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Untangling The Retail Supply Chain With Analytics

Retail supply chains are longer and more tangled than ever before – the complexity of the data sets and the management of far-flung suppliers coupled with high customer expectations around service and reliability are taxing traditional approaches to supply chain management to their limits.

Supply chain analytics and management plays a significant role not only in a retailer’s cost structure and profitability but also in the quality of the customer experience. Buyers will no longer tolerate delivery problems or out-of-stock inventory – retailers that can’t live up to impeccable order delivery and perpetually in-stock inventory can’t count on loyalty to keep customers in the fold.

How significant is the attrition risk?  A study released by Capgemini revealed that a full 89% of consumers stated that they would shop a different retailer in the future if an order arrived later than expected, and 73% reported that they would purchase an item from a different retailer than originally planned if that item wasn’t in stock.  These statistics are sobering, and the magnitude of the potential business impact around fulfillment issues and inventory availability is clear and significant.

The problem with traditional retail supply chain management is three-fold.

First, with the increased convolution around multi-faceted large-scale retail operations featuring growing store count, e-commerce sites, more products, order variations and a diverse supplier base, traditional supply chain management solutions can’t handle the complexity without end-to-end visibility throughout the supply chain.  Second, with heightened expectations around service quality coupled with customers shopping both online and traditional channels in concert, the integration between discrete online and traditional retail business units has become critically important.  Third, the demand fluctuations created both predictable peak and seasonal requirements and unforeseen happenstances affecting operations can lead to both localized and systemic supply chain disruption.

This is where real-time data analytics comes into the picture.  If you’re able to analyze streaming data in real-time across siloed supply chain components, you achieve end-to-end visibility throughout the supply chain, integration between traditional retail and online business units, and the agility and flexibility required to manage both peak and seasonal requirements and unexpected disruptions.

Put simply, if you’re analyzing data after the fact, you can’t pinpoint problems and make adjustments fast enough to prevent missed deliveries and out-of-stock situations before they cycle all the way through to the customer. However, when retailers are able to analyze streaming data to respond to supply chain complexities, they are able to make better predictions, decisions and adjustments in real-time, before the customer experience is negatively affected. 

If your interested how Gravity can help you predict what is going to happen in your supply chain tomorrow in real-time get in touch.



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