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Syft Adds AI Capabilities to its Real-Time Supply Chain Analytics Platform

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New Machine Learning Artificial Intelligence Algorithms Are Driving Smarter Supply Chain Forecasting

Syft, a leading national provider of healthcare inventory control and end-to-end supply chain cost management software and services, announced new artificial intelligence (AI) capabilities in its Syft Synergy Platform 4.1. 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 percent) of healthcare executives surveyed earlier this year say supply chain management is a moderate to high priority and 97 percent believe supply chain analytics can positively impact costs.1 However, many hospitals and health systems today are not equipped to optimize their supply chains, relying on standard statistical approaches that may use homegrown spreadsheets to analyze procedure supply costs, identify outliers, and forecast demand. And, while value-based care programs such as the Bundled Payments for Care Initiative-Advanced (BCPI-A) make it imperative for health systems to know their costs, most hospitals today are unable to identify their true cost per case or analyze their cost variances by surgeon, procedure of specialty.

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To optimize supply chain management, organizations need sophisticated, enterprise-wide solutions. A new 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 Syft Synergy® 4.1) and Syft integrated with Oracle Supply Chain Management Cloud to create a more efficient and integrated, warehousing, distribution, and clinical supply chain experience for customers.

Syft’s new 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 continually update its forecasts 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 a powerful analytics engine that provides actionable insights.

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“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 percent 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/inventory demand intelligence to update in real time as new information comes in. AI will revolutionize 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.”

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