Tools are NOT Skills

Skills NOT Tools

Tools are NOT Skills

ALERT: A list of tools is NOT a professional skills inventory

BUT all too often this is the situation.

It’s like saying the skill of arboriculture (tree surgery) and cabinet making are the same because they both use a saw!!

You need clear skill definitions preferably based on a global skills framework, of course, SFIA (Skills Framework for the Information Age) is definitely worth considering because it’s the de-facto skills framework for the data/digital economy.

It’s time to call out the tools vs skills overlap because it’s not helping properly define targeted career development plans. I’ve seen too many times the TAB in a Human Resource system entitled ‘Skills’ but when clicked we see a list of tags, some broadly aligned with competencies but often associated with technology. Documenting ‘JavaScript’ or ‘ITIL’ or ‘Agile’ is missing the point. For sure, it’s useful to know somebodies’ specialism(s) but more importantly we need consistent and accurate definitions of the competencies/professional skills first. I would rather know what level of Project Management skill someone has rather than which methodology/approach they use.

I look forward to the time we see a job advert like this:

  • ‘Programming/Software development Level 4 (SFIA) with JavaScript and C# knowledge’.

Rather than the usual

  • ‘JavaScript Programmer’.

It’s only a subtle difference but makes a world of difference in terms of specifying what’s required for the job and building development plans based on professional skill gaps.

A reason we often see a list of tools/technologies is because it’s considered easier. But easier isn’t necessary the case and even if it is so it doesn’t mean that the data has commensurate value. And when it comes to data, in theory, a key reason we capture, store and manipulate into information is to inform our decisions. This can be at a personal level, deciding what direction to drive our career or what’s the next eLearning course to attend. If we view the data in aggregate, we can use it to build broad upskilling programs across a workforce and in so doing reduce business risk. If the data is no more than self claimed tags or lacks refinement, we can make some pretty silly decisions, waste hours consuming irrelevant content and reduce the wrong risks. Authentic and complete data is a passion of ours. We make huge development investments to ensure our clients have the appropriate options to give them confidence in the data.

Let’s have a look at the options as a sliding scale of confidence, with even the lower end still being better than technology tags:

The scale of data confidence

Skill data confidence defined.

I have outlined a more detailed description for each step on the scale here:

  1. A thorough and tested methodical survey based self-assessment. Guiding someone through the SFIA framework without the need for prior knowledge. Providing options in the surveys to accommodate different personality types.
  2. Running sophisticated narrow AI based analytics across the self-assessment data to highlight outliers/exceptions for possible review.
  3. Meaningful collaboration between leadership and the workforce to review/discuss and agree individual skill profiles. Workflow based to trigger communication and collaboration that leads to an approved skill profile.
  4. Third party formal endorsement of an individual’s SFIA skill profile via a one-on-one discussion with an accredited or internal assessor. The outcome of which is an endorsed SFIA skill profile to run alongside their self-assessed profile.
  5. And finally, for higher value professional skills, the use of leading asynchronous video technology to assess competency and having experts in the skills provide an evaluation. This is ideal in our new remote working landscape. Basically, an individual replies (via video) to video-based questions that can then be distributed to experts and/or peers for evaluation and scoring. Critical in a chartering or professional certification environment.

Professional Skill data or a Skill Inventory informs your decisions.

Depending on the requirement, the level of confidence can be determined. With our clients we advise to wait for the data to reveal how far to go with optional steps on the scale. So, analyzing the self-assessed data first and either addressing the outliers specifically or deciding to implement other options. More recently we find level 3 on the scale (Very confident with leadership approval) is a great goal to aim for. Not only does it drive trust in the data but initiates and guides career-based conversations between the workforce and leadership. This is something that is often lacking and only takes place during (bi)annual performance reviews. Much better that the conversations are ongoing and more collaborative with good data as the touch point.

Upskilling or reskilling is a big investment.

Let’s now take one decision type that is informed by the data. ‘What skills do we need to Build?’ So, basically where do we focus our upskilling/reskilling resources. Answering this question MUST have good data to describe the starting point for EVERY individual. How could we map an upskilling journey accurately without knowing this first? We can’t!! And, if your starting point is a list of tagged technologies or specialisms….well you get the picture. Or, if your self-assessed skill profiles were created using ‘light-touch’ or gamified techniques it may be relatively accurate but woefully inadequate. We’re talking about investing lots of time and dollars on L&D but then cut corners on probably the most important factor, an accurate starting point. No wonder L&D costs are continually reviewed for ROI.

There’s a meme going around:

  • CFO: What if spend all that money on training and they leave?
  • CIO: And what if we don’t and they stay?

Of course, it’s tongue-in-cheek but it has some validity. Here’s a more common situation:

  • CFO: What if spend our training budget on the wrong training?
  • CIO: We often do!!!

Whether you use the SFIA framework or your own ‘consistent’ competency or skills framework you should aim to answer two questions confidently:

  • What skills do we have? And
  • What skills do we need?

If the datasets behind the answers to these questions are robust and accurate, you’re on the road to better decisions, better use of L&D spend, practical resourcing decisions AND more importantly treating every employee or contractor as an individual and improving their workplace experience in the process.

Capturing a skill inventory is easier than you think.

Sounds good I hope, but wait where do you start? Capturing all that data is like a huge stock-take of the skills across the workforce.

Well, there’s great news, it’s not as difficult as you imagine, we can populate data up to step 3 on the scale within a few short weeks with our automated SaaS solution and practical organizational communication. And if you want to know where your organization sits with regard to having and using a skill inventory why not assess your own organization’s current maturity around skills management as a starting point, you’ll get a benchmark score and over 50 pages of advice and guidance. And except for 15 to 20 minutes of your time it’s free. Register HERE.

Or dive in and request a free trial including sandbox data to play around with. Register HERE

Paul Collins