Survey results: The age of unbounded data
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  • 1. Leading inThe Age of Unbounded DataSurvey Results, 2010Nauman Haque
  • 2. IntroductionWelcome to the age of unbounded data © 2011 Moxie Insight. All Rights Reserved. 2
  • 3. Leading in the Age of Unbounded DataEnter the highly-instrumented enterpriseEnterprises Have BecomeHighly-Instrumented; Using new sources of datacombined with sophisticated analytics to distinguish signal from noise, create better situational awareness, drive new insights, and uncover the ROI of collaborative initiatives. © 2011 Moxie Insight. All Rights Reserved. 3
  • 4. Leading in the Age of Unbounded DataIt‟s not just that we have more data… More data Over 50% of respondents ‘agree’ or ‘strongly agree’ that more data leads to better decision making, but 46% spend more time looking for information today than before. More data from new and expanding sourcesAlmost 60% of respondents report an increase in the number of data sources used for decision-making in the past 12 months; two-thirds of companies believe managing data from new sources is an important issue. More interactions among data types and between people and data 70% of respondents ‘agree’ or ‘strongly agree’ that executives who have more varied types of data will improve the quality of their decisions. Growing availability of open data Over 70% of companies say that deciding how much data to open or share is either an ‘important’ or ‘very important’ issue. Making sense of this data ecosystem is the fundamental challenge facing enterprise decision-makers, analysts, and IT departments Despite the glut of available data, only 33% of respondents indicated that they have the data they need to do their jobs. © 2011 Moxie Insight. All Rights Reserved. 4
  • 5. Leading in the Age of Unbounded Data…enterprises must make sense of the data ecosystem Sense-making trumps all other data priorities Improving the ability to interpret data (and get it to senior executives) is the number one data priority; far more important than getting access to more data. Data quality is a bigger problem than data availability ‘Data integrity and quality’ is the number one data problem vexing survey respondents; deemed to be a far greater issue than ‘data availability.’ The use of unstructured data in measurement is a significant contributor to quality issues. Focusing on customer data will be a competitive priority Data from customers will drive competitive advantage, but currently data quality is low and sharing of information back to customers (i.e. creating a two-way value proposition) is a low priority. Both new data and legacy data are causing problems Managing legacy data is proving almost as hard as managing data from new channels (rated as ‘very important’ by 32% and 34% of respondents respectively). Companies still lag when it comes to measurementOnly 23% of respondents are measuring the ROI of collaborative initiatives; just over half are measuring employee productivity. In both cases, fewer than 40% report ‘good’ or ‘excellent’ quality data. © 2011 Moxie Insight. All Rights Reserved. 5
  • 6. Leading in the Age of UnboundedSurvey methodology 0% 10% 20% 30% • Survey results gathered from Consulting 23% Software/Technology 16% January 15th to March 1st 2010. Government 13% Finance/Banking 9% • Responses from over 70 major Medical/Healthcare 5% Retail/Consumer Products 5% organizations, including several Advertising/PR 5% state/provincial governments Transportation 4% and many global corporations. Education/Training 4% Telecomunications 4% Publishing 3% • Majority of respondents are Utilities 3% director-level or higher Other 6% executives from within various functions. Staff 16% 35% Manager 19% Director Senior/Executive Management 30% © 2011 Moxie Insight. All Rights Reserved. 6
  • 7. Moxie Insight Data SurveyData-driven competitive advantage © 2011 Moxie Insight. All Rights Reserved. 7
  • 8. Survey Overview: Data-Driven Competitive AdvantageExternal data is a key driver of competitive advantage What sources of data drive competitive advantage in your organization? 0% 20% 40% 60% 80% 100% From customer and user interactions 77% Internally created 68% Co-created with customers 49% Co-created with business partners 44% Acquired from external parties 43% Open data 22% Other Competitive advantage is not data-driven 12% 88% of respondents say that data drives competitive advantage. Collaboration around data is an important part of seizing the opportunity. While internally created data and data gleaned from user and customer interactions are still seen as most important, increasingly data from outside the enterprise is also driving competitive advantage. Data created with customers and partners, data acquired from third parties, and open data are all considered integral contributors to competitive strategies. © 2011 Moxie Insight. All Rights Reserved. 8
  • 9. Survey Overview: Data-Driven Competitive Advantage Most pronounced worry among decision makers is data integrity and quality More data improves decision-making, metrics, and agility, but also creates complexity and more noise in the system. Some critical issuesinclude availability and timeliness of data for decision-making, data security and access rights, and deciding how to share data and with whom. How important are the following problems related to enterprise data? 0% 20% 40% 60% 80% 100% Data integrity & quality 73% 18% Timeliness of data 56% 31% Data availability 53% 30% Data security 53% 26% Managing data rights 39% 32% Deciding how much data to open or share 39% 32% Managing data from new channels 36% 32% Managing legacy data 34% 27% Other 9% 6% Very Important Important © 2011 Moxie Insight. All Rights Reserved. 9
  • 10. Survey Overview: Data-Driven Competitive Advantage Across data types, fewer than half rate the quality of data as „good‟ or „excellent‟ The low quality of customer data is particularly worrying Rate the quality of data for day-to-day decision making (only 27% say it is ‘good’ or excellent’), as this data was 0% 20% 40% 60% 80% 100% seen as a key driver of competitive advantage. Function-specific data 47% 27% 23% Fortunately, many new tools Employee data 42% 25% 23% and technologies are emerging to help address this, includingEnterprise data (cross-function) 29% 26% 40% ‘voice-of-the-customer’ listening platforms and Customer data 27% 27% 34% sentiment analysis tools, as well as prosumer platforms that harness customer insight Partner and supplier data 17% 32% 35% and ideas, and next-generation social CRM solutions that Good/Excellent Average Below Average/Poor promise to integrate data from social media interactions into customer databases. © 2011 Moxie Insight. All Rights Reserved. 10
  • 11. Survey Overview: Data-Driven Competitive Advantage Sense-making is paramount in a world of abundant information What are the data priorities for your organization? (percentages shown are based on respondents rating priorities as ‘high’ or ‘very high’) Sharing data is still not huge 0% 20% 40% 60% 80% 100% priority, but we believe that it’s going to have to be givenGetting data to senior executives more quickly 79% the growing importance of Improving our ability to interpret data 75% data ecosystems. In order to Improving data quality 74% fully leverage opportunities Getting more timely data 70% related to customer data and data from external partners, Measuring customer experience 69% companies will need to Getting data to front line employees more… 62% share their own information Sharing data with employees 61% and create two-way value Managing unstructured data 61% propositions. The lack of priority being placed on Getting access to more data 58% sharing and measuring Measuring return on collaborative initiatives 52% return points towards a real Managing data from social media 43% opportunity for leading Sharing data with customers 40% organizations to redefine competitive advantage. Sharing data with external partners 34% © 2011 Moxie Insight. All Rights Reserved. 11
  • 12. Data and the Ability to Measure What was previously unknown can now be known © 2011 Moxie Insight. All Rights Reserved. 12
  • 13. Data and the Ability to MeasureWhat are companies measuring? The Age of Unbounded Data is a result of a dramatic increase in the amount of sensor technology, web analytics, document tracking, and other instrumentation that is now commonplace in our homes, organizations, and public places. The influx of more and different types of data provides organizations with an unprecedented opportunity to improve what and how they measure and report. Which of the following do you measure? ROI of collaborative initiatives 23% Customer experience 65% Employee productivity 53% © 2011 Moxie Insight. All Rights Reserved. 13
  • 14. Data and the Ability to MeasureThe ROI of collaborative initiativesToday, only 23% of respondents are measuring the impact of collaborative initiatives.• Among those that are having success, most are using a combination of analytics and proprietary techniques.• As workflows are increasingly digitized, process mining will uncover new types of ROI metrics for tasks and initiatives that were previously qualitatively measured (if at all) due to their unstructured nature.• Over half of companies say that measuring ROI of collaborative initiatives is a high priority. Given how important it is, we expect the number of organizations measuring ROI to increase significantly over the next 12-24 months.• Moxie Insight’s research has shown that measuring ROI depends on identifying an intent for the collaborative initiative that is tied to a specific business outcome— why are you collaborating and what type of collaboration are you going to use? © 2011 Moxie Insight. All Rights Reserved. 14
  • 15. Data and the Ability to MeasureCustomer experience65% of survey respondents actively measure customer experience.• There isn’t a huge difference in the type of methods used by those having success in this area and those struggling—the vast majority use customer surveys and feedback forms—indicating that the major issue for companies with customer experience measures may be the questions being asked and the processes surrounding customer feedback rather than the data-gathering methods.• By systematically gathering and analyzing customer anecdotes (e.g., using social media monitoring and text mining), companies can augment survey measures and satisfaction scores with more story-driven measures of experience.• Just about any organization can listen to and leverage the stories of average people that write online in blogs, forums, Twitter, and social networks every day.• There are effective new methods for collecting and analyzing customer data that are not yet widely used including social media monitoring tools, listening platforms, text analysis, and customer sentiment analysis. © 2011 Moxie Insight. All Rights Reserved. 15
  • 16. Data and the Ability to MeasureEmployee productivityA little over half (53%) of respondents are actively measuring employee productivity.• The leading types of measurement used are a combination of time tracking, performance management software, and 360-degree peer reviews.• New sources of data can create visibility into poorly-understood informal networks and allow organizations to redirect their attention towards what’s going on ‘below the surface’ of established structures.• Software is now available that can track e-mail messages, shared documents, calendar information, call logs, and contact information to model collaborative behaviour and map informal lines of communication.• By mining employee processes, companies can target key influencers, find new efficiencies, strengthen existing forms of collaboration, and encourage nascent creativity. We can know which employees are producing high-value information, which employees are good curators of information, and which employees may be engaging in harmful activities. © 2011 Moxie Insight. All Rights Reserved. 16
  • 17. Data and the Ability to MeasureThe role of unstructured data Unstructured data is playing a significant role in what is being measured. Over 50% of those that measure collaboration, employee productivity, or customer engagement incorporate some form of unstructured data. What type of data do you use to measure? 0% 20% 40% 60% 80% 100% ROI of collaborative initiatives 44% 56% Customer experience 44% 16% 40% Employee productivity 44% 32% 24% Structured Unstructured Both © 2011 Moxie Insight. All Rights Reserved. 17
  • 18. Data and the Ability to Measure Consistency of data quality decreases as amount of unstructured data increases How would you rate the quality of the data used for measurement? 0% 20% 40% 60% 80% 100% Those using structured data reported higher quality rating than those using unstructured Structured 17% 42% 42% data. Unstructured data like text, images, audio, and video is hard to organize and analyze; however, the technologies that allowUnstructured 38% 38% 24% companies to do so are starting to become enterprise-grade. Companies that harness tools Both 23% 48% 30% like text mining, picture and video tagging, and voice analysis will definitely have an edge in Below Average/Poor Average Good/Excellent measurement. ROI of collaborative initiatives Customer experience Employee productivity 0% 0% Very Poor 4% 4% 2%10% 22% 14% Below Average 39% 24% 34% 20% Average Good 39% 44% 44% Excellent © 2011 Moxie Insight. All Rights Reserved. 18
  • 19. Data Improves DecisionsMore information, more decision-makers, and greater agility © 2011 Moxie Insight. All Rights Reserved. 19
  • 20. Data Improves DecisionsOver 50% „agree‟ or „strongly agree‟ that more data leads to betterdecisions The majority of survey To what degree do you agree with the statement respondents agree that more is better when it comes to data. “having more data lead to better decisions”? Additionally, 70% ‘agree’ or ‘strongly agree’ that executives who have more varied types of 5% data (e.g., audio, video, text, statistics) will improve the 16% 26% Strongly Agree quality of their decisions. Agree Yet more data can also lead to more noise and distraction. Neither Agree nor Disagree There was also a contingent— Disagree 21% of respondents—that 27% ‘disagreed’ or ‘strongly 26% Strongly Disagree disagreed’ that more data lead to better decisions. Clearly, simply having more data is not a panacea. © 2011 Moxie Insight. All Rights Reserved. 20
  • 21. Data Improves Decisions“If HP knew what HP knows, we would be three times as profitable.”– Former HPCEO Lew Platt Improving the ability to interpret data is a top priority for companies. A major obstacle is that, in many companies, data still tends to be siloed. Close to 80% of respondents indicate that data sharing is sub-optimal: 44% state that data is siloed by department and 27% state that even when data is shared across departments, it is often inconsistent. Sharing and making sense of data in real-time accomplishes two goals: greater agility through immediate response and better predictions about the future behavior of people and markets. What statement most accurately reflects the situation in your organization? 0% 10% 20% 30% 40% 50% 8% Nobody knows anything Data tends to be siloed by department 44% Data is shared but is often inconsistent 27% There is a single version of the truth accessible to all departments 5% Data is available for simulation and modeling across the enterprise 16% © 2011 Moxie Insight. All Rights Reserved. 21
  • 22. Data Improves DecisionsEmerging data opportunities tied to predictive analytics How does your organization use predictive analytic tools? Predictive models can 0% 10% 20% 30% 40% 50% help decision makers refine business plans in We do not use predictive analytics 36% response to unexpected Customer relationship management 38% challenges or opportunities by giving Financial modeling 35% them insight into the Up-selling or cross-selling 29% likely outcomes of decisions. Everyday Risk management 19% workers can optimize Direct marketing 18% some of the most important decisions andSupply chain or inventory management 12% signal which initiatives Fraud detection 9% to launch, accelerate, or Security threats 9% stop using ‘what-if’ scenarios that leverage Manufacturing or equipment failures 6% both historical and Other 4% current data. © 2011 Moxie Insight. All Rights Reserved. 22
  • 23. Data Improves DecisionsBeyond local optimization: Leveraging and sharing data enterprise-wide isthe goal While the majority said that certain individuals use data to support decisions, the clear opportunity is in the collaborative and automated spaces. While there is little activity in those areas today—a little over a third using collaborative data and only 16% using automated decisions—we believe there is a big upside for companies willing to take a leadership position in these areas. Incorporating collaboration and automation into the decision- making process could bring more effective and faster means of making successful decisions. How is data used for decision-making? 0% 20% 40% 60% 80% Data is used to drive decisions by certain individuals 69% Data is used to conduct analytics that support decisions 60% Data is used to drive collaborative decision-making 33% Data is used to support professional expertise or "gut-feel" 27% Data is used to automate decision-making 16% Data is rarely used for decision-making 9% © 2011 Moxie Insight. All Rights Reserved. 23
  • 24. Data Improves DecisionsEnabling „everyman analytics‟ How does your department• With the proliferation of data, we’re also seeing the handle its analytic needs? democratization of analytics. This will have vast implications for the role of the analyst, which will 3% 10% 17% 4% become much more specialized.• Our survey shows that while analytics is pervasive, it’s not always strategic: 66% of respondents conduct analytics themselves but only 10% have a dedicated analytics group. 66%• Since we didn’t define “analytics” in the survey, we can We have an analytics group assume that the 66% includes everything from ‘Excel We outsource most of it warriors’ and power users, to users of free tools such as We do it ourselves Google analytics, to more sophisticated business We do not currently use analytics intelligence software. Other• 17% are not conducting analytics at all. © 2011 Moxie Insight. All Rights Reserved. 24
  • 25. Data Enables Customer EngagementA clearer view of customers‟ behaviours, preferences, and actions © 2011 Moxie Insight. All Rights Reserved. 25
  • 26. Data Enables Customer EngagementCustomer data is highly valued Already, data created by customers and users—either indirectly by mining their interactions or directly via co- creation—was ranked very high when respondents were asked to identify which sources of data drive competitive advantage in their organizations (1st and 3rd respectively). Not surprisingly, almost two-thirds of companies are measuring customer experience (see Slide 15 for details). What sources of data drive competitive advantage in your organization? 0% 20% 40% 60% 80% 100% From customer and user interactions 77% Internally created 68% Co-created with customers 49% Co-created with business partners 44% Acquired from external parties 43% Open data 22% Other Competitive advantage is not data-driven 12% © 2011 Moxie Insight. All Rights Reserved. 26
  • 27. Data Enables Customer Engagement Customer priorities are often out-of-synch What are the data priorities for your organization? (percentages shown are based on respondents rating priorities as ‘high’ or ‘very high’) While measuring customer experience was rated a ‘high’ 0% 20% 40% 60% 80% 100% or ‘very high’ data priority by 69% of respondents, sharingGetting data to senior executives more quickly 79% data with customers was Improving our ability to interpret data 75% deemed a priority by only Improving data quality 74% 40% of respondents. Getting more timely data 70% Sharing data with customers Measuring customer experience 69% is one way of creating a more Getting data to front line employees more… 62% valuable customer experience. Organizations Sharing data with employees 61% that share data and are Managing unstructured data 61% transparent will build trust Getting access to more data 58% with customers, open the Measuring return on collaborative initiatives 52% door for co-innovation, and ultimately gain competitive Managing data from social media 43% advantage from customer- Sharing data with customers 40% and user-created data. Sharing data with external partners 34% © 2011 Moxie Insight. All Rights Reserved. 27
  • 28. Data Enables Customer EngagementMany organizations are stuck in a CRM-centric view of customer data How do you use data collected from social media tools such as social networks, Twitter, blogs, and forums? 0% 10% 20% 30% 40% 50% We do not collect data from social media 36% Market research 39% Brand management 30% Relationship management 29% Customer experience management 27% Hiring and recruiting 22% Product development 18% Other 64% of respondents report monitoring social media. Social media data can reveal an individual’s or group’s attitudes towards a brand, a person’s influence within atarget demographic, or an emerging issue in the marketplace. Unfortunately, only 43% of respondents view social media as an ‘important’ or ‘very important’ data priority. We expect to see this channel become more of a priority as organizations get better at mining and finding value in that data. © 2011 Moxie Insight. All Rights Reserved. 28
  • 29. Data As a ProductAggregated, anonymized data is a valuable commodity © 2011 Moxie Insight. All Rights Reserved. 29
  • 30. Data As a ProductFuture opportunities extend beyond enterprise data to data ecosystems• There is a potential market for data: Over 40% of respondents said data from external sources led to competitive advantage.• Companies that have social platforms are increasingly seeing a business model around providing free services and aggregating anonymized customer and user data for sale. This user data is being leveraged in many ways, with 77% indicating that data from customer and user interactions are a source of competitive advantage.• 71% of respondents said deciding how much data to open and share is ‘important’ or ‘very important,’ but sharing of data with external partners and customers was rated as a relatively low priority (last and second-last respectively on a list of 13 data priorities). © 2011 Moxie Insight. All Rights Reserved. 30
  • 31. Data As a ProductOpen data initiatives are still immature What is the organization’s open data strategy? 0% 10% 20% 30% 40% 50% An open data strategy has not yet been 31% considered Open data is an important part of our future 30% growth strategy Open data has been considered and is not on 17% our current strategy agenda Our open data strategy is still being debated 22% ‘Open IP,’ where companies and institutions add to the data commons, is an emerging, if somewhat immature trend. Currently only 30% of respondents have open data identified as an important part of their strategy; 31% have not yet considered a strategy for open data. Discouragingly, 17% of respondents say they have considered but rejected an open data strategy. © 2011 Moxie Insight. All Rights Reserved. 31
  • 32. Key Takeaways Uncover new opportunitiesand unleash hidden potential © 2011 Moxie Insight. All Rights Reserved. 32
  • 33. Key TakeawaysLeading in an age of unbounded data requires new thinking Leading in an Age of Unbounded Data is Not Just About Having More Data , but also about how we manage interactions among data types and interactions between people and data, our ability to interpret data and find meaning, and the extent to which we embrace data sharing and open data Decision-Makers Must strategies. Understand the Data Ecosystem. © 2011 Moxie Insight. All Rights Reserved. 33
  • 34. Key TakeawaysLeading in an age of unbounded data requires new thinking Key learnings from the project include: • Data is a critical enabler of the next generation enterprise. • The data revolution is not just about more data. • Future opportunities extend beyond enterprise data to data ecosystems. • Digitizing processes will lead to new types of measurement and optimization. • Customer data is a leading contributor to competitive advantage. • More types of data lead to better decision making. • Sense-making is paramount; the most successful companies compete on analytics. • Aggregated, anonymized data is a good way to monetize interactions. © 2011 Moxie Insight. All Rights Reserved. 34
  • 35. Key TakeawaysLow hanging fruit: Opportunities for leading enterprisesWe believe they are several elements of data strategy that are critical to driving the nextgeneration enterprise, but that are still nascent. The lack of activity in the following areas revealsan opportunity for leading organizations:• Leverage tools to get high-quality customer data – Although customer data is identified as a key driver of competitive advantage, few companies are currently getting data that is of high quality. New tools such as ‘voice-of-the-customer’ software, listening platforms, prosumer platforms, and sentiment analysis tools, as well as emerging social CRM offerings, will help close this gap.• Share data – Companies that open and share their data will reap the benefits of an ecosystem of customers, partners, and employees. Sharing data with customer creates a two-way value proposition and generates new opportunities for co-innovation. Sharing data internally improves analytic capabilities , customer responsiveness, executive visibility, and overall agility.• Measure ROI – Over 50% of companies say that measuring the ROI of collaboration is a high priority, yet only 23% actually do so. Part of the problem is the difficulty related identifying metrics. Still, companies that have success in this area will be able to optimize collaboration and improve productivity. © 2011 Moxie Insight. All Rights Reserved. 35
  • 36. Key TakeawaysLow hanging fruit: Opportunities for leading enterprises• Focus on social media – Customers are focused on social media, and companies should be too. Communicating via social media can lower costs and data gathered from social media channels can not only lead to new insights, it can even generate new revenue when anonymized and packaged for interested third parties.• Prepare the enterprise for analytics – The most successful organizations compete on analytics. Data analytics leads to better data interpretation and sense-making. Companies that are really good at analytics are also good at gathering data, sharing data, and consolidating it to get a ‘single version of the truth’ across the enterprise.• Support decision-making with automation and collaboration – Few companies are currently looking to decision-automation or collaborative decision-making as high-priority data opportunities. Leveraging machine intelligence will improve the speed and accuracy of decisions and also help push decisions to front-line employees making for a more responsive organization. Collaboration via simulations, visualizations, and data sharing platforms allows companies to harness the knowledge of a much broader base of individuals. © 2011 Moxie Insight. All Rights Reserved. 36
  • 37. Nauman Haquenhaque@moxieinsight.com (416) 863-8825 www.MoxieInsight.com