Retail supply chains are longer and more tangled than ever – 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 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.
The problem with traditional retail supply chain management is three-fold. First, existing solutions can’t deliver end-to-end visibility across an increasingly complex supply chain. Second, with heightened expectations around service quality coupled with customers shopping both online and traditional channels, the integration between discrete online and traditional retail business units has become critically important. Third, the demand fluctuations created by both predictable seasonal requirements as well as unforeseen happenstances can lead to supply chain disruption.
This is where real-time data analytics comes into the picture. If you’re able to track and trace events across a siloed supply chain in real-time, you achieve end-to-end visibility throughout the supply chain and the agility required to manage both peak 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 impact the customer. However, when retailers can analyze streaming data, they are able to make better predictions, decisions and adjustments in real-time, before the customer experience is negatively affected.
How do streaming data analytics capabilities empower large-scale retailers to improve supply chain management?
End-to-end visibility and coordination throughout the supply chain. As retail businesses grow, each additional supply chain link further tangles the web through increased interdependencies, siloed systems and communication gaps. A streaming data analytics solution can not only provide a retailer with an up-to-the-minute and comprehensive view of all facets of the supply chain, but it can also let them collect, correlate, analyze and act on data from diverse sources and systems in real-time.
How does this play out in the real world? Let’s say that you’re operating a quick-serve restaurant chain and your orange juice supplier misses a delivery. If you’re analyzing supply chain data after the fact, you find out about this problem when stores call in to report being out-of-stock. However, if your supply chain management solution includes streaming data analytics capabilities, you become aware of the delay in real-time and your system orchestrates a workaround solution such that operations and inventory levels are undisrupted and customers remain happy.
Integration between multi-channel supply chains for traditional stores and online businesses. Retailers can count on customers to be savvier and more selective than ever. Allison Kenney-Paul, Vice Chairman and U.S. Retail and Distribution Leader at Deloitte LLP states that innovative retailers are focused on delivering an integrated “omni-channel” experience, recognizing that the same customers are shopping both online and in-store and that channel integration is important for delivering the best possible customer experience.
Retailers that are successfully tackling this problem are equipped with four capabilities: 1) an end-to-end transparent view of the supply chain across both traditional and online business units; 2) an ability to identify and fix problems in real-time before the customer is impacted; 3) an ability to integrate data from diverse, siloed sources across business units to offer consistent service levels ; and 4) an ability to leverage historical data to set baselines to better analyze streaming data to make more reliable and timely predictions.
Managed fluctuations in demand. Traditional supply chain management approaches rely on historical data for inventory planning – and it’s helpful for planned cycles and peak requirements. However, historical data isn’t terribly useful for unanticipated happenstances that have immediate impact on inventory requirements.
If you have real-time visibility across your supply chain and can make adjustments to manage the unexpected, you are able to respond to demand fluctuations in real-time to meet your customers’ needs because you’re operationally agile.
Implementing real-time data analytics vastly improves supply chain efficiency, and innovative retailers are leveraging these capabilities to improve supply chain management across various operational functional areas. Real-time analytics capabilities improve forecasting and demand planning and better integrate sourcing and production operations. For inventory management across channels, real-time analytics links business units and siloed systems to ensure that items are perpetually in stock and delivered promptly.
At the end of the day, it’s all about keeping the customer happy and loyal through anticipating their needs and consistently delivering the experience they expect. And with real-time analytics, you’re always one step ahead with retail supply chain management.