Attrition, for a long time has been a taboo word in the Indian employment workspace -primarily driven by the fact that there is a lot of hush hush and secrecy surrounding this. India is probably the only employment market in the world where there is no published industry data for this. If you still doubt it, ask the consulting giants.

They will give you an apple hood mother pie statement saying “Well, attrition in India varies from 10% to 120% – this is driven by a host of blah blah!”. Oh Jeez – That’s a 1100% range spread! (Range spread is (max-min)/min expressed as a %)

I don’t know if it is for the right or wrong reasons – this gets a lot of attention. People in the higher echelons of power want to review this every day, “clients & business partners” who are constantly worrying about the service quality as a result of attrition thankfully want to review it on a monthly basis and there are a host of other stake holders who want to slice and dice this information for statistical joy!

So how does one define attrition? “Someone leaving a firm on his/her own accord?”

How should organizations compute and report attrition?

What I was taught in school by the profs was to look at the number of people who left in a period, upon the average headcount

((no of people who left)/ (opening headcount + closing headcount)/2))

For a long time, this was the way firms were reporting attrition (at least that is what I think). With the rise in attrition numbers during the boom days, firms obviously were under a lot of pressure. Apart from the analysis of the data that separate teams were commissioned to do, there were multiple meetings to discuss this and task forces created to manage this. The numbers were so large in some cases that companies set up separate teams to do the traditional exit interviews – yes, they created a new department in the HR function!!

The thought leaders of the business obviously didn’t like the numbers they were seeing. With no immediate fix to the problem in sight (no one saw the recession in the hay days), they asked the fundamental question – is this the right way to compute attrition?

Now that’s a subtle way of the management saying, “listen, reduce the number!”… Wow! Talk about radical thinking!

In July of 2008, I was in a NASSCOM HR summit in Chennai. The Chief People Officer of a large Indian IT major, also a very good friend of mine was a panelist to speak on a topic titled “HR Leadership: Paradigm shift from process recruiters to business leaders”.He shared the dais with the heads of HR of two of India’s largest IT services firms. (Satyam wasn’t there ok! ).

While delivering his address, he looked at one of these speakers and said “I don’t know how you compute attrition, but the 10% number you report is incredible”.

While the speakers themselves burst into a chuckle, this was greeted to a rousing applause and roar from the near 3000 strong HR audience. The point to underscore here was the HR community, through their reactions, reiterating the fact that the methodology of computing is something that is rampant. His counterpart didn’t answer the question by the way!

Let’s get a sneak peek of some of the techniques that I have been exposed to:

1. Number of people who leave – Can we relook at the reasons for people to leave on their ” own accord”
2. Someone wants to resign and asks for leave. Manager says “NO” – the guy absconds. Great! He didn’t leave on his own accord
3. All leavers in the last two months of the performance measurement cycle are rated as “below par performers”. They would have been asked to leave anyways and hence must be considered as not having left on their own
4. What’s the ideal time to leave – first 30 days is not counted as this amounts to bad hiring. This is in some firms a HR metric and the poor recruiters are held accountable for this.
5. Process improvements on the above – 30 days is too little – let’s determine something between 60 and 90

Those were some of the ways to reduce the numerator. Sadly, the denominator can’t be changed – unless of course, you are Ramalinga Raju and decide to fudge headcount. Average headcount remains as it is. So where are the changes?

Here they are. While the formula gives you the result for a month, what does it look like for a year? The solution is in “annualizing”.  Read on for some of the industry best practices!

1. Compute your monthly attrition and multiply by 12. (That means my numbers will change on a monthly basis. If one month’s number was high, then I am dead)
2. Let’s look at calendar year – Annualized attrition is sum of attrition over 12 months. (Attrition will be high in the beginning of the year if it happens, but will reduce as the year goes on. Expect to have a few good months – read as low attrition)
3. Calendar year is a bad idea – let’s do rolling 12 months. This is a more holistic representation (peaks and troughs will get ironed out. This is my personal favorite as this is the right way to do it)
4. An American multinational with a long standing record, pioneers in the outsourcing space and an American giant, absolutely statistically inclined uses this method. Compute the monthly attrition; divide it by the number of the month (1 for Jan, 2 for Feb, 3 for March and so on) and then multiply this by 12! Wow.. how confusing. Is this were the adage of saying, if you can’t make someone understand, confuse them comes from!
5. I bumped into this Indian American in my last job. He was well educated and his gyan around attrition was like this. There’s a financial concept of Risk Adjusted Rate of Return. When you compute return on an investment, you discount the risk and look at the absolute return. So let’s assume that the risk on an investment is 10%. Your return on that investment is 15%. Therefore, your absolute return is 5%! So, define a risk adjusted target and knock off your attrition by this number. Eureka Eureka!! This is THE way in which my attrition will be the lowest. By the way, how defines the Risk Adjusted number? Does this change every month? What happens if the number goes negative? While I don’t have answers to this, he made me do it. I didn’t have a choice so to speak as he was well connected and I hence had to budge!

I don’t know if I want to go on here. There are a few more methodologies here!

I’m left with two choices.

A)  Hire a smart techie and a smart MBA graduate as interns – have them develop a “cute” methodology to compute attrition in a manner that the outside world will see this as scientific, rationale, thought through, scale proof and all the other management jargons that I know! (Hopefully this will be a big hit and I will be called a Management Guru. I will call this the Nars methodology of computing attrition and will become world famous. If I am not dreaming, I’ll be invited to talk around the world in forums, colleges and companies!)

B)  Write to Bill Gates and have him incorporate another function in Excel – ATTRITION (RANGE) where there is a standard method across and organization will hopefully be more willing to adopt!

While I know which way I am going, do you want to take a guess?

Attrition is maddening by the way eh!

I just got a note from someone here late last night saying they want to quit! What a way to start the day!!!

Image Credit: J Botter

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