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Sales and Workforce Analytics

Make Smart Sales Assistants Even Smarter

Integrating analytics into the workforce helps organizations design and execute a comprehensive sales and talent management process. Data backed workforce selling not only helps in provision a data backed customer journey to the employee but also helps in optimum allocation of organization levers across to maximum the enterprise objectives. The below overlay gives a snapshot of how you can design a analytics backed workforce strategy.

The essential objectives of any Salesforce deployment are:
Project Objective Enterprise Objective
Devise a targeting strategy Identifying present customer behavior
Implementation plan for the same Devise strategies for sales force to adapt and leverage data backed learning

Devising a workforce targeting strategy is an optimization problem of maximizing profits with the constraint of constant number of visits and customer touches. So the strategy shall be to maximize the marginal profit with every additional visit. This can be achieved by:

  • Identification of customer characteristics based on available data which would help Sales force in formulating the optimization problem. This would involve identification of segment with highest market potential for sales, highest in terms of market growth rate and highest sensitivity to number of visits ("S" Curve) - It’s the most important customer segment.
  • This must be done with careful analysis of the response rate of all the segments where they lag. The market innovators must be addressed separately with each sale to them causes proportional increase of chances of sales to other segments too.
  • The number of visits for each sales force to each segment will be valuable only if mapped to historical and current sales data.

Thus the targeting approach for the right sales force deployment can be modeled to be objective function Max ∑ [ S(Vij)R(Vij) – C ], subject to ∑V = Z; S is response function of buyers, R is the revenue and C is the cost function of the existing market share ,the response of the buyer and incentive plan of sales rep.

Strategies for data led Sales Force Deployment:

With respect to compensation mechanism each enterprise would have to identify base salary + data based bonus for the sales force. Following are few approaches

Regional competitive landscape

Applying a constant metric (x% market share) as a benchmark over the whole considered will discourage the sales personnel in regions with high competition. A modeled differential compensation based on regional competition will help augment and maximize sales

Using past relationship to scale the sales

Past relationships modeled through a suitable rfm scale where resells should be given more or less weight compared to new sales and help scaling up the sales accordingly

Performance vs Pay-out matrix

We will recommend building a performance vs pay-out matrix using a balance scorecard approach for each sales person to identify the stars and dogs

Historical heuristics

Empirical studies show effectiveness of incentives decrease if their levels are increased to more than 30% of total compensation. We would analyze data to identify what is the right maximum in case on NovaCare’s employees and recommend it

Ease of communication of the plan to sales force

This plays an important role in keeping the motivation of the employees up. While compensation can be optimized through complex functions we must keep an eye on transparency of the methods as well

Technology platforms:
salesforce microsoft azure


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