Spend analytics and sourcing of goods case study of tyre industry company
Manninen, Miska (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025120633126
https://urn.fi/URN:NBN:fi:amk-2025120633126
Tiivistelmä
This thesis was conducted for Nokian Tyres Plc to examine how spend analytics can improve procurement decision-making and to evaluate the suitability of the company’s current spend classification tool. The aim was to support the organisation in enhancing spend visibility and optimising indirect procurement processes. The study was carried out in collaboration with the procurement department and included interviews with category managers, practical implementation of the spend classification tool, and a review of alternative analytics solutions available on the market.
Qualitative methods were applied, including semi-structured interviews and hands-on testing of the tool with real purchase order data. The process was followed step by step, from taxonomy upload to performance analysis, except for a few features where instructions were insufficient. The tool’s strengths and weaknesses were assessed, focusing on classification accuracy, usability, and resource demands. The results showed that the tool did not achieve the required level of accuracy for reliable analytics, and manual validation was time-consuming, especially due to data imbalance and interface limitations. Based on these findings, key requirements for future analytics tools were defined, and a highlevel market review was conducted to identify more suitable solutions.
The findings indicate that data quality and balance are essential for effective spend analytics, and that process complexity and usability have a significant impact on adoption. It was concluded that the current tool does not meet the company’s needs for accuracy, ease of use, or analytical coverage. Recommendations include expanding the key requirements, initiating a formal RFI process, and improving master data, particularly in MRO categories, to ensure that any new solution can deliver accurate and actionable insights.
Qualitative methods were applied, including semi-structured interviews and hands-on testing of the tool with real purchase order data. The process was followed step by step, from taxonomy upload to performance analysis, except for a few features where instructions were insufficient. The tool’s strengths and weaknesses were assessed, focusing on classification accuracy, usability, and resource demands. The results showed that the tool did not achieve the required level of accuracy for reliable analytics, and manual validation was time-consuming, especially due to data imbalance and interface limitations. Based on these findings, key requirements for future analytics tools were defined, and a highlevel market review was conducted to identify more suitable solutions.
The findings indicate that data quality and balance are essential for effective spend analytics, and that process complexity and usability have a significant impact on adoption. It was concluded that the current tool does not meet the company’s needs for accuracy, ease of use, or analytical coverage. Recommendations include expanding the key requirements, initiating a formal RFI process, and improving master data, particularly in MRO categories, to ensure that any new solution can deliver accurate and actionable insights.