Typically, retailers sell the stock they have. But, given the turbulent times, many retailers often don't have that stock on hand. Stockless order fulfillment enables brands to network with retailers and distributors to share inventory data. If the stock is unavailable at the brand's warehouse, orders can be fulfilled from the partner retailer's warehouse. For example, under such an initiative, Adidas can directly ship products to customers of a fashion retailer Very, when the latter is unable to fulfill the orders directly.
When consumers browse through brands or retailers, they can see the entire shared inventory. Orders are fulfilled from the nearest warehouse to the destination, allowing sellers to choose the most efficient way to deliver and delight customers.
With many moving parts, a lack of visibility restrains a flexible supply chain. Inventory control towers that provide real-time insights can enable organizations anticipate and fulfill demand. These towers become the single point of contact for information flow between multiple locations and parties. They integrate supply chain planning, ordering, transportation, and inventory management. These features make control towers a powerful tool to control end-to-end supply chain operations.
More sophisticated control towers can support faster and more automated decision-making, releasing teams to focus on other strategic tasks.
Infosys helped a leading U.S.-based sporting goods company ensure that lack of stock doesn't affect sales. It built a platform for order management across different markets, which helped the company fulfill orders efficiently using the network of affiliates, marketplaces, and its own distribution centers, helping its digital sales grow by 20% in a year.
Uneven demand in highly fluctuating environments is a major challenge for companies, especially for multiple products across geographies. Demand forecasting errors can lead to excess stock or out-ofstock situations. Regional factors such as weather, sports events, and cultural differences add to the complexities. Several parameters in a complex supply chain make it difficult to manage decisions and demand.
Better demand forecasting capabilities can reduce the effort required to fire fight sudden emergencies, allowing companies to focus on strategic initiatives.
AI helps retailers identify relationships between datasets, recognize patterns, detect demand fluctuations, and recommend optimal stock levels for thousands of stock-keeping units at their distribution centers. AI-powered demand forecasting can reduce forecasting errors by up to 50% and inventory levels by 20-50%, reducing lock-in of working capital. AI helps companies incorporate wide scope of parameters ranging from external market conditions to granular store level data. This allows companies to plan their assortments, labor requirements, promotions, and pricing.
A European CPG company built predictive demand forecasting capabilities with the help of Infosys. The company could make weekly forecasts with 92% accuracy overall and 93% at an individual retailer level. It also built a dashboard to simulate forecasts by changing sales drivers such as price, promotion, distribution, and the number of products to accommodate the fluctuations. This helped the company get real-time insights and helped faster decision making.
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