How to predict turnover of sales team
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This document discusses predicting sales team turnover. It notes that annual turnover is 27% with an average tenure of less than 2 years, costing the company billions in training and incentives. Benefits of predicting turnover include intervening to increase appreciation and motivation, making counteroffers, and substantial cost savings. The document proposes a quantitative model to identify high turnover risk individuals and why, using performance metrics, peer effects, and meeting targets. The model found middling performers most likely to turnover. Peer performance variation and turnover influence each other. Implications are identifying predictors from big data and considering peer effects.
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Sumeet Sharma has over 9 years of experience in marketing, sales management, and business development for e-commerce and financial organizations. He currently serves as the Senior Regional Manager for DB Corp Ltd., where he designs and implements marketing strategies for their e-commerce portal in 10 cities across Madhya Pradesh and Chhattisgarh. Previously, he held roles like Area Manager for Snapdeal and Branch Manager for Indiamart, where he successfully expanded operations and increased profits and revenues. He possesses strong leadership, analytical, and interpersonal skills.
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How to predict turnover of sales team
- 1. Prediction of sales team turnover Tahmina Khatoon ID: 10414 ACMP Phase-2, Batch 4 1
- 2. Objectives ● Effect of turnover ● Benefits of prediction of turnover ● Quantitative model for prediction and it’s outcomes ● Implication of prediction model 2
- 3. Effect of turnover ● Annual turnover - 27% ● Avg. tenure - less than 2 years ● Company faces a number of direct & indirect costs 3 Of sales team
- 4. Direct & Indirect Cost for turnover 1. $15 billion for training 2. $800 billion for incentives 3. Reduces the Return On Investment 4. Empty position may hurts sales 5. Learning curve for new employees to rebuild client relationships 4
- 5. Benefits of prediction “If I Know Before They Have an Offer, That’s a Big Plus” Jay Mincks, Executive vice president, Insperity 5 Of turnover Intervention Appreciation & motivation Counter offer Substantial savings
- 6. Quantitative model For turnover prediction 6 1. Who’s Your Most Valuable Salesperson? 2. Who is at high risk of leaving & why? ● Performance Measurement ● Peer effect
- 7. Sales Person’s Performance Measurement 7 Past performance according to revenue Customer satisfaction Monthly target fulfilment
- 8. Expected vs Actual outcomes 8 Performance TurnoverRisk Expected result Actual result It is the ‘middling’ salespersons who are likely to turn over
- 9. Peer Effect 9 ● Variation in performance among coworkers ○ Less performance variation -> Less challenge - > High turnover ○ High turnover -> Lass faith & strength -> More turnover ● Voluntary and involuntary attrition
- 10. Implication of prediction model ● Identify turnover prediction variables using big data ● Pay careful attention to peer effects 10
- 11. 11 Do you have any question?
- 12. 12 Thank you for your patience!