When the economy is booming in India, the attrition rate of some companies especially in the IT services sector touched more than 15%. What could be the quantitative matrix, to generate a schema for curbing the attrition rate?
The answer could be in the schema of analytics. Let us assume that the maximum attrition happens around 2 years time frame around 40%, around 3 years around 25%, around 5 years around 15%, and the rest 8-20 year group as 20%. So it dips and then goes up in terms of numbers. The question is which sector we should target to curb the attrition. I feel the 3 year group and the 5 year group. There are a few reasons for that also:
1.      1. The 3 year and the 5 year group make up for the most loyalty factor and if they get settled, they can be groomed in the long run
2.      2. The 2 year group cannot be kept back for most of the cases, as the retention factor is low for them
3.      3. The other group also has a great retention factor also, as most of them are executives who have moved at the top of the ladder
Let us concatenate these factors

Let us assume that the percentage of attrition for the 2 year group as 40% of the total group. Similarly, the company thinks that out of them, 40% can be retained with specific incentives/ carrots. So the effective attrition factor psychologically is actually a formula:
Effective factor for Attrition = (Percentage of Attrition * (100 – Retention Factor))/ 100
Hence we see that the actual attrition is actually a down ward curve.

So, we have a few conclusions:
1.      We should focus on the retention factor more than anything
2.      The last 3 segments especially the last 2 segments are worth looking for
3.      Somehow we have to make  a transition towards the 5 year group, by providing incentives for long terms
4.      We should never focus on the 1st segment as nearly 1/ 4th of the group actually fade away
5.      The 3 year period is very crucial, as they have to be targeted

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