Demand shifts in days, retailers expect every order on time and in full, and every new SKU adds another decision. Aera senses changes across demand, inventory, orders, and supply; recommends actions that protect service levels and margin; and executes them within policy guardrails.
The data already exists in your systems. The cost lands in what happens between the data and the action.
Shifting consumer trends, competitor moves, and changes in channel mix can redirect demand in days, while planning cycles still run weekly or monthly.
Retailers expect on-time, in-full delivery and fine the misses, while short supply still gets allocated across customers and channels by hand.
Promotions are planned long before launch and reviewed only now and then, so a weak one keeps running and a strong one goes unfed.
Aera automates the routine decisions, augments the complex ones, and executes both in real time. CPG teams see the payoff in five areas of the business.
Forecasts refine continuously from historical sales, distributor and point-of-sale data, and syndicated sources, with separate logic for existing, new, and promotional products.
Excess and shortage are spotted across distribution centers and shared supply nodes every day, with stock transfers recommended and truck loads built from the right mix of SKUs.
Shipments are timed, consolidated, or switched to a different mode based on service risk, freight cost, and emissions targets, so expedites drop without putting availability at risk.
Available-to-promise dates draw on inventory in transit and in the production plan, and short supply is allocated by customer priority, penalties, and revenue at stake.
Supplier risk, material cost, and changing demand are connected through the bill of materials, with quotas reallocated or alternate sourcing triggered before a shortage reaches the line.
We moved from our monthly planning cycle to a weekly S&OP cycle, which is far more nimble, far more agile and we could reduce 50% of the time spent in the planning.
Prepackaged decision logic your teams can run on day one, tuned to volatile demand, retailer delivery standards, and trade spend that has to pay back.
Recommends forecast increases or decreases at any level of the hierarchy, with statistical forecasts tailored to existing, new, and promotional products.
Recommends transferring stock from one location to another for a group of materials, with truck utilization optimized by combining the right mix of SKUs.
Recommends changing a shipment's mode to expedite it or consolidating shipments to cut cost, weighing service risk and emissions targets.
Recommends whether to hold an order to raise its fill rate or release it at a lower one, with allocations and available-to-promise dates set by customer priority.
Recommends reallocating quotas across suppliers or triggering alternate sourcing, with risk predicted by connecting materials to demand through the bill of materials.
Recommends changes to the promotion calendar, timing, and mix, and flags underperforming promotions early enough to change course.
In this episode of the Future of Decisions Now Podcast, Unilever’s Juan Carlos Parada, Executive Vice President of Global Customer Operations, reveals how decision intelligence is enabling market-changing innovation for the CPG industry.
Five use cases drawn from work with global CPG companies: demand forecasting, inventory balancing, shipping and stockout prevention, order fulfillment, and supply resilience.
Aera CEO Frederic Laluyaux and Kraft Heinz's Arjun Kannan, Head of Digital Supply Chain & Analytics, on what decision intelligence has changed in practice.
Why so few supply chain organizations execute decisions in real time, and what changes when recommendations are automated, trusted, and learned from.
