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.
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 in November, 2013 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.
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
Retail businesses grow and thrive through adding stores, items, online businesses and new suppliers, all of which increase supply chain complexity. However, while these evolutions are critical to growth and success, each additional component further tangles the supply chain web through increased interdependencies, siloed systems and communication gaps.
End-to-end visibility throughout the supply chain means that retailers have an up-to-the-minute and comprehensive view of all facets of the supply chain, and that data from diverse sources and systems can be collected, correlated, analyzed and applied in real-time. Balancing operational cost management with customer expectations can feel like walking a tightrope without a net – if you tip the delicate balance too far in either direction, you fall. However, with real-time data analytics, you’re able to make the small adjustments that keep you balanced and moving forward all the way from one end of the rope to the other.
How does this play out in the real world? Let’s say that you’re operating a quick-serve restaurant chain and you need to distribute perishable goods at regular and frequent intervals to thousands of stores across the country. You rely on a network of regional suppliers to provide specific goods to various territories, and you aggregate supplier shipments in your DC to deliver to your storefronts. Your orange juice supplier gets stuck in a road block and can’t make it to the DC in time to load the store-bound truck that’s stocked with other perishable goods and scheduled to depart within the hour. What happens next?
If you’re analyzing supply chain data after the fact, you find out about this problem when store #1452 calls in to headquarters to report that there was no orange juice on the delivery truck. Then you receive a series of similar calls from stores on the same route – no orange juice, no back stock, what to do?
The reality is that these stores will open up the next morning with no orange juice, and for those customers who expect their daily dose of freshly squeezed citrusy goodness, this will be cause for significant disappointment and lost confidence. Not good.
However, if your supply chain management solution contains real-time analytics capabilities, you become aware of the delay in real-time and your system orchestrates a workaround solution such that these stores receive their orange juice in time for tomorrow’s morning rush. And then you’re golden.
Integration between multi-channel supply chains for traditional stores and online businesses
Retailers can count on customers to be savvier than ever before – they’re better informed, more interactive and more selective than ever. Deloitte’s 2014 Retail Industry Outlook reveals that the growing popularity of online shopping is pushing retailers to look for new ways to deliver high-touch, personalized service to customers. The quick and easy access to information about competitive offers, merchandise availability and pricing means that retailers that don’t stay on top of what their customers want and need in real-time will lose their business when they turn to a competitor enticing them with better convenience, value and service.
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 vitally important for delivering the best possible experience to the customer. Customers expect to be able to order online and pick up in-store. They expect inventory to be available – if an item is out of stock in-store or backordered online, they expect the retailer to figure out a workaround to get them the item that they want within the window that they need it. Customers don’t think about how difficult it can be to coordinate operations between online and brick and mortar retail establishments – they want what they want when they want it. And if a retailer “can’t do,” they will find another that can.
Kenny-Paul also talks about the vital importance of being able to mine vast quantities of customer data – in 2014 it will not be just about looking at historical information. Rather, the most innovative retailers will also be leveraging real-time analytics and predictive data to guide retail strategists on what customers will want in the future.
With respect to retail supply chain management and multichannel integration, the key is having the right goods in the right quantities in the right place at the right time. However, this is far easier said than done. Retailers that deliver best on this value proposition are equipped with four key capabilities: 1) they have an end-to-end transparent view of the supply chain across both traditional and online business units; 2) they have the ability to identify bottlenecks and problems in real-time and the agility to take corrective action before the customer experience is impacted; 3) they are able to integrate data from diverse and siloed sources across business units to offer coordinated and quality service levels for the omni-channel shopper; and 4) they can collect, correlate and analyze both historical and streaming data to make more reliable and timely predictions to better manage their business.
How does multichannel supply chain integration play out for customers?
Let’s say you’re a customer that has surfed the net and have found what you think are the perfect pair of green boots online, but you’re reluctant to buy them without trying them on. So you head to the retail store to see how they fit and to make sure that they look and feel as great as you imagined. You show up at the store and ask to try them on in size 7. The sales clerk returns from the back with a stack of boxes for your consideration – none of which contains the green boots in size 7.
The clerk tells you that size 7 is in-stock in black and brown but not green, and the green is available in 6 ½ and 7 ½ and encourages you to consider other sizes and colors. But you want the color you want in the size that you wear and aren’t willing to settle.
For a retailer, what happens next determines whether or not you keep or lose not only this sale but also this customer. Your clerk could offer to call around to nearby stores and have them held for pick up or shipped to your home at your expense. Or, the clerk could suggest that you try on the brown boots for size and go online yourself and order them in the color that you want.
The problem with these traditional and prevalent approaches to dealing with “out-of-stock” situations is that you’ve got the customer in the funnel but can’t deliver on what they expect in real-time. If they have to drive to another store, they will likely abandon the sale. If they have to pay for shipping because their closest store is out of stock, they will be annoyed and frustrated. If you send them home to buy them online, they will search for other retailers selling the same item to compare offers and price because they know precisely what they want to buy. In this scenario you have essentially put the sale and the customer you had in the basket up for bid with your competitors.
However, if you can treat your customer as an omni-channel shopper and leverage your online business unit to meet their needs within the critical window of opportunity, you’ve not only kept the sale but also built good will. For instance, if you can check stock availability and place the order from your own online store and offer free overnight shipping on the fly while the customer is still standing at the register, you’ve kept your customer in the fold and your sale intact. This is just one example of how multi-channel integration benefits both retailers and customers.
Managed fluctuations in demand, peak and seasonal requirements
Traditional supply chain management approaches with respect to inventory planning start and stop with historical data. If you sold 50K pairs of snow boots last year, it’s a reasonable assumption that you’ll experience about the same volume this year and you plan your inventory and purchasing cycle accordingly. What happens when it starts dumping snow in the Midwest in early October and you’re not scheduled to cycle in snow boots in-store for another two weeks?
If you’re able to coalesce streaming data and historical data in real-time, you can accelerate the delivery and merchandising cycle to the stores in the region affected without disrupting core operations. The key benefit of this capability is that you can effectively respond to unanticipated demand fluctuations in real-time, meet your customers’ needs and protect your sale because you are operationally agile.
While there will always be unplanned anomalies that stir up trouble in the supply chain, planned peak requirements can also present significant challenges. For instance, if you’re a grocery store outlet, you likely stock turkey in your meat case year round and sell a modest yet steady quantity – that is until November hits.
Of the roughly 250 million gobblers consumed each calendar year, approximately 30% are purchased between Thanksgiving and Christmas. That means that grocery outlets are funneling nearly 80 million turkeys through the supply chain over a five week period. The successful execution of this seasonal demand spike requires careful planning and a watchful eye on core operations. You need to not only get the gobblers on the trucks and in stores in droves within a very narrow time period but also achieve this feat without messing up deliveries and warehousing for other critical items like milk, eggs and bread – because this will understandably make your customers cranky.
If you’re able to meld both historical data and streaming analytics in real-time, you can not only make more accurate predictions around the demand cycle but also proactively plan for contingencies and protecting core operations from disruption during peak distribution time periods.
Implementing real-time data analytics vastly improves supply chain efficiency and efficacy, and innovative retailers are leveraging these capabilities to improve supply chain management across a variety of operational functional areas. Real-time analytics capabilities improve forecasting and demand planning and better integrate sourcing and production operations. When it comes down to distribution and inventory management across channels, real-time analytics links business units across channels 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.
