Fundamental changes in the healthcare sector are arising from increased connectivity of assets and prevalence of data. Real-time monitoring as well as big data analytics enable healthcare providers to deliver more precise and patient-centric services. New digital technologies allow new players to enter the market and traditional providers to transform towards a digital clinic.
To actively drive these changes a number of challenges need to be addressed and solved. Big data needs to be processed into smart data, which requires intelligent analytics and profound domain expertise. At the same time patient data privacy and cybersecurity need to be ensured.
Companies solving those challenges will benefit from cost savings realized through AI-based optimization of their processes, their capacity and asset management as well as from improved diagnostics and personalized treatments that secure higher quality in treatments.
Unlocking the productivity potential in procurement data
Project reference for big data analytics in the healthcare industry
Following the trend of big data analytics, a client in the healthcare industry expected great cost savings from uncovering hidden data patterns in material cost and payment term data.
We used machine learning and cloud infrastructure to identify hidden patterns in the global purchase data. For instance, through text mining we could identify similar materials that are purchased at different price levels across ERP systems.
Our analysis identified over 8000 materials for strategic review and validation, leading to a significant cost saving potential.