Retailers might be forgiven for

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1 RETAIL SOLUTIONS BRIEF By ADAM BLAIR Navigating Today s Fast- Changing Data Landscape Social, mobile growth increase forecasting and planning challenges Retailers might be forgiven for feeling that when it comes to forecasting and planning, they are caught in an eternal game of catch-up as they deal with an everexpanding and constantly changing data landscape. However, new analytics solutions, including those using cloud-based delivery systems to boost data crunching and computing power, are helping retailers keep pace. Several factors are remaking the data landscape. The rapid rise of mobile technology, for example, has created more than a new commerce channel to be integrated into merchandise and sales forecasts. It s also spawned a slew of new data points to track: not just who customers are and what they bought, but what devices and operating systems they are using, where they are located at any given point and how that affects their responses to messaging and promotional offers. Mobility s growth has helped feed the social networking phenomenon, with consumers sharing their experiences and opinions in real time via their ubiquitous mobile devices. This explosion of usergenerated content generates a rich mountain of data, containing nuggets that, if they are dug out, analyzed and used, are relevant to an expanding range of retail activities. These include (but are not limited to) marketing and advertising, merchandising, store operations, customer service and new product development. Social media has also democratized the If an opinion leader with many thousands of Twitter followers and Facebook Likes expresses enthusiasm (or disdain) for a particular product, retailers carefully wrought forecasts of this product s sales can rapidly become irrelevant. power to influence. If an opinion leader with many thousands of Twitter followers and Facebook Likes expresses enthusiasm (or disdain) for a particular product, retailers carefully wrought forecasts of this product s sales can rapidly become irrelevant. Unexpectedly high demand can create out-of-stocks and disappointed customers; drastically lower-than-expected demand means retailers are stuck with items that need to be marked down, or must be sold in different regions or through alternate channels. Channel Complexities The acceleration of social and mobile s impact has also coincided with the industry s move from a multi-channel model, with its relatively firm boundaries between store and digital channels, to an omni-channel R I S N E W S. C O M M AY

2 RETAIL SOLUTIONS BRIEF model. Retailers that had treated different channels almost as separate businesses are now being confronted with consumers who, increasingly, expect the same product selection, prices and service levels in every channel. Omni-channel s impact on forecasting and planning has been significant. For example, does a rise in online or mobile search activity for a particular product portend higher store traffic, requiring additional merchandise and higher staffing levels to ensure brick-and-mortar shoppers will find what they re looking for? Or will the searches be converted primarily into digital sales that will need to be fulfilled through the retailer s e-commerce supply chain? What will be the impact of promotions and price differences between channels? What about price changes by a retailer s competitors? Forecasters and planners operating in omni-channel enterprises are facing these kinds of complex, multi-variable queries every day. More channels means more customer touchpoints and, therefore, more opportunities to gather data. Recent RIS News research indicates how the multiplication of data sources has expanded retailers measurement responsibilities. As would be expected for a mature channel, more than three-quarters of retailers responding to a November 2011 survey said they used upto-date technology to measure website traffic as a means to sense customer demand. Retailers are moving quickly to measure activity in newer channels as well: of responding retailers currently measure mobile site/app traffic and collect real-time, item-level sales data across channels, and 38.5% monitor social media for company/product mentions. These figures are on the rise, with retailers either in the process of updating these technologies or with plans to do so this year or in Tackling Big Data These and other survey results show that retailers are dealing with a wider range of What does your company do to more accurately sense customer demand? Measure website traffic Monitor promotions with campaign management tools Measure store traffic Measure mobile site/app traffic Collect real-time, item-level sales data across channels Monitor social media for company/product mentions Use exception-based reporting to identify demand spikes/dips data types than ever before. In addition to the data they have always collected from their own transaction logs and other internal sources, retailers are seeing the need to factor in so-called unstructured data, such as blog entries, Facebook postings, YouTube videos and Tweets. There s also the added dimension of location-based information, made possible with more sophisticated traffic-counting solutions as well as tracking of consumer mobile devices. The opportunity this data offers is a big one: retailers can gain a greater understanding of consumer preferences, desires, purchase intentions and real-world shopping patterns. The challenges are that this type of data doesn t easily fit into existing analytical tools that were designed to discern patterns and monitor exceptions in POS, inventory and pricing data. The need to analyze these larger, more complex data sets what some term Big Data is being addressed by new forecasting solutions, particularly those using cloud-based approaches that make higher levels of computing power available to an expanding base of users. Data crunching that would have taken days, weeks or months with hardware-bound in-house so- 45.8% 76.9% 38.5% 34.6% 11.5% 37.5% 25% 20.8% 3.8% 15.4% 3.8% 16.7% 25% 12.5% 20% 8%12% 20% 8%12% 16% 24% 24% 20% 12% Up-to-date tech in place Updating now Will begin updating in 2012 Will begin updating in 2013 No plans Source: RIS News, November 2011 Retailers are seeing the need to monitor mobile and social channels, along with store and online activity, to understand customer demand 4% 11.5% 3.8% 12.5% 4.2% lutions can now be accomplished quickly and cost-effectively by taking advantage of massed server power in the cloud, available and priced for on-demand usage by retailers. For example, Predictix deploys 1,600 computing cores simultaneously for a Tier 1 retailer, providing supercomputer-scale power with software and Big Data analytics designed expressly for the cloud. The retailer is able to generate more accurate store-level promotional forecasts than had been possible with its previous system. Business users within the enterprise can generate item/store/week promotional forecasts for any of tens of thousands of SKUs across thousands of stores for a wide range of promotional types: price discount, Buy One Get One Free (BOGO), circular or event. More accurate forecasts help to align inventory with demand and drive sales increases while also reducing the incidence of overstocks and out-of-stocks. Marketing Roles Expand More and more retailers are seeking these kinds of enterprise-wide analytics capabilities. A big motivating factor has been that the rise of social and mobile have pointed 16 M AY 2012 R I S N E W S. C O M

3 INDUSTRY PERSPECTIVE ADVERTORIAL The Detail of Demand Driven Unlocking the benefits of consumer demand QAre companies changing their view on how to best drive improvements in their merchandising and supply chains? Yes. Traditionally, companies have focused on the supply chain, by using a variety of historical data feeds like shipments, withdrawals or aggregated sales to optimize forecasts, procurement decisions and the movement of goods from suppliers to customers. In the past couple of years there has been a laser focus on acquiring tools that use a consumer demand signal to improve customer service levels, reduce excess inventory, markdowns and carrying costs at the market or store level. Industry leaders are now employing bottoms-up detailed views of demand to optimize inventories and allow multi-echelon capabilities. These advances have provided a significant reduction in the occurrences of lost sales and improved merchandise turns. What type of solution is needed to deliver this view of consumer demand? To effectively address these issues requires a solution architected to handle extreme scale and support a bottom-up process to develop demand forecasts of each item, by location at the weekly and daily levels. These solutions must be capable of employing historical demand, possess great depth in identifying seasonal and causal impacts, and respond automatically to the latest trends to deliver accurate and responsive forecasts with a minimum of manual intervention. The Aprimo Demand Chain Manager solution is one of the leading tools in this area. Accurate forecasts are then combined with inventory and replenishment strategies, serving to effectively pull inventory through the multi-echelon supply chain based on expected sales across the network. What types of companies are taking this approach to understand demand? At one time only the very largest multi-billion dollar companies could afford a best of breed solution, building out store sku forecasts and running those on a regular basis. But within the past two or three years with the improvements of scale and demands on sound financials we have seen many smaller companies wanting to take advantage of this capability and drive those improvements across their supply chains. Businesses employing a demand-driven approach have seen tremendous benefits in outof-stock reductions, inventory turns and personnel productivity. Achieving these improvements, while optimizing customer service levels, delivers increased cash flow, profits and long-term business benefit to any company focused on improved returns. What type of benefits can be expected from improved demand forecast accuracy? Companies that employ accurate consumer demand forecasts reduce stock outs and lost sales across the board and at the same time reduce excess inventory and improve merchandise turns. These companies are also using forecasts in unconventional ways, like the merchandise allocation processes, previously driven by historical time periods or volume groups, resource scheduling, capacity planning and assortment plans. In addition the focus on multi echelon capabilities demands an accurate forecast that recognizes changing trends and allows the business to simulate multiple decision scenarios and share the forecasted demand with their vendor partners to improve purchasing. How will consumer demand driven tools assist retailers as they move towards a more inclusive Omni-channel perspective? The move to centralizing decisions in the Omni-Channel makes it even more critical to ensure the business has the most accurate view of demand by store, DC, at the website, depot or partner facility. Multiple channels offer the consumer more choice, wider product ranges and the option of shopping at their convenience, any time of the night or day. Simply providing the ability to buy goods at all nodes in the channel is not enough for the highly empowered consumer of today. It is essential that the promise of the goods desired is met with optimized service levels and balanced inventories. Understanding the changing consumer needs, where inventory is located and when, allows the business to satisfy customer demand seamlessly throughout the Omni-Channel. Aprimo, a Teradata company, is a leading global provider of marketing and enterprise software and services that enhance the productivity and performance of marketing and merchandising organizations. Aprimo Demand Chain Manager enables companies to obtain an accurate view of demand, and optimize inventories to satisfy that demand. Aprimo is headquartered in Indianapolis with offices worldwide. For more information, call or visit M A y 2012 R I S N E W S. C O M 17

4 RETAIL SOLUTIONS BRIEF up the still-wide division between retailers marketing and merchandising departments. The increasingly valuable customer data that is coming from new touchpoints is being handled primarily by marketing. However, merchandising is still in charge of translating forecasts into plans that determine what items are delivered where, at what time and in what quantity. And even when retailers make a sincere effort to link marketing-based forecasts with merchandising plans, institutionalized separations between these often siloed departments can get in the way of effective action. Desiring Data Integration Belk, the 300-unit department store chain, announced earlier this year that it would build a new integrated database-driven analytics environment powered by Teradata Data Warehouse Appliances and the Teradata Retail Logical Data Model. We were ready for a new data warehousing system to meet our requirements for a scalable, enterprise-class analytic environment capable of handling more numerous and more complex queries to explore and utilize growing volumes of valuable data, said Belk CIO Mike Laurenti. The database infrastructure deployment includes consolidating data from existing data marts into an integrated data warehouse, as well as a test and development platform. For many retailers, the volume of internal data alone can present an analytics challenge. Save Mart Supermarkets had been analyzing its transaction log (TLOG) data manually in what was a tedious and time-consuming process. We knew that we were missing out on actionable intelligence by not having access to our market basket information, said Aashish Chandra, senior director of information technology for Save Mart. The retailer implemented 1010data for analysis and reports in areas including finance and bookkeeping, loss prevention and promotion measurement. We now 18 Unstructured social media data doesn t easily fit into existing analytical tools that were designed to discern patterns and monitor exceptions in POS, inventory and pricing data have visibility and insights into our new sales initiatives that we never had before, said Chandra. The ability to measure the performance of our promotions and marketing initiatives allows us to make appropriate changes in a timely manner, to be more effective in our planning and execution. Retailers operating in rapidly changing markets need a combination of a solid platform with high levels of flexibility from their forecasting and planning solutions. M.Video, Russia s largest consumer electronics retailer, has rolled out successive Predictix applications, most recently its Assortment Planning, Store-Level Forecasting and Target Stock Optimization modules. The Predictix merchandising suite is based on a unified platform that extends across all its applications and connects seamlessly to M.Video s enterprise applications, including SAP and MicroStrategy, and also provides high levels of flexibility. The Predictix Cloud 2.0-based architecture provides M.Video with virtually unlimited computing power on demand, enabling more powerful and accurate forecasts. M.Video and Predictix are working together to create something very special, said Christopher Mangham, CIO of the 325-store chain. The Predictix platform and cloud-based architecture have shown the unique ability to adapt rapidly to M.Video s changing needs. Based on our early results, we anticipate great returns when the latest rollout is complete. Accurate planning and forecasting are essential to any retailer s success. So no matter how many new sales channels pop up or how unpredictably consumers behave, retailers will need to track, analyze and translate each new wave of data into useful, actionable information in order to stay in the game. RIS M AY R I S N E W S. C O M 15.rsb_0512_v4.indd 3 4/23/12 12:31 PM

5 INDUSTRY PERSPECTIVE ADVERTORIAL Driving Better Omni-Channel Decisions Cloud Offers Key Advantages for Forecasting and Planning QHow has the spread of omni-channel retailing increased the demands placed on planning and forecasting? Managed properly, multiple channels offer retailers an exciting opportunity; research shows that consumers who shop across multiple channels spend 4.5X more than single-channel shoppers. Getting it right is tricky, however. When retailers message and behave inconsistently across channels, they can easily alienate these most valuable of customers. Retailers must carefully examine each channel to ensure they re making the right offers to the right customers, and that demand is being accurately forecasted across them. In addition, all planning and operational decisions need to be coordinated across the business, both top down and bottom up, in near real time. Retailers must adopt the do no harm principle from medicine s Hippocratic oath; this means they must ensure that omni-channel promotional strategies don t harm their most valuable customers, but reward them instead. Can cloud computing solutions improve retailers planning and forecasting, and if so, how? Most retailers are stuck with software assets that weren t designed for today s omni-channel retailing world or the sophisticated analysis it requires. A casual walk around many retail planning and merchandising departments reveals that retailers are trying to solve this problem by resorting to Excel, since their IT can t keep pace. Moreover, old solutions rebranded for the cloud don t offer better planning or forecasting, merely lower IT costs. The few solutions that are designed for the flexibility and Big Data power of the cloud do yield significant benefits. At Predictix, Big Data power means our clients can better predict consumer demand and make better decisions based on that information. Also, our modern, configurable cloud technology ensures that each solution suits our client s needs from the beginning and that it can easily adapt and stay current despite rapid and unprecedented changes in retail. Increasing numbers of retailers are expressing interest in analyzing Big Data for the insights it can provide. What are the most important tools they will need to do so? Tools are just one part of the answer. Retailers must start with a clear strategy for what they want to do with Big Data, as well as the expected benefits. Pecking and hunting analytics do not lead to better operational decisions and consequently don t drive sales, improve the customer experience or reduce retailers costs. Retailers also should remember that Big Data is not a new phenomenon; old sales and inventory data, analyzed anew with the benefit of Big Data analytics, can yield significant benefits. How can retailers take full advantage of the cloud? To unlock the cloud s full potential, retailers must ensure that new applications are designed from the ground up for the cloud. Retailers with significant investments in traditional technologies and no current plans to replace systems should identify high-value areas where cloud-based solutions can extend and improve existing processes; forecasting and replenishment optimization are two such areas. Retailers that are replacing core planning or pricing systems should take advantage of the opportunity to move from traditional solutions to cloud-based ones that not only can handle these core processes in a more flexible, futureproof way, but more importantly provide the predictive analytics that are key to making better decisions. Retailers, wholesalers and brands make better forecasting, planning, assortment, pricing, and replenishment decisions with the Predictix merchandising software suite. Our clients get started quickly and see value early, thanks to the only Cloud 2.0 merchandising software suite designed from the ground up to handle Big Data, omni-channel retail, and our clients unique forecasting and planning needs. M AY 2012 R I S N E W S. C O M 19