Business intelligence implementation for optimizing the timber supply chain of a Finnish sawmill corporation

Abstract

The subject of this thesis was business intelligence (BI) implementation and the optimization possibilities it enables in the context of the timber supply chain. Research questions were “What to consider when designing and implementing a BI system for optimizing the timber supply chain?” and “Did the implemented BI system improve the data management of the timber supply chain?”. Of the timber supply chain activities, purchasing, timber harvesting, transport, and sorting, were researched. Previous research on optimization possibilities, BI competence, and data warehouse implementation were examined. The case study was conducted following an action design research framework. The thesis was commissioned by the case company, a Finnish sawmill, with 15 units and nearly 900 employees. The results were summarized in two conclusions. Instead of suboptimization efforts, supply chain optimization requires collaboration through the whole supply chain towards a shared objective to provide value for the end customer. A solution including a scalable BI system with a centralized EDW and adequate processes to support decision-making at both strategic and operational levels supports the optimization of a supply chain. Sufficient storage and compute capacity, source data quality, in-house resources and skills, and end-user training are key factors in BI implementation and maintenance. The BI system containing data warehouse and visualization achieved 14 of 16 data management demands, and nine reports were created for end-users.