Every time I talk to people about skills management, we arrive at two conclusions: 1) skills management has a ton of potential benefits; and 2) it’s incredibly confusing. The market is full of articles unpacking number one, so I want to share what I’ve learned about number two. Skills management might seem simple at first, but lifting the hood feels like opening Pandora’s box. Here are just a few questions that fly out, demanding answers:
First, you realize there are different types of skills; the most simplistic split being technical or “hard” skills vs. core or “soft” skills. Technical skills are easier to measure, assess, and quantify, but the core skills, which everyone agrees are critical for organizational and individual success, are much harder to evaluate, standardize, and track. So how will you manage these core or soft skills? How will you assess them?
Say you can decide which skills you want to keep track of, but how do you know for sure that someone has a skill? What level is their skill proficiency — I don’t want to be operated on by someone with a beginner’s level knowledge of anatomy, thanks — and who is the best judge of that? Do you trust the person’s self-estimation of their skills? The Dunning-Kruger effect says maybe you shouldn’t, and at the same time, we are blind to our skills: AI can identify three times the number of skills that humans can when appraising themselves. But if you don’t allow self-reporting, does that alienate your employees and risk causing feelings of unfairness?
Speaking of evaluation, skills management leaders now have more choices about which voice to trust because skills technology can ingest peer feedback, managers’ assessments, learning management system (LMS) course completions and assessments, work activity, customer feedback, and the list goes on. If you name the data source, you can probably factor it in. So what kind of weighting would you give to each stakeholder’s opinion about a person’s skill? How will you account for the biases that crop up when one person judges another?
It’s a lot to consider, and we haven’t even talked about proprietary skills, harmonizing skills data across platforms, or how siloed products can limit your understanding of skills and the value you get from them. It’s no wonder why organizations are searching for a clear beacon of truth and no wonder why there are several consultancies willing to serve as that lighthouse. Some vendors try to help their customers avoid this “analysis paralysis” by putting guardrails up and providing more answers out of the box. To illustrate: One skills intelligence vendor told me they don’t try to approximate proficiency levels and core skills through their AI because that’s where humans have a role to play, not the system. On the other hand, another vendor cares deeply about proficiency levels and has standard definitions of each skill’s proficiency levels out of the box.
I originally said we arrived at two conclusions when contemplating skills management, but there is a third conclusion we all reach about skills-based talent practices, and that is that you should “just start,” and people smarter than me say the same. But it’s understandable to get stuck — not all skills intelligence vendors are the same, especially in their appreciation for how complex and nuanced skills management is. The great news is that in such a hot market, vendors are moving quickly to develop better solutions to address the nuances and make the Pandora’s box less scary.
This post was written by VP, Principal Analyst Betsy Summers and it originally appeared here.