“The Great Resignation” is picking up again – attrition in the Indian data science space is possibly at its highest so far. The country’s generally significant rate had almost halved amidst the pandemic, owing to the fear of no new opportunities. Now that hiring sprees are back, so are potential attrition instances. The rates are predicted to shoot up from 12% last year to 23 by the end of 2021, adding up to one million potential resignations.
The industry is massively imbalanced, with a high demand for data scientists and a low supply of capable experts. This is a matter of concern for the Indian IT industry and data science organisations banking on data scientists. The industry leaders at AIM’s Leaders Council have created and/or led some of the most sought after companies to work at by data science professionals. Today, they have leveraged their years of data science experience to share inputs on why the attrition rates are so high and suggest successful ways to retain the best talent.
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Why are attrition rates so high?
- Lack of Connection between Employees And Employer
In the “work from home” mode, the relation between employees and employers has become very transactional. There is no sense of belonging, no connection to a bigger purpose or the sense of a team accomplishing something together. We often fail to realise that when one spends a good amount of their awake time in the office, it is not just about the work but also about the social connection they build with their colleagues. We need to focus on engaging more with our team members, creating a sense of belonging and helping them connect to the organisation’s bigger purpose.
Sayandeb Banerjee, Co-Founder and CEO at TheMathCompany
- Move to Start-ups
There have been more opportunities, especially in the start-up ecosystem. That, along with a fear of missing out (FOMO) when their colleague gets an offer, have been some of the key reasons for the high attrition rates.
Manoj Madhusudanan- Head of dunnhumby India
- High Salary Expectations
Given the market situation, folks across entry-level to 5-6 years experience expect a hyper-growth in salary, designation, roles and responsibilities. While this is fine in cases where it is deserved, it becomes tough in a services scenario where a higher salary or designation comes with the expectations on other attributes like solution strategy, data science thought leadership or client management skills as against just technical depth and execution, which a lot of purely technical focussed folks are not able to demonstrate neither are keen to ramp up on. Such expectations lead to dissatisfaction on both employee and employer end, misalignment in organisational vs personal goals and assessment against those, slower growth and salary hikes compared to captive units, among other challenges.
Ruble Joseph, Lead Strategist (VP) – Global Data Science and Analytics Practice
- Inability to be Generalists
When employees join the company while we are already working on a project, there is a mismatch between candidates expectations vs what they end up working on, at least at the start of the tenure. This becomes challenging with folks with a myopic view of working …….
Source: https://analyticsindiamag.com/council-post-the-great-attrition-in-data-science-what-do-experts-say/