Utilization of installed base data in spare part inventory management and the data quality assessment

Abstract

This study focuses on the spare part inventory management using installed base data in the capital equipment industry. It focuses on how installed base data can enhance various inventory management processes compared to traditional methods as it serves as a more proactive and forward-looking source of information compared to methods relying on only historical information. Even though various methods have been widely researched, their practical application still scares. Therefore, this study also highlights the data quality dimensions and criteria it creates for the data As also the capital equipment industry has become more focused on providing high-quality services for their customers compared to traditionally very product focused approach the spare parts inventory management and availability have become increasingly critical part of the business. While decision-making has become more data-driven in many functions as the amount of data available for decision makers has grown the inventory management processes have remained very unchanged using mainly only historical sales data when forecasting the future . In the past decade, research has focused more on causal forecasting methods and bringing more data into the processes such as installed base data. This approach has enhanced the demand forecasting accuracy and return on investment in the spare parts business. Applications like geographical distribution of spare part inventory and forecasting demand during different life cycle phases have proven to be efficient and outperformed traditional methods. Past research has been theoretical and often runs into the same limitation: the data quality of the installed base data that companies have currently. The research was conducted using qualitative methods and examined through a theoretical framework that included the context of spare part inventory management, installed base system and applications and data quality management. This was combined with empirical data collected from different stakeholders involved in inventory management decision-making in the case company. By interviewing a wide range of stakeholders from different functions and regions in the case company, a very comprehensive understanding was developed regarding the current state of processes and data utilization and how the data quality dimensions are seen. The empirical data was then combined with the theoretical framework to create a more practical focus on the most appealing use cases of installed base data, considering the willingness of different stakeholders and processes that are currently underperforming. The interviews were also used to create criteria on the data quality dimensions and to understand the subjective data quality perspective better. Even though the study did not conduct any quantitative measurement of data quality, it was identified that the current installed base in the case company is not at the level that it could be utilized in more sophisticated applications which require data such as spare part age or replacement. This issue is common for also other global capital equipment providers as the root causes are related to the complexity of processes and systems in the company which make the management of data difficult. The most promising application of installed base data was identified as geographical distribution planning of spare parts with installed base data. The study showed significant benefits of utilizing installed base data compared to traditional methods. Additionally, requirement for the data and its quality was low er compared to other applications. From the interviews and literature, criteria for the data quality dimensions were also very broadly set to satisfy different stakeholders if the data would be used in these processes.