A Practical Approach to Sales Compensation takes readers through the evolution of academic research on sales compensation. By examining the relevance of existing research, it provides practical guidance on the design of an effective compensation system. Furthermore, the monograph discusses how recent technological advances in artificial intelligence (AI) and machine learning (ML) shape sales strategy transformation and, thus, sales compensation systems of the future.
After an introduction, Section 2 illustrates a practical outline for designing a sales compensation system and the associated dilemma that organizations often face. Section 3 examines the theoretical foundations of effective sales compensation structures and their validity--in particular, application of the principal-agent theory, which derives optimal compensation systems under the presence of agents' moral hazard. Section 4 addresses recent developments in field research: randomized field experiments jointly conducted by academics and organizations as well as structural econometric methods using micro-level performance and compensation data. Section 5 illustrates how advances in technology affect organizations' sales strategies and, thus, the challenges and opportunities in utilizing compensation structure to motivate salespeople.