Revenue management systems as symbiotic analytics systems: insights from a field study

Revenue management is a complex operational planning process involving predictive and prescriptive analytics. As real-world implementations strongly rely on the joint outcomes from both algorithms and analysts, we consider the revenue management system as an example of symbiotic analytics systems. This paper presents insights from a field study observing a natural experiment in revenue management. As a firm updates its automated revenue management systems, it also updates the related processes and the corresponding organizational structure. We use this opportunity to examine the multilevel use of symbiotic analytics systems based in a field study and explore the implications for the design of future systems. Specifically, we identify two different perspectives on the revenue management process. In the functional view, jobs are organized sequentially with a high degree of system-oriented specialization. The process view organizes jobs in a parallel structure, differentiating two perspectives on demand. Depending on what view the firm implements, different structural fault lines turn the communication and training of analysts into keystones of the planning process. Furthermore, as we point out, even implementing more sophisticated algorithms and redesigning planning processes and organization do not seem to reduce the relevance of human analysts.