Iris-Katharina Schmutz

The field of pricing holds high potential for professional- ization since it comprises a multitude of decisions based on sparse information sets, data-driven tasks and an ever more dynamic and fast-moving market environment. Therefore, advances in artificial intelligence (AI) will influence and maybe even disrupt pricing man- agers’ roles within the pricing process. Using a Delphi study design, we aimed to take a look at future tasks and profiles of pricing managers. The results allowed us to extend existing models of pri- cing capabilities and classify which skills and know-how pricing managers should nurture and which ones may be left to artificial intelligence. Furthermore, we were able to derive implications for curricula as well as talent selection.

Literature on pricing has proposed pricing processes of a normative nature. With these representations implicitly come necessary and sufficient sets of information for pricing decisions. However, they seem to be a misfit with realities in B2B business. Firstly, the concepts partly miss B2B distinctive elements, such as price negotiations and close long-term customer relationship management. Secondly, pricing competences are often spread across functions and roles within the company. This renders pricing a companywide task and makes a fully integrated pricing process difficult. This research-practice gap has been established in pricing literature. In order to contribute to the understanding of B2B-pricing practice and to further close the research-practice-gap, we aim to identify and describe pricing managers‘ deviations from normative pricing processes. We found that price-related information deficits might cause strong deviations from normative pricing processes. This paper analyses pricing managers’ compensation mechanisms, in cases of price-related information deficits. Furthermore, we aim to identify which complementary or substitutional information pricing managers target instead. We approached this explorative research subject with a qualitative method and analyzed it with Grounded Theory. The interviewees are seventeen pricing managers from various industrial sectors, who all operate on innovative and international markets. As results we describe reactions to price-related information deficits and propose a typology of approaches chosen by pricing managers. The typology differentiates pricing managers’ reaction to price-related information deficits along market information situations and individual strategic reasoning. The results of our study contribute to an in-depth understanding of pricing practices and provide a conception of pricing reality in B2B companies.

This research project aims to describe and identify the effects that AI technologies will have on the field of pricing. As the technology and its possibilities are widely discussed and the extensive benefit companies could hold using these technologies in pricing, the details about implementation and feasibility still prevent the technology’s market penetration. However, technological process is knowingly extremely fast and in order to keep pace (future) managers have to educate themselves and develop a very different set of skills, which on the other hand is a process with long-term scope. This dilemma can only be solved by taking a look in the future and focus resources on the most promising capabilities. The closest we can get to this would be by consolidating expert opinions and make them reflect on accordances as well as using differences for deeper reflection. This procedure is called Delphi study design and will be explained in detail in the next chapters.

This thesis investigates the information behavior of pricing managers during the price-setting process. Price-relevant information deficits are a frequently encountered problem in pricing practice and often stand in the way of normative or planned pricing processes. This thesis conceptualizes and assesses the reactions of pricing managers confronted with an information deficit. It connects information-seeking processes and strategic management knowledge with the realm of pricing. The studies discuss the problem of information maximization and, based on this discussion, propose stopping rules for price analysis. Furthermore, four relevant types of heuristics in price analysis are identified and their relationships to pricing capabilities as well as firm performance are established. It is found that pricing managers can successfully bridge price-relevant information deficits by applying causal as well as effectual heuristics in price setting. Therefore, established normative pricing models are supplemented by the dimension of effectuation theory which supports the understanding of real-world pricing practices under severe uncertainty and pressure. In addition to contributing to a better understanding of B2B pricing practices, the models proposed in this monograph provide some orientation on information behavior in pricing and build the ground for further investigations of price management decisions. Moreover, the results of this thesis provide valuable insights for companies asking themselves whether investments in pricing will pay off, and if so, where and when to invest. Since pricing managers are the research subjects of this thesis, the results provide actionable recommendations regarding their potential for professionalization.