trying to gauge team skill sets, including the subjectivity born out of recency bias (although more continuous performance management can help mitigate some of these issues).

Often, performance reviews come with self-assessment as well and, for much of the last decade, we’ve measured skills and skills growth by asking people how confident they feel in their ability to do something.

There’s danger in this of course, not just because of the Dunning-Kruger effect where we assess ourselves above average, but because we start to treat skills as confidences instead of actual abilities.

Companies have built their ROI stories around employee development on this idea of confidence. You can see iterations of Degreed doing this below—the ratings in this case are given by the person (or a manager) and are self-reported.

focus skills screenshot

In the “audacious” future I described at the start of this article, there will be no need for self-assessment of skills, only effort and sentiment. 

The idea of trying to gauge how good we are at something will be met with a swift change—the way I should not insist I could be a professional bowler or major leaguer. I don’t have what it takes, regardless of how I feel.

There’s good news though. Adaptive assessments will not only positively impact the employee journey, they’ll also be easier and easier to make—having profound repercussions in building employee strengths, productivity, and recruiting.

Adaptive Assessments As The New Way

We know from studies like this that employees stay at jobs where they feel like they’re growing. 

But that’s just where that data ends—this piece of retention is based on a feeling

We haven’t yet translated what it could do to an organization’s culture if workers are actually getting better at the necessary skills for their roles and careers. If they could see their own progress and recognize their employer as a true facilitator of their growth and development. 

From onboarding to offboarding, a person should be able to approximate their growth in a certain skill or two.

We should be able to look back at jobs and see them for the skill accelerations or jumps they provided, not just the titles or roles we had. 

I think we’ll look back and wonder how it was that hiring managers selected the best candidates in recruiting without knowing their real skill benchmarks. How did we allow the creation of resumes where someone swore they had certain skills without ever having proven it?

Companies should want to know this data too. Learning and development teams need to start being more data-forward and should, in the next few years, be expected to hand data to their leadership on skill growth by department and aggregated over groups or the company as a whole.

Those that are doing this today (and I demonstrate how you can do so here), are better equipped to meet the demands of a changing workforce and get more budget for L&D programs by showing the business and productivity impacts.

So you see where I’m going in my vision. Assessments are a net positive for everyone—from human resources teams, to recruiters, to business leaders. It’s the catalyst to a new age of learning (which will be AI-powered in its ability to enable personalized learning plans and tutors) and our approach to uncovering the true skill level of all. 

And the good news is this: it’s never been easier to produce assessments. AI will make it easier than ever to create the needed kind of content: questions, tests, quizzes, hands-on practice, etc.

This new technology will shape much of what the testing experience is like going forward. We’ll have thousands of questions on any skill to test on, and they won’t just be the same multiple choice or true/false that you’re used to. Imagine doing a case study that adapts to your answers in real-time—that’s what AI can do.

And it will be able to do it on any topic, starting with any piece of content. Generative AI tools can take a video, PDF, or article and turn it into assessable content. Imagine quizzing folks on the company’s 5-year strategy to make sure they understand.

I’ve been advising (full disclosure) a company called Learnswell this year that’s doing just that, but many others are now too. The technology simply makes it easier than ever to test on whatever you’d like.

Employee training will see the revolution from better assessments and better analysis and it will be part of the productivity rise that AI can promise.

Wrapping Up On Skills

Skills is the buzz about the proverbial town right now. Organizations are building frameworks to understand what skills are needed to succeed in each role. Companies are selling trainings wrapped around specific skill-building. 

This feels like all the right infrastructure for now, especially when you consider that estimates say as many as 40% of current skills will need to be changed in the workplace by 2030. 

The advancements in technology, data analysis, and employee platforms make it as ripe of a time as any for massive innovation into how we build, measure, and deploy skills and skill strategies. Gone should be the days of watching a video about a skill you think you might need in the coming months. 

What should come should usher in a revolution in skills measurement and personalized learning that comes from that.

You’ll have something akin to a baseball card with your metrics and ratings on whatever skills you’re pursuing. Companies can and will hire from this. Organizations will sell you what you need to get better. It may sound a bit funky but it could usher in the most effective upskilling era in human history.

So let’s get to it!

Curious to hear your thoughts here to leave something in the comments or join the conversation over in the People Managing People Community, a supportive community of HR and business professionals passionate about building organizations of the future.

By Eric Grant

Eric Grant has 12+ years in Learning & Development managing programs and teams in high-growth environments at organizations such as LinkedIn and Coinbase. To add greater depth to his practice, he's currently pursuing his Masters in Analytics where he’s focused on how to leverage data science to unlock human potential.