Quick and Dirty – Not Optimum

Quick and Dirty

Quick and Dirty – Not Optimum


Quick and dirty skill data can be tempting in the short term!

OK, let’s get serious for a moment about why quick and dirty is not optimum. You want data that will help you make KEY decisions. And I’m talking about very important decisions such as, what skills do I need to build and what skills can I make better use of (mobilise)? These are crucial questions in this world where the gaps in digital skills are increasing dramatically. So, what are the consequences of getting the wrong answers to these questions?

  • At best, you waste a LOT of money
  • At worst you put your organisation at serious risk.

If your skill inventory is based on quick and dirty data capture your decisions will equally be quick and dirty (and likely wrong).

So what’s so wrong with shortcuts to populate your digital skill profiles?

It is tempting to capture the skills of your workforce using restricted, simplistic selections hoping it will save you a lot of time. And ‘hey’ you’ve still captured a skill inventory. But I assure you, you will ultimately pay the price. Shortcuts are wonderful things in the correct context, provided you still arrive at the correct destination. Populating a skill inventory is not one of those times. Would you consider a warehouse stock-take accurate, if it was carried out by only approximating what’s on each shelf? Or if if they just counted what’s in the racks they were easily able to reach and ignored the ones that were too difficult?

What to avoid when populating a digital skill inventory.

Real world examples of digital skill short cuts:

Scenario 1

We want to help our employees navigate their careers. So, we build the job definitions from months of Mismatched Dataworkshops and interviews with workers. And, for sure, we get some great data that defines our skill requirement. Then, we give our employees a click and play method to select their skills. Firstly, there is little structure for folks to follow, just browse around and click some stuff that ‘hopefully’ relates to their experience and skills. Then we bring the two datasets together, one created through months of research and feedback and the other largely a result of random clicking. No prizes for the guessing the inherent flaw in this approach.



Missing PiecesScenario 2

You ask some general upfront questions that then limits what skills your workers are able to select. This approach completely missing the fact that each of us has a unique career journey and experiences that got us to where we are. For example, practical use of the SFIA framework can result in over 828,000,000 skill combinations that truly recognises our uniqueness, and is as simple as completing SkillsTx self-assessment surveys. You should aim for the goldilocks zone, not too much information to be overwhelmed and not too little to be of no value. A little advert here, we believe we have the correct balance in SkillsTx.


Scenario 3

Probably one of the most problematic approaches we see, you limit your skill framework structure to the capability of our HXM/HRIS solution. Here’s an example of what this can result in ‘I need a security expert’. This approach can also extend to defining tools as skills using techniques such as tags. The following ‘Tools are not Skills’ article highlights the potential shortfall using this technique. So, we go with a limited framework merely to comply with the restrictions of our incumbent HR solution rather than develop or buy something that really meets our needs. The digital/data economy is driven by digital skills. In order to make good decisions, we need a true representation of each and every employee’s skills, not a generalist approximation, that will ultimately not only short-change the organisation, but the workers as well.

Simple and Efficient skill capture can be good.

We at SkillsTx DO believe in making things as simple and efficient as possible when used in the correct context. For example, we’ve got over 440 SFIA based sample jobs and roles that have been defined over years of research by governments and industry bodies around the World. While they are unlikely to be an exact match for your requirements, they are a great starting point. Also, if you’re answering ‘what skills should we build?’ we have over 4,500 training courses, certifications and other development actions all mapped to SFIA. This can make if very efficient when looking for appropriate career development/upskilling actions. However, when it comes to defining what digital skills you have there’s no escaping that it will require some effort. In our world, it starts with a methodical online self-assessment, with backend algorithms scanning for out-liers. We then allow evidence to be provided, leadership approval of the skills, third party endorsement of skills and even asynchronous video assessment. But the ONE thing we never allow is someone else to ‘edit’ a person’s skills. This truly sends the wrong message and overrides the truism #weownourskills.

To summarise our perspective on quick and dirty skill inventories:

If you’re convinced that you’ll be OK with quick and dirty then we’re probably not for you, although we may meet in the future. However, if you believe in data quality or are open to exploring the difference approaches we’d love to talk.

Book a call.

If you would rather do more investigation then why not check out your organisation’s Digital Skills Management Maturity for free.

Paul Collins