Smarter analytics for retailers Delivering insight to enable business success


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Smarter analytics for retailers Delivering insight to enable business success

  1. 1. 50 Years of Growth, Innovation and LeadershipSmarter Analytics for RetailersDelivering Insight to Enable Business Success A Frost & Sullivan White Paper Robert Worden Brian Cotton
  2. 2. Frost & Sullivan Abstract................................................................................................................................... 3 Insight in the High-Velocity Retail Environment................................................................. 3 Smarter Analytics for Smarter Retail................................................................................... 5 Introducing Smarter Analytics.............................................................................................. 5 Performance and Organizational Benefits of Smarter Analytics...................................... 7 Retailers Using a Smarter Analytics Approach to Gain Competitive Advantage............ 8 GS Retail Propels Growth with Customer Insight............................................................... 8 Intersport is Future-Proofing with an Analytics Advantage................................................ 9 Migros.................................................................................................................................... 9 Deeper Insight, Better Responsiveness, and Business Success........................................... 10 Conclusion............................................................................................................................... 11 CONTENTS
  3. 3. Smarter Analytics for RetailersABSTRACTThe fundamental relationship between retailers and consumers has changed. Power has shiftedto consumers, enabled by Web and mobile technologies and the influence of social media.Retailers are challenged to adapt to these changes and renew their relationships with theircustomers to strengthen the brand experience and maintain customer loyalty. This requiresthem to change their operational model to better understand their customers and to meetincreasingly more demanding expectations. Insight into their customers—their preferences,needs, pricing, and buying behavior—is critical, as is insight into their own operations, frommarketing and merchandising to supply chain and order fulfillment.Forward-thinking retailers are applying a Smarter Analytics approach to become morecustomer aware, build customer loyalty and achieve higher levels of customer satisfaction. Torealize the benefits of this approach, retailers need to design their information technology (IT)infrastructures to be able to support specific types of analytic domains, rather than rely on aone-size-fits-all design. Retailers such as GS Retail Co. Ltd., INTERSPORT Group, and Migros,are using the Smarter Analytics approach to build a business intelligence infrastructure thatenables them to deepen their insight, respond better and faster, and achieve business successin a highly competitive market.INSIGHT IN THE HIGH-VELOCITY RETAIL ENVIRONMENTRetailers today are facing more technology-savvy, demanding customers and more sophisticatedcompetitors, which are forcing changes in retail business models. This transformation is beinginfluenced by three imperatives defining the retail landscape: 1) delivering a smarter shoppingexperience, 2) developing smarter merchandising and supply networks, and 3) building smarterretail operations. Retailers recognize that one of their primary opportunities in the fast-changingretail environment is adapting to today’s empowered consumer. The power of the consumercomes from their ability to leverage social and mobile technologies to gain access to competitiveproduct and price information and special offers, all to their advantage. By understanding theircustomers better, retailers can more accurately predict their needs, preferences, and responsesto promotions, which can drive higher levels of customer satisfaction and, ultimately, highersales. In fact, a recent National Retail Federation (NRF) survey revealed that 82 percent ofretailers are making customer service strategies their primary strategic focus.1 The challengefor retailers wanting to provide better service to these connected customers is to “know”them better. With a deeper level of insight, retailers are better able to meet the customeron the customer’s terms, with personalized service, offers, and promotions. But to be trulysuccessful, retailers need to be able to shape their future success by driving their organizationson the basis of insight.By applying business analytics, retailers can develop this insight. Retailers are exposed to awide variety of data. Structured, historic data, such as a customer purchase or billing records,will only provide a partial picture of the customer. Increasingly, the connected customer isgenerating data that is largely unstructured, such as customer service call recordings, chat 3
  4. 4. Frost & Sullivan sessions, product reviews, or social media postings. These can be rich sources of valuable insight, as up to 85 percent2 of customer insight lies in unstructured data. Moreover, data needs to be accurate to be useful, and an average of 23 percent of data in an organization’s database is inaccurate, incomplete or out of date.3 Retailers are realizing that business analytics is an important component to strategic success, and a recent study of CIOs found that 86 percent of retail industry CIOs place business intelligence and analytics at the top of their list of visionary plans.4 The types of insight that retailers can use to serve their customers better, and ultimately drive business success, are illustrated in Figure 1 below. For instance, better insight into customers and their price sensitivity needs to be complemented with operational insight (e.g., sales, marketing, and merchandising insight) to give retailers the ability to link customers, suppliers, and business partners together in a customer-oriented strategy. This enables retailers to move away from reacting to customers based on history, to anticipating and planning for customers based on insight. Deeper insight provides retailers with the ability to predict the likelihood of a desired outcome and dynamically select the most acceptable offer to put forward to a customer within seconds at the point of impact. Figure 1: Information Drives Insight to Enable Retail Business Success Pricing Insight Customer Insight Know what price point will draw Sell what customers want at their customers and increase profitability mix preferred point of purchase Sales Insight Marketing Insight Adapt new services and Deliver personalized new ways to sell based on promotions and optimized how customers are buying marketing spend Merchandising Insight Business Success Optimize inventory investment Drive maximum revenue and with minimal stockouts profitability through all channels Source: IBM and Frost & Sullivan Analysis The types of analytics that produce insight range in complexity and answer different questions. Simple, descriptive analytics include operational and ad-hoc reporting (“What happened?”,“How many?”, “Where?”), and directed queries and drill-downs (“What exactly is the problem?”). Retailers can apply these analytics to produce flash reports, marketing performance metrics, and financial reports. More complex analytics include alerts (“What actions are needed if something happens?”), simulations (“What could happen if…?”), forecasting (“What happens if these trends continue?”), and predictive modeling (“What would be the best outcome if…?”). Retailers could use these analytics to understand the impacts of cost changes, missing sales targets, or the entry of new competitors into markets. Highly complex analytics include 4
  5. 5. Smarter Analytics for Retailersoptimization (“How can we achieve the best outcome?”) and stochastic optimization (“Howcan we achieve the best outcome given the effects of variability?”). These analytics can helpretailers create localized assortments, work with supply chain or production constraints, andcreate personalized promotions.Shifting from reacting to customers and market conditions, to anticipating future scenarios,to actively using the variability in them can create complexity for retailers because they needto make infrastructure design modifications to produce the kinds of insight their organizationneeds. Although retailers are actively focusing on using IT to support a number of customer-centric functions,5 they often need guidance to transform their current infrastructure tobecome insight-oriented. Smarter Analytics is IBM’s approach to designing integrated systemsthat harness all types of data to deliver focused, valuable insight and make it usable throughoutthe organization for current and future action.SMARTER ANALYTICS FOR SMARTER RETAILIntroducing Smarter AnalyticsTo successfully apply insight, retailers have to make a commitment to embed the practice andapplication of business analytics into the fabric of their organizations. Recent advances in theway organizations are deploying business intelligence and analytics applications are driven bythe massive volumes of data, arriving at high velocity, in a variety of formats.This has importantimplications to the computing infrastructure required to effectively run the applications in adynamic environment. Retail CIOs and IT managers have to consider the volume, velocity, andvariety of data available to their organizations to make informed infrastructure decisions, andto think about this in the context of a structured approach.The Smarter Analytics approach to building and deploying IT architectures is intended toenable the application of analytics to all types of data. The goal is to provide retailers with thesystems and tools to adapt to the new imperatives of the retail industry by leveraging analyticsto become more relevant to customers, create competitive advantages, and drive profitablegrowth. Retailers following the approach build their analytics infrastructures around threecentral pillars: • Align the organization and the IT infrastructure around information to effectively gather, manage, and analyze the growing volume, variety and velocity of data, which drives the need for a scalable integration platform to meet current and emerging data warehousing needs. • Anticipate and accelerate actionable insights with systems and storage optimized for analysis and information delivery to understand consumer behavior and build strategy, shifting the analytics process from a purely passive, after-the-fact model, to an active, during-the-fact model. As the number and diversity of stakeholders in a retail organization requesting insight grows, the amount of processing resources in the analytics infrastructure will grow, so an efficient and optimal harmony between analytics hardware and software is necessary to ensure that the stakeholders are supported. 5
  6. 6. Frost & Sullivan • Act with confidence in real time with pervasive and embedded analytics supported by an infrastructure foundation capable of swiftly handling critical actions to drive action. Integrating analytics into time-sensitive point-of-sale or point-of-service retail applications means that resiliency is critical, so the analytics infrastructure has to provide very high availability. A central premise of the Smarter Analytics approach is that no one type of analytics architecture will optimally meet all types of analytics needs. Instead, retail CIOs and line-of- business managers have to jointly understand the organization’s insight needs to determine a solution that is fit-for-purpose. Consistent with the Align principle, a retailer can start by understanding the nature of the data it has as the raw material of insight, and must consider the role of massive volumes of data, be it static, streaming, structured, unstructured, or any of the above (e.g., Big Data) feeding into a retailer’s information supply chain. The questions concern the volume of relevant data generated, such as millions of call records or transactions, which can occur daily. Other criteria concern the velocity of data, which can be historic data collected about a customer’s previous transactions, or be constantly streaming in from thousands or millions of online shoppers accessing pages on a website. They can also revolve around the variety of data, including static, structured data or rich, unstructured data including images, social media, or audio recordings from a customer contact center. The key point from these considerations is that different data types require different software and systems to analyze them, and thereby deliver the various types of insight required by the organization. Another set of considerations from the Smarter Analytics approach concerns the analytics required to support the insight needed. Following the Anticipate principle of the Smarter Analytics approach, retailers may need to employ descriptive analytics to support insight into the current state of customers, operations, and the supply chain, as well as insight into understanding historic trends. This could cover, for instance, what products different customer segments have purchased, what promotions trigger them to respond, how often they contact customer service, or how often they purchase through the same channel. Retailers may also need predictive analytics to enable them to predict future states and develop contingency plans to enact should any future states become realized. These analytics support insight into potential customer responses to promotional offers, pricing changes, or new products introduced. Prescriptive analytics can be used to direct business activity to shape the trajectory of the business to attain strategic goals and business success. These analytics support insight- informed decision-making around new services and new ways to sell to groups of customers, develop personalized promotions, and optimize inventory investment. Other considerations using the approach revolve around what the stakeholders in the retail organization need from the analytics, and the level of resiliency built into the analytics architecture. Building on the Act principle, some stakeholders may need on-demand, real-time access to analytic tools in fail-safe environments. Others may be content with daily or less frequently produced reports and are more tolerant of latency in getting results from the system. Still others may only need analytic results that are infrequent or are not bound by specific timeframes, and are tolerant of high levels of latency. The business insight tied to the analytic results is enabled by embedding analytics throughout the retail organization. Figure 2 illustrates this principle, showing that some areas, such as point-of-sale or point-of-contact, 6
  7. 7. Smarter Analytics for Retailersneed real-time insight. Other areas, such as just-in-time inventory insight on perishable orvolatile goods, are sufficient for daily insight, whereas inventory insight on non-perishablegoods can tolerate longer latency. It is not enough that the analytics infrastructure is always on;it must also be always available, always secure, and always absolutely reliable.Figure 2:Velocity of Retail Insight Embedded in Retail Organizations Customer Perishable/ Non-perishable/ Month-to-Month Year over Year Care Volatile Goods Non-volatile Sales Comparisons Comparison/ Inventory Goods Inventory Trends Fraud Store Sales Advertising Detection Figures Calendar REAL TIME DAILY WEEKLY MONTHLY ANNUAL Insight Velocity (Frequency of Report Needed) Source: Frost & SullivanGuided by these considerations, CIOs can design an analytic architecture with a mix ofoperating points and the means to adjust systems to suit unplanned or emerging needs.With anarchitecture inspired by the Smarter Analytics approach, CIOs can leverage the vast amounts ofdata they have to better understand their customers and uncover patterns pointing to factorsthat can positively impact sales.These could be insights such as time of day, geographic locationsthat drive traffic or pages on the retailer’s website that are heavily browsed. Through analyticsand pattern recognition, retailers can better anticipate customer purchasing behavior and arewell prepared to act to minimize any disruption or event that could affect their reputation orreduce customer confidence.Performance and Organizational Benefits of Smarter AnalyticsThe performance benefits retailers can gain from using a Smarter Analytics approach flow fromhardware components that are carefully tuned to address specific analytic needs and workin harmony with the analytics software to take full advantage of the capabilities of a fit-for-purpose system. Increased performance is gained from better data management and storage,data processing, and collaboration around the insight generated. It is also gained from moreefficient use of computing resources, and system management, energy, and data center spacesavings. Performance benefits extend throughout the organization and can improve decisionsupport with systems that can reason and learn. 7
  8. 8. Frost & Sullivan In addition to the performance benefits generated, a Smarter Analytics approach to implementing fit-for-purpose analytic infrastructures can also deliver real business benefits to retailers by enabling retailers to better understand customer behaviors unique to their businesses to build stronger strategies to meet buyer demand. For instance, retailers can use descriptive analytics to sense what is happening with customers, suppliers, or the market, and then respond to the trends. They can also uncover and infer buyer, supplier, and competitor behavior, and then create and execute strategies to address potential outcomes. Web analytics may help determine the optimal response times to encourage a sale, influence the best page navigation or even the most attractive page design. Finally, retailers can create breakaway competitive advantage by developing precise, targeted marketing campaigns, and highly personalized shopping experiences. Ultimately, retailers applying a Smarter Analytics approach enable themselves to harness the full power of analytics on structured and unstructured data, with superior IT economics. The approach allows the retailer to get a holistic view of what is happening with customers, suppliers, partners, and the market, beyond the surface indications of purchasing activity. This allows them to tune and optimize all the related systems in the organization to help them efficiently meet the needs of the enterprise, and provide a personalized shopping experience in a seamless manner across multiple touch points and channels. RETAILERS USING A SMARTER ANALYTICS APPROACH TO GAIN COMPETITIVE ADVANTAGE Retailers are facing new business requirements to address newly-empowered and connected customers, rising levels of competition, and increasing operational costs, and are using business analytics to solve these challenges and gain competitive advantage. Retail CIOs are being challenged to support these new business requirements and adopt new technologies and access new data, while squeezing higher efficiencies out of their IT infrastructures. CMOs and line-of-business managers are challenged to know which customers to target, how, when, and with what. What follows are examples of how some forward-thinking retailers are solving these challenges by following a Smarter Analytics approach and are recognizing the returns on their investment. GS Retail Propels Growth with Customer Insight GS Retail Co., Ltd. (GS Retail) is a diversified enterprise consisting of four retail chains based in Korea. GS Retail relies on analyzing customer data to maintain insight into customer needs and has traditionally maintained separate data warehouses for its convenience store, supermarket, and customer relationship management (CRM) systems. As the retailer’s business grew, the performance of the systems decreased as the number of demands placed on them increased. The time to generate reports and analytic results became a liability, and managers could not perform complex customer, pricing, sales, or merchandising analyses they needed to stay competitive. GS Retail decided to implement a new analytics system following a Smarter Analytics approach.Working with IBM, the company updated the design of its infrastructure to accommodate an appliance-like system, combining database, storage, and hardware elements 8
  9. 9. Smarter Analytics for Retailersto create a fast and easy-to-deploy, end-to-end business intelligence environment. The fit-for-purpose nature of the solution meant that GS Retail achieved a faster time to value and reducedthe total cost of ownership (TCO) of the system by 30 percent. Other performance benefitsincluded a 60 percent reduction in storage space for their data, due to updated data managementand compression processes, and a reduction in time to analytic results, down to six hours, versusnine to 15 hours with their previous system. Importantly, GS Retail laid the foundation foremploying sophisticated customer analysis tools, such as market basket analysis, enabling theretailer to develop new cross-sell and up-sell opportunities to targeted customer segments.Intersport is Future-Proofing with an Analytics AdvantageINTERSPORT International Corporation (IIC) is the purchasing and management companyfor Austria-based INTERSPORT Group, a worldwide leader in sporting goods retail. IIC hasa tradition of using business intelligence to inform decisions throughout the many companieswithin the group. With more than 4,900 associated retailers in 32 countries, business growthbegan to overwhelm the IIC’s ability to use its analytics infrastructure effectively. As businessgrew, the demands on the system to analyze transaction data increased, resulting in delayedor unobtainable daily sales reports. This caused significant impacts on retail associates’ abilityto manage sales and pursue opportunities. Working with IBM, IIC designed and implementeda new infrastructure optimized to support a highly resilient and available analytics system,and also enhanced the company’s disaster recovery capabilities. The new Smarter Analytics-inspired architecture consolidated and virtualized the IT infrastructure, enabling workloadsto be distributed between two powerful servers. Coupled with high-performance solid-statestorage, the new system greatly enhanced the performance of the analytics system and thedesign of the architecture ensured a far greater level of resiliency than before. Because the newsystem is optimized for transaction analysis workloads and leverages the servers’ virtualizationcapabilities, peak time demands on the system can be easily accommodated, which solvesthe problem of delayed or unobtainable daily sales reports. Moreover, the company is seeingoperational benefits from spending less on system management and by using 90 percent lessenergy to power the new system.MigrosFounded in Switzerland in 1941, the Migros Group comprises 10 supermarket and nonfoodretailers in a cooperative. Migros is the largest employer in the country, and to maintain its salesmomentum it is developing new channels (such as eCommerce) and new retail concepts thatblend commerce, food service, and entertainment. Migros Aare is the competence center forthe group and acts as a central hub that consolidates all of the IT solutions developed in-houseby the various cooperatives.The mainstay for Migros is fresh goods, which have a strictly limitedtime frame, so sales data on them needs to be processed rapidly and on time. The companyneeded to upgrade its IT infrastructure to enable it to keep up with its data processing needs,and also to provide new sales and merchandising insight to support its new channels. Workingwith IBM and its strategic partner SAP, the company built a new infrastructure based on twopowerful servers, leveraging the virtualization capabilities of the machines to accommodatethe multiple diverse workloads from the group’s many cooperative companies. By following 9
  10. 10. Frost & Sullivan a Smarter Analytics approach to designing this new infrastructure, Migros was able to have a vastly improved sales and merchandise analysis capability, giving it far better visibility into buying patterns. Improved insight also increased its responsiveness to changing patterns of demand, and enabled better customer service and easier intelligence sharing among the cooperatives. It also realized hard business benefits from a reduction of hardware acquisition, maintenance, and software license costs, and a lower total cost of ownership for the new IT infrastructure. DEEPER INSIGHT, BETTER RESPONSIVENESS, AND BUSINESS SUCCESS There is no question that today’s retail environment is forcing retailers to change their business models to become more responsive and competitive by understanding their customers better. For retailers working to meet the imperatives guiding their transformation, the Smarter Analytics approach can help. • Retailers striving to deliver a smarter shopping experience want to engage their customers on a personal basis, serving them whenever and wherever the customers want, and matching inventory and brand experience across channels. Adopting a Smarter Analytics approach enables retailers to harness the vast amounts of customer data at hand to develop single views of their customers, find patterns in them, and make this insight available to the marketing, finance, sales, and customer service personnel in the organization. • Developing smarter merchandising and supply networks involves gathering customer information continuously at every touch point to manage and deliver assortments based on customer insight. Single-view perspectives of the customer, and of the retailer’s partner ecosystem, can be used to anticipate customer needs and supply chain events, to enable optimized supply chain management and product development. Fit-for-purpose and highly resilient and available systems are able to support these demands. • Building smarter retail operations involves inserting intelligence into customer data management and processes to understand and predict sales trends, while improving management across production, product development, and assets to drive operational excellence and lower costs. Scalability and dynamic computing resource allocation are critical to ensuring the availability and security necessary to realize this imperative, particularly as the underlying analytics are embedded throughout the retail organization. Following the approach means that retail CIOs need to carefully consider their organization’s needs for insight to make the right infrastructure choices to support the analytics that will produce the insight. An infrastructure design supported by Smarter Analytics can bring top- line benefits and bottom-line savings to retailers. The return on investment from implementing Smarter Analytics can translate to higher customer spend and growing revenue in new markets with new customers.The approach can, at the same time, result in a highly efficient infrastructure, which enhances IT economics by optimizing analytic workload performance on all the relevant information available to the retailer. As the approach is extended throughout the retail organization to its suppliers and customers, decision-making can be accelerated by delivering intelligence where it’s needed, shortening the time to value delivered by the analytic systems. 10
  11. 11. Smarter Analytics for RetailersRetail CIOs and line-of-business managers should consider adopting a Smarter Analyticsapproach if: • The organization typically relies on information that is weeks or days old • More management time is spent looking back at historic data than at real-time findings or predicting probable outcomes • Analysis is limited to looking at lists of data output, rather than looking at exceptions, proactive alerts, and graphic visualizations of findingsTo be successful, retailers must become more relevant to their customers and proactivelycreate competitive advantages, and this will propel profitable growth. Following a SmarterAnalytics approach to create an informed, insight-driven strategy can help achieve these aims.REFERENCES 1 NRF Foundation and KPMG LLP, Retail Horizons: Benchmarks for 2011, Forecasts for 2012, February 2012. 15 February 2012 release. Retrieved 20 April 2012. 2 “Autonomy CEO: H-P Deal Marks IT Shift,” Wall Street Journal, Aug. 30, 2011. europe/2011/08/30/autonomy-ceo-says-h-p-deal-marks-fundamental-shift-in-it/. Retrieved 04 April 2012. 3 Experian QAS. “The Dilemma of Multichannel Contact Data Accuracy.” 19 July 2011 release. http://www.qas. com/about-qas/press/experian-qas-releases-latest-research-report-the-dilemma-of-multichannel-contact-data- accuracy-985.htm. Retrieved 01 May 2012. 4 IBM. The Essential CIO: Insights from the Global Chief Information Officer Study, Retail Industry Highlights. May 2011. Retrieved 09 May 2012. 5 NRF Foundation and KPMG LLP, op cit.XBL03021-USEN-00This report was developed by Frost & Sullivan with IBM assistance and funding.This report mayutilize information, including publicly available data, provided by various companies and sources,including IBM. The opinions are those of the report’s author and do not necessarily representIBM’s position. 11
  12. 12. Silicon Valley San Antonio London 331 E. Evelyn Ave. Suite 100 7550 West Interstate 10, Suite 400, 4, Grosvenor Gardens, Mountain View, CA 94041 San Antonio, Texas 78229-5616 London SWIW ODH,UK Tel 650.475.4500 Tel 210.348.1000 Tel 44(0)20 7730 3438 Fax 650.475.1570 Fax 210.348.1003 Fax 44(0)20 7730 3343 877.GoFrost • http://www.frost.comABOUT FROST & SULLIVANFrost & Sullivan, the Growth Partnership Company, partners with clients to accelerate their growth. The company’sTEAM Research, Growth Consulting, and Growth Team Membership™ empower clients to create a growth-focusedculture that generates, evaluates, and implements effective growth strategies. Frost & Sullivan employs over 50 years ofexperience in partnering with Global 1000 companies, emerging businesses, and the investment community from morethan 40 offices on six continents. For more information about Frost & Sullivan’s Growth Partnership Services, visit information regarding permission, write:Frost & Sullivan331 E. Evelyn Ave. Suite 100Mountain View, CA 94041Auckland Dubai Mumbai Sophia AntipolisBangkok Frankfurt Manhattan SydneyBeijing Hong Kong Oxford TaipeiBengaluru Istanbul Paris Tel AvivBogotá Jakarta Rockville Centre TokyoBuenos Aires Kolkata San Antonio TorontoCape Town Kuala Lumpur São Paulo WarsawChennai London Seoul Washington, DCColombo Mexico City ShanghaiDelhi / NCR Milan Silicon ValleyDhaka Moscow Singapore