A seasonal illness spike, a tariff change, and a batch nearing expiry can all land on the same day, across hospitals, distributors, and warehouses. Aera senses changes across demand, inventory, and sourcing; recommends actions that keep devices available and reduce expiry write-offs; and executes them in your systems.
The data already exists in your systems. The cost lands in what happens between the data and the action.
Seasonal illness, surgical volumes, and health crises shift demand faster than disconnected planning systems can follow, so devices run short in one place while stock piles up in another.
Batch-level expiry dates are tracked by hand across warehouses, hospitals, and distributors, so inventory nearing its date is often found only when the write-off can no longer be avoided.
A single trade policy change can shift the cost and continuity of a component at once, while procurement plans still move on a fixed cycle.
Aera automates the routine decisions, augments the complex ones, and executes both in real time. Medical device teams see the payoff in five areas of the business.
Forecasts refine continuously across device categories, care settings, and regions, adjusting to seasonal illness cycles, surgical volumes, and new product launches as the signals arrive.
Inventory is watched across warehouses, distributor locations, and consignment stock at hospitals and clinics, with transfers and replenishment recommended before a shortfall reaches a care setting.
Batch-level expiry dates are matched against projected demand at every storage location, with inter-facility transfers and priority allocation recommended while the stock can still be used.
Tariff exposure and supplier risk are monitored across the sourcing network, with trade policy scenarios modeled and the supplier mix rebalanced before a change erodes margin or interrupts supply.
Routine forecasting, rebalancing, and sourcing decisions run without a planner in the loop, so teams spend their time on the calls that protect supply and service.
With Aera, we can see exactly where the product is, and depending on where that product is in the supply chain, dynamically calculate when we can expect it.
Prepackaged decision logic your teams can run on day one, tuned to demand spikes, batch-level expiry, and tariff exposure across a global sourcing network.
Recommends adjusted forecasts based on real-time signals across device categories and care settings, with statistical forecasts tailored to existing, new, and promotional products.
Recommends transfers and replenishment actions to prevent stockouts and reduce excess, with rebalancing evaluated between locations to match supply with actual demand.
Recommends inter-facility transfers that move expiring inventory to high-demand locations, and initiates disposal workflows for expired or unusable devices.
Recommends sourcing decisions based on real-time tariff and supplier risk signals, with tariff scenarios modeled and alternative sourcing options weighed for cost impact.
How decision intelligence handles demand spikes, device expiry, and tariff exposure, with four Skills and two customer case studies.
What changes when demand, inventory, expiry, and supplier risk decisions stop waiting on the planning cycle.
How Alcon, with Aera and EY, moved supply chain planning from firefighting to explainable, real-time recommendations.
Jared Guckenberger, VP of Global Supply Chain at Avantor, on starting a decision intelligence journey in life sciences.
