A billion is huge. Really, really huge.
That’s how many people are on the U.I.D.A.I.’s Aadhaar database, making it, possibly, one of the world’s largest people information databases. While the Aadhaar scheme has had to battle many challenges in and out of court in the years since its introduction, the recent passage of the Aadhaar (Targeted Delivery of Financial and other Subsidies, Benefits and Services) Act, 2016 (“the Aadhaar Act”) by Parliament means that many of these challenges would now be rendered toothless. There is still some work left to be done in terms of publishing the rules that the Act says would govern the day-to-day functioning of the Aadhaar system, but one supposes that this is only a matter of time.
Exit interviews, as we all know, involve feedback taken from an employee before leaving the company, considered for organisational improvement. Exit interviews are most effective when the data is accurate.
The trouble with exit interviews is that few people speak the truth. Some find it hard to believe that their feedback would remain anonymous. Others probably want to set the record straight and perhaps even get back at a few individuals in the organisation. Nonetheless, organisations spend a lot of time and effort conducting exit interviews and often base decisions on this data. It follows that we really should try and get the exit interview process right.
To predict employee retention, we need to start with the simple question – What does the perfect employee look like? This isn’t merely someone who has been around for donkey’s year – not everyone who has stuck around for a long time is desirable! You are really looking for the mythical super hero who scales the corporate ladder really fast and then never leaves until he/she retires! Such a person will serve as an organizational benchmark. It will let you decide who to hire and who to retain. Therefore it is quite important to find such a person.
They say employee retention is a dark art. But that is probably so, because we haven’t dug deep, looked at the data and asked why. How wonderful it would be to have a simple equation that would help us understand and improve it!
I think the scientific approach to Employee Retention starts with the question – “Why does an employee leave a company?” If we analysed a cross-spectrum of companies we would probably find many common answers and some unique ones. The different factors can be broadly classified into the following:
I am the COO of IDfy and I am responsible for Enterprise Sales and Operations. Until recently, I was Director of the Life Sciences practice at BT. As Director, I developed the industry’s first cloud service for research and development, launched it in twelve countries, and was responsible for its P&L.
What, you might ask, is someone with credentials like that doing at IDfy? IDfy is a people information company with a mission to make decisions about people safer and simpler. Allow me to walk you through what I thought were the similarities in these two spaces.