Assess point and contextual anomalies with relevant explanations and early warning signals for functional and executive personas to respond in near-real-time.
Help your planners make short-term decisions based on recent events and demand signals from across the Supply Chain. Overcome latency issues associated with traditional time-series forecasting methods.
Maintain optimum inventory levels throughout the distribution network. Use what-if scenario engines to determine volumetric and financial effects. Automate model switching and account for actual demand variability using Machine Learning.
Collaborate with upstream partners on weekly demand forecasts (aggregate and granular levels). Optimize order processing workflow along with hub-and-spoke network operations.
Drive categorization and prioritization of customer service elements by profitability tier and customer segment. Gauge affordability of service level actions through cost/benefit analysis. Optimize order processing workflow and hub-and-spoke network operations.
Leverage Nielsen and retailer-syndicated store and shopper-level data to optimize Supply Chain processes through JIT delivery, full truckloads of inventory (TLs), on-time shipment, forecast accuracy and efficiencies at distribution centers to maximize on-shelf availability.
Preempt order backlogs and last-mile delivery challenges. Deliver near-real-time order visibility to retail and D2C customers with reliable ETAs, and consistently invest in nurturing trust and loyalty among customers.