Accenture seamless retail analytics


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Findings from Accenture’s global retail analytics survey on the three imperatives retailers face when building a digital customer experience.

Today’s digitally connected shoppers no longer just want to move seamlessly across channels – they expect to do so. Many retailers are currently feeling overwhelmed by these customer demands. However, by moving toward a robust retail analytics capability, they will be more equipped to know what their customer wants.

In order to deliver a personalized customer experience, retailers must first know their customer – and must know what that customer is looking for regardless of time, place, ethnicity, demographic or economic status.

The advent, adoption and maturation of analytics as a business discipline promised the tools and solutions required to support a seamless retail experience. But where does the actual implementation of retail analytics stand? How are retailers using this potent new capability? Is the practice delivering on the promise?

Accenture surveyed current analytics use among retail practitioners in an attempt to answer these questions. Our research revealed three imperatives facing retail enterprises as they put analytics to work today.

December 12, 2013


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Accenture seamless retail analytics

  1. 1. Seamless Analytics: Three Imperatives for the Retail Digital Marketplace
  2. 2. 2 Seamless Analytics Using Analytics To Shape a Seamless Experience: Retail Imperatives A perspective from Accenture with findings from a global survey of retail analytics “Analytics is the fuel of the digital marketplace.” Pierre Nanterme, Accenture CEO Today’s non-stop shopper wants and expects to move seamlessly across channels in pursuit of that perfect dress, that latest device, that ultimate experience. This customer expects to be recognized and respected no matter where, when or in which channel she or he surfaces. In today’s fast-moving markets, a seamless retail experience is becoming a prerequisite for any retailer that wants to remain relevant. In tomorrow’s markets, seamless retailing will be indispensable. Understandably, many retailers feel overwhelmed. The advent, adoption and maturation of analytics as a business discipline promised the tools and solutions required to support that seamless experience. But where does the actual implementation of retail analytics stand? How are retailers using this potent new capability? Is the practice delivering on the promise? Leading retailers have adapted to the new reality, customizing their offerings, in context and across channels to forge relationships with shoppers as individuals. They are consolidating functions and developing the skills needed to ensure a seamless customer experience. They are building the IT platforms and integrated data services needed to support such a seamless experience. But others are still striving to take an integrated enterprise-wide approach to analytics. For this reason, it is perhaps unsurprising that a large percentage of retail analytics practitioners have not yet seen an adequate return on their analytics investment. Accenture believes that recognizing and responding to the imperatives revealed in this study will be critical for retailers who seek to turn analytics into a competitive advantage. Many retailers stand at a vital juncture in the journey toward building an enterprise driven by customer insights. Those in the competitive set of the future are already using analytics to take a holistic view of their customers, to provide those customers with seamless experiences across channels, and to enable their organizations to make better decisions in marketing, merchandising, supply chain management and other functions. Everyone else has a choice to make. They can either respond by embracing analytics to focus relentlessly on the insights, actions and outcomes they need to meet the competitive challenge, or continue with business as usual. The choice is clear: the digital marketplace is the future, and the decisive difference is analytics. Behind all three imperatives is a single seismic shift: every customer is increasingly digital, and so every retailer must increasingly become a digital business.
  3. 3. Seamless Analytics 3 What Does Any (or Every) Customer Want? There are some six billion retail customers out there, shopping, hunting, scrounging daily for quite literally everything under the sun. What is the one thing they all want, regardless of time, place, ethnicity, demographic or economic status? Accenture surveyed current analytics use among retail practitioners in an attempt to answer this question. Our research reveals three imperatives facing retail enterprises as they put analytics to work today: 1. The Insights Imperative Retailers are striving to harness data for sharper customer insights. 2. The Actions Imperative Retailers must find ways to turn insights into actions at speed and at scale. 3. The Outcomes Imperative Retailers must engineer the links across their enterprise that tie decisions and actions with the outcomes desired. Of the three imperatives, this is arguably the most critical of all, as well as the most difficult for retailers to achieve.
  4. 4. 4 Seamless Analytics 1 The Insights Imperative: Apply Analytics to Data for Sharper Customer Insights It is imperative for retailers to have the right data in the right place at the right time. Most retailers appreciate the importance of integrating and leveraging data from many different sources. Fewer are collecting, managing and leveraging their data in a consistent manner across the enterprise. For too many, data is still being processed on an ad hoc, one-off basis. 52% of our survey respondents are reporting data collection as a key challenge 58% admit that harvesting customer insight from data is another key challenge The need for master data management is understood, but at least half the retail industry is still searching for a solution. Until retailers solve this puzzle, their ability to mine their data and to develop sharper insights into customer wants and needs will be impaired. When they do, they will discover that integrated data is the most direct path to the creation of a seamless customer experience across all channels. The insights made possible by integrated data will give retailers a 360-degree, 24/7 view of their customers, their personalities and their shopping and buying preferences. Good News, Bad News Retailer attitudes toward their proprietary data read like a ‘good news, bad news’ story. The good news is that two-thirds of retail respondents (67 percent) believe that unique or proprietary data is “very” or “quite” valuable, and in comparable numbers regard the data they have as consistent, accurate and complete. • wice as many retailers believe their own T data is unique when compared with the data of competitors: 49 percent rate their own data “completely unique” versus 23 percent who say the same about competitor data. • wo-thirds (67 percent) of all retailer T respondents believe unique or proprietary data enables their company to differentiate their products and services from the competition. Clearly, retailers have a particular appreciation for the power of data to help differentiate their products and services from the competition and to confer competitive advantage. So if their data set is as valuable as they claim, why aren’t retailers already deriving greater benefit from it? Our respondents report that only one in four active users of analytics use their data “to a great extent” for generating new ideas and opportunities for the business. A large segment – 40 percent – only rate their data as a “moderately” useful source for new ideas and new customer insights. The ‘good news, bad news’ ambivalence of our retail analytics practitioners toward their own data suggests that they know they are sitting on a very valuable asset. But they also know that they are having difficulty turning its riches into actionable customer insights, and that they could be doing more with the data they already possess.
  5. 5. Seamless Analytics 5 How do respondents rate the usefulness of their data for generating new ideas, opportunities for the business and new customer insights? When asked how unique their data was when compared to their competitors... Only 25% of active analytics users use their data “to a great extent” 49% rate their own data as “completely unique” 40% rate their data as “moderately” useful 23% say that their competitors’ data is also unique 67% of all retailer respondents believe unique or proprietary data enables their company to differentiate their products from their competition
  6. 6. 6 Seamless Analytics As part of our research, selected respondents agreed to in-depth interviews, of which a few stand out as typical examples of how analytics is working today. Here is the real-world experience of one retailer who is implementing the latest analytics tools and digital decision models across the enterprise in order to segment its customers more precisely and develop holistic relationships with them. Retailer Case in Point: Using Analytics Across the Online Enterprise This online retail group sells to consumers primarily through websites and catalogs. The goal is to use data analytics to manage multiple accounts of a single customer as one holistic relationship, a prerequisite for developing a truly seamless retail experience. The company has traditionally been very strong at measuring offline data from telephone sales. The company now needs to understand what customers are looking for on its websites, harness the growth in social media, and fully integrate all channels into its analytics. Using analytics online has greatly improved the company’s effectiveness in tracking customers’ pre-purchase activities and optimizing product positioning accordingly. As a result, the company now has more sales, bigger orders and better sales conversion. Going forward, the goal is to develop a cross-channel customer data solution that enables the company to use customer records to start and sustain a single customer conversation. Embracing mobile devices and wireless web applications will be critical to the company’s continued success. As one of its seasoned customer service executives recently noted: “The biggest challenge is that nothing stays still in our market for very long – three or four years ago we wouldn’t have been talking about how we incorporate social media data into our data structure, whereas now we can predict trends more accurately using data analytics. The landscape changes almost on a weekly or monthly basis. It’s very easy to be left behind.” To remain competitive and continue to drive positive outcomes, the company plans to expand its toolset and data analysis across the enterprise, with a clear understanding that a rich and relevant seamless retail experience must include shopping easily at home, on the phone and on the go. The biggest challenge is that nothing stays still in our market for very long—three or four years ago we wouldn’t have been talking about how we incorporate social media data into our data structure. Customer Service Executive
  7. 7. Seamless Analytics 7 Leadership’s Commitment is Clear Turning Data Pain into Data Gain The importance of analytics is already well-recognized among retail C-suite executives: 74 percent of respondents characterize the level of leadership commitment to analytics in their company as “totally” or “highly committed.” Gathering information is clearly not the major issue; if anything, retailers are struggling to keep their heads above an ever-rising flood of data. But processing, moving and managing that data in a systematic way across the enterprise so that analytics practitioners can take advantage of its power is a different matter altogether. • 54 percent are hiring and developing analytical talent. • 1 5 percent have already invested in analytical tools and software. For the overwhelming majority of respondents, the C-suite’s commitment to analytics translates into practical policies for data management: • Nearly three in four (73 percent) say their leaders demonstrate their belief in data by sharing a determination to establish clear protocols on what data needs to be collected, how the data should be collected, and how it should be shared across the enterprise • Almost as many (70 percent) ask their teams to analyze data not just to describe what is happening in the company today, but to predict what will be happening in the future. Retailers clearly want to move beyond a historical focus – “what happened, and what exactly is the problem?” – to ask and answer more predictive questions – “what happens next?” and “what are the best possible outcomes for our business?” While some have already put effective master data management infrastructures in place, too many others are not updating and cleaning their data in a consistent, uniform fashion. Data governance models are buckling under the stress of multiple demands placed on large amounts of data by multiple users. Compounding the problem of data management is the growing need to move beyond traditional sources of data. Retailers who want to seize opportunities for new customer insights must incorporate innovative and often unstructured sources of data from areas such as: • oice analytics from call center V interactions • onitoring the customer experience in M real time using web analytics • eeing things from the sky S (geospatial data) • nderstanding patterns of physical U movement from geo-location data • onitoring movement (visual data) M • Understanding attitudes/behavior (customer, employee). Online retailers have been more aggressive in tapping into new sources of customer insight. To meet and match this competitive threat, traditional retailers must recognize that even if their retail business is mostly ‘brick and mortar,’ their customers are increasingly digital, and they must be ready to see, sense and serve rapidly shifting customer needs regardless of channel. 54% of our survey respondents are hiring and developing analytical talent 51% of our survey respondents have already invested in analytical tools and software
  8. 8. 8 Seamless Analytics 2 The Actions Imperative: Turn Insights into Actions The goal in collecting and analyzing data is to harvest the rich insights that will help retailers shape a seamless and successful experience for the customer, guiding smarter decisions about which products to stock, what prices to charge and which offers to make to whichever customer you as a retailer interact with at this moment in time. A store manager faces hundreds of pricing decisions on a daily or weekly basis. 72% More than seven in 10 retail leaders demand fact-based decisions from their organizations A category manager faces hundreds of thousands of decisions annually on what items to order, and which assortments to stock in which stores. A store manager faces hundreds of pricing decisions on a daily basis. The marketing manager must shape offers on everything from promotional campaigns to real-time online up-sells and cross-sells. The supply chain manager may touch or tweak hundreds of space planning diagrams every quarter. With these levels of high-speed, granular decision making, the second imperative facing retailers today revolves around using data analytics to drive insight-rich, fact-based decision making that is faster, smarter, more flexible and more precise. Large online retailers are already there, making informed decisions at speed and at scale. Retailers looking to respond can count on analytics as one of the best ways to respond to this competitive threat. A recent study of 179 companies led by an economist at the MIT Sloan School of Management suggests that data-driven decision making is leading to measurable performance gains. Companies that adopted data-driven decision making have productivity levels 5 to 6 percent higher than can be explained by other factors, including investment in technology.1 Fact-Based Decision Making Retail leadership’s commitment to a future based on more enterprise-wide strategic and analytical decision making is strong: • 49 percent say they are committed to more enterprise-wide strategic analytical decision making • 3 4 percent report that more decisions are now based on complex data analysis than was the case two years ago. These leaders are expecting their people to bring supporting data to the decision making table. They are using data to assess performance and to identify new growth opportunities for the enterprise. • More than 40 percent report that more decisions are now being made based on complex data analysis. Survey respondents report that it is of immense value to model ‘what if’ scenarios to aid decision making in near-real-time environments. An American retail executive expressed it this way: “...customers are faster to move than they used to be… we need to be faster as well and need to analyze trends at a faster rate than we have in the past…. For that, we need to have analytics at our fingertips that can look at different ways and make decisions very quickly.” 1. Accenture Technology Vision: “Design for Analytics,” page 22.
  9. 9. Seamless Analytics 9 2 1 Using advanced analytics capabilities, the retailer collects and filters massive amounts of online data The results are displayed in user-friendly dashboard reports 3 The company can leverage real-time business intelligence and trend analysis 4 Make informed decisions that target consumer purchase preferences and product needs from a geographic perspective Retailer Case in Point: Dynamic Decision Maker The use of analytics at this high-end retailer has evolved considerably in recent years, enabling the organization to be savvier about customer segmentation and decision making. As a result, the company now targets its consumers and customizes its value proposition by geography. As a niche player in the luxury market, fast, fact-based, dynamic, decision making is critical to drive sales from current customers and to identify new growth opportunities. “(The use of analytics) enables us to cater to those certain nuances that are critical when it comes to getting as close as you can to that customer, ensuring that they have a truly memorable experience versus one that can prove to be rather frustrating.” Results to date indicate that the approach is working: getting into the mind of the consumer and customizing its services has enabled the company to increase customer retention and loyalty to the brand. Using advanced analytics capabilities, the retailer collects and filters massive amounts of online data from news, business and social networking sites, blogs and forums. With the results displayed in user-friendly dashboard reports, the company can leverage real-time business intelligence and trend analysis to make informed decisions that target consumer purchase preferences and product needs from a geographic perspective. As the retailer’s IT and marketing director has noted: The retailer is now looking to gain the greatest value from its analytics-driven decision making processes. Since this is not a mass market company with a lot of volume, it will continue to focus on customer segmentation and leverage its learning across the enterprise. Advanced analytics and business intelligence will be used to develop an innovative approach to brand monitoring, tailor products, adapt promotions, manage inventory, and improve the overall bottom line. (The use of analytics) enables us to cater to those certain nuances that are critical when it comes to getting as close as you can to that customer, ensuring that they have a truly memorable experience versus one that can prove to be rather frustrating. IT Marketing Director
  10. 10. 10 Seamless Analytics Engineering When asked about how Facts vs. Gut Instincts Decision Support decision making processes reported managerial decisions are Themany retailers show how difficult it by Today it is the ability to make informed can be to change the deeply engrained taken in their area or decisions at speed on a very large scale that business habits formed over a career in the sets retailers apart. Using analytics to adapt department, “personal business of retailing. Retailers are looking assortments, promotions and merchandising for analytics to answer questions in a broad to customer demand can generate experience” is still the range of functions and areas. But retailers increases in sales and additional margin. themselves still rely as much on intuition top factor in aiding or Synchronizing replenishment with offer can and personal experience as they do on hard decrease inventory and reduce shrinkage. informing the decision evidence of effectiveness. But these gains only come when analyticsWhen asked about how managerial decisions driven decision making support is available making process. The art and science of decision making Simple data and more complex data analysis Intuition and experience Accenture’s point of view is that the scientific side—consideration of simple data and more complex data analysis—in the mix with intuition and experience, collectively creates the art and science of decision making. are taken in their area or department, “personal experience” is still the top factor in aiding or informing the decision making process. “Intuition” and “more complex data analysis” are ranked equally influential. Changing attitudes on the role of data in decision making may still be a work-inprogress for many executives. In light of the continuing importance of intangible factors such as intuition, personal experience and consultation, a realist may conclude that data-based approaches still lose out to the instinctive style of decision making. As one executive said, “Sometimes in business there’s that gut instinct… how to take that information and apply it to make business strategies work is one of the biggest challenges.” Accenture’s point of view is that the scientific side -- consideration of simple data and more complex data analysis -- in the mix with intuition and experience, collectively creates the art and science of decision making. at the point of decision, when and where retailers are actually making those hundreds or thousands of dynamic decisions. The merchant who is trying to determine what to stock doesn’t have a lot of spare time; they need the analytics guidance at their fingertips. The merchandisers who must decide when to up-sell or cross-sell need the analytics guidance as they are interacting with their customers. When marketers have to determine where the last remaining dollars in the quarterly promotion budget are going to be allocated, they need the data to make that decision. Synchronizing analytics-driven support with decision making processes across the enterprise requires intensive rethinking and re-engineering, a massive undertaking in itself. Where do you begin? Focus on measurable business outcomes, where the greatest value is. Build pockets of analytics support around those decisions that have the greatest impact on your bottom line, then add and link these support structures across functions until they encompass the entire enterprise.
  11. 11. Seamless Analytics 11 3 The Outcomes Imperative: Focus on Business Outcomes It can take a retailer many years of experience to acquire the knowledge and sensitivities required to read a single customer’s wants and desires reliably. To engineer an entire retail organization so that it can intuit and respond appropriately to millions of customer interactions in real time is the very definition of complexity. In theory, analytics promises this responsiveness. In practice, the application of analytics in the retail environment requires a continuous fine-tuning of decisions and actions to business outcomes. Retail practitioners tell us that analytics has arrived, is in wide use and has strong C-suite support. The greatest returns on analytics investments will go to those retailers who focus first and foremost on business outcomes. Incomplete Implementation Only one in five retail companies (21 percent) report that they are aggressively using analytics “as part of an integrated approach across the enterprise that is ingrained in the fabric of their companies.” Nearly half of respondents (47 percent) report that analytics implementations to date have been tactically focused rather than strategic, limited in scope or uncoordinated and piecemeal. This incomplete implementation of analytics creates the third imperative facing retailers. Practitioners can either start linking the analytics capabilities they have and expanding these capabilities across the enterprise, or they will run the risk of being left with islands of isolated analytics expertise that never achieve the cause-andeffect impact and critical mass required to affect broad business outcomes. Accenture believes that companies wanting to compete more aggressively with analytics will need to industrialize the discipline on an enterprise-wide scale, redesigning how fact-based insights get embedded into key processes, leading to smarter decisions and better business outcomes. This is the path that every sophisticated retailer must follow in order to arrive at a meaningful return on the analytics investment. It is a sobering fact that some 80 percent of retailers still appear to be in the earliest stages of the journey. The news is not all negative. Businesses today are using analytics to develop a more holistic view of the customer. As one sales executive at a UK retailer put it, “We used analysis earlier to understand our potential customer base… now we use it to understand each customer’s needs, in order to personalize the services we can offer.” With greater access to multiple channels, there is a greater need to manage all these channels. Mobile technology and the web have driven companies to need analytics, not just to want it. All these forces are driving demand for smarter decision making. Using data to delve deeper in consumer priorities and preferences has enabled companies to be smarter in recognizing each customer as a “market of one,” and of customizing key decisions accordingly.
  12. 12. 12 Seamless Analytics Connecting Actions with Outcomes Establishing the linkage between data analysis and decision making with the outcomes predicated by analytics is proving to be a more difficult task for many than data collection or data integration. The clear remedy is to develop an enterprisewide analytical capability, where the pieces integrate to solve strategic business problems. This requires more effort, but the enterprisewide results in revenue growth, profitability, return on capital, customer value and other measures of value, make the effort worthwhile. The smartest businesses are creating a virtuous feedback loop that lets them collect data, analyze the data, harvest insights and then make decisions and respond in an increasingly agile style (see “Closing the Loop”). More Strivers than Clear Winners on the Journey to ROI While a clear majority of retailers (56 percent) report some degree of satisfaction with analytics, only three in ten retailers (30 percent) state that they are “very” satisfied with the outcomes they have realized as a result of their analytics investment. Significantly, 44 percent are either not very satisfied, not at all satisfied or don’t know. Why are less than half the practitioners surveyed not seeing the ROI (Return on Investment) they expected? Some may be focused on the wrong results, as witnessed in this statement from a retail executive in the U.S: “We expect to generate store-for-store growth and we are organically growing the stores that already exist today. Closing the Loop Questions on Key Metrics Business Review Cycles Enterprise MGMT Analytics Commercial MGMT Analytics Operations MGMT Analytics Insight Generation Analytics COE CORE ANALYTICS FUNCTIONAL ANALYTICS CROSS-FUNCTIONAL ANALYTICS Technology Enablers Value Realization BI and Packaged Workbench Root Cause Analysis Tools Execution Statistical Models Optimization Tools Insight Validation We are improving the assortments and improving the customer satisfaction and driving more business in each one of the stores. We just have a bit more to go before seeing true ROI.” It appears that this company could be focused almost exclusively on traditional metrics such as same-store growth, while possibly overlooking the growth than can come through multi-channel customer metrics. An executive at another company may be waiting for a day that might never arrive: “We are well aware that the implementation and use of relevant skills and technology will take time. Only when everything gets streamlined can we expect significant return on investment.” One wonders what the timeline for everything to get streamlined actually is. Many retailers may be measuring too many things that don’t matter, without putting sufficient focus on those that do. They establish a large set of metrics, but are often lacking a causal mapping of the key drivers of their business. Accenture studies show that only 20 percent of organizations claiming to have a good performance management capability have any proven causal link between what they measure and the outcomes they are intending to drive.
  13. 13. Seamless Analytics 13 STORE 1 Two major grocery retailers merged their operations 2 They united a strong footprint in North America with a presence in other markets around the world 3 Their online operations were minuscule compared with their brick-andmortar businesses 4 They aim to use analytics to build their online business and to shape a seamless experience Retailer Case in Point: Insightful Grocers Two major grocery retailers merged their operations, uniting a strong footprint in North America with a presence in other markets around the world. Both went to market via well-established discount brands, but their online operations were miniscule compared with their brick-and-mortar businesses. The merged enterprise expects to achieve cost efficiencies, enabling it to use analytics to build its online business and to shape a seamless experience so that it can sell to customers wherever they are, whenever they want to buy. As an IT executive stated: “Right now, industry growth online is strong and should continue for the next several years while same store sales are level. We had to find a way to get into the online game, or risk being overwhelmed. So all our resources are now focused on building that seamless customer experience across our stores and online.” Recognizing that online grocery shopping offers unmatched convenience and can be a profitable operation in highly concentrated urban areas, the enterprise prioritized the redesign of the architecture supporting e-commerce operations. Analytics is being used to gain insight into the strongest elements of the established brand identities so that everything can be unified under a single powerful brand, and the customer experience will be consistent regardless of channel. Equally important, the combined company is convinced that personalization can have disruptive consequences, so analytics are also being used to develop customer-level metrics and track profit per household, rather than profit per square foot of retail space. With the insights gained from this data, customer marketing initiatives are being adapted to achieve personalized interaction and a faster, more focused customer experience overall. The enterprise recognizes the on-going importance of understanding individual shoppers in context and across channels, especially given the rapidly changing retail landscape. Analytics will continue to be used to trigger personalized messages and marketing campaigns. Customer data will also be mined to yield additional insights that can drive dynamic programs including marketing, customer retention, and behavioral targeting. Right now, industry growth online is strong and should continue for the next several years while same store sales are level. IT executive
  14. 14. 14 Seamless Analytics Shaping the Seamless Customer Experience Data alone won’t get the job done. Neither will isolated islands of analytics across the company. Accenture believes it is imperative to focus on business outcomes, infuse insights into operations, embedding analytics into business processes in a robust, industrialized way, and generating the right action recommendations, to the right role at the right time. When retailers routinely start making data-driven and analytics-supported decisions with the seamless customer experience in mind, they will increasingly see the impact in their bottom line. High-performing companies make analysis an integral part of everyday business processes—the methods by which work gets done and value is created. Developing a repeatable decision making process that leverages data and analytical methods should be a high priority for every organization interested in analytics. Once analytics has been embedded into management processes and decision making, industrializing this virtuous cycle, practitioners then must have the courage to ask, “Did we achieve the outcomes we want?” If the answer is no, refocus and try again, learning as you go. The promise of analytics is expansive: data-based decisions, leading to clear business outcomes, yielding a measurable return on investment. Even though the business discipline is still developing, what is the verdict? Positive, but cautiously so, suggesting that some enterprises are successfully leveraging the power of analytics within and across functions, while others are still struggling to see a meaningful ROI. When retailers routinely start making data-driven and analyticssupported decisions with the seamless customer experience in mind, they will increasingly see the impact in their bottom line. The promise of analytics is expansive Data-based decisions Clear business outcomes Measurable ROI
  15. 15. Seamless Analytics 15 About This Research The findings contained in this report are based on 100 telephone interviews undertaken during August and September 2012 among Director-level executives and equivalent managers within large retailers (1,000+ employees) located in the U.K. and U.S. who have knowledge and/or responsibility for analytics within their organization. Consumer goods brands with retail outlets were excluded from the survey. To obtain a full summary of the survey data and findings, contact Accenture Analytics at About Accenture Analytics In the field of analytics, Accenture delivers insight-driven outcomes at scale to help organizations improve performance. Our extensive capabilities range from accessing and reporting on data to advanced mathematical modeling, forecasting and sophisticated statistical analysis. We draw on over 12,000 professionals with deep functional, business process and technical experience to develop innovative consulting and outsourcing services for our clients in the health, public service and private sectors. For more information about Accenture’s work in analytics, visit About Accenture Accenture is a global management consulting, technology services and outsourcing company, with approximately 275,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. Through its Skills to Succeed corporate citizenship focus, Accenture is committed to equipping 500,000 people around the world by 2015 with the skills to get a job or build a business. The company generated net revenues of US$28.6 billion for the fiscal year ended Aug. 31, 2013. Its home page is
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