Every time I talk to people about skills management, we come to two conclusions: 1) the potential benefits of skills management abound; and 2) it’s incredibly confusing. The market is full of articles on spotting number one, so I want to share what I’ve learned about spotting number two. Skill management may seem simple at first, but lifting the hood feels like opening a Pandora’s box. Here are some of the questions that fly up, demanding answers:
First, you realize that there are different types of skills; The simplest division is technical or “hard” skills versus core or “soft” skills. Technical skills are easy to measure, evaluate and quantify, but core skills, which everyone agrees are critical to organizational and individual success, are much harder to assess, standardize and track. So how do you manage these core or soft skills? How would you rate them?
Let’s say you can decide which skills you want to keep track of, but how can you be sure that someone has the skills? At what level is their skill proficiency – I wouldn’t want to be driven by someone with beginner level knowledge of anatomy, thanks – and who is the best judge of that? Do you trust the person’s self-assessment of their skills? The Dunning-Kruger effect says you probably shouldn’t, and at the same time, we’re blind to our skills: AI can identify three times the number of skills that humans can when evaluating themselves. But if you don’t allow self-reporting, does it alienate your employees and run the risk of creating a sense of unfairness?
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When it comes to assessment, skills management leaders now have more options on which voices to trust as skills technology peer feedback, managers’ assessments, learning management system (LMS) course completion and assessments, work activity, customer feedback, and can swallow the list. , If you name the data source, you can probably factor it out. So what kind of weight would you give to each stakeholder’s opinion of an individual’s skills? How do you account for those biases when one person judges another?
That’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 many counselors are eager to serve as that beacon. Some vendors try to help their customers avoid this “analysis paralysis” and provide more out-of-the-box answers. To paraphrase: A skills intelligence vendor told me that they don’t try to predict proficiency levels and core skills through their AI because that’s where humans play a role, not systems. On the other hand, another vendor cares deeply about proficiency levels and has standard definitions of proficiency levels for each skill out of the box.
I originally said that we come to two conclusions when considering skills management, but we all come to a third conclusion when it comes to skills-based talent practices, and that is that you “must start now”. And people smarter than me say the same thing. But getting stuck is understandable – not all skill intelligence vendors are created equal, especially in their appreciation for complex and nuanced skill management. The good news is that in such a hot market, vendors are moving quickly to address the nuances and develop better solutions to make Pandora’s Box less intimidating.
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This post was written by VP, Principal Analyst Betsy Summers and originally appeared Here,
