Unifying data from multiple sources into a single model to provide a holistic view of overall flow health. Proactively pinpoint future production bottlenecks and anticipate issues before they become a problem. Identify root causes and assess downstream impacts.
In the next three years, we will be fighting the virus while continually realigning hospital supplies to varied levels of elective surgeries. It is not one chain, but many—all to be synchronized simultaneously.
With Radiant Path, we focus on a new approach that maps changing flows across all supply chain tiers to ensure a feasible, aligned plan. Now, when hospital cases surge, a medical device manufacturer can track and redirect five-tiers of supply flows by locality. This investment to drive visibility will drive lasting change, leading to new capabilities.
Data is bottled up in highly latent legacy systems, preventing supply chain leaders, planners and recovery teams from gaining timely insight into the effects of changing supply and demand. Lack of visibility leads to inventory and resource utilization imbalances. Imbalance means waste and uncaptured revenue.
Model alternatives in real-time. Compare multiple scenarios simultaneously, effortlessly testing contingencies and building mitigation strategies.
Forecasts adapt over time, giving an evolutionary set of data products that fit their distinctive situation. Adaptive learning combines the previous generation of rule-based, simple machine learning, and deep learning approaches into a more insightful set of analytics.
Recommendations guide better outcomes by prioritizing across a number of key metrics such as yield, utilization, schedule adherence and cost.
Collaboration through sharing scenarios enables the ability to convey complex plans and alternatives with colleagues in an easy to understand format.
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