A warm welcome to our guest blogger- Arun Prabhu, Founder and CEO of inTouch Analytics. inTouch analytics delivers ‘everyday analytics’ to clients in India, United States and Europe while focusing on leveraging customer and employee relationships to deliver business value. Their forte being Talent Analytics (among other things), Arun interestingly outlines how they took on the challenge of modeling the problem of employability.

Using Analytics to Solve the Problem of Employability Main

For more than a decade, much business discourse has taken place about the problem of Employability – specifically about India and, generally, about the world’s labour markets at large. None of the discussions has delved deep enough to provide a robust, actionable, framework for labour market stakeholders – education, business, government and skill training providers – to take concrete steps toward better employability. Today, the term ‘Employability’ is reduced to being a buzz word that barely helps scratch the surface of the mammoth problem.

At inTouch, we have taken on the challenge of modeling the problem of employability. This means that we first had to define the problem, hypothesize about the attributes it is made up of, validate them and finally arrive at an appropriate measurement framework. The below paragraphs briefly explain how we went about accomplishing these steps.

Defining Employability as an analytical problem

Treating employability as an analytical problem helps us get to the multiple attributes that influence it. Secondly, it helps map the (inter)dependencies amongst attributes so we can establish the nature and magnitude of cause-effect. We adopted an ILO definition of Employability and suited it for the Indian context as a supply-demand concept, with attendant attributes, as below:

Employability is a candidate-centric measure of –

1. Willingness and Ability to be relevant and attractive for the labour market (supply factors)
2. By anticipating and responding constructively to changes in work environment and labour market conditions (demand factors)
3. Aided by and making use of the human resource development instruments available (institutions)

Identifying and Validating Employability Attributes

Using Analytics to Solve the Problem of Employability 1

Using Analytics to Solve the Problem of Employability 2

Next, we sorted the demand- and supply-sides and listed out attributes as follows:

Attributes were validated through a combination of literature reviews and primary research with experts.

The Measurement Framework

The final step in the exercise was to formulate a measurement framework. We employed a combination of surveys (literature and primary), predictive modeling techniques (to profile the supply and demand attributes) and linear programming to build out an Employability Index.

Using Analytics to Solve the Problem of Employability

The results of the exercise are illustrated in the following infographic:  http://ow.ly/i/2kwaS/original

Info 2

Interested in a career in Data Science?
To learn more about Jigsaw’s Data Science with SAS Course – click here.
To learn more about Jigsaw’s Data Science with R Course – click here.
To learn more about Jigsaw’s Big Data Course – click here.
SHARE
share

Are you ready to build your own career?