Utilizing business intelligence in product cost management for procurement decision-making

Decreasing product costs is a crucial goal for many manufacturing businesses. Awareness of cost structures is essential in evaluating profitability of products. To ensure correct sales margin and ensuring its adequacy for enabling business activities, precise product costs in manufacturing must be noted. This research focuses on material cost analysis, examining component purchase price development and build up in the structure of products. This aims to create transparency in product costs and therefore enabling strategic resource allocation for cost control. Analysis of cost management and procurement’s contribution to product costs, as well as utilizing business intelligence in these areas were examined. Furthermore, opportunities in BI tool utilization in manufacturing SMEs, and current cost reporting was analyzed, as opportunities and challenges in implementing business intelligence were discovered from conducted interviews. Product cost structure visualizations’ contribution to cost management and procurement decision-making was examined with observations of produced report’s usage and functionality from management point of view. Cost structure visualizations created a glance on cost build ups in products in different hierarchy levels, revealing essential information on component price increases. This enables allocating procurement resources more strategically, lessening the amount of operative analysis in procurement function. When examining product costs, it is important to take into consideration the possible inconsistencies in visualizations and components outside of structures, and their contribution to the total costs. Actions are encouraged for components where price increases are significant, or the volume of the component in one or more products is big enough to create value in the total product costs. Utilizing business intelligence was stated to contribute to cost management and procurement analytics by enhancing data-driven decision-making. Possible challenges and the importance of organizational commitment should be accounted for when attempting to implement BI tools for broader usage in SMEs. Challenges in information management in this research and previous studies are recognized in the context of utilizing BI tools in SMEs. Documenting processes and transforming tacit knowledge into explicit knowledge will enhance organizations’ development and growth, enabling implementations of new solution s such as business intelligence tools into the organization.