I am not sure of the reception in a recent interview opening with: "I know we are aligned. Your mention of a Skills-Based Approach in a recent article confirms you, along with the industry, are playing a game my team defined with a methodology (Skills-Based Approach) and again with a system/method (Skills Label)" ...
Much of the interview centered on how our labeling system, apps, and platforms differentiate. For me, there is so much, but mainly precision, source of truth, Skill Points, the label rendering itself, and Human-in-the-Loop. The analogy I use frequently is the use of skills and Skill Points to define and quantify, like atoms and coefficients.
In the 17th Skills Label Insights Report, Ranked Skill Atom Report, we provide an overall ranking of our top skills (with % of Job references), reveal our acronyms and show the average Skill Points using an atoms theme.
Here are some of the challenges I faced in the interview:
"I get the science analogy, but what does that mean in practice?" (paraphrased)
Stacking. Use the same skills and Skill Points to connect a series of learning to jobs, and to corporate tasks and projects, all proportionally. (A simple 1 to 5 scale is not sufficient.)
"Why a 1M scale (mastery of a skill) for the Skill Points?" (asked skeptically)
Simplicity and Precision. Coefficients coalesce the variance in skill acquisition rates, so the 1M scale is measured and works. (Being immersed in the iterative design of the label’s appearance, it makes sense for legibility.)
Fortunately, we agreed time is not a good indicator of skill acquisition rates.
View the complete report on Skills Label Insights. The PDF version includes the top 100 ranked skills, while the live version renders 16 randomly selected skills. All the data is solely sourced from the Job Label Catalog.