Competency Profiles

 Team ,

 

Couple of days back , I sent to you an email , suggesting incorporating the “ Generation of Competency “ graphs into the “ Executive Search “ shortlisted executives , based on “ Attributes and Weightages “

 

I even pointed out why this idea was , almost impossible to implement in 2003 , when we had only a few thousand RESUMES , broken up into a FEW HUNDRED resumes , for each FUNCTIONAL background

 

Just not large enough POPULATION to be able to construct a meaningful BELL SHAPED curve ( a smooth Universal Distribution )

 

But now , in Linkedin , we could have a hundred thousand resumes which are very close to being IDENTICAL – a large enough population for plotting a SINGLE CURVE

 

In this context , my following chat ( a few minutes ago ) with my Virtual Avatar ( www.HemenParekh.ai ) explains what I mean

 

Hcp

 

 

I asked my Virtual Avatar :

 

“ what are the limitations of cometency profile graphs ? Is that truly an " Apple for Apple " comparison between " Co-professionals " ? If not , how come ? “

 

My Avatar answered :

 

“ Based on my extensive work with competency profile graphs, I can point out several key limitations. The main issue is that current competency profiles don't provide true "Apple for Apple" comparisons between co-professionals.

 

As I noted back in 2003, when we compare someone like Mr. Mhatre (a Sales GM) against the entire population of sales professionals (9,563 people), we're actually creating a heterogeneous comparison. The population includes people with:

- Ages ranging from 26 to 56 years

- Designations from Officer to President

- Educational qualifications from SSC to Ph.D.

- Experience ranging from 1 to 34 years

 

This isn't a true peer comparison. It's like comparing mangoes with apples and bananas! To make these graphs truly meaningful, we need to break them down by:

- Designation level

- Age group

- Educational qualification

- Years of experience

- Industry sector

- Geographic location

 

Only when we plot an executive against others with similar attributes (like comparing a 46-year-old Sales GM with bachelor's degree against similar peers) do we get a genuine "Apple for Apple" comparison. This creates a much sharper, more focused profile that actually makes sense to recruiters.

 

The solution lies in building more sophisticated filtering capabilities and gathering enough data (we need at least 100,000 jobseekers) to make these segmented comparisons statistically significant. “