ANALYTICAL ENABLEMENT

Transcription

1 ANALYTICAL ENABLEMENT HOW LEADERS HARNESS DISTRIBUTED BUSINESS INTELLIGENCE TO DRIVE BREAKTHROUGH RESULTS The most successful business intelligence programs feature processes that place analysis and decision-making solutions in the hands of business units. FOREWORD Most executives are well aware of the degree to which business intelligence (BI), the harnessing of data to enable sophisticated analysis, can lead to improved business insight. Moreover, most executives are likely aware of the overall trend toward greater access to enterprise data. Salespeople use the cloud and mobile technologies to access inventories and pricing. Field engineers share site visit reports via tablets. And in BI, the trend is toward providing more and more data and data analysis solutions to more and more business executives and front-line teams. But what most executives may not realize is the profound correlation between the rise of such distributed BI programs and stronger business performance: the greater the degree of self-service, the more the data is shared into the hands of those who need it, the more successful the BI environment. Certainly, there are reasons for some degree of centralized control. Indeed, IT departments and business unit heads alike are concerned about data governance issues affecting everything from data security to its completeness and veracity. But the advantages of a more distributed environment are so compelling that companies using cooperation, innovation and the latest BI solutions are finding that effective data governance and broader data sharing can work hand in hand. What are the benefits of a distributed approach to BI? For one thing, this puts data and analysis capabilities in the hands of those closest to business challenges and opportunities. Such business users are not only certain to possess keen insight into their activities, but since they hold bottom-line accountability, they are also the most likely to be highly motivated to seek enhanced business performance. But the benefits by no means end there. Businesses report everything from greater responsiveness to a shift from static to forward-looking analysis, and even enhanced visual presentations, which lead to clearer understanding and sharper insight. As the below research demonstrates, leaders, or those with the most effective BI programs, tend to have a significantly higher degree of distributed, self-service elements. Based on what we re observing, we predict the trend toward such an approach can only accelerate in the future. Bruce Rogers Chief Insights Officer, Forbes Media IN ASSOCIATION WITH:

2 EXECUTIVE SUMMARY The most successful business intelligence (BI) programs feature processes and solutions that place analysis and decision-making tools in the hands of business units (self-service or distributed BI). The majority of respondents, 53%, say their overall BI programs are already delivering either significant (3) or very significant benefits (7%). But this figure climbs to 87% among leaders, a group shown to exhibit significantly higher degrees of self-service. In a distributed BI environment, data governance protecting its integrity, reliability, completeness and security can still be maintained by a central IT or BI function. Moreover, a central BI team can still play a critical, or even leading, role in assisting executives throughout the firm with analysis and perhaps the development of fundamental dashboards. But the difference is one of enablement versus control. In a distributed environment, business units themselves have a greater degree of self-service access to both data and analytical solutions. In other words, those executives closest to the day-to-day business arguably those with the most motivation to drive business improvement and the keenest intuitive insight have greater freedom to model, explore and examine data at their fingertips. Distributed models deliver greater faith in the data. Business units often express concern regarding the veracity, reliability and completeness of the data at their disposal. Here, the Forbes Insights survey demonstrates that the more distributed capabilities are at work, the more satisfied organizations become in terms of key aspects of their data. Benefits from distributed data environments include greater effectiveness in identifying business opportunities, pricing, gauging productivity, optimizing sales and marketing spend to name only a few. Today and also likely in the next 8 months, the most frequently cited form is internal biometric often associated with time/motion studies. But going forward, companies will increase their use of a wide range of data, including device-generated (or Internet of Things IoT), third-party open source/ government-provided, and social media. Executives welcome the benefits of a self-service model: 73% say improving data visualization is a strategic imperative; 63% agree self-service data analysis models create a significant competitive advantage; and 63% believe distributed self-service enables end-users to develop more visually compelling analysis. Most initiatives (64%) are driven by a combination of senior management direction and bottom-up, organic activity. Key challenges include integrating data from multiple sources, ensuring data security and working with IT to enable access to needed data. Nonetheless, 57% of companies plan to accelerate investment in distributed BI capabilities. Future directives include enabling business units to interact with more forms of corporate and external data, expanding training for executives, as well as providing greater mobile and cloud access to needed data streams. Over half of companies, 54%, say they are also pursuing the creation of a center of excellence to improve their distributed data performance (rising to 68% among leaders). 2 ANALYTICAL ENABLEMENT

3 THE AGE OF ANALYTICAL ENABLEMENT The fact that corporations around the world are embracing business intelligence (BI) should come as no surprise. As you d imagine, the advanced analytics developed by worldclass BI practitioners leads to deeper insight and significantly enhanced performance. But decidedly newsworthy is the degree to which the most successful BI programs are migrating toward a self-service, distributed BI delivery model a sort of analytical enablement. DEFINITIONS Business Intelligence and analytics: An umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. Self-Service or Distributed BI: A condition where data and analytical solutions are made available to, and can be modeled and analyzed by, business units themselves in the course of their decision making. Source: Gartner, Market Opportunity Map for Business Intelligence and Analytics, Worldwide, Jim Hare et al, 7 March 206 As our global survey of 449 senior IT and business professionals reveals (see Methodology), the most successful BI programs are significantly more likely to feature a distributed model for analysis. That is, among those firms self-described as having expert-level, seven out of 0 (69%) say their programs feature a significantly higher degree of distributed capabilities relative to the overall sample. This expert group, referred to as leaders throughout this report, also tends to derive significantly greater benefit from its BI initiatives. Most executives are familiar with BI and have programs in place. However, some may need a bit more background on what is meant by a distributed model for BI. The term distributed in this context describes a condition where data is made available to, and can be modeled and analyzed by, business units themselves. Overall, 52% of respondents say their BI environment features a significant (4%) or very significant degree (%) of distributed elements rising to 69% among leaders. Note that in a distributed BI environment, data governance protecting its integrity, reliability, completeness and security can still be maintained by a central IT or BI function. Moreover, a central BI team can still play a critical or even leading role in assisting executives throughout the firm with analysis and perhaps the development of fundamental dashboards. But the difference is one of enablement versus control. In a distributed environment, business units themselves have a greater degree of self-service access to both data and analytical solutions. In other words, those executives closest to the day-to-day business arguably those with the most motivation to drive business improvement and the keenest intuitive insight have greater freedom to model, explore and examine data at their fingertips. COPYRIGHT 206 FORBES INSIGHTS 3

4 IN TERMS OF BI CAPABILITIES WHAT IS YOUR LEVEL OF EXPERTISE? 5 LEADERS (FAR ABOVE AVERAGE) 4 ADVANCED (ABOVE AVERAGE) 34% 3 AVERAGE 37% 2 BELOW AVERAGE 0% FAR BELOW AVERAGE 3% Self assessment on a -5 scale. HOW DISTRIBUTED ARE YOUR BI INITIATIVES? Leaders are significantly more likely to pursue a distributed BI environment. Self assessment on a -5 scale. Leaders } } 5 VERY 25% % 69% 52% 4 44% 4% 3 TO SOME DEGREE 24% Overall 30% 2 4% 4% NOT AT ALL 3% 4% THE REVOLUTION IS HERE There s a global revolution under way. Business executives are no longer satisfied with the long waiting periods, high costs and questionable quality of data-driven decision support being developed on their behalf. Taking matters into their own hands, leaders are embracing a more distributed model, where end-users can take control of their own analytics, modeling, visualization and decision making. The results, say practitioners, are profound. Consider these examples: Delving into data points as diverse as trip utilization, on-time performance and customer service surveys, the U.K. s international transport-focused National Express is able to rapidly assess, adjust and optimize its menu of destinations, routes, timetables and fares. At a major insurer, after placing analysis solutions in the hands of business units, end-users overlaid dates of claims with traditional fields to identify and isolate two agents who had been falsifying claims. Analysis of device-usage data at a major U.S. bank revealed the means to reducing printing costs by over $5 million per year. At a leading provider of services to the asset management and banking industries, an accounting executive with no formal prior BI training was able to develop an array of dashboards providing insights so compelling that once shown to prospects, the firm was able to, nearly immediately, sign five new major clients. Results like these are by no means exceptional. Rather, they are becoming the norm at companies where front-line business executives, those in the right place at the right time to translate insight into action, are given the keys to drive today s most powerful analytics and decision-making platforms. 4 ANALYTICAL ENABLEMENT

5 DISTRIBUTED MODELS DELIVER STRONGER RETURNS Such enablement, the survey shows, drives performance. The majority of respondents, 53%, say their overall BI programs are already delivering either significant (3) or very significant benefits (7%). But a deeper dive reveals that the more distributed the BI environment, the greater the benefits derived from the initiatives. Nearly nine out of 0 leaders, 87%, report significant (3) or very significant (5%) benefits from BI. Recall this is a group already shown to operate with relatively higher degrees of self-service. HOW MUCH BENEFIT IS BEING GENERATED FROM YOUR BI PROGRAMS TO-DATE? Leaders, with more distributed approaches, are experiencing significantly greater benefit. Leaders Overall } } VERY SIGNIFICANT BENEFIT 5% 7% 87% 53% SIGNIFICANT BENEFIT 3 3 MARGINAL BENEFIT 0% 28% VERY LITTLE BENEFIT 3% 0% NO BENEFIT / NOT APPLICABLE 0% 0% Those describing their level of expertise in BI as expert or far above average. WHAT DRIVES THE BENEFITS? Undoubtedly, higher degrees of self-service in terms of tools and data access correlate with greater success from BI initiatives. The survey sheds light as to which elements of such an environment are most likely to be viewed as generating value. Seven out of 0 leaders (7%) say distributed solutions tend to accelerate learning and responsiveness. This is closely related to the fact that such an approach tends to place more tools in the hands of those closest to the business and its challenges a benefit cited by 68% of leaders, but only 54% of the overall sample. Other key benefits include enabling business units to develop their own dashboards, as well as creating more avenues for modeling tradeoffs/options (the pursuit of optimization) and achieving greater business optimization. The overarching point is that when executives have the right solutions and data at hand, they have greater freedom to really explore their performance and opportunities. WHAT ARE THE BENEFITS OF A DISTRIBUTED ENVIRONMENT? Accelerates learning/responsiveness Places tools in the hands of those closest to the business Enables business units to develop relevant dashboards Encourages more creative thinking/innovation Enables greater flexibility of analysis 55% Enables optimization: clearer choices between tradeoffs 45% 48% 4 54% Reveals valuable and unexpected relationships in data 50% 57% 6% Enables clearer, more intuitive visual presentation of data 5% 53% 57% 64% 64% 68% 67% Percentages = those expressing strong satisfaction (a 4 or 5 on a -5 scale). 7% Leaders Overall COPYRIGHT 206 FORBES INSIGHTS 5

6 GREATER FAITH IN THE DATA Data modelers often express concern regarding the veracity, reliability and completeness of the data at their disposal. Here, the survey demonstrates that the more distributed capabilities there are at work, the more satisfied organizations become in terms of key aspects of their data. For example, regarding both completeness and timeliness, leaders (decidedly more distributed than the overall sample), are in both cases significantly more satisfied than others. HOW SATISFIED ARE YOU WITH THE FOLLOWING ASPECTS OF YOUR DATA? Completeness Timeliness Accuracy Distribution Confidence 5% 5% 59% 60% 65% 65% 68% Percentages = those expressing strong satisfaction (a 4 or 5 on a -5 scale). 72% 72% 79% Leaders Overall KEY TRENDS POINT TO GREATER DISTRIBUTION Using five-point scales, survey respondents were asked to share how their data environments are evolving across three core continuums: nature, focus, timeliness/delivery. The resulting evidence reveals that key business needs and objectives are trending in ways that are aided by a more distributed, self-service-oriented BI framework. NATURE: SHIFTING TOWARD MORE TIMELY/FORWARD-LOOKING/PREDICTIVE: Dated/ look back Timely/ forward-looking/ predictive OVERALL LEADERS FOCUS: SHIFTING FROM STATIC (REARVIEW MIRROR) TO ACTIONABLE: Static/ reportingoriented Actionable (in time to inform decisions/improve performance) OVERALL LEADERS TIMELINESS: A SHIFT FROM SLOW/SILOED TO EXPEDITED: Delayed/ siloed Expedited: right place/right time/ multifunctional OVERALL LEADERS Whether the desire is for data to enable timelier, more actionable or more predictive business models, these goals are better served when decision makers have greater access to the needed solutions. 6 ANALYTICAL ENABLEMENT

7 WHERE IS VALUE CREATED? In terms of how value is created within a distributed BI framework, overall respondents most frequently cite improvements in activities such as identifying business opportunities (69%), optimized or dynamic pricing (65%) or gauging productivity (63%). But other frequently cited drivers include being better able to predict customer behavior or optimize logistics, energy consumption or marketing spend. As to where value is being created today, the most frequently cited functions include finance (67%), sales (6%), marketing (60%) and compliance (60%). Note that among leaders, the most frequent deployment is in marketing (72%). Going forward asked where their organization should be using more distributed BI processes the incidence for each function rises significantly in nearly every case. The steepest climb is in risk, rising from 53% (in use today) to 7 (should be in use). But respondents also note the need for wider deployment in areas such as logistics and R&D. One area, finance, actually shows a statistically insignificant decline in the should use category. Likely, this indicates no change, meaning the majority of firms are relatively satisfied with their current levels of finance team access to BI. HOW IS THIS VALUE DERIVED? Identifying business opportunities Optimizing prices (dynamic pricing) Gauging productivity Analyzing workflows Optimizing sales and marketing spend Predicting customer behavior Energy optimization Optimizing logistics Identifying societal trends 53% 5% 47% 49% 4 49% 58% 6% 7% 69% 69% 65% 68% 63% 63% 58% 6% 62% Percentages = those expressing strong satisfaction (a 4 or 5 on a -5 scale). Leaders Overall WHERE ARE THESE TOOLS IN USE TODAY AND WHERE SHOULD THEY BE DEPLOYED? Finance Sales Marketing Compliance Production Tax Risk R&D Logistics 49% 48% 54% 53% 6% 60% 60% 57% 67% 65% 63% 64% 68% 67% 67% 68% 7% Are using Should be using 7 COPYRIGHT 206 FORBES INSIGHTS 7

8 WHAT DATA SHOULD YOU BE USING? As for data being analyzed within a distributed framework, today, and also likely in the next 8 months, the most frequently cited form is internal biometric often associated with time/motion studies. Though mentioned by 44% of companies overall, this form of data rises to 6% among media firms and 59% among healthcare. Its prevalence reaches 57% of companies over the next 8 months. Device-generated, or Internet of Things (IoT) data, today holds second place at 39%, but is significantly more evident at technology (60%) and automotive (50%) firms. Though the use of IoT increases over the next 8 months, it drops in relative position as third-party and open source (e.g., government databases) data use grows even faster. WHAT DATA DO YOU USE TODAY AND WITHIN 8 MONTHS? Now 8 months INTERNAL BIOMETRIC (E.G., TIME/MOTION STUDIES) 44% a 57% IoT 39% b 44% DATA FROM PARTNERS/SUPPLIERS 37% c 49% THIRD-PARTY (PURCHASED) 35% d 5% OPEN SOURCE (E.G., GOVERNMENT DATABASES) 33% e 49% SOCIAL MEDIA 29% f 39% a 6% media; 59% healthcare; b 60% technology; 50% automotive; c 60% technology; d 50% technology and telecommunications; e 50% technology and telecommunications; f 40% technology. Percentages = those expressing use (a 4 or 5 on a -5 scale). THE CASE FOR A DISTRIBUTED SOLUTION: FINANCIAL SERVICES According to the head of BI at a major asset management and banking services provider, If you re trying to run centralized, one size fits all, that model will not be as effective as something more distributed and tailored. Even custom-tailoring centralized application development faces severe limitations. What tends to happen, says the executive, is that companies spend months going back and forth between developers and end-users, each speaking a different language, so neither ever really understands the other. Consequently, the output becomes just another static end-of-month PDF or spreadsheet that, while likely an improvement on prior reporting, still isn t timely, meaningful, flexible, interactive or on point. For these and related reasons, the executive and his team began searching for the means of developing a better BI solution. What we needed, he explains, was something simple, powerful and intuitive that end-users, those actually closest to the business, could use to explore their own data and build their own analytics and dashboards. Results to date are nothing short of amazing. Using self-service solutions, field executives are now able to develop their own dashboards and visualizations in a matter of hours versus what might have taken a typical development team many months to deliver and at an accompanying cost. A model giving line executives so many analytic capabilities in a flexible, immediate and highly visual and therefore more readily understandable manner, says the spokesperson, represents an absolute paradigm shift. 8 ANALYTICAL ENABLEMENT

9 KEY DRIVERS OF THE DISTRIBUTED MODEL Beyond specific business benefits, the survey also provides insight into the experience and attitudes of business executives, illustrating the forces driving growth in distributed BI models. A key feature of the most capable and user-friendly self-service solutions, for example, is that they provide end-users with an array of options for creating insight-revealing charts and graphs. Here, 73% of those using a distributed data and analysis model say improving data visualization is a strategic imperative. Moreover, 63% of those using a distributed model, and 53% of those who are not yet using one, agree that they enable more visually compelling analysis. Similarly, nearly two-thirds of executives who are using a distributed model (63%) agree with the statement: self-service data analysis creates significant competitive advantage. Closely related, half of these companies believe such an approach can help to reveal commercially valuable insights. DO YOU AGREE? Distributed 2 Not Distributed 3 IMPROVING DATA VISUALIZATION IS A STRATEGIC IMPERATIVE 73% 54% SELF-SERVICE DATA ANALYSIS MODELS CREATE SIGNIFICANT COMPETITIVE ADVANTAGE 63% 40% DISTRIBUTED SELF-SERVICE ENABLES END-USERS TO DEVELOP MORE VISUALLY COMPELLING ANALYSIS 63% 53% SELF-SERVICE ENABLES BUSINESS UNITS TO UNCOVER INVALUABLE COMMERCIAL INSIGHTS 5% 43% Percentages = those citing agreement (a 4 or 5 on a -5 scale). 2 Using distributed data and analysis in their organization (n = 369). 3 No effort/under consideration to use distributed data and analysis (n = 80). Executives also point to a range of circumstances likely driving their pursuit of a more distributed BI environment. The most commonly cited is working at a company where senior management sees the approach as valuable and creates a mandate. Often, such executives and others in the company are in turn driven by related drivers, such as the need for timelier and/or better-quality analysis, or perhaps the demands and influences of customers. HOW SIGNIFICANT ARE THE FOLLOWING IN TERMS OF DRIVING THE SHIFT TOWARD GREATER DISTRIBUTION OF BI ANALYSIS AND DECISION-MAKING SOLUTIONS? Direction from senior management Senior management attitudes Need for more timely analysis Need for better-quality analysis Customer demands/influence IT initiative Company culture Individuals taking personal initiative Supplier/partner demands 49% 43% The above chart shows, undoubtedly, that senior management plays a key role in the shift toward a more distributed BI environment. However, in the next question, respondents were asked to choose the description that best characterizes the key forces behind their adoption of distributed BI practices. In about a third of instances, senior management plays the lead role. But for most companies, 67% of leaders and 64% overall, some combination of senior management alongside an organic, bottom-up set of initiatives is what leads to the adoption of distributed practices. 54% 5% 55% 62% 60% 65% 67% Percentages = those expressing strong satisfaction (a 4 or 5 on a -5 scale). 75% 75% 7 74% 7% 74% 77% 82% Leaders Overall 8 WHICH BEST DESCRIBES THE KEY FORCES BEHIND YOUR ADOPTION OF A MORE DISTRIBUTED BI ENVIRONMENT? Leaders Overall TOP DOWN ENCOURAGED/DIRECTED BY SENIOR MANAGEMENT 27% 24% BOTTOM UP ORGANIC/AGGRESSIVE ADOPTION BY THE RANKS 2% SOME COMBINATION OF THE TWO 67% 64% COPYRIGHT 206 FORBES INSIGHTS 9

10 IDENTIFYING KEY CHALLENGES None of this is to say there are no hurdles. Respondents were asked to choose their top three challenges from a list of commonly cited issues. Here, the issue most frequently chosen as the most challenging is the potential difficulty in combining data from different sources (9% overall; 24% among leaders). Another key challenge is ensuring data security (4% overall; % among leaders). Indeed, for a distributed model to be successful, its principals need to develop an effective data governance model one that not only preserves data security and integrity, but also gives end-users confidence that their analysis works with complete and accurate data sets. Other challenges, though not as frequently cited, will nonetheless require attention. For example, figuring out how to get the right information into the right hands is a challenge well suited for a more distributed BI model. As for understanding what the data means, those closest to business challenges often have the keenest insight again, a circumstance that benefits from a self-service model. Respondents also indicate the need to work closely with IT to enable access to potentially critical data. This is an area that benefits from first achieving senior-level buyin to incentivize cooperation, adjustments and workarounds but that also dovetails with the need to develop a robust data governance environment. WHAT ARE THE KEY CHALLENGES TO BE OVERCOME? Top choice Leaders Overall COMBINING DATA FROM DIFFERENT SOURCES 24% 9% ENSURING DATA SECURITY % 4% GETTING THE RIGHT INFORMATION INTO THE RIGHT HANDS 8% % UNDERSTANDING WHAT THE DATA MEANS % 0% WORKING WITH IT TO ENABLE ACCESS TO NEEDED DATA 3% 0% FUTURE STEPS Beyond working to address the above key hurdles, executives who have already implemented a more selfservice approach to analysis and decision making are also taking a range of general actions to improve the quality and results of their distributed data programs. For example, 7% say they are, today, directing their IT departments to work more closely with business units to expand access to more forms of corporate and external data. Over the next 8 months, this figure declines to 6%, but that s likely because by then, for many organizations, the expectation is that the mission will have been accomplished. Another key undertaking is the expansion of training for executives to improve their understanding and usage of distributed analysis solutions. Today, 64% are taking such action, with the figure rising to 7% within 8 months meaning for most, this will remain an ongoing initiative. Other critical actions include expanding cloud and mobile access to the enterprise as well as expanding the emphasis on distributed BI skills in hiring, training and career development. Worth noting, the survey also found that 62% agree that line managers need to take significant steps to become more data literate (rising to 67% among distributed companies). 0 ANALYTICAL ENABLEMENT

11 WHAT STEPS ARE YOU TAKING NOW AND IN 8 MONTHS? DIRECT/ENCOURAGE OUR IT DEPARTMENT TO WORK MORE CLOSELY WITH BUSINESS UNITS TO EXPAND ACCESS TO MORE FORMS OF CORPORATE AND EXTERNAL DATA 7% 6% EXPAND TRAINING FOR EXECUTIVES TO IMPROVE THEIR UNDERSTANDING AND USAGE OF DISTRIBUTED ANALYSIS TOOLS 64% 7% PROVIDE CLOUD ACCESS TO ENTERPRISE DATA FOR DISTRIBUTED ANALYSIS 59% 6% PROVIDE MOBILE TOOLS FOR DISTRIBUTED ANALYSIS 58% 60% EMPHASIZE THE ABILITY TO DEVELOP CRITICAL ANALYSIS USING DISTRIBUTED TOOLS IN OUR HIRING AND CAREER DEVELOPMENT 57% 65% DEVELOP A CENTER OF EXCELLENCE TO FOSTER AND IMPROVE THE QUALITY OF DISTRIBUTED ANALYSIS 54% 68% Using distributed data and analysis in their organization (n = 369). Today In 8 months NATIONAL EXPRESS: EMBRACING DISTRIBUTED SOLUTIONS A good example of a company embracing distributed BI solutions is the U.K. s international transport-focused National Express. Distributed tools, says Frank Kozurek, head of business intelligence, means people can work with what we provide, but then they are also free to add their own tables and charts they don t have to come back to us to build for them what they want. It s all very customizable and flexible. Moreover, the executive is also very impressed with the visualizations achievable, which as Kozurek explains, lead to better insights. CONCLUSION Given all of the above, it should come as no surprise that 5 of companies overall and 54% of leaders plan to accelerate investment in self-service, distributed BI capabilities. Unquestionably, companies are deriving tremendous business benefit from their BI programs. But at the same time, as this research reveals, the most effective BI programs are not purely centrally controlled but rather, tend to feature significantly greater elements of a distributed, self-service nature. Leaders are placing the power of advanced, highly intuitive and associative solutions into the hands of the business users ideally placed to execute some of the most timely, creative and informed analysis and take action. Results to date speak for themselves, raising the question: is there any business or similar entity that would not benefit from such an approach? COPYRIGHT 206 FORBES INSIGHTS

12 METHODOLOGY The insights and commentary found in this report are derived from both a survey and qualitative interviews with senior executives. In March 206, Forbes Insights, in collaboration with Qlik, conducted a robust global survey of 449 senior IT and business unit executives. Key demographics include: 9% 0% 3% 8% 24% % 44% TITLE CIO VP/business unit director CFO/treasurer/controller Director CMO SVP/VP CEO Note: Does not add to 00% due to rounding. 50% 32% LOCATION 8% 8% 9% 8% 57% Europe (composed of 8% each for the U.K., France, Germany, Italy, Netherlands, Spain and Sweden) U.S. Australia/New Zealand Japan India Note: Does not add to 00% due to rounding. INDUSTRY Manufacturing/industrial 0% Technology 7% Telecommunications Banking Consumer or business services Energy 7% Consumer packaged goods Financial services Government Healthcare Insurance Pharmaceuticals Retail Automotive Media & entertainment Other 5% 5% PRINCIPAL FUNCTIONAL ROLES (executives could select as many as deemed relevant) IT Strategy Operations General Management M&A/Business Development Product Management Finance/Accounting Sales 7% Human Resources Supply Chain 9% 20% 8% PROFITABILITY (measured by average EBITDA growth over past three years) 9% 2% 5% 22% 9% 8% 8% Customer Experience R&D 8% 2% % 37% 53% +%-0% No change/flat +%-9% 20% or more Not sure/do not divulge Decrease Note: Does not add to 00% due to rounding. While the authors call out key differences based on key demographic variables, the data set is so robust that it would be impractical to highlight every instance of statistically significant variation. One key finding is that there is surprisingly little variation by region or country; that, in fact, the real variation had more to do with familiarity and experience with distributed BI solutions. Nonetheless, readers are encouraged to visit to view the full data set, and perform their own analysis of the survey respondents by industry, function, country, region and many additional characteristics using Qlik. As for the industry vignettes and quotes appearing in this report, these are abstracted from a companion, fully qualitative Forbes Insights report, Decisions, Decisions: How Leading Firms Are Arming Frontline Executives With Data-Driven Insight. Also executed on behalf of Qlik, the full report can be downloaded at 2 ANALYTICAL ENABLEMENT

13 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 William Millar, Briefing Author Charles Brucaliere, 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