Syft adds AI to supply chain analytics platform
September 3, 2019
Syft has added AI capabilities to its real-time supply chain analytics platform. The machine learning artificial intelligence algorithms are driving smarter supply chain forecasting.
Connecticut-based Syft, a provider of healthcare inventory control and end-to-end supply chain cost management software and services, has added the AI capabilities to its Synergy 4.1 platform. The AI algorithms in the supply chain software enable procedural level decision support metrics on costs and variance data linked to patient outcomes.
Almost all (98 per cent) of healthcare executives surveyed earlier this year say supply chain management is a moderate to high priority and 97 per cent believe supply chain analytics can positively impact costs. However, many hospitals and health systems are not equipped to optimise their supply chains, relying on standard statistical approaches that may use home-grown spreadsheets to analyse procedure supply costs, identify outliers and forecast demand.
And, while value-based care programmes such as the Bundled Payments for Care Initiative-Advanced (BCPI-A) make it imperative for health systems to know their costs, most hospitals are unable to identify their true cost per case or analyse their cost variances by surgeon, procedure of specialty.
To optimise supply chain management, organisations need enterprise-wide systems. A Syft white paper details the top seven areas of impact AI has on supply chain management. This year, Syft's supply chain software has been updated twice (currently to Synergy 4.1) and integrated with Oracle Supply Chain Management Cloud to create a more efficient and integrated warehousing, distribution and clinical supply chain experience.
The AI capabilities harness the power of machine learning, a type of AI in which computers can continually refine algorithms as additional information is captured. AI enables the health system to update its forecasts continually to make them increasingly precise. The first time the system forecasts demand, it can only use past data; over time, AI enables the system to become more intelligent as the data set grows. The result is an analytics engine that provides actionable insights.
"Applied extensively in imaging and population health, machine learning is just beginning to be used in supply chain management," said Kishore Bala, Syft's chief technology officer. "When we surveyed healthcare leaders earlier this year, only 63 per cent said they saw a clear return on investment for supply chain analytics. Artificial intelligence is going to push that number up to 100. There's a tremendous amount of rich data constantly flowing from EHRs and enterprise resource planning (ERP) systems. AI allows queries like cost variance analysis and procedure and inventory demand intelligence to update in real time as new information comes in. AI will revolutionise the operating room and materials manager's ability to plan for and deliver critical supplies at the right time and place, and at the right cost. The vast potential for this technology is exciting."