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The Benefits of Involving Sales Managers When Designing Salesperson Compensation Packages

The Benefits of Involving Sales Managers When Designing Salesperson Compensation Packages

Ratan Kumar and Shipra Pandey

Sales manager incentives sized

Journal of Marketing Research Scholarly Insights are produced in partnership with the AMA Doctoral Students SIG – a shared interest network for Marketing PhD students across the world.

In the sales compensation domain, Basu et al.’s (1985) principal–agent model is the predominant model academicians as well as practitioners have used over the past three decades. The model’s key assumption is that the firm is a single decision-making entity. However, in practice, a firm is a collection of individuals who make decisions for and on behalf of the firm. Sales managers are among these individuals, so an optimal compensation plan should consider and use their insights and perspectives. Arguing this point, Dr. Rob Waiser has provided a fresh perspective on the design of an optimal compensation plan for salespeople using local information from sales managers.

This new model, which extends the principal–agent model, entails companies establishing a generic compensation plan for all territories with tight design constraints, instead of customized plans for each territory. Then, if a sales manager wants to relax these constraints, the company asks them to provide extra information regarding the territory or salesperson in question. In general, each salesperson wants to maximize their own incentives. Therefore, because sales managers’ compensation is attached to compensation plans designed for salespeople, they are motivated to supply additional information to the company. Aside from their salespeople, sales managers are the key personnel who have access to detailed information about sales territories, salespeople, geography, etc., that can provide value to the firm. Because of their specialized knowledge, sales managers can provide valuable information to the firm at no extra cost. Using this information, firms can design customized compensation plans that are optimal and acceptable to all stakeholders—upper management, sales managers, and salespeople.


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The key benefit of this new model is that it does not require lengthy internal negotiations within the organization and prevents extensive lobbying by sales managers and salespeople to convince their supervisors to relax the norms they typically use when designing compensation plans. Also, this model utilizes the information asymmetry between upper management, sales managers, and salespeople. Further, it motivates sales managers to acquire and update their local information about territory, salespeople, customers, and so on. This model is based on a key assumption that firms (upper management) and sales managers have different interests: firms focus on maximizing profits, whereas sales managers have an interest in maximizing their own compensation incentives. Waiser’s model accommodates the fact that these different interests mean that sales managers do not typically share all available information with their subordinates on regular basis.

The model has applicability in all industry types and sales situations, whether it be B2B sales, B2C sales, or channel sales. The model is equally applicable in non-sales situations in which firms design compensation plans based on the outcomes of their employees’ efforts where employees and managers have information that not available to the rest of the firm.

Q & A with Author Rob Waiser

Q: There is a lot of research in the sales force compensation design domain. What inspired you to explore this area from a new perspective? How did you move from the ideation stages to the final research product?

A: Before I started my PhD, I worked for several years as a management consultant at a firm called ZS Associates, which specializes in sales and marketing management. That gave me quite a bit of experience working with sales organizations on a range of issues. When I started learning about how marketing scholars typically approach sales force compensation design (as a PhD student), I was surprised at how different it was from the approaches I had seen and used in practice. Much of my research agenda since then has been focused on closing what I believe are important gaps between the way that incentive compensation is treated in the academic literature and the challenges faced by practitioners in that area.

One of the dominant models in the academic literature on incentive design since the mid-1980s is the principal–agent model, which I had never heard of before grad school. I found it to be a powerful and elegant way to think about incentive compensation, but I also thought it was missing some key elements of how practitioners typically make decisions. For example, the principal-agent model assumes that each salesperson (agent) maximizes their expected utility; in other words, they act in their own self-interest. On the other hand, a firm (principal) is treated as a single decision-making entity that maximizes profits. In reality, of course, a firm is a collection of individuals making decisions on behalf of their organization and those people can be just as self-interested as a salesperson! In particular, sales managers at various levels might have input into a salesperson’s compensation plan design, but those managers have their own incentive plans. Furthermore, sales managers’ incentives are typically more closely aligned with those of the salesperson than they are with the firm’s profit-maximization objective. As a result, I wondered how traditional sales compensation modeling would be affected if we account for the involvement of self-interested sales managers. That led me to formulate an extension of the principal–agent model in which such a manager represents a third player. That model ultimately formed the basis of my article.

Q: Could you explain the term “information rent” in the context of sales compensation? How is it relevant for all stakeholders—sales executives, sales managers, and upper management (firm)?

A: To understand information rent in this context, consider the following example:

Some salespeople are better at selling than others. Under a given compensation plan, a more skilled salesperson can expect to earn more money and more total utility than a less skilled one. For simplicity, let’s assume that a salesperson can be one of two “types”—high-skill or low-skill—and that a salesperson always knows their own type. If a firm knows a salesperson’s type, then it can maximize profits by offering them a compensation plan that will induce them to exert the optimal amount of selling effort and pay them just enough that they are willing to accept that plan instead of leaving the firm. In other words, the salesperson’s expected surplus would be 0. Suppose, however, that the firm does not know the salesperson’s type (i.e., they have private information). If the firm aims to ensure that the salesperson will accept its contract, then the terms need to be generous enough to allow a low-skill salesperson to earn at least 0 expected surplus at some effort level but a high-skill salesperson to  then earn more than 0. We refer to the high-skill salesperson’s positive surplus as “information rent” because it is a result of their informational advantage over the firm.

That informational advantage doesn’t have to be about their skill level; it can be about anything that is relevant to the design of their compensation plan (e.g., the value or difficulty of their territory, the value of an alternative job opportunity). This is relevant for stakeholders within the firm (e.g., managers, executives) because it is often the case that a salesperson has some information that those stakeholders don’t have. That informational advantage has important effects on the compensation design process.

Q: What are the roles/duties/responsibilities of sales executives, sales managers, and upper management with respect to the difficulty level of handling the territory, when designing a successful compensation model?

A: First, it is important to note that territory difficulty is used in my model as a proxy for private information held by a salesperson and their manager. It could be replaced, for example, by information about the salesperson’s selling ability (as in the previous example), and the model would apply the same way. With that in mind, the roles of sales executives or senior management cannot vary according to territory difficulty in my model, because that information is assumed to be privately held by the salesperson and sales manager. In other words, executives cannot play a different role in compensation design for easy and difficult territories because they don’t know which ones are difficult and which are easy until that information is revealed by a sales manager during the compensation design process.

In practice, compensation design often involves a top-down process (in which a high-level sales target is allocated to progressively lower levels, such as nation → regions → districts → territories), a bottom-up process (in which salespeople and/or managers provide estimates of sales potential at the territory or customer level, which are then aggregated to higher levels), or a combination of the two. This is too complex to fully capture analytically, so my model is a simplified representation of the salesperson, sales manager, and firm roles. The important thing was to capture the information possessed by a sales manager and how their own incentives might motivate them to use that information. 

Q: How does this model apply to different industries or sales employee role contexts (e.g., channel sales, direct sales or B2B sales)?

A: What I had in mind when I created the model was a B2B, “outside sales” context, but the model can be applied in any situation (including non-sales contexts) in which (1) an employee whose effort is unobserved receives incentives on the basis of an outcome other than firm profit, (2) that employee’s manager has relevant information that they can choose to share with the firm, and (3) the manager’s incentives are aligned with those of the employee (i.e. they are measured using the same metrics).

Q: What are the implications of this research for various stakeholders, if salespeople are in B2C sales versus B2B sales?

A: As long as the conditions described in the previous response are met, the implications of the research are effectively independent of these variables. This research mainly has implications for the firm (sales executives and senior management), and individual salespeople largely remain unaffected. Firms currently use a variety of formal and informal processes to access the information held by their sales managers when designing sales force compensation. However, managers often have an incentive to misrepresent that information because their own compensation is based on the output of their salespeople. I propose a mechanism that the firm can use to reliably and efficiently induce a sales manager to use their information to benefit the firm. Under this “request mechanism,” the firm delegates the design of sales incentives to the manager subject to tight constraints but offers an opportunity for them to request relaxed constraints by meeting specified requirements. I find that such constraints and request requirements can always be designed such that the manager chooses the best possible incentive plan for the firm given their private information. Furthermore, I show that the request mechanism can entice the manager to invest in acquiring additional information when it most benefits both them and the firm.

Read the full article here:

Waiser, Rob (2021), “Involving Sales Managers in Sales Force Compensation Design,” Journal of Marketing Research, 58 (1), 182–201.

Ratan Kumar is Assistant Professor, Jagdish Sheth School of Management - India.

Shipra Pandey is a doctoral scholar (Operations Management), Management Development Institute, Gurgaon, India.