Improving operational efficiency through digitalization : a novel approach to pricing data management : case study in the renewable energy industry

Abstract

Pricing execution in asset-heavy industries is a data-intensive and cross-functional process that depends on accurate information flow across systems. Yet in many organizations, despite their exorbitant and well-established digital ecosystems, this process remains fragmented, manually intensive, and structurally prone to errors. This thesis investigates how digitalization can support pricing data management in achieving first-time-right (FTR) accuracy and hence enhancing operational efficiency, using an in-depth qualitative case study of a large renewable energy company operating across international markets.

Ten semi-structured interviews were conducted across six organizational functions of the case company, followed by a document analysis. Data were analyzed using inductive thematic analysis following Braun and Clarke’s six-phase framework. Consequently, the findings identify two core operational inefficiencies, three underlying causes, and three digitalization levers capable of improving FTR performance. However, the study also demonstrate that technical solutions alone are insufficient. Effective digitalization requires simultaneous progress on semantic data alignment, extended governance covering transactional data, and cultural changes that distribute data quality accountability across functions.