In collaboration with MIT Sloan Management ReviewIBM Global Business ServicesBusiness Analytics and OptimizationExecutive ...
IBM Institute for Business ValueIBM Global Business Services, through the IBM Institute for Business Value, developsfact-b...
IntroductionBy David Kiron, Rebecca Shockley, Nina Kruschwitz, Glenn Finch and Dr. Michael HaydockIn this second joint stu...
2   Analytics: The widening divideNew analytical tools for making decisions, such as Watson, arebringing about entirely ne...
IBM Global Business Services    3Our initial joint study in 2010 identified three progressive                             ...
4    Analytics: The widening divideThe gap is widening                                                                    ...
IBM Global Business Services   5Transformed organizations use analytics                             By comparison, analyti...
6     Analytics: The widening divide                     Respondents rely on data and analytics for:                      ...
IBM Global Business Services         7                                                                    Focused on the n...
8   Analytics: The widening divideThe speed at which some organizations operate today outpaces         A report from the C...
IBM Global Business Services       9By using analytics across the enterprise to monitor, detect and      Engaging customer...
10   Analytics: The widening divideTransformed organizations are learning to use customer             Many organizations, ...
IBM Global Business Services      11Analytics competencies                 Manage the data                                ...
12   Analytics: The widening divide                                                                    Capability: Insight...
IBM Global Business Services   13Advanced skills and techniques also make it possible to embed        Competency #3: Data-...
14   Analytics: The widening divideBAE Systems: A new business model takes flightLike most organizations, BAE Systems once...
IBM Global Business Services         15Transformed organizations act on the data(percent proficient, Transformed versus As...
16    Analytics: The widening divideIn using analytics as a strategic asset core to their business and                    ...
IBM Global Business Services      17•	 The Collaborative path. An enterprisewide information                              ...
18   Analytics: The widening divideThe Specialized path and the three competencies                       3. Data-oriented ...
IBM Global Business Services   19On the Collaborative path, organizations draw on information      positioned to create se...
20   Analytics: The widening divideThe Collaborative path and the three competencies                        Collaborative ...
IBM Global Business Services   21Each path poses different challenges. Organizational issues                              ...
22   Analytics: The widening divideRecommendation 1: Assess your analytics                                Transformedsophi...
Analytics: The widening divide
Analytics: The widening divide
Analytics: The widening divide
Analytics: The widening divide
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Analytics: The widening divide


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In 1997, a computer named Deep Blue defeated Garry
Kasparov, the world chess champion at the time. In 2011,
another computer, Watson, competed and won against former
champions of Jeopardy!, the popular U.S. television quiz show.
Both events changed perceptions about what computers could
do. Deep Blue demonstrated the power of new parallel
processing technology, and Watson showed that computers can
understand ordinary language to meet the challenges of the
“real world.”

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Analytics: The widening divide

  1. 1. In collaboration with MIT Sloan Management ReviewIBM Global Business ServicesBusiness Analytics and OptimizationExecutive ReportIBM Institute for Business ValueAnalytics: The widening divideHow companies are achieving competitive advantagethrough analytics
  2. 2. IBM Institute for Business ValueIBM Global Business Services, through the IBM Institute for Business Value, developsfact-based strategic insights for senior executives around critical public and privatesector issues. This executive report is based on an in-depth study by the Institute’sresearch team. It is part of an ongoing commitment by IBM Global Business Servicesto provide analysis and viewpoints that help companies realize business value.You may contact the authors or send an e-mail to for more information.Additional studies from the IBM Institute for Business Value can be found Sloan Management ReviewMIT Sloan Management Review is a website, quarterly journal, and community thatexplores and reports on the most important new ideas in management innovation.It focuses on the trends in the competitive landscape that are the chief drivers ofcoming change in management practice and strategy – and brings research-basedinsights about those changes to the executives and managers who need them.You may contact the authors or find additional reporting from MIT SloanManagement Review at
  3. 3. IntroductionBy David Kiron, Rebecca Shockley, Nina Kruschwitz, Glenn Finch and Dr. Michael HaydockIn this second joint study from MIT SloanManagement Review and IBM Institute for Business Value, we see a growing dividebetween those companies that, on one side, see the value of business analytics and aretransforming themselves to take advantage of these newfound opportunities, and those,on the other, that have yet to embrace them. Using insights gathered from more than4,500 managers and executives, our 2011 New Intelligent Enterprise Global ExecutiveStudy and Research Project identifies three key competencies that enable organizationsto build competitive advantage using analytics. Further, the study identifies two distinctpaths that organizations travel while gaining analytic sophistication, and providesrecommendations to accelerate organizations on their own paths to analytictransformation.In 1997, a computer named Deep Blue defeated Garry In computer science terms, Jeopardy! is much harder thanKasparov, the world chess champion at the time. In 2011, chess. Whereas Deep Blue used specialized computer chips toanother computer, Watson, competed and won against former calculate outcomes of possible chess moves, Watson answeredchampions of Jeopardy!, the popular U.S. television quiz show. unpredictable questions put forward in peculiarly humanBoth events changed perceptions about what computers could speech patterns. Today, almost any computer can scan ado. Deep Blue demonstrated the power of new parallel database to match structured queries with answer. In contrast,processing technology, and Watson showed that computers can Watson was able to “read” through a massive body of humanunderstand ordinary language to meet the challenges of the knowledge in the form of encyclopedias, reports, newspapers,“real world.” books and more. It evaluated evidence analytically, hypoth- esized responses and calculated confidence levels for each possibility. It offered up, in a matter of seconds, the one response with the highest probability of being correct. And it did all that faster and more accurately than its world-class human opponents.
  4. 4. 2 Analytics: The widening divideNew analytical tools for making decisions, such as Watson, arebringing about entirely new opportunities. With the digitiza-tion of world commerce, the emergence of big data, and the Analytics: The use of data and relatedadvance of analytical technologies, organizations have extraor- insights developed through applied analyticsdinary opportunities to differentiate themselves through disciplines (for example, statistical, contextual,analytics. The majority of organizations have seized theseopportunities, according to the 2011 New Intelligent Enter- quantitative, predictive, cognitive and otherprise Global Executive Study and Research Project by the MIT models) to drive fact-based planning, decisions,Sloan Management Review and the IBM Institute for Business execution, management, measurement andValue. Fifty-eight percent of organizations now apply analyticsto create a competitive advantage within their markets or learning. Analytics may be descriptive,industries, up from 37 percent just one year ago (see Figure predictive or prescriptive.1).1 Significantly, these same organizations are more than twiceas likely to substantially outperform their peers. To understandhow organizations are using analytics today, we surveyed 4,500executives, managers and analysts from more than 120countries. About the research To continue to deepen our understanding of the challenges and opportunities associated with the use of business ana-Creating a competitive advantage lytics, for the second year in a row the MIT Sloan Manage-2011 ment Review, in partnership with the IBM Institute for Busi- ness Value, conducted a global survey of more than 4,500 58% business executives, managers and analysts from organiza- 57% tions located around the world. This marks a 50 percent increase increase in the number of respondents, broadening our anal- 37% ysis to include individuals in more than 120 countries repre- senting more than 30 industries, and involving organizations2010 of a variety of sizes. The sample was drawn from different sources, including MIT alumni, MIT Sloan ManagementNote: Percentage of total respondents who rated the level that information and businessanalytics is able to create a competitive advantage for their organization within their industry or Review subscribers, IBM clients and other interested as either substantial or significant on a five-point scale from 1= very little extent to 5=significant extent compared with the responses to the same question in 2010. N=3236. In addition to these survey results, we also interviewed aca-Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM demic experts and subject matter experts from a number ofInstitute of Business Value analytics research partnership. Copyright © Massachusetts Instituteof Technology 2011. industries and disciplines. Their insights contributed to a richer understanding of the data, and the development ofFigure 1: The ability of organizations to create a competitive recommendations that respond to strategic and tacticaladvantage with analytics has surged in the past 12 months. questions senior executives address as they operationalize analytics within their organizations. We also drew upon IBM case studies to further illustrate how organizations are already using business analytics as a competitive asset.
  5. 5. IBM Global Business Services 3Our initial joint study in 2010 identified three progressive three key competencies: (1) information management, (2)levels of analytical sophistication: Aspirational, Experienced analytics skills and tools, and (3) data-oriented culture.and Transformed (see Figure 2).2 Year-to-year comparisons of Mastering these competencies enables organizations to gainthese groups reveal that Experienced and Transformed full benefit from analytics.organizations are expanding their capabilities and raising theirexpectations of what analytics can do, while the Aspirational We also found, however, that organizations take one of twoorganizations are falling behind. This growing gap has major different paths to achieving analytics sophistication. Each pathimplications for businesses seeking to make the best possible is comprised of a different mix of competencies so organiza-decisions based on a flood of insight arising from the intercon- tions choose the best route to follow based on their strengthsnected world. and circumstances. The chosen path influences their overall approach to analytics, the kinds of projects they pursue – andWe closely examined what the Transformed organizations, the the steps they will need to take to achieve full analyticalmost sophisticated users of analytics, are doing well and found prowess.Analytics sophistication Aspirational Experienced Transformed Percentage of 32% 45% 24% total respondents Analytic use Basic user Moderate user Strong and sophisticated user Reliance on To guide decision making in financial To guide future strategies, and To guide decision making in day-to- analytics management and supply chain increasing reliance on analytics to day operations and future strategies management guide activities in marketing and across the organizations operations Information Few standards are in place; structured, Enterprise data integration efforts Enterprise data creates integrated foundation siloed data supports targeted activities are underway view of the business with a growing focus on unstructured data Analytics tools Primarily uses spreadsheets Expanding portfolio of analytics Comprehensive portfolio of tools to tools support advanced analytics modeling Analytics skills Ad hoc analysis is done at point-of-need; Analysts work in line-of-business Many are combining line-of-business has difficulty hiring analytics talent units with growing focus on units with centralized units that cross-training and hiring skills provide advanced skills and externally governance Culture Managers are focused on executing Open to new ideas but lacks Strong top-line mandate to use day-to-day activities top-line leadership and champions analytics supports a culture open to to support changes new ideas and champions who shepherd methodology and skillsSource: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute ofTechnology 2011.Figure 2: Analytics competencies can be assessed by analyzing key attributes as they relate to the organization, including leaders’ reliance onfact-based decision making.
  6. 6. 4 Analytics: The widening divideThe gap is widening The widening divide between organizations is also evident inThe growing gap between Transformed and Experienced the use of analytics to inform core business strategy andgroups, on the one hand, and the Aspirational group, on the day-to-day operations. Fully 70 percent of the Transformedother, is evident on two fronts: using analytics to create and 55 percent of the Experienced groups say they havecompetitive advantage, and integrating analytics into strategy increased their use of information and analytics in theirand operations. Among all respondents, the number of business strategy and operations in the past 12 months. Onlycompanies using analytics to create a competitive advantage 34 percent of the Aspirational group has done so (see Figure 4).has surged by 57 percent in the past year. Yet all of the gains incompetitive advantage have been made by the Transformedand Experienced groups, which grew by 23 percent and 66percent, respectively, from 2010 to 2011. The Aspirational Increasing integration of analytics into strategy and operationssegment, by contrast, fell 5 percent behind during the sameperiod (see Figure 3). Transformed 70%Increasing competitive advantage ExperiencedTransformed 55% 2011 80% 23% Aspirational increase 2010 65% 34%Experienced Percentage of total respondents who reported their organization had increased the level to which analytics and information was integrated into the business strategy and day-to-day 2011 63% operations in the past 12 months. 66% Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts increase Institute of Technology 2011. 2010 38% Figure 4: The rate at which Transformed and ExperiencedAspirational organizations have integrated analytics into their core business strategies and operations during the past year indicates that the 2011 37% competitive and performance gaps between these organizations 5% and Aspirational organizations will continue to widen. decrease 2010 39%Percentage of respondents who cited a competitive advantage using analytics year-over-year grouped by analytic sophistication levels.Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBMInstitute of Business Value analytics research partnership. Copyright © MassachusettsInstitute of Technology 2011.Figure 3: The ability of organizations to create a competitiveadvantage with analytics has surged in the past 12 months.
  7. 7. IBM Global Business Services 5Transformed organizations use analytics By comparison, analytics is less frequently relied upon formore widely decisions involving customers, business strategy and humanFinancial and operational activities have historically been resources. On average, fewer than one-quarter of Aspirationaldata-driven, and are typically the first areas where analytics is organizations said they rely primarily on data and analytics toadopted.3 A majority of organizations affirmed they rely on make key decisions in these areas, compared to one-half ofdata and analytics to manage financial forecasting, annual Transformed organizations (see Figure 5).budget allocations, supply chain optimization and streamliningoperations. Among Aspirational and Transformed organiza-tions alike, these were the four areas where leaders rely onanalytics to make decisions (see case study sidebar, “McKesson:Efficiency at scale”).McKesson: Efficiency at scaleImproving process efficiency within the supply chain has ment of inventory within its distribution centers. The ability tobeen standard practice in the last several years, particularly assess changes in its policies and supply chains has helpedfor those organizations that operate in high-volume, low- it increase customer responsiveness, as well as reducemargin businesses. McKesson, a U.S.-based pharmaceutical working capital. Overall, McKesson’s transformation of thedistribution and healthcare technology company, ranks supply chain has reduced more than US$100 million inamong the largest companies in the world, and has gone working capital.farther than most in incorporating advanced analytics into a McKesson recognizes that analytic tools are only part of thesupply chain operation that processes over two million equation. The company has invested significantly in buildingorders per day, and oversees more than US$8 billion of the analytical skills and capabilities of its entire workforce. Itinventory. has used the Six Sigma program as a consistent way ofFor management of in-transit inventory, McKesson has thinking about, and approaching, data-related issues. Thedeveloped a supply chain model that provides a highly accu- ability to weed out extraneous activity, minimize defects andrate view of its cost-to-serve – by product lines, transporta- reduce inventory through these structured improvementtion costs and even by carbon footprint. This detail provides methodologies has had significant payback in terms of time,the company with a more realistic view of how it is operating resource allocation and any given point in time, said Robert Gooby, vice president Just as importantly, company leaders now recognize that theof process redesign. company’s operations are so complex they can no longer be“But where most models are simplifications of the physical managed without analytics. “You reach stages where yourworld, this one has all of the complexities and all of the data intuition is no longer enough. You have to go into detailedof our reality. It allows us to quantify in extreme detail the analysis. There are too many things, too many opportunitiesimpacts of making fundamental changes to our operation.” that can exist undetected unless you dive into the details,”Gooby explained. “This model is not a simplification.” said Gooby.Another area where McKesson has applied advanced Together, the combination of process expertise andanalytics is simulating and automating the physical place- advanced analytics capability has provided McKesson with the right formulation for supply chain success.
  8. 8. 6 Analytics: The widening divide Respondents rely on data and analytics for: 10% 20% 30% 40% 50% 60% 70% 38% Customer Enhancing customers’ overall experience Optimizing the match of sales reps to customers Defining marketing campaigns Identifying target customers Human Allocating employees’ time and efforts resources Evaluating employee performance Strategic Establishing organizational strategic objectives Developing/refining new products or services Operational Streamlining operational processes Managing supply chain or logistics Financial Allocating annual budget Establishing financial forecasts Aspirational Experienced TransformedPercentage of respondents who indicated their organization relies on data and analytics to execute these activities. The question choices ranged from 1 = Intuition/Experience,3 = Equal parts experience/data to 5 = Data/Analytics. Respondents above selected 4 or 5.Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © MassachusettsInstitute of Technology 2011.Figure 5: The majority of organizations rely on analytics to make decisions about financial and operational activities, but even Transformedorganizations have room to increase the use of analytics in other areas.Transformed organizations leave Most organizations are expanding their use of analytics beyondothers behind finance and operations. However, the Transformed group hasToday’s business environment is characterized by increasing set the pace and has already distinguished itself in the market-uncertainty and competition. At the same time, customer place. Overall, organizations that used analytics for competitiveloyalty is eroding. All of this, and more, makes it very difficult advantage were 2.2 times more likely to substantially outper-for organizations to gain lasting benefits unless analytics is form their industry peers. Transformed organizations in thatapplied broadly. A piecemeal approach to analytics adoption group were 3.4 times more likely to do so.misses the opportunity to link supply chains to customerchannels, for example, or financial forecasts to more precise While Transformed organizations use analytics broadly acrossresource planning. the organization, their business objectives are highly focused. Using an analytical technique called binning, we found that Transformed organizations are concentrating on three critical areas that span the enterprise: speed of decision making, managing enterprise risk and understanding customers.
  9. 9. IBM Global Business Services 7 Focused on the need for speed in decision makingBinning: An advanced analytics techniquethat analyzes the responses of all respondents to Transformeda series of direct and indirect questions related 72%to a specific subject area. Responses are then Experiencedcategorized into bins based on the level of 49%interest. For this study, the bins were analyzedby sophistication groups. Aspirational 22% Percentage indicates respondents who exhibited an intense level of focus on the speedMoving faster with analytics of decision making grouped by sophistication level. This level of focus was assessed by analyzing a series of questions.Big data, and the fast pace and complexity of today’s market- Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBMplace require that leaders make decisions faster than ever Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011.before. Nearly seven out of ten CEOs interviewed for the IBMGlobal CEO Study 2010 told us that they already face unprec- Figure 6: An intense level of focus on the speed of making decisionsedented uncertainty and volatility – and are expecting more is one area where Transformed organizations are using analytics.ahead.4 We found that Transformed organizations keenlyappreciate the value of more precise and near-real-time Organizations focused on the speed of decision making aredecisions, and are more than three times more likely than using analytics to manage operations and improve output levelsAspirational organizations to focus intensely on the speed of based on real-time supply and demand management. Theydecision making (see Figure 6). automate their inventory replenishment processes and optimize production by doing things such as embeddingWhile proven instincts and experience were once a leader’s triggers that signal maintenance needs before equipmentbest guides, decision makers are now in a position to use an breaks down.extraordinary amount of data to inform their choices.Decisions based on large amounts of data, however, can’t come We found that two-thirds of Transformed organizations areat the price of speed. The digital transformation of business has relying on analytics to manage day-to-day operations, more thanput pressure on organizations to become more effective in four times the percentage of Aspirational organizations. In sometheir reactions to market shifts and to shorten the time to ways, using analytics for these immediate operational needs canmarket for new products and services. be more difficult than crafting long-term strategies. Whereas future strategies are typically iterated over time, operational decisions require precise and accurate insights to be available much more quickly: hence, the need for analytics speed.
  10. 10. 8 Analytics: The widening divideThe speed at which some organizations operate today outpaces A report from the Corporate Executive Board found thatthe processing capacity of the human brain. McKesson, for strategic risks, rather than financial risks, were responsible forexample (see case study on page 5), processes more than two 68 percent of severe market capitalization declines betweenmillion orders per day. To operate at this speed, McKesson has 1998 and 2009. These strategic risks include decline in demandembedded algorithms into the intake process to manage and competitor infringements on core products, destructiveorders, issue stockroom holds and process inventory replenish- price wars and margin pressure, and failure to expand newments without human intervention. revenue sources.5 Yet a 2011 American Productivity and Quality Center (APQC) study found that 56 percent of theWhen a pharmacist re-orders at the end of the day, the product respondents admitted they were least prepared to managearrives by 10 a.m. the next day. “That’s what we do,” said these kinds of risks.6 Managing strategic risk calls for a betterRobert Gooby, vice president of process redesign. “We need to line of sight into the organization and its markets, and anbe outstanding in our execution, and lower costs,” he said, ability to anticipate and act ahead of events that might derailexplaining the manpower to manually keep up with that level progress.of demand is cost prohibitive. In a US$112 billion company, henoted, even a 99.9 percent degree of accuracy in execution can Transformed organizations understand that in the face oflead to the loss of more than US$100 million. “We need to growing volatility and uncertainty, they must improve theirreduce our write-offs to the millions, not hundreds of millions. abilities to anticipate and predict. We found that 86 percent ofAnd when you’re talking about that level of accuracy, you have Transformed organizations were highly focused on under-to rely on data and analytics.” standing the full range of organizational risks that can impact their businesses. None of the Aspirational organizations hadAnalytics confers greater agility, acuity and certainty in today’s the same level of focus (see Figure 7).fast-changing business environment. It allows leaders to isolatethe components of complex activities and ecosystems, as well as Focused on identifying and managing enterprise risksto see and understand the dynamic interrelationships of theirbusinesses and the markets they operate in. Detecting and Transformedanalyzing trends and patterns, they can predict what is mostlikely to occur next. Using modeling techniques and what-if 86%scenarios, they can even prescribe the next best action. ExperiencedManaging risk for strategic advantage 6%Propelled by the digital transformation of entire industries andthe globalization of business operations, leading organizations Aspirationalcontinuously re-evaluate and re-define the strategic decisionsthat underpin their success. Almost three out of four Trans- 0%formed organizations use analytics to guide their future Percentage indicates respondents who exhibited an intense level of focus on usingstrategies compared to fewer than one in seven Aspirationals. analytics to better understand and manage enterprise risks. This level of focus was assessed by analyzing a series of questions.These new business and operating tactics promise competitive Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBMdifferentiation. But they are not without risk. Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011. Figure 7: The vast majority of Transformed organizations are intensely focused on using analytics to better address enterprise risks.
  11. 11. IBM Global Business Services 9By using analytics across the enterprise to monitor, detect and Engaging customers as individualsanticipate events, organizations are learning to avoid unneces- In addition to an intense focus on risk, our analysis revealedsary risk. Armed with real-time information, they are moni- Transformed organizations pay more attention to under-toring supply levels to help minimize disruptions. They are standing and engaging with their customers in new ways, ourautomating tasks – moving inventory from one location to analysis revealed (see Figure 8). They appear to be respondinganother when a trigger is set off, for example – and using more pervasively to a profound market shift, namely thepredictive analytics to anticipate needs based on dynamic explosion of new customer expectations generated in part byvariables like weather or political upheavals. The most adept our digital, social and mobile marketplace. Likewise, Trans-are forging bold strategies, such as taking a risk-based pricing formed organizations are also seizing the competitiveapproach to introduce services and products that once would advantage created when they understand their customers ashave been deemed too risky to develop. Others are anticipating individuals and engage them in more “authentic” or personal-regulations before they are enacted in their markets, proac- ized ways.tively adjusting their products to get ahead of regulatoryconstraints. Focused on customersChevron Corp., a global energy company, understands the link Transformedbetween risk and performance. Each drilling miss can cost thecompany upward of US$100 million. But the seismic surveys it 62%uses to evaluate potential drilling sites – each up to 50terabytes of data – take an enormous amount of time and Experiencedcomputing power to analyze.7 Chevron’s geologists always 49%knew they wanted to do more, but were restrained by one ofthe biggest challenges organizations face in using analytics: a Aspirationallack of bandwidth to focus on analytics. 34%In the summer of 2010, the U.S. federal government tempo-rarily suspended all deep water drilling permits in the Gulf of Percentage indicates respondents who exhibited an intense level of focus on using analytics to better understand and connect with customers. This level of focus wasMexico, regulation that essentially shut down all oil explora- assessed by analyzing a series of questions. Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBMtion in the region for nine months. Rather than sit idle, Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011.geologists at Chevron seized the opportunity. Using recentadvances in computing power and data storage capabilities, as Figure 8: Transformed organizations are intensely focused on usingwell as refinements to their already advanced computer models, analytics to create personalized relationships with customers.geologists were able to improve the odds of drilling asuccessful well at certain of its deep-water prospects to nearly 1in 3, up from odds of 1 in 5 or worse. The intensive review ledthe company to change the next year’s drilling schedule toexplore several higher-probability wells first.8
  12. 12. 10 Analytics: The widening divideTransformed organizations are learning to use customer Many organizations, for example, are learning to anticipateanalytics that yield something better than broad statistical customer needs by understanding what customers actually doaverages. Instead of segmenting customers along two or three when they go online. Pfizer Inc., a global biopharmaceuticaldimensions – sales and interactions, for example, or income, company (see case study on page 19), has taken this approach.age and geography – they are analyzing a broader set of “What’s really changed this past year or so, as we continued tocustomer dimensions. These dimensions can include every- evolve to a digital interaction and multi-channel model, is thething from transactional patterns to psychographic profiles of sheer magnitude of data we collect directly about ourhow customers prefer to shop, their likelihood of product customers. It’s more activity-based,” says Dr. David Kreutter,purchases and their cumulative value to the company. The vice president of the company’s U.S. Commercial Operations.result is a highly individualized understanding, otherwise “We’re focusing on discerning patterns early, and using themknown as a “market of one,” making authentic, or personalized, in a predictive way.” As a result, conversations initiated bycustomer engagement possible.9 representatives are tailored and approved based on these patterns, and consistent with policies to provide the informa-As one Australian respondent in the financial services industry tion that busy physicians need and are likely to act upon.noted, “As interactions become more electronic and distantfrom staff interactions, insight to customer behavior and needs Every organization, regardless of size, industry or market, hasis increasingly essential.” Analytical insights and actions help an opportunity to benefit from the petabytes of new data beingrestore the sense of a personal relationship that human tellers created. The impact of this information surge, of nearonce provided, he said. real-time data and unstructured content, is only beginning to be understood. But the past 12 months have already introducedTransformed organizations are putting analytical insights like some startling changes in what organizations are doing, andthese into the hands of customer–facing employees. Two-thirds underscore the growing gap between those who are standingof them support these employees with insights to drive sales still and those with a sense of urgency to act.and productivity compared to one-fourth of Aspirationalorganizations. Mastering analytical competencies To achieve analytics sophistication, we found, organizations typically master three competencies: (1) information manage- ment, (2) analytics skills and tools, and (3) data-oriented culture. We then dug deeper to define the capabilities required to achieve each one (see Figure 9). To help organizations improve on these competencies, we analyzed the specific capabilities required for each and compared the proficiency levels of Transformed organizations, which have largely mastered the competency, with Aspirational organizations, which lack most of the key capabilities.
  13. 13. IBM Global Business Services 11Analytics competencies Manage the data Understand the data Act on the data Information management Analytics skills and tools Data-oriented culture Skills developed as a Solid information foundation Fact-driven leadership core discipline Standardized data Enabled by a robust set of Analytics used as a management practices tools and solutions strategic asset Insights accessible and Develop action-oriented Strategy and operations available insights guided by insightsSource: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute ofTechnology 2011.Figure 9: Organizations must master three analytics competencies to achieve competitive advantage.Competency #1: Information management In a world where the quantity of data continues to riseCompanies with a strong information foundation are able to astoundingly, standards for data quality must be establishedtackle business objectives critical to the future of the entire with rigorous consistency across all business units andenterprise. Their robust data foundation makes it possible to functions. Is data being extracted from disparate data sources,capture, combine and use information from many sources, and both internal and external, accurately and thoroughly? Can itdisseminate it so that individuals throughout the organization, be used by multiple business units and functions? Is it compat-and at virtually every level, have access to it. This ability to ible with existing processes? Can it be managed in real time, orintegrate information across functional and business silos is a nearly so?hallmark of Transformed organizations, which are 4.9 timesmore likely to do this well than the Aspirational group.The information management competency involves expertise in avariety of techniques for managing data and developing acommon architecture for integration, portability and storage.
  14. 14. 12 Analytics: The widening divide Capability: Insights accessible and available • Make information readily accessible to employeesInformation management competency: – 65 percent versus 21 percent • Make insights readily available to all employeesThe use of methodologies, techniques and – 63 percent versus 16 percent.technologies that address data architecture,extraction, transformation, movement, Competency #2: Analytics skills and tools Organizations that deploy new skills and tools for analytics canstorage, integration, and governance of typically answer much harder questions than their competitors.enterprise information and master data Which customers, for example, are most likely to opt intomanagement. high-margin services? What will be the impact of a delivery route change on customer satisfaction and on the company’s carbon footprint? How will specific shortages within the supply chain impact future delivery capabilities? CompetencyThis competency also involves a rigorous approach to data in analytical skills and tools, essential for answering key businessgovernance, a structured management approach designed to questions, can be achieved through internal development andtrack strategic objectives against the allocation of analytical cross-training or external hiring and outsourcing in areas likeresources. Decision makers at every level of the organization advanced mathematical modeling, simulation and visualization.can then be confident they have the right information to dotheir jobs effectively and make informed decisions usinganalytics to guide day-to-day operations and future strategies. Analytics skills and tools competency:Transformed organizations effectively manage data(percent proficient, Transformed versus Aspirational Enhances performance by applying advancedorganizations) techniques such as modeling, deep computing,Capability: Solid information foundation simulation, data analytics, and optimization• Integrate data effectively – 74 percent versus 15 percent improve efficiency and guide strategies that• Capture data effectively – 80 percent versus 29 percent. address specific business process areas.Capability: Standardized data management practices• Use a structured prioritization process for project selection – 80 percent versus 45 percent• Use business rules effectively – 73 percent versus 39 percent.
  15. 15. IBM Global Business Services 13Advanced skills and techniques also make it possible to embed Competency #3: Data-oriented cultureanalytical insights into the business so that actions can take In a data-oriented culture, behaviors, practices and beliefs areplace seamlessly and automatically. Embedded algorithms consistent with the principle that business decisions at everyautomate processes and optimize outcomes, freeing employees level are based on analysis of data. Leaders within organiza-from routine tasks (for example, looking for customer records tions that have mastered this competency set an expectationto process a claim or repeatedly recalculating variables to that decisions must be arrived at analytically, and explain howdetermine the best distribution route). As a result, individuals analytics is needed to achieve their long-term vision.have time to apply data and insights to higher-level businessquestions, such as using analytics to detect fraud or findingpatterns that yield new customer insights.One key success factor in achieving mastery of this competency Data-oriented culture: A pattern ofis the creation of analytics champions. Transformed organiza- behaviors and practices by a group of peopletions have analytics champions that initiate and guide activities who share a belief that having, understandingby sharing their expertise to seed the use of analytics and using certain kinds of data andthroughout the enterprise. These specialists pair expertise witha deep understanding of the business. They are able to provide information plays a critical role in the successguidance in getting started with analytics, as well as identifying of their organization.resources for ongoing support. Without an established internalcompetency, it’s harder for beginners to recruit needed talent.Transformed organizations understand the data Organizations with this culture are likely to excel at innovation(percent proficient, Transformed versus Aspirational and strategies that differentiate them from their peers (see caseorganizations) study sidebar, BAE Systems: A new business model takes flight). They typically benefit from a top-down mandate, andCapability: Develop skills as a core discipline leaders clearly articulate an expectation for analytical decision• Have strong analytical skills – 78 percent versus 19 percent making aligned to business objectives. Transformed organiza-• Have analytics champions – 59 percent versus 18 percent. tions, in fact, are nearly five times more likely to do this thanCapability: Enabled by a robust set of tools and solutions Aspirational organizations.• Excel at visualization tools – 74 percent versus 44 percent• Excel at analytical modeling – 63 percent versus 28 percent. In these data-driven cultures, expectations are high. Before “giving the green light” to a new service offering or opera-Capability: Develop action-oriented insights tional approach, for example, leaders ask for the analytics to• Develop insights that can be acted upon support it. They express their conviction in the value of faster – 75 percent versus 38 percent develop and more precise decisions by using analytics to guide to• Use algorithms to automate and optimize processes day-to-day operations. Employees are confident they have the – 68 percent versus 31 percent. information to make data-based decisions. They are encour- aged to challenge the status quo, and follow the facts in order to innovate. Transformed organizations are more than twice as likely as Aspirational groups to be receptive to new insights.
  16. 16. 14 Analytics: The widening divideBAE Systems: A new business model takes flightLike most organizations, BAE Systems once used analytics At the same time, Peters’ team began developing and demon-primarily for the basics – modeling costs and analyzing other strating a whole suite of training courses. Best practices werefinancial information. However, when the global defense put into the company’s Life Cycle Management processes,contractor moved into long-term “performance-based” with techniques regularly shared at communities of practicecontracts for its military and technical services, it needed to events. After five years, the goal of all these activities remainsstrengthen its analytical capability. The new performance- the same: to make sure consistent “best practice” analyticalbased contracts shifted long-term risk of equipment avail- capabilities for modeling solutions and business impact areability from customers to BAE Systems. embedded in BAE Systems projects at the point of use.To make this business model work, BAE Systems needed The central analytics team can advise, train and initiate. Butanalytics. So five years ago, Michael Peters, Head of Business once an analytics project begins, the individual business unitand Solution Modeling for BAE Systems, was appointed to takes control of the ongoing work, and funds the requiredaddress this issue. The business challenge, he explained, was expertise. Peters helps them with this transition by using histo answer the fundamental business questions posed by the network of contacts to quickly form virtual teams of subjectnew strategy. “How do we know we can guarantee the avail- matter experts from across BAE Systems global talent poolability of the particular system we’re offering? How do we and external consultancies to meet the needs of each team,know we will make revenue on this and can actually perform bringing the best combination of skills to that particular busi-against the key performance indicators in the contract, and, ness’s problem.indeed, what should the KPIs be?” He needed to find an inte- Working together, the centralized team, business unit expertsgrated and consistent approach to making those contract and virtual teams have radically increased speed of response.decisions so that BAE Systems understood the relationship “When we first modeled a performance-based ‘availability’between cost, performance, revenue and risk. project in the air sector, it took a considerable period becausePeters put together a methodology and a small team to we had to learn, develop and adapt new techniques, andsupport the new business model. His analytics champions because it was such a huge program,” Peters said. “Afterfrom across the business units showed leaders in the major several iterations with similar projects and the reuse of modelsprograms that a common methodology, which worked for the developed over the last five years, the air sector can now doair sector, would also work for its land and sea divisions. Now, its modeling and analysis relatively quickly and support towith mature capabilities in the air sector and growing capabili- decision making now takes hours rather than weeks. Genericties elsewhere, the common methodology is used to embed building blocks are created to re-use analytical know-howanalytical capability in projects, enabling leaders to make across projects.” He pointed out, however, that re-use ofdata-driven decisions for formulating contract commitments models from one project to another has inherent risks unlessand optimizing through-life performance. very carefully done; hence the need for continued training, updating and sharing of expertise.How does a small core team, just four people and a network ofsubject matter experts in the business units, change the On average, Peters has found the payback on the analyticsmindset within a global company to enable a shift in analytical investment to be on the order of 20-50 to one, much of it asthinking to support their major programs? From the beginning, direct savings to customers. By using analytics to take onPeters was fortunate to have two very senior sponsors. These performance risk while passing on the cost savings, BAEconnections bolstered credibility when his corporate team Systems moves closer and closer to its customers, and fartherengaged business units on the relevance of business and and farther away from competitors.solution modeling, and ensured effective sponsorship throughthe allocation of resources to support the business’s priorityprograms.
  17. 17. IBM Global Business Services 15Transformed organizations act on the data(percent proficient, Transformed versus Aspirational Key characteristics of a Transformed organizationorganizations) Ability to analyze data 78%Capability: Fact-driven leadership Ability to capture and aggregate data 77%• Open to new ideas that challenge current practices – 77 percent versus 39 percent Culture open to new ideas 77%• Individuals have data need for decisions Analytics as a core part of business strategy and operations 72% – 63 percent versus 16 percent. Predictive analytics embedded into processes 66%Capability: Strategy and operations guided by insights Insights available to those who need them 65%• Guide future strategies with analytics – 72 percent versus 15 percent Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts• Guide day-to-day operations with analytics 67 percent versus Institute of Technology 2011. 15 percent. Figure 10: Transformed organizations rate themselves as highlyCapability: Analytics is used as a strategic asset effective at each of the key characteristics, represented by the percentages.• Use analytics as core part of business strategy and operations – 72 percent versus 15 percent• Increased use of analytics in the past year The breadth of these leading characteristics suggests that – 70 percent versus 34 percent. excellence in all three analytics competencies noted in our study is fundamental to the competitive use of analytics. AnEach of these three competencies – information management, organization may be able to capture, integrate and analyze itsanalytics skills and tools, and data-driven culture – is critical to data, but it will not likely be able to act on what it finds unlessanalytics sophistication. Mastery of these competencies is how it has a culture that is ready to embrace ideas that depart fromTransformed organizations manage, understand and act on intuition or experience. For example, a leading global bankdata to create a competitive advantage. transformed its operations when it decided to analyze the impact of debit and credit card purchases on mortgage default settlements. The bank was able to use this new customerThe most distinctive characteristics of information effectively because it developed a culture thatTransformed organizations encouraged multiple departments to collaborate on managing,For organizations seeking to emulate Transformed organiza- understanding and acting quickly on data and ideas that wenttions, it is useful to know which actions have the biggest impact above and beyond traditional approaches to lending decisions.on their level of sophistication. Analysis showed that of all thecharacteristics exhibited by Transformed organizations, theirproficiency (represented by the percentages) in six characteris-tics distinguished them the most (see Figure 10).
  18. 18. 16 Analytics: The widening divideIn using analytics as a strategic asset core to their business and Two paths to transformationoperations, Transformed organizations embed data-based While Transformed organizations serve as benchmarks forinsights into every process – from scenarios that manage risk, establishing analytics competencies, almost half of the organi-to algorithms that process orders coming in through new zations we surveyed are at the Experienced level, somewheredigital channels. Going one step further, they also empower between the most basic and the most advanced segments.10 Weemployees to act confidently and decisively in a fast-paced took a closer look at this large transitional segment to bettermarketplace. understand those organizations (see Figure 11).For example, a global telecommunications company faced We found that organizations, after starting, diverge in theircustomer attrition that was rising by double-digit percentages. approach to analytics. We characterize the alternative paths asIt quickly succeeded in stemming these defections after using Specialized or Collaborative, based on the way analytics issocial network analysis to re-segment its portfolio, then leveraged and deployed:comparing segment profitability to create customized solutionsfor use by call center employees. Only by providing data and • The Specialized path. Deep analytics expertise is developedinsight to employees across the enterprise are organizations within lines of business or specific functions using a wideable to benefit from fresh perspectives of customers and array of analytical skills and techniques. Analytics is used tooperations. improve specific business metrics. Slightly more than half of the Experienced organizations took this route.Paths to transformation High Enterprise driven Collaborative Transformed path Information management Data-oriented proficiency Experienced culture Specialized Aspirational path Low Line-of-business driven Low Analytics skills and High tools proficiencySource: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute ofTechnology 2011.Figure 11: Experienced organizations take either a data-centric enterprise-driven path or a skills and tools-centric path on their journey towardanalytic transformation.
  19. 19. IBM Global Business Services 17• The Collaborative path. An enterprisewide information efficiency. They use their analytical prowess in advanced skills platform is created, enabling insights to be developed and and techniques, such as predictive modeling, to focus on shared across lines of business. Analytics is used to improve orchestrating marketing campaigns, and finding the best match enterprise objectives. Slightly fewer than half of Experienced between individual customers and sales representatives. organizations took this route. In addition to the revenue gains resulting from these programs,See Figure 12 for a comparison of the relative proficiency the Specialized path takes organizations through a wide range oflevels these paths exhibit for each of the three analytics efficiencies and cost savings. Predictive scenarios and simula-competencies. tions, for example, make it possible to understand how changes caused by internal strategies and external forces will impactThe Specialized path can lead to well-defined gains individual units in terms of resource allocations, revenue growthWith impetus coming from within lines of business, organiza- and operating costs. We found that organizations on this pathtions on the Specialized path pragmatically focus on improving increased their use of analytics over the last 12 months, buttheir operational metrics while growing revenue and increasing rarely as a core part of the overall business strategy.Observed competency levels Specialized Information management Collaborative Solid information foundation Standardized data management practices Insights available and accessible Analytics skills and tools Skills developed as a core discipline Enabled by a robust set of tools Delivers action-oriented insights Data oriented culture Fact-driven leadership Analytics used as a strategic asset Strategy and operations guided by insights Level of competency Rudimentary Minimal Moderate Significant MasterySource: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute ofTechnology 2011.Figure 12: Each path to transformation has unique strengths and weaknesses in the three competencies, which pinpoint areas forimprovement and investment.
  20. 20. 18 Analytics: The widening divideThe Specialized path and the three competencies 3. Data-oriented culture will require extra momentum. On the1. Information management is siloed. Because advanced tools and Specialized path, organizations are open to exploring newtechniques abound here, organizations on the Specialized path analytical techniques and applying them liberally withinmay well be the first to meet today’s newest data challenges: discrete areas of the business. However, when it comes tofinding ways to mine real-time information from the Internet taking an enterprise approach, most respondents consideredand unstructured content from emails, interaction logs and the organizational challenges extremely difficult to confrontother internal documents. However, integrating and dissemi- and resolve. Political constraints and a lack of cohesion withinnating data across the enterprise is a hurdle they have yet to the organization can be major barriers to integrating data andovercome. Functional and line-of-business leaders, for using analytics for enterprisewide objectives.example, retain control of “their” information and maydetermine data definitions unilaterally. Unless these hurdles are overcome, the Specialized path to analytical transformation may reach a point of diminishingOn the Specialized path, identification and selection of projects returns as siloed programs impede establishment of analytics asis made within business units, often by using process-driven a core enabler of business strategy and operations. Either aproblem-solving methodologies like Six Sigma. Analysis takes strong push from senior leaders or grassroots momentum fromplace where and when insights are needed, or by analytics individuals at many levels will likely be required to create adepartments within the business lines. While this approach culture that is open to new ideas and ready to move forward onserves individual business lines well, it can create or deepen the basis of fact-based insights.barriers to developing the information management compe-tency, because collaboration for effectively integrating and The Collaborative path crosses organizationalsharing enterprise data is insufficient or lacking. boundaries By contrast, organizations taking the Collaborative path use2. Improvement of analytical skills and tools is a passion. On this analytics more broadly and effectively. Unlike Specializedpath, organizations are eager to keep up with new technical organizations, which typically have pockets of excellence in oneadvances and apply them to the data they have on hand. To do area or another, Collaborative organizations achieve consistentthat, they develop and cross-train a strong talent pool that can levels of effectiveness across functions. Like a rising tide thatuse a wide variety of analytical approaches to understand not lifts all boats, analytics in Collaborative organizations spreadsjust what’s happening, but why. Within their individual lines of beyond finance and operations to bring capabilities to the samebusiness, these organizations have the capability to spot and levels across unit and function – from marketing and sales toanalyze trends, patterns and anomalies. human resources to strategy and product development.Passionate about a wide range of analytical tools, organizations By connecting information and programs across silos, organi-on this path embark on a journey that takes them far beyond zations can create an agenda that makes analytics core tospreadsheets and basic visualization techniques. For budget operations and business strategy. In doing so, the Collaborativeplanning and resource allocation, what-if scenarios are used to path creates an appetite for new ways of understanding valuepredict threats and opportunities. Algorithms automate tasks and competitive advantage that permeates the entire organiza-ranging from mundane report development to complex data tion (see case study sidebar, Pfizer: Next generation salesanalysis. And a wide range of discrete business processes, such insights through analytics).as automatic inventory replenishment or call center assign-ments, are optimized by embedded algorithms.
  21. 21. IBM Global Business Services 19On the Collaborative path, organizations draw on information positioned to create seamless one-on-one interactions withfrom many functions and departments. They develop ways to customers across channels and over time. Not surprisingly,improve the customer’s experience and overall relationship they are twice as likely as organizations taking the Specializedwith the organization. Consequently, they may be better path to provide customer-facing employees with access to data and insights.Pfizer: Next generation sales insights through analyticsAfter years of exclusive sales from its Lipitor patent, which engaging each physician found it,” explained Kreutter. “Ourdelivered almost 20 percent of its annual U.S. revenue in master customer dataset has all that click-stream data for2010, the patent’s looming loss made capital allocation a top each representative and each doctor they met, nearly in real-priority at Pfizer Inc., a global biopharmaceutical company.11 time compared to our syndicated data.”“From a business challenge perspective, taking billions of The value of the interactive data lies in linking behaviors –dollars out of a corporation in one fell swoop is a little bit what sales content is used by reps, how physicians responddaunting” said Dr. David Kreutter, vice president of U.S. com- to it, and whether there is a corresponding uptick in pre-mercial operations. He believes the new business environ- scriptions. Business analysts will then be able to determinement makes analytics more critical than ever before, whether, for example, a drop in prescribing by that physicianbecause each expenditure must be rigorously evaluated for is tied to flawed execution (if the rep failed to provide theits contribution to company strategy. most appropriate approved available information to physi-With scientific research at the core of its business, the com- cian at the right time) or the strategy is flawed (if thepany has no lack of skills in areas of quantitative analysis. approved product information delivered according to planYet too often, Pfizer’s business leaders have been able to did not meet physician’s needs or preferences). As presenta-pick and choose which decisions should be guided by data. tions of all kinds are tracked against actual prescriptions inThose days of “cherry picking” are going away, Kreutter the days and weeks ahead, strategy and execution can besays, because without the multi-billion dollar operating buf- finely calibrated. New data-based insights can be efficientlyfer of past years, the stakes are simply too high. reviewed, approved and delivered to reps along with the daily synchronization of data between the field and head-Kreutter believes analytics can play a new role in a leaner by enabling a “frame shift” based on understand-ing the interplay between strategy and execution. Use of How will Pfizer stay abreast and ahead of healthcare industrymarket data remains foundational. Generally, every major changes, including new prescribing dynamics brought on bypharmaceutical company knows which products doctors are physician participation in new types of healthcare organiza-prescribing. But it takes six to eight weeks before this data tions? Competitive advantage, Kreutter believes, will to aarrives, a time lag that limits the usefulness of the data. great degree come from hiring and motivating an analytic tal- ent pool on par with those in more analytically sophisticatedNext-generation insights, says Kreutter, will be gleaned from industries, such as consumer goods and financial services.streams of data uploaded daily by representatives in the Most importantly, this talent needs to be outfitted with con-field. Armed with tablet devices, Pfizer reps customize infor- text and knowledge about Pfizer’s particular business chal-mation using interactive presentations and then synchronize lenges and compliance requirements. At that point, saysdata obtained from their sales meetings at the end of every Kreutter, “The question isn’t how much money do we spendday. “We’re able to see things like the order of presentations, on data and analytics; it’s how much value are we gettingthe messages that were delivered, the responses, and how from them?”
  22. 22. 20 Analytics: The widening divideThe Collaborative path and the three competencies Collaborative organizations have cultures where individuals are1. Information management is an enterprise endeavor. On the prepared to challenge current ideas and practices on the basisCollaborative path, organizations gain valuable ground by of new information. To support this culture, they are twice asapplying themselves to the integration of disparate data into an likely to provide insights to anyone in the organization whoenterprise analytics platform. needs them. As a result, they’ve democratized the access to data and insights, empowering employees and executives alike.This cross-unit endeavor is enabled by a willingness to share These organizations enjoy executive-level endorsement for theand accept data and insights from other parts of the organiza- broad use of analytics to manage day-to-day operations andtion. The enterprise moves toward consistent data definitions, shape future management standards and shared responsibility foranalytics. Governance and information quality become leading Understanding the path aheadconcerns, and the organization works its way through “turf Ideally, as organizations begin their transformations towars” that almost certainly will accompany the creation of an analytical sophistication, they start building a solid informationenterprisewide information management foundation for the foundation and acquiring analytics capabilities simultaneously.entire enterprise. In reality, we find that they tend to do one or the other, based on their existing culture, organizational structure and skills.2. Analytics skills and tools are not fully developed. Despite compar- The two paths observed in our analysis represent reasonableative weakness in analytics skills and tools, organizations on the and pragmatic courses of action based on the strengths andCollaborative path are adept at using visualization techniques. weaknesses of individual organizations.Data visualization and departmental dashboards providesnapshot views of performance. Scenarios are developed to A propensity toward acquiring new analytical techniques and“paint a picture” showing how changes in strategies and refining skills steers some organizations toward the Specializedprocesses can impact the business. These “user-friendly” path, with momentum for analytics coming from individualapproaches help individuals who are less accustomed to departments or functions. Skeptics elsewhere can then beworking with large quantities of data interact with information converted when urgent business issues are addressed and theand make analytically based decisions. value of analytics is demonstrated.3. A data-oriented culture has emerged. Organizations on the Where the culture responds well to enterprise initiative andCollaborative path integrate data from silos and then dissemi- innovation, organizations will lean toward the Collaborativenate the insights across the enterprise. They are almost three path. Targeting analytics for key strategic objectives createstimes more likely to use analytics to guide future strategies support for shared investments and consensus-based decisionthan Specialized organizations, and twice as likely to rely on making. As a result, analytics will be used sooner rather thananalytics for day-to-day operations. later for strategic objectives aimed at increasing competitive advantage.
  23. 23. IBM Global Business Services 21Each path poses different challenges. Organizational issues The main challenge on the Collaborative path? Because ofmay be particularly difficult on the Specialized path, where their ongoing focus on integrated data management, thesesolid leadership consensus is needed to integrate siloed data. In organizations may be inclined to be so persistent in gettingaddition, organizations where capabilities are developed largely data to its “ideal state” that they wait to acquire the tools andfrom the ground up are likely to progress unevenly until skills to analyze is embraced as a leadership mandate. Thus, existing conditions are likely to determine which path isAn instructive finding supports this concern about the Special- taken by a particular organization. To keep moving forwardized path. Overall, respondents were nearly twice as likely to with confidence, however, every organization needs to thor-find organizational challenges difficult to resolve compared to oughly understand its analytics strengths and weaknesses, astechnology challenges (see Figure 13). Those on the Special- well as the terrain ahead.ized path will need to overcome organizational difficultieseventually while collaborative organizations, having already Moving forward with analyticsmade inroads on culture and consensus, may have an easier In this study, we have laid out three competencies based on ourjourney in front of them. analysis of how Aspirational, Experienced and Transformed organizations use analytics, and what they were able to achieve competitively. The challenge, however, is typically not inRespondents who rate these challenges as extremely finding the business case; it’s in identifying the starting pointdifficult to resolve and creating a plan. To help organizations begin and reachOrganizational challenges their goals, we make the following suggestions based on our experience with a broad spectrum of organizations in multiple 44% industries: 1.8x greater difficultly • Recommendation 1: Assess your analytics sophistication 24% • Recommendation 2: Improve your analytics competencies • Recommendation 3: Use an information agenda to connectTechnology challenges your path to your competencies.Source: The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBMInstitute of Business Value analytics research partnership. Copyright © Massachusetts Instituteof Technology 2011.Figure 13: Changing the way people behave and interact with oneanother within an organization poses a more difficult challenge thanchanging their tools or technologies.
  24. 24. 22 Analytics: The widening divideRecommendation 1: Assess your analytics Transformedsophistication Look ahead. If your organization already has an integratedHow close is your reality to the vision of your organization information platform as well as a robust set of tools and talent,transformed by analytics? Consider whether some functions or you probably have a culture where information is accessible,some lines of business are farther along than others, and bring abundant and constantly scrutinized for possible actions. Thepeople together to share aspirations and concerns as they relate need here will be to continuously refresh your informationto analytics. Explore the big business challenges that can be agenda and stay attuned to unexpected challenges: newaddressed by analytics and evaluate together your organiza- competitors and customer expectations; emerging digitaltion’s readiness to address them. Figures 1 and 12 contain business models; and the capture of big data, much of itinformation to help you assess your level of analytics sophisti- unstructured and rapidly streaming through a digitallycation and understand next steps. connected world. Another key is to create consistency in the level of analytics use and skills with your organization byAspirational targeting areas that may be lagging behind.Start with the most important metrics. You may have a visionfor analytics, but have not made it part of an information Recommendation 2: Improve your analyticsagenda, with an analytics strategy that is measurable and can be competenciesacted upon. Data management is ad hoc, not part of a gover- Having assessed your path, focus on the capabilities withinnance system, while spreadsheets and standardized reports each competency to drive improvements. If you’re on thecapture all your organization’s analytical activity. Business Collaborative path, you will need to work more on developingleaders across levels should launch efforts to select business analytics skills and tools. If you are on the Specialized path, youchallenges that can be addressed analytically and set specific will need to develop a strong information managementobjectives for doing so. Dashboards and scorecards should be platform and orient your culture to the use of data. On eitherused to monitor performance against these targets. path, set regular reviews for assessing progress in all competen- cies.ExperiencedUnderstand your path. If you have made some progress toward Information managementanalytical transformation, determine which path you have A strong information foundation makes high-quality informa-taken – Specialized or Collaborative? Use Figures 12 or 14 to tion accessible to all who need it. What steps are you taking toassess your organization’s strengths and weaknesses. Play to help ensure that employees have the data and tools to do theiryour strengths but remediate your weaknesses. If you’re jobs and make decisions that support the business? Determinepursuing analytics projects but avoiding internal conflicts over what’s holding people back from using available information. Isdata standards, find out how other organizations have negoti- it too difficult to digest? Too old to be useful? Too inconsis-ated these shoals. If you’re putting all of your resources into tent? Do sources need to be more transparent? Look also atestablishing or meeting enterprise data standards, start levels of segmentation – are they too broad or too narrow, anddeveloping analytics skills and tools to reap value from the are users free to redefine them?information you have. Get support for acquiring tools andskills that will bring state-of-the-art analytical capabilities intoyour organization.