The project develops a method and a commercial softw are product for procurement management. The project utilizes advanced data science, and big data databases. The project relates to creating supply market intelligence (SMI); the w ays to capture, maintain and use multisided know ledge from the supply market. W e investigate from a research perspective how to effectively utilize big data, predictive analytics and data science in spend management and supply planning.
The developed softw are is expected to result in improvements in current best purchasing practices and procurement efficiency. Research w ill provide literature reviews and cutting edge empirical case study based results on how big data can be used, including analytics, to create supply market intelligence. It w ill also describe challenges and drivers for implementing and applying big data analytics in procurement for different types of companies and supply chains.
To ensure the efficiency and suitability of the softw are product, the project selects, analyses and demonstrates innovative use cases. Use cases describe w hat the Big Data enabled supply management can achieve. The use cases describe present big data applications and future possible scenarios. They are expected to provide understanding on the preconditions to reach the supply intelligence desired, the actors, the stakeholders involved and their interests, triggers, basic information sources and flows, and success scenarios.
Professor at Technology Management and Economics, Supply and Operations Management
Senior forskare at Technology Management and Economics, Supply and Operations Management
Funding years 2017–2019
Area of Advance
Area of Advance