Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do. There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

Friday 5 May 2017

FW: FW: Assignment 2- Executive Director Foundation for Sustainable Agriculture


Rohit,

After getting your results ( of “ Employability Score “ and “ Probability of Declining “ ), I wondered :

What could be the “ Correlation Coefficient “ between these two sets of numbers ?

Could such correlation , possibly reveal :

·         Higher the Employability Score , higher the Probability of Declining ? or vice versa ?

My grand daughter Aneree helped to answer this question with her attached statistical analysis . Thanks , Aneree !

But , this current analysis , may not be conclusive , considering that our dataset was small .

Another question :

Does such analysis ( to find any hidden pattern ) have to be confined to EACH mandate / assignment , separately or could it be done for all 1275 mandates , together ?

I believe , we need to do this separately for each assignment

In the first instance , what is however much more important from 3P’s needs is to find out :

“ To what extent the software was able to mimic the human brain , in selecting the best candidate , for a given assignment ? “

I suggest , Prashant re-arrange the shortlisted ( 50 ? ) candidates in the descending order of the “ Employability Score “ – then locate where ( in which percentile ) is that BEST ( meaning , selected / appointed by the client ) candidate is located

If there is a HIGH DEGREE of correlation between the “ Algorithmic Score “ and the “ Nebulous Score ( of the client ) “ , then it is a proof that iPredictt is on the right track !

Of course , if we wish to establish such a PROOF beyond any doubt , then we need to carry out this exercise for ALL 1275 mandates and establish a Correlation between the two !

As far as extraction of “ data fields “ from the text resume and creation of a structured / searchable , database is concerned , I find a few data missed out during the parsing process

I have a solution for improving the accuracy of parsing , which I can discuss with you / your software guys . I can visit your office if desired


Warm Regards,

Hemen Parekh
+91 98675 50808

From: Aneree Parekh [mailto:aneree92@gmail.com]
Sent: 05 May 2017 09:50
To: Hemen Parekh
Subject: Re: FW: Assignment 2- Executive Director Foundation for Sustainable Agriculture

Hi dadu,

Attached is the output of the Pearson's Correlation r. There appears to be no sig. correlation between Employability Scores and Probability of Decining (r = .087, n =  42, p = .585)

On Thu, May 4, 2017 at 8:53 PM, Hemen Parekh <hcp@recruitguru.com> wrote:



Warm Regards,

Hemen Parekh
+91 98675 50808

From: Rohit Verma [mailto:rohit.v@ipredictt.com]
Sent: 04 May 2017 18:12
To: Mitchelle
Cc: Hemen Parekh; Nirmit Parekh; Prashant Sharma
Subject: Re: Assignment 2- Executive Director Foundation for Sustainable Agriculture

Hi Mitchelle,

We have created a 3P Consultant account for you on the platform.


Pwd:    3p@789

Following are the advised steps to experience the features –

1.       Review the JD (You can edit or add information  - like Skill sets)
2.       Review the PARSED resumes (You can edit or add information)
3.       Open the dash to see the trends
4.       Download Excel sheet for quick reference (attached)
5.       Review the top listed resumes to decide on next steps
6.       Provide us feedback

We currently ran the parser to collect Resume information and also ran various algorithms to get results for Employability score., Probability of Decline .
Please study the accuracy and let us know patterns you see.

Also share details of selected candidates you have originally have for this role. The funnel should be

1.       Candidates selected for interview
2.       Candidates made offers
3.       Candidates hired

Further, Our Data Science team will work on this to improve results which we will discuss as we progress.
Should you have any issue or need clarity, please call me

Regards,

Rohit




From: Mitchelle <mitchelle@3pconsultants.co.in>
Date: Wednesday, 3 May 2017 at 12:36 PM
To: <rohit.v@ipredictt.com>
Cc: Hemen Parekh <hcp@recruitguru.com>, Nirmit Parekh <nirmit@3pconsultants.co.in>, Prashant Sharma <prashant@3pconsultants.co.in>
Subject: RE: Assignment 2- Executive Director Foundation for Sustainable Agriculture

Dear Rohit,

Many thanks for your response.

As agreed ; we shared with you two descriptive JD’s along with evaluation criteria at our end on the basis of which candidates were shortlisted and resumes (50 batch size/assignment).

Basis these documents shared; we expected the iPredict software to accurately pars these resumes and derive an accurate shortlisting with an employability score.

The objective of this exercise was to then match the candidate shortlist derived out of the iPredict automated algorithm along with an Employability score vis a vis the manual shortlisting done at our end.
This would help us correlate the effectiveness and shortlisting accuracy along with the employability score of the algorithm vis vis manual shortlisting.

We would thus request you to share with us the same for each of the two Assignment details shared with you.

Do also indicate a timeline for us to receive this.

Warm Regards,

Mitchelle
+91 98675 50810

From: Rohit Verma [mailto:rohit.v@ipredictt.com]
Sent: Wednesday, May 3, 2017 10:55 AM
To: Mitchelle <mitchelle@3pconsultants.co.in>
Cc: Hemen Parekh <hcp@recruitguru.com>; Nirmit Parekh <nirmit@3pconsultants.co.in>; Prashant Sharma <prashant@3pconsultants.co.in>; Manoj Pandey <contact@3pconsultants.co.in>; Akshay Sehgal <akshay.s@ipredictt.com>
Subject: Re: Assignment 2- Executive Director Foundation for Sustainable Agriculture

Thanks, all for the time and patient hearing.

Hope some of the discussion points intrigued you and I hope we work together in the future to create value in not only recruitment space but also in areas of descriptive dashboards, performance, attrition analytics for companies who you have built relationships with.

As email ID is the key resume identifier, we are tweaking our processes to include this change. Will share the results once done.


My responses in line

Accurate Parsing based on which Accuracy in shortlisting at our end with minimal manual intervention / subjectivity – Currently available
Employability score – Available , needs data for further machine training.
Decline Probability – Available , needs data for further machine training.
How would these algorithms assess Cultural fit – Can be done on case to case basis by accessing the social media data (Facebook, Twitter, Linkedin etc) – refer to the attachment. Can be done on case to case basis
What additional trends / analytics can you predict based on the data input – This depends on the questions you have. For instance, if you are interested in looking at next job trends, can be understood by social media tracking.
Also we would like to see the algorithm extrapolate and show us a comparative table /ranking in terms of relevance of candidate profiles shared to the Data points / Job criteria – Will be mailed
We have intentionally not shared the candidate contact details – as we do not want to activate the chatbot tool at this stage to maintain confidentiality – Sure, but Chatbot only works if manually activated for each of resumes. Its not automated.
Any accurate inferences on ability to predict attrition levels / and when will which position come up for hiring (replacement / new), what kind of hiring trends / industry / function wise that are seeing traction etc.,- Probability of decline is an indicator to that respect/


Regards

Rohit




From: Mitchelle <mitchelle@3pconsultants.co.in>
Date: Tuesday, 2 May 2017 at 4:33 PM
To: <rohit.v@ipredictt.com>
Cc: Hemen Parekh <hcp@recruitguru.com>, Nirmit Parekh <nirmit@3pconsultants.co.in>, Prashant Sharma <prashant@3pconsultants.co.in>, Manoj Pandey <contact@3pconsultants.co.in>
Subject: Assignment 2- Executive Director Foundation for Sustainable Agriculture

Dear Rohit,

Many thanks for the interactive session this morning.

As agreed, enclosed please find the documents for your reference :

Position Specification –Executive Director for the Foundation for Sustainable Agriculture
Evaluation Criteria – Data Points comprising Personal and Technical attributes which formed the basis of our evaluation/elimination criteria
Candidate Profiles sourced for this position

We would be keen to view the following based on the data shared :

1.       Accurate Parsing based on which Accuracy in shortlisting at our end with minimal manual intervention / subjectivity
2.       Employability score
3.       Decline Probability
4.       How would these algorithms assess Cultural fit
5.       What additional trends / analytics can you predict based on the data input
6.       Also we would like to see the algorithm extrapolate and show us a comparative table /ranking in terms of relevance of candidate profiles shared to the Data points / Job criteria
7.       We have intentionally not shared the candidate contact details – as we do not want to activate the chatbot tool at this stage to maintain confidentiality
8.       Any accurate inferences on ability to predict attrition levels / and when will which position come up for hiring (replacement / new), what kind of hiring trends / industry / function wise that are seeing traction etc.,

Do feel free to speak to me in case of any additional inputs required.

Warm Regards,

Mitchelle
+91 98675 50810



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