GETTING COMPETITIVE EDGE IN OUR WEB SERVICE

Kartavya

Getting “Competitive Edge” in our Web-service

21-02-03

I repeat what I have said earlier, many times:

“It is not too difficult for our competitors (other placement agencies or software cos.), to develop RESUMINE / RE-SEARCH tools. And many of these competitors have far more resources (money & manpower) than we do. They can, once they see our service, easily come up from behind & overtake us. In fact, they can learn from our mistakes and come up with a superior product. So, our FIRST-MOVER ADVANTAGE cannot last forever!”

So, the questions before us are:

• “How can we / how do we, forever continue to maintain a competitive edge over our (potential) competitors?”

• How can we maintain this edge at least possible cost?

• How can we raise the “entry barrier” so high, that no potential competitor would ever even think of launching a competing product?

Sounds difficult?

It is, – but not impossible!

All we need to do is to “leverage” the knowledge residing in the brains of thousands (at least hundreds, to begin with) of HR Mgrs/Recruitment Mgrs – or even Line Mgrs.

If we can succeed in “capturing” this knowledge on a CONTINUOUS / ONGOING basis, then no competitor can challenge us.

I have following proposal to “capture” this knowledge so as to perpetually increase our “Knowledge Base” (automatically and at no cost to us).

See enclosed screen-design for proposed SEARCH-ENGINE.

Here, we are making it mandatory for a recruiter to click ☐ one or more keywords specific to the:

• Industry chosen by him

• Function

This is like asking hundreds of recruiters to give/assign “Weightage” to those keywords which they consider important/relevant to the Industry/Function chosen by them.

As soon as he selects ☑ any given Industry/Function in the top boxes, the bottom boxes will get filled up by the keywords belonging to that particular industry or that particular function, in the corresponding bottom boxes.

These keywords are already stored in our knowledge-base & already arranged in the descending order of their frequency-of-occurrence. This is the same order in which they will appear/display in the bottom box.

So, after 10,000 searches, we would have TWO distinct WEIGHTAGES for each keyword:

• Weightage as per frequency of occurrence of each word as found in thousands of resumes.

Now, if 100 webservice subscribers, between them, are daily converting 10,000 resumes, our software must daily “index” all the words (not merely keywords) found in those 10,000 resumes, and daily re-compute the new/latest “FREQUENCY OF OCCURRENCE.”

With 80% cut-off, over a period of time, some keywords will overtake some other keywords (displace them from 80% cut-off). Ranking will change DAILY.

• Weightage as per ticks ☑ made by all the recruiters everyday against
  → Industry Keywords
  → Function Keywords

We can aggregate these ticks ☑ on each keyword and find some method (statistically pure/correct method) to alter/modify the “FREQUENCY BASED WEIGHTAGE.”

So, now, we are gradually moving away from

→ knowledge-base of jobseekers (as captured in their resumes’ keywords)

to

→ knowledge-base of recruiters (as captured by their explicit preferences for certain keywords in relation to all other keywords).

I am, at least for the moment, not suggesting that the search-engine should try to look for these ticked ☑ keywords in the resumes (– even though, we may give that impression to the recruiters!).

Of course, we can also reinforce such an (erroneous) impression of the recruiter, by actually highlighting (red?) those keywords that he has ticked ☑, in the resumes returned – provided those keywords actually exist in those resumes.

(Signature)

21/02/03