BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

Transcription

1 BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION EXECUTIVE BRIEFING The enterprises leading the way in data analytics are demonstrating an enormous capability to capture, process, scale and make available data to their organizations and across their networks of customers, partners and suppliers. But is this enough? The challenge is to develop this data into insights that can be applied to increase business value moving from data to insight to action. Executives say there is a direct correlation between well-designed analytics programs and success in the marketplace. However, while many executives are embracing customer data analytics to guide their businesses, the infrastructures and processes they require to support and sustain such efforts still lag. These are the findings of a new survey of 105 executives of large global organizations, conducted by Forbes Insights in partnership with SAS, which explores the depth of their embrace of data analytics. The survey finds that while half of large enterprises (with $500 million or more in annual revenue) have tightly integrated customer data analytics into their key processes, there are many areas that are still works in progress. KEY FINDINGS FROM THIS SURVEY INCLUDE THE FOLLOWING: Half of large enterprises are still in the learning stages of customer analytics, and are in the process of applying these analytics to enhance their customer experience. The results of such efforts, no matter how nascent, are encouraging. A majority report positive results with the data analytics they have applied so far. There s a strong push to enable real-time insights from customer data. Most of the advanced analytics enterprises now have real-time capabilities and seek to apply them across all channels. Predictive analytics is the advantage most companies are seeking in their analytics initiatives; a majority report they are already seeing better engagement with customers. The greatest challenges to insightful analytics lie in the conversion of ongoing initiatives into repeatable processes. Measuring the results of such efforts also is a challenge. While executives report progress in programming, application development and data acquisition, there is still much work to be done in other phases of the analytics lifecycle such as analysis design, presentation and integration into customer channels. A majority of even the most advanced enterprises do not consider key departments or business areas to be highly proficient yet in data analytics. Even marketing and IT departments lag. IN ASSOCIATION WITH:

2 ALIGNMENT AND STRATEGY Half of large enterprises are still in the learning stages of customer analytics, and they are in the process of applying these analytics to enhance their customer experience. The results of such efforts, no matter how nascent, are encouraging. A majority report positive results with the data analytics they have applied so far. While the survey group consisted of significantly large organizations that presumably have significant resources, at least half consider their customer analytics experiences to still be works in progress. Close to one in five admit that such efforts are fragmented or even non-existent. Fifty percent of the executives responding to the survey report their enterprise analytics is well aligned with their efforts to reach customers. Another 46% are still working toward this goal (Fig. 1). For purposes of this survey, these two groups will be identified as Leaders and Learners (those able to provide a superior customer experience through analytics versus those with less-developed efforts). The industry groups with the highest percentage of respondents identifying themselves as Leaders include manufacturers and technology providers (Fig. 2). 1 IN YOUR EFFORTS TO BECOME A MORE CUSTOMER-CENTERED BUSINESS, WHICH OF THE FOLLOWING STATEMENTS HOLDS TRUE FOR YOUR ORGANIZATION? We provide a superior customer experience through a well-developed and designed enterprise data analytics effort We are rapidly and systematically developing data analytics capabilities to improve our customer experience 1 % 14 % 3 % We have data analytics capabilities in many parts of the organization, and are beginning to apply these analytics to improve the customer experience We are not using analytics for customer experience We are still working on developing data analytics and have difficulty providing consistent customer experience 32 % 50 % 2 PROVIDE SUPERIOR CUSTOMER EXPERIENCE THROUGH ANALYTICS BY INDUSTRY GROUP Manufacturing/industrial products/automotive 66 % Technology/software/systems Banking/insurance/financial services Consumer products/retail Healthcare/ pharmaceuticals 21 % 33 % 50 % 63 % 2 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

3 No one argues that data analytics has a positive impact on enterprises ability to deliver value to their customers. A majority of executives, 54%, see a direct correlation between their use of data analytics and delivering a positive customer experience. Another 41% say their efforts aren t there yet, but are moving in a positive direction or have potential (Fig. 3). Almost all of the Leaders identified in the survey again, those reporting the delivery of superior customer experiences through well-developed and well-designed data analytics say analytics is delivering this for them. Only one in four of the Learners have reached this point yet (Fig. 4). 3 TO WHAT ROLE HAS DATA ANALYTICS PLAYED IN YOUR ORGANIZATION S ABILITY DELIVER A SUPERIOR CUSTOMER EXPERIENCE? Data analytics has had an extremely positive impact on our customer experience Data analytics has pushed the needle in a positive direction 8 % 5 % Data analytics has shown potential in areas where it has been applied Data analytics has not played a significant role yet 32 % 54 % 4 DATA ANALYTICS HAS HAD EXTREMELY POSITIVE IMPACT ON ABILITY TO DELIVER SUPERIOR CUSTOMER EXPERIENCES LEADERS VERSUS LEARNERS Leaders 85 % Learners 25 % COPYRIGHT 2016 FORBES INSIGHTS 3

4 REAL-TIME POSSIBILITIES There s a strong push to enable real-time insights from customer data. Most of the advanced analytics enterprises now have real-time capabilities, and many seek to apply them across all channels. There are some essential capabilities that are now being delivered as part of customer analytics, among both advanced organizations as well as those in the development stages. The ability to translate data points into customer usage patterns and preferences is a key area, as is the ability to provide sales projections. Predictive analytics is also an up-and-coming capability. Real-time analytics the ability to see and respond to transactions or customer actions as they happen is also seen across many enterprises in the survey. Among enterprises leading the way in data analytics, there s a strong push for real-time capabilities. Half of the Leaders in the survey are employing real-time customer engagement, as are 45% of the Learners. The enterprises with more advanced analytics efforts are more likely than their less developed counterparts to be engaged in real-time sales tracking 56% of the Leaders, versus 38% of the Learners. A majority of the Leaders also are employing realtime visibility into the Internet of Things (machine and sensor tracking) and social media, versus one in four of the Learners. Overall, customer usage and preferences, along with sales projections, are the two areas that are seeing the most applications with data analytics (Fig. 5). The ability to deliver insights and respond quickly at the moment when customers are engaging with a channel is the next great frontier for organizations. One of the challenges in analytics today is moving to a more real-time environment, says John Carpenter, senior director of enterprise marketing solutions with Sirius XM Radio, Inc. We eliminated what was ultimately a three-to-four-day delay with respect to our data, to understanding where the customer is on their journey, what experiences they have with our brand, and trying to move that to a more real-time dialog with them. 5 YOUR IN WHICH AREAS HAVE DATA ANALYTIC CAPABILITIES BEEN PUT INTO ACTION WITHIN ENTERPRISE? ALL LEADERS LEARNERS Customer usage and preferences 51% 58% 45% Sales projections 50% 50% 51% Predictive analytics 49% 54% 43% Real-time customer engagement 48% 50% 45% Financial planning and analysis 47% 48% 45% Real-time sales tracking 47% 56% 38% Customer profitability/lifetime value 47% 56% 38% Contract/supplier management 46% 44% 47% Customer behavior next-best action 43% 46% 40% Real-time supply chain/inventory/distribution tracking 43% 44% 42% Real-time machine and sensor data tracking 41% 54% 28% Real-time social media tracking 38% 52% 25% Experiments/pilots/market tests 33% 35% 32% Portfolio risk 28% 37% 19% Fraud detection 28% 27% 28% 4 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

5 Real-time data collection and insights are becoming a critical component of data-driven customer experiences. Close to half of the executives in the survey say they are working with real-time data on their customers, available across all channels (Fig. 6). Seven in 10 of the Leaders in the survey have a highly integrated approach within their domains, versus less than one in four of the Learners (Fig. 7). Among industry groups, manufacturing leads the way, with two-thirds of executives in this group reporting that all channels leverage real-time customer data (Fig. 8). 6 WHAT IS THE SOURCE OF THE DATA HOW WELL INTEGRATED IS YOUR CUSTOMER DATA ACROSS CHANNELS? (IN-PERSON, CALL CENTER, WEB, MOBILE, ETC.) All channels leverage the same customer data in real time All channels leverage the same customer data, with some delay 22 % 1 % Channels leverage different datasets 47 % Other 29 % Note: Does not add to 100% due to rounding. 7 HIGHLY INTEGRATED ENTERPRISES BY INDUSTRY GROUP Manufacturing/industrial products/automotive 66 % Technology/software/systems Consumer products/retail Banking/insurance/financial services Healthcare/pharmaceuticals 33 % 31 % 29 % 50 % 8 HIGHLY INTEGRATED ENTERPRISES LEADERS VERSUS LEARNERS Leaders 71 % Learners 23 % COPYRIGHT 2016 FORBES INSIGHTS 5

6 RESULTS HOPED FOR, RESULTS SEEN Predictive analytics is the advantage most companies are seeking in their analytics initiatives; a majority report they are already seeing better engagement with customers. Executives were asked to describe the benefits they hope to achieve, as well as the benefits actually seen. Predictive analytics is coming to the fore as an important aspect of data analytics, and an area that executives hope to see deliver greater insights. Executives say the use of data analytics is helping them to more accurately predict what their customers are going to need and want, thus providing them a more complete or unified view of their customers. The use of analytics to improve the customer experience is also seen as an important goal (Fig. 9). 9 VIEW WHAT BENEFITS CAN BE GAINED FROM ACHIEVING A MORE COMPLETE OR UNIFIED OF THE CUSTOMER? More accurately predict customer needs and desires 63 % Improved customer experience/service Greater feedback for product/service innovation Greater ability to target and optimize for specific customer Achieve higher conversion rates Create and automate multichannel interactions 36 % 28 % 60 % 55 % 52 % 6 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

7 What have been the actual benefits achieved so far? Data analytics initiatives have been successful in bringing many enterprises closer to their customers, with a majority reporting greater engagement and more insight (Fig. 10). A number of executives report they are seeing internal advantages emerge as well, which helps strengthen their teams and offerings. While most industry groups cite outward-facing benefits such as greater engagement with customers as the greatest advantage seen, manufacturers are more focused on internal improvements. They report their greatest improvements have been seen on an inward-facing basis with greater management confidence in decision making and more departmental collaboration (Fig. 11). 10 WHAT BENEFITS IS YOUR ORGANIZATION GAINING FROM DATA ANALYTICS SO FAR? Greater engagement with customers Better insight into and a common enterprise view of customers Decision making is faster Greater collaboration between departments Managers and employees are more confident about their decisions Increased sales/revenues Cost savings/more effective use of marketing spend Able to more quickly react to market changes More repeat business from customers Able to test and develop more innovations in our products and services 3 % Unsure we are not able to measure the impact yet 53 % 51 % 46 % 46 % 46 % 41 % 41 % 40 % 35 % 38 % COPYRIGHT 2016 FORBES INSIGHTS 7

8 11 TOP BENEFITS SEEN BY INDUSTRY GROUP TECHNOLOGY/SOFTWARE/SYSTEMS Better insight into and a common enterprise view of customers 88 % Decision making is faster 75 % CONSUMER PRODUCTS/RETAIL Greater engagement with customers 44 % Greater collaboration between departments 44 % MANUFACTURING/INDUSTRIAL PRODUCTS/AUTOMOTIVE Managers and employees are more confident about their decisions 50 % Greater collaboration between departments BANKING/INSURANCE/FINANCIAL SERVICES 47 % Greater engagement with customers 75 % Better insight into and a common enterprise view of customers 56 % HEALTHCARE/PHARMACEUTICALS Greater engagement with customers Better insight into and a common enterprise view of customers More repeat business from customers Cost savings/more effective use of marketing spend 43 % 43 % 43 % 57 % 8 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

9 Where is the data coming from to help shape the customer experience? There are many ways to get at information, as identified in the survey. Customer databases are the most prominent sources of data that are delivering customer intelligence. A majority also are leveraging data coming in from emerging digital channels such as the web or social media to better understand and act on customer requirements. CRM and point-of-sale systems are also popular data sources (Fig. 12). The ability to gather data may vary considerably from industry to industry (Fig. 13). Consumer products organizations and retailers say point-of-sale data is the most important to building customer profiles, while technology companies rely on call center interactive data. For some industries, the ability to ascertain customer or audience preferences may be even more challenging. On our streaming platforms we have granular listening behavior available; however, for satellite delivery we don t always know what content is being listened to, says Carpenter. The solution, Carpenter continues, is to develop insights from data that is available to know and predict audience preferences such as contests and click-throughs to specific content. If we send out an newsletter with several blocks of content and the subscriber clicks on the Britney Spears content, for example, we can assume the subscriber likes pop music. Carpenter s team also conducts analysis against social media data to infer listener preferences. We are a media business, so content is king. We have a lot of original content, so we want to make sure we appropriately market it. We do quite a bit of analysis on that. 12 WHICH OF THE FOLLOWING DATA SOURCES ARE ESSENTIAL TO GAINING INTELLIGENCE ON THE CUSTOMER EXPERIENCE? Customer databases 70 % Digital channels (website, mobile, apps, etc.) CRM systems Point-of-sale systems Social media sites Call centers Preference centers Third-party systems 37 % 31 % 58 % 57 % 57 % 52 % 49 % COPYRIGHT 2016 FORBES INSIGHTS 9

10 13 TOP DATA SOURCES BY INDUSTRY GROUP MANUFACTURING/INDUSTRIAL PRODUCTS/AUTOMOTIVE Customer databases 79 % Digital channels TECHNOLOGY/SOFTWARE/SYSTEMS Call centers CRM systems Customer databases 61 % 63 % 63 % 75 % BANKING/INSURANCE/FINANCIAL SERVICES CRM systems 69 % Customer databases CONSUMER PRODUCTS/RETAIL Point-of-sale systems CRM systems Digital channels HEALTHCARE/PHARMACEUTICALS Customer databases Digital channels 69 % 56 % 44 % 44 % 64 % 50 % 10 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

11 CHALLENGES AND PAIN POINTS The greatest challenge to insightful analytics is the conversion of ongoing initiatives into repeatable processes. Measuring the results of such efforts also is a challenge. One of the challenges to customer analytics particularly within large organizations with multiple units and departments is the ability to scale analytic successes. Often, such efforts are undertaken and delivered by small analytics teams who applied their solutions against one particular business problem. Repeating that success many times over across the business is another story. Difficulty turning isolated insights into repeatable processes that benefit the whole enterprise, converting what are often one-off efforts into repeatable processes, as well as difficulty measuring the results of their work, are the key challenges to analytics at this time (Fig. 14). Lack of visibility and a lack of communication between sites and stakeholders also add difficulties to efforts to develop insights from data. 14 WHAT ARE THE CHALLENGES TO OPERATIONALIZING ANALYTIC INSIGHTS WITHIN YOUR ORGANIZATION? Difficulty turning isolated insights into repeatable processes that benefit the whole enterprise 27% Difficulty measuring direct impact of data analytics 27% Not enough visibility for business users into key data sources 26% Not enough communication between analysts, business users and other stakeholders 25% Incomplete back-end data integration 24% Lack of incentives or misaligned incentives for acting on insights 24% Still working on platform infrastructure integrity and security 23% Still trying to understand data-to-insight processes 23% Lack of collaborative environment and systems to ensure that analytics are solving the right problem 21% Need for greater visualization and dissemination 20% No (or incomplete) systematic approach to data management 17% Underdeveloped analytical models 17% Not fully evolved to a shared analytics organization 13% No significant challenges that we re aware of 4% COPYRIGHT 2016 FORBES INSIGHTS 11

12 The challenges vary as organizations gain maturity in data analytics skills. For Learners, the top challenge cited is trying to understand the data-to-insights process, and how it can be applied within their organizations. Among the advanced data analytics companies, the ability to measure the impact of their efforts takes prominence (Fig. 15). For many enterprises even those with highly advanced data-to-insights initiatives the nature of their markets may pose additional challenges. Some companies reside within complex, digital ecosystems in which data may flow from numerous sources. For example, a broadcast media company such as Sirius XM Radio has a number of customer channels with which it needs to engage and understand. Social media is also a significant source for listening preference, Carpenter says. There are individual channels at SiriusXM that have pages, and in addition, individual SiriusXM talent and hosts with their own well-trafficked pages as well. Our customers are interacting with all of that. 15 TOP 3 CHALLENGES LEADERS VERSUS LEARNERS LEADERS Difficulty measuring direct impact of data analytics 37% Not enough communication between analysts, business users and other stakeholders 31% Still working on platform infrastructure integrity and security 29% LEARNERS Still trying to understand data-to-insight processes 30% Difficulty turning isolated insights into repeatable processes that benefit the whole enterprise 28% Not enough visibility for business users into key data sources 26% 12 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

13 BACK-END BLUES While executives report progress in programming, application development and data acquisition, there is still much work to be done in other phases of the analytics lifecycle such as analysis design, presentation and integration into customer channels. While the survey finds a great deal of progress in applying analytic insights to advancing customer relations and retention, there is still a great deal of work that needs to be done at the back end. Executives consider their data analytics efforts to be the most highly advanced at the front-end stages of the process programming, application development and data acquisition (Fig. 16). While the leading enterprises identified in the survey are well along in application development, most have not fully developed other aspects of their operations. For example, fewer than half consider themselves to be highly advanced in the data collection process, while only one-third are highly proficient in data management or data analysis design. For those organizations still building their capabilities (the Learners), many of these important milestones in analytics development have yet to be reached. For most of these milestones, less than one in 10 executives would say they are truly ready to deliver insights through their data. 16 ON A SCALE FROM 1 TO 5 WHERE 1, IS NOT MATURE AND 5 IS HIGHLY ADVANCED, PLEASE RATE HOW FAR YOUR ORGANIZATION HAS ADVANCED INTO THE FOLLOWING STAGES OF DATA ANALYTICS DEVELOPMENT. Percentage of executives reporting their organizations are highly advanced (rating of 5 ): ALL LEADERS LEARNERS Programming/application development 32% 54% 11% Data acquisition/collection 31% 44% 19% Data preparation/management 22% 33% 11% Analysis design 21% 33% 9% Data analytics 21% 35% 8% Visualization/presentation 19% 33% 6% Integration of insights into customer channels 16% 25% 8% Integration of insights into key customer-facing and marketing processes 18% 27% 9% Predictive analytic environment 16% 29% 4% Ongoing management and monitoring of all models 19% 31% 8% Data architecture 11% 21% 2% COPYRIGHT 2016 FORBES INSIGHTS 13

14 LAGGING BEHIND A majority of even the most advanced enterprises do not consider key departments or business areas to be highly proficient yet in data analytics. Even marketing and IT departments lag. Along with the analytics capabilities that still need development among even the most advanced enterprises, many of the departments or business units of these enterprises are still not fully prepared. Overall, customer relationship management is the most wellpositioned area of the business to move forward with data analytics, the survey finds. Close to one-third of executives consider their CRM functions to be highly proficient giving them the highest ratings of any department or area when it comes to enterprise data analytics (Fig. 17). However, it s notable that for the most part, a majority of even the most advanced enterprises do not consider key departments or business areas to be highly proficient in data analytics. Just under half say their CRM areas are on top of their game, while two in five feel their content production areas are highly proficient. Tellingly, only just over one-third consider their marketing and IT departments to be highly proficient to deliver data analytics capabilities and these are often the two departments that will be most involved. There has been notable progress in putting data in a place where it can be easily accessed by end-users or applications. One of the important aspects of a data analytics-to-insights initiative is the ability to have all the right data available at the right time to the right decision makers. A majority of organizations, 58%, report that the majority of their enterprise information is now readily accessible within a well-integrated presentation layer or format (Fig. 18). This is particularly pronounced among the Leaders in the survey, of whom 73% report a majority of their enterprise information is now widely accessible, versus 44% of the Learners (Fig. 19). Technology, consumer products and manufacturing companies also lead the way in information accessibility (Fig. 20). 17 ON A SCALE FROM 1 TO 5, WHERE 1 IS NOT PROFICIENT AND 5 IS HIGHLY PROFICIENT, PLEASE RATE THE PROFICIENCY OF THE FOLLOWING DEPARTMENTS OR FUNCTIONAL AREAS OF YOUR ORGANIZATION WITH DATA ANALYTICS. Percentage of executives reporting their departments/areas are highly proficient (rating of 5 ): ALL LEADERS LEARNERS Customer relationship management 32% 48% 17% Content production/management 28% 42% 13% Marketing 28% 37% 19% Information technology 28% 37% 19% Production 27% 37% 17% Sales 27% 38% 15% Finance/accounting 24% 31% 17% Human resources 24% 35% 13% Supply chain/inventory 24% 35% 13% Branch offices 13% 21% 6% 14 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

15 18 HOW MUCH OF YOUR ENTERPRISE INFORMATION IS NOW READILY ACCESSIBLE TO DECISION MAKERS IN A SINGLE, HIGHLY INTEGRATED PRESENTATION LAYER OR FORMAT? Little to none 2 % 1%-25% 9 % 51%-75% 30 % 44 % 26%-50% 76%-100% 1 % Don t know/unsure 14 % 19 MOST ENTERPRISE INFORMATION ACCESSIBLE TO DECISION MAKERS LEADERS VERSUS LEARNERS Leaders 73 % Learners 44 % 20 MOST ENTERPRISE INFORMATION ACCESSIBLE TO DECISION MAKERS BY INDUSTRY GROUP Technology/software/systems 75 % Consumer products/retail Manufacturing/industrial products/automotive Banking/insurance/financial services Healthcare/pharmaceuticals 44 % 36 % 66 % 66 % COPYRIGHT 2016 FORBES INSIGHTS 15

16 DEMOGRAPHICS 21 RESPONDENTS TITLES CIO/CTO/Technology executive 46% CEO/President 16% Senior Director/Director 10% COO/Operations executive 7% Other C-level executive or General Manager 5% CFO/Treasurer/Comptroller 4% SVP/VP 4% Line of Business head 4% Chief Analytics Officer 3% Chief Data Officer 1% CMO/Marketing executive 1% 22 RESPONDENTS ROLES Customer service/support 81% Customer experience 74% IT/Security 74% Corporate management 61% Operations 59% Strategy 42% Sales 37% Marketing 37% Finance 31% 16 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

17 23 RESPONDENTS ORGANIZATIONS BY REVENUES $500 million - $999.9 million 31% $1 billion - $4.9 billion 28% $5 billion - $9.9 billion 14% $10 billion - $49.9 billion 21% $50 billion or more 6% 24 RESPONDENTS ORGANIZATIONS BY INDUSTRIES Manufacturing/industrial products 35% Financial services/asset management 10% Healthcare 10% Consumer products/retail 9% Technology (software, systems) 8% Energy (oil & gas, power & utilities, mining) 6% Services (business or consumer) 5% Banking 4% Media & entertainment 3% Pharmaceuticals/life sciences 3% Public sector/government 2% Telecommunications 2% Insurance 2% Automotive 1% Other 2% 25 RESPONDENTS LOCATIONS North America 32% Europe 30% Asia/Pacific Rim 29% Rest of world 10% COPYRIGHT 2016 FORBES INSIGHTS 17

18 CONCLUSION Organizations have only begun the process of enriching their customers experiences, whether it is through direct face-to-face contact, by phone call, web or mobile app. Even among significantly sizable organizations, efforts to employ data analytics to better understand customers and improve the customer experience are still in their infancy stages. While there has been progress in building out front-end capabilities, many organizations still do not have a full picture of their customers across their myriad of back-end systems. As the results of this survey show, even the largest enterprises those with more than $500 million in annual revenues are still in the learning stages of applying data analytics to customer experiences. Half of the executives surveyed admit that such initiatives are still under development. At the same time, where data analytics has been applied, the results have been extremely positive. While typical customer data analytics has focused on historical, after-the-fact insights, enterprises are seeking the ability to manage experiences as they happen and be able to provide for customer needs in a proactive fashion. Customer analytics is moving to real-time and predictive modes. Most of the advanced analytics enterprises now have real-time capabilities. In addition, predictive analytics is the advantage most companies are seeking in their analytics initiatives; a majority report they are already seeing better engagement with customers. However, while success has been seen in the projects or scenarios in which customers analytics has been applied, these efforts may be too narrow, or the result of specific projects. The challenge now is enabling these efforts to scale across the enterprise, in an automated, repeatable fashion. In many cases, while data analysts or specialists may be delivering customer analytics capabilities, key areas of the business such as marketing, customer relations or IT need to be brought deeper into the process. 18 EXECUTIVE BRIEFING: BLAZING THE TRAIL FROM DATA TO INSIGHT TO ACTION

19 ABOUT FORBES INSIGHTS Forbes Insights is the strategic research and thought leadership practice of Forbes Media, publisher of Forbes magazine and Forbes.com, whose combined media properties reach nearly 75 million business decision makers worldwide on a monthly basis. Taking advantage of a proprietary database of senior-level executives in the Forbes community, Forbes Insights conducts research on a host of topics of interest to C-level executives, senior marketing professionals, small business owners and those who aspire to positions of leadership, as well as providing deep insights into issues and trends surrounding wealth creation and wealth management. FORBES INSIGHTS Bruce Rogers Chief Insights Officer Erika Maguire Director of Programs EDITORIAL Kasia Wandycz Moreno, Director Hugo S. Moreno, Director Joe McKendrick, Report Author Dianne Athey, Designer SALES North America Brian McLeod, Commercial Director bmcleod@forbes.com Matthew Muszala, Manager William Thompson, Manager EMEA Tibor Fuchsel, Manager APAC Serene Lee, Executive Director RESEARCH Ross Gagnon, Director Kimberly Kurata, Research Analyst 499 Washington Blvd., Jersey City, NJ