Business Process Reengineering of a Large-Scale Public Forest Enterprise Through Harvester Data Integration

Abstract

Despite the extensive use of cut-to-length mechanized systems, harvester data remains largely underutilized by most stakeholders in Germany. Therefore, the goal of this study was to determine how business processes should be restructured to allow for a continuous use of forest machine data, with the main focus on harvester production data, along the German wood supply chain. We also wanted to identify possible benefits and challenges of the restructuring through a qualitative analysis of the newly designed business process. The Bavarian State Forest Enterprise was chosen for a case study approach. Based on expert interviews, the current and to-be processes were modeled. Results obtained from the qualitative data indicated that an integration of harvester data is achievable in Germany. Harvester data from forest operations can be provided to all subsequent activities along the supply chain. Core changes were the addition of a digital work order, the data exchange between harvester and forwarder, the pile order and the exchange of production data. Benefits for every stakeholder were determined. Through the reengineered process, harvesting and timber information are available and known at an earlier stage of the process, throughput information stations could be eliminated and working comfort could be improved. Ecological benefits could also be achieved through an anticipated reduction of CO2 emissions and protection of sensitive nature areas. Negative consequences of harvester data integration could appear in the social sphere and were in line with the reduction of personal contact. Challenges for the implementation in reality, besides the legal situation, could be the availability of on-board computers in forwarders, cost for new IT applications, willingness of stakeholders to cooperate and availability of internet access. Further research should be focused on the combination of harvester data with other data types and the practical implementation of the TB process.