Skills Mapping from Sweat Beads to Easy Solution in Under 3 Minutes! See How!

Hey there! This is an unusual Monday drop. Remember last time we wrapped up with a teaser about using AI to simplify the arduous process of skills mapping?

Today, we dive into that promise. { Keep Reading to Watch the Video and more }

But why?

That's right. We're tackling a scenario where some want 50 skills, some 10, some 15, some 3!

Stakeholder buy-in. Executive management pressures. Proving ROI. Endless debates about which skills matter and how many to focus on.

And yes, the process often doesn’t even capture a complete list of skills. That’s the harsh truth!

Change management, emotions, egos and beliefs at play here!! Can you see the tangled web!  Just thinking about it, I can feel sweat beads forming on my brow. 😅

And how do we even begin to tackle this bitter - complex web?

I need my favorite Gajar ka Halwa (Carrot Halwa) to boost my energy! (I did say I food associate, right?)

Be back in a second... Well, I ended up with my second favorite: oats soaked in apple juice and powdered with cinnamon. They’re utterly delicious! You want to give them a try sometime..

Nope, I won’t indulge you with the recipe today. 😊

Having witnessed these frustrating sessions and that quicksand-like feeling pulling me in, I knew the answer had to be simplicity.

 Simplify, Simplify, Simplify!

Our first solution? Decentralize - we talked about it last time!

Next, forget fretting over how many skills is too many or too few . What if we could remove that hurdle altogether?

Enter Generative AI

With an age-old problem of arduous skills mapping, I turned to generative AI. Could it generate a comprehensive skills map?

So, I did what I usually do with my best collaborative partner.- specified my request:

Here's how I would rephrase that in a more concise, simple English style:

I requested ChatGPT 4 to create a skills map based on our discussions. After some tweaking, the prompt got refined and smooth. (Iterative refinement is good practice, as I often recommend in my sharings and masterclasses.)

Prompt 


Objective:
Generate a detailed skills map for the role of Learning Consultant in a tabular format. The process will begin with user inputs on organizational details and include autonomous research to define the role's responsibilities and required skills, presented in a structured table.

Steps to Follow:

Initial User Input:

Ask the user for the name of the organization or the specific business segment or function where the Learning Consultant role is situated.
Query the user on the desired number of skills to include in the skills map, with options such as 5, 15, or 40.
Inquire about the preferred number of proficiency levels for each skill, with choices like 3, 5, or 6 levels.
Autonomous Research:

Conduct research based on the provided organizational name or function to understand the typical services, mission, and market position of the organization. Use this information to infer key aspects of the Learning Consultant's responsibilities within this specific context.
Skill Identification and Proficiency Definition Using Bloom’s Taxonomy:

Independently identify key skills required for a Learning Consultant based on the business context and role analysis.
For each skill, define proficiency levels according to the user’s selection (e.g., basic, intermediate, advanced), detailing what each level entails using Bloom’s Taxonomy verbs.
Creating the Skills Map in Tabular Format:

Present the identified skills and their proficiency levels in a structured table format. Clearly delineate the progression from basic to expert levels for each skill, ensuring that each row represents a skill and each column represents a proficiency level.
Review and Refinement:

Show the draft skills map in a table to the user for review. Encourage feedback and request any necessary adjustments or additions to better align with the company’s specific needs.
Suggest validating the skills map with relevant stakeholders within the company to ensure its accuracy and applicability.
Execution:
Carry out the steps interactively, allowing for user input at the initial stage and subsequent reviews. Ensure that the bot autonomously conducts the research and skills identification and presents the results in a tabular format to create a tailored and effective skills map.
        

Proof of Pudding - Video - Watch it in Action

What was the result?

Now, you have a cost-effective, efficient method of listing skills. Distribute them, get people to collaborate to sign them off.

 But that's not what I did—or rather, what I would do!

 I ran a test pilot. I found people and teams willing to give a simple solution a try. Converted it into a simple self-assessment in Excel format. Teams and managers assessed their groups, and it drew a graph...

Now, we can do it in so many different ways—create AI agents, or simply ask Copilot in Excel to do it!

Or convert it into an HTML-based tool, which is what I did once the Excel format was successful. I also tied a set of developmental and performance-boosting activities to the skills.

So what did this do? Running a pilot or several pilots in a low-cost, low-resource manner gave me data to prove its impact. It helped me refine the skill assessment too.

The simplicity of using it to one’s advantage! Being able to improve specific productivity and performance boosted adoption and liking!

In Closing:

This isn’t an advert for AI, nor a passionate sale by a tech enthusiast.

I share this because it solved a problem for me and continues to do so. I hope you feel inspired to solve a skill mapping process problem too, using a prompt.

Curious to give it a try? Jump in, experiment with the prompt, and let’s simplify our lives.

And as always, if you’ve tried this out, share your stories! I’m eager to hear how AI is making a difference in your skills mapping journey.

Stay tuned for more insights and practical tips in our next piece. Let’s keep making skills mapping as simple and effective as possible, one step at a time!

I'm off for a coffee ice cream 😊