SAS/MIT/Sloan Data Analytics


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SAS/MIT/Sloan Data Analytics

  1. 1. From Value to Vision:Reimagining thePossible withData AnalyticsWhatmakescompaniesthataregreatatanalyticsdifferentfromeveryoneelseBy MIT Sloan Management Review and SAS InstituteIn collaboration withRESEARCHREPORTSPRING 2013FINDINGS FROM THE 2013 DATA & ANALYTICS GLOBALEXECUTIVE STUDY AND RESEARCH REPORT
  2. 2. Portions of this report previously appeared in “Innovating With Analytics,” MIT Sloan Management Review, Volume 54,no. 1 (Fall 2012) 47-52.Copyright © MIT, 2013. All rights reserved.Get more on data and analytics from MIT Sloan Management Review:Visit our site at the free data and analytics newsletter at us to get permission to distribute or copy this report at or 877-727-7170.AUTHORSDAVID KIRON is the executiveeditor of MIT Sloan ManagementReview’s Big Ideas initiatives.He can be reached at BOUCHER FERGUSON isthe Data & Analytics contributingeditor at MIT Sloan ManagementReview, researching the currentand new analytical approachesthat change how executives makedecisions and innovate. She canbe reached at KIRK PRENTICE is thechief research officer at SASInstitute Inc., specializing inderiving insights from qualitativeand quantitative informationto help address key businessissues. She can be reached Mangelsdorf, Editorial Director, MIT Sloan Management ReviewMax Harless, Graphic Designer, MIT Sloan Management ReviewMalene Haxholdt, Global Analytics Marketing Manager, SAS Institute Inc.CONTRIBUTORS
  3. 3. 2 / Introduction3 / Signs of an Analytics RevolutionCASE STUDY: Oberweis Dairy4 / Three Ways to Compete with AnalyticsCASE STUDY: Caesars Entertainment6 / The Analytical Innovators• Mindset and Culture• Key Actions• Outcomes: Power Shifts to Those with Insight11 / On Becoming an Analytical Innovator• The Analytically Challenged• The Analytics Practitioners17 / ConclusionCONTENTSRESEARCHREPORTSPRING201318 About the Research 19 AcknowledgmentsMORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 1
  4. 4. How organizations capture, create and use data is changing the way we work and live. This big idea, which isgaining currency among executives, academics and business analysts, reflects a growing belief that we are onthe cusp of an analytics revolution that may well transform how organizations are managed, and also trans-form the economies and societies in which they operate.Among companies,this revolution has several dimensions.First,companies have more data to use than everbefore,at a volume and with a variety that are unparalleled in human history.Second,by using internal and ex-ternal data,companies are beginning to understand patterns of consumer activity that had once been impossibleto perceive or act upon.And third,companies are using new analytic tools and services to understand their ownoperations and behavior at a much finer level of detail,enabling new questions to be asked and answered.At the vanguard of this revolution are companies that are using analytics to compete and to innovate.Understanding these companies gives insight into both the direction and the pace of the analytics revolu-tion. Lessons about what hurdles these companies face and how they are addressing them suggest a pathforward for many other companies.As part of a multiyear research initiative,MIT Sloan Management Review is partnering with SAS better understand companies that are shaping (and are being shaped by) this analytics revolution.In2012,we conducted a survey of more than 2,500 respondents in two dozen industries.Fifty-five percent of therespondents were executives at the vice president/director level or above.The survey included over 30 detailedquestions about how organizations are using data to advance their business objectives.We also interviewed 29academics and senior information technology executives at a diverse group of companies,including eBay,Inc.,Kaiser Permanente,LinkedIn Corporation,Neiman Marcus,Inc.,PayPal,Inc.,PepsiCo,and SouthernCalifornia Edison Company.Fully 67% of survey respondents report that their companies are gaining a competitive edge from theiruse of analytics.Among this group, we identified a set of companies that are relying on analytics both to gaina competitive advantage and to innovate. These Analytical Innovators constitute leaders of the analytics rev-olution. They exist across industries, vary in size and employ a variety of business models. They also share adistinctive orientation toward data and analytics that includes three key characteristics:1. A widely shared belief that data is a core asset that can be used to enhance operations, customer ser-vice, marketing and strategy2. More effective use of more data for faster results3. Support for analytics by senior managers who embrace new ideas and are willing to shift power andresources to those who make data-driven decisionsThis report provides an in-depth look at Analytical Innovators, including their beliefs, practices and out-comes. Our profile of this group provides insights into what success factors are currently required to excel intoday’s analytics revolution. In addition, we offer a framework that shows how other companies — regard-less of their analytical sophistication — can become more like Analytical Innovators.S P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C SINTRODUCTION2 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICS
  5. 5. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 3Signs of an Analytics RevolutionIncreasingly, top thinkers in academia and business believe that analytics, especially analytics con-nected with big data, is going to be a driving force in our economy and society in the next 10 to 20years. This belief is being matched with action in the public and private sectors.In February 2013, MIT Sloan launched a digital economy initiative to explore how digital tech-nologies are influencing both productivity and employment, declaring,“The digitization of theeconomy is one of the most critical issues of our time.”1The broad use of analytics is an importantfactor in the development of the emergent digital economy.This view is supported by General Electric Company executives Peter Evans and Marco Annunziata, whoargue that the“industrial Internet”— a system of machine-to-machine sensors — will add $10 trillion to $15trillion in economic benefit to the global gross domestic product through 2030.2GE is putting its moneywhere its mouth is, investing $1 billion in developing the talent, software and analytic tools to better identifywhen machines need fixing or replacement.3A recent study of senior executives at Fortune 500 companies found that 85% of those organizations hadlaunched big data initiatives.4Intel announced a five-year, $12.5 million partnership with MIT to create aresearch center that will focus on big data. The state of Massachusetts, host to more than 100 companies thatemploy more than 12,000 people in big data-related businesses, has launched a public-private Big Data Con-sortium to grow its innovation economy.5In 2011, big data companies received more than $350 million inventure capital.6Alex “Sandy” Pentland, director of the Human Dynamics group at the MIT Media Lab, argues that as wemove into a society driven by big data,“most of the ways that we think about the world change in a ratherdramatic way”:This is the first time in human history that we have the ability to see enough about ourselves that we canhope to actually build social systems that work qualitatively better than the systems we’ve always had. …S P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C SFrom Value to Vision:ReimaginingthePossiblewithDataAnalytics
  6. 6. 4 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C SWe can potentially design companies, organi-zations, and societies that are more fair, stableand efficient as we get to really understandhuman physics at this fine-grain scale. Thisnew computational social science offers incred-ible possibilities.7While much of the promise of data and analyticsis couched in terms of “big data,” some suggest thattoday’s big data will likely become just tomorrow’sdata.8If we are to achieve anything close to thepromise of big data (or data),it will need to become,as one research report says,“a key basis of competi-tion, underpinning new waves of productivitygrowth, innovation, and consumer surplus.”9And this is precisely what our research team andothers are beginning to see in the market.Companiesthat are leading the analytics revolution are alreadymaking data and analytics a source of competitivedifferentiation. In 2012, the MIT Center for DigitalBusiness, along with research sponsor CapgeminiConsulting, completed a two-year study with morethan 400 companies to determine which companieswere achieving a “digital advantage” over industrypeers through their use of analytics, social media,mobile and embedded devices. The study found thatcompanies that do more with digital technologies —and support their digital investments with leadershipand governance capabilities — are 26% more profit-able than their industry peers, and outperformaverage industry performance by 6% to 9%.10Companies that many of us deal with every dayare already making use of data to advance a varietyof business goals and to help consumers:Kaiser Permanente collects petabytes of health in-formation on its 8-million-plus members, afantastic amount.Some of this data was used in anFDA-sponsored study to identify risks with Vioxx,Merck’s pain medication,which was pulled shortlyafter the research identified a greater risk of heartattack in a subset of the patient population.Southern California Edison is collecting hourly(rather than monthly) data on customer usagefrom new digital smart meters in millions of resi-dences. It will soon be monitoring and givingfrequent feedback to customers about their energyuse, a significant benefit for energy grid manage-ment and customer service.Pepsi has an ordering algorithm that lowers therate of inventory out-of-stocks. The companyshares information from this application withpartners and retailers, improving its relationshipswith key stakeholders.Three Ways to Competewith AnalyticsYou don’t have to lead the analytics revo-lution to create value from analytics.This past year, two-thirds of our surveyrespondents said they are gaining a com-petitive advantage from their use of analytics. (SeeFigure 1: Finding Competitive Advantage with Ana-lytics.) This represents a significant jump from our2011 Global Executive Survey (58%) and an evenlarger jump from the 2010 survey (37%). Otherresearch supports this trend.11Companies that gain a competitive edge withanalytics can be found at all levels of technologicalsophistication. At one end are traditional compa-nies like Illinois-based Oberweis Dairy, which haveolder technologies but add new analytics talent.(See case study on next page.) At the other end arecompanies like LinkedIn, which include analytics aspart of their corporate DNA but still find new waysto capitalize on analytic insights.In 2006, LinkedIn had 8 million users, but some-thing wasn’t clicking: Users weren’t seekingconnections, a key component of success, at the ex-pectedrate.ReidHoffman,thecompany’scofounder(and current executive chairman), brought in Jona-than Goldman, who has a background in physics, toFIGURE 1:FINDING COMPETI-TIVE ADVANTAGEWITH ANALYTICSThe percentage ofcompanies thatcreate a competitiveadvantage withanalytics is trendingupwards.37%58%67%2010 2011 2012Percentagebelieving thatbusinessanalytics createsa competitiveadvantage intheir organization
  7. 7. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 5test different ways to encourage members to link toone another. Goldman came up with the algorithmthat would become the “People You May Know”function on LinkedIn’s homepage — arguably oneof the site’s key user benefits today.12Because the product team initially did not seevalue in the algorithm, Hoffman suggested Gold-man run a test on LinkedIn pages in the form of anadvertisement: “Find out what happened to yourformer colleagues or classmates.” The result was astaggering 30% click-through rate in an industrythat views click-through rates of 1% to 3% as a suc-cess. LinkedIn raced ahead of its competitors.Some of the more traditional companies strug-gling in mature industries are increasingly turningto analytics for insights that provide an edge.A casein point is in the pharmaceutical sector, wherecompanies have found themselves challenged bytheir payers,the largest managed-care customers orgovernments.Milkmen, glass bottles, door-to-door service.In some ways, not much has changed at Oberweis Dairy, Inc. fromits founding at the turn of the last century. Milk is still procured fromlocal dairy farms. Dairy products are additive-free. Milk is delivered inglass bottles to customers’ doorsteps, although nowadays Oberweisuses refrigerated trucks rather than horse-drawn milk carts.In other ways, everything is changing at the nearly 100-year-oldcompany.What started as an Illinois farmer selling his surplus milk to neigh-bors in 1915 is now an analytics-savvy company with revenuesapproaching $100 million. Oberweis Dairy has three distribution chan-nels: home delivery, with thousands of customers; retail, with 47corporate and franchise stores; and wholesale, to regional and na-tional grocery chains like Target. In 2012, the company began lookingto expand from its Midwestern roots to the Eastern Seaboard.At Oberweis, the usual approach to regional expansion was tobring together operations executives to figure out the best configura-tion for these resources. This time was different.This time, CEO Joe Oberweis brought to the strategy table anexecutive with just three years’ experience at the company, BruceBedford, vice president of marketing analytics and consumer in-sights. He had been brought on board in 2009 to inject someanalytical thinking into the family-run company. However, he was arelatively unknown figure to the operations executives. According toBedford, on the day of the strategy meeting:The CEO invited a large number of operational decision makers— literally, people who manage the company’s drivers andtransfer centers. When I got to the meeting I said, “Hey, thereare some things I’d like you to consider beyond just operations.I’d like you to think about our customers, particularly the cus-tomers that we currently have, who are great candidates forour service. And then let’s also evaluate customers that we’vespent a lot of money to acquire in the past, that didn’t ulti-mately turn out to be great customers.”Bedford took the team through his analysis of Oberweis’s targetcustomer segments using data sets based on community-leveldemographic information. Contrary to the company’s conventional wis-dom, he had discovered that the so-called Beamer and Birkenstockgroup — liberal, high-income, established couples living leisurely life-styles — weren’t a good fit for Oberweis’s high-end retail dairyproducts. Analytics essentially shattered the company’s preconceivednotions about its target market.Once Bedford demonstrated the possibilities of utilizing data ana-lytics to segment the customer market, the meeting shifted fromtactical, focusing on operations — how many trucks and transfercenters would be required and where they should be located — tostrategic, stepping back to define the target market. “From a market-er’s point of view, this seems to make perfect sense,” said Bedford.“But it didn’t necessarily make sense initially to people in that room.Because that’s not how they think.”Oberweis’s expansion plans are now being driven by analytics. Moreimportantly, Bedford says, the company’s decision makers are thinkingabout using data analytics within their own areas of expertise:I’ve started to see people now say, “Wait a second, you knowwhat, this analytic stuff, there’s some power here, and maybe Ishould take the time to learn a little bit more about what Bruceis doing that maybe I could do.” They’re saying, “I’m not surewhat I should be asking about, but let me at least ask if there’ssomething that I should ask about.” It comes down to having a number of people who don’t or-dinarily use analytics stop and see the light bulb go off. Thechange is cultural, and to a point now where people want to ac-quire a better understanding of analytics tools because theycan see that there is real benefit.The Oberweis story calls attention to how analytics can transformeven the most traditional of companies. Indeed, the dairy companylacks modern ERP systems (although it is planning a state-of-the-artERP implementation) and continues to process much of its inventory byhand. Yet when its CEO gave analytics a seat at the strategy table andoperations executives subsequently began using analytics to makebusiness decisions, the company did not merely move on from its geo-graphical roots — Oberweis reinvented how it would compete.CASE STUDY: Oberweis Dairy
  8. 8. 6 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C SFor example, AstraZeneca Group found that itspayers were combining data from the pharmaceu-tical giant’s clinical trials with proprietary data toconduct comparative-effectiveness studies. Payers,in effect, knew more about AstraZeneca’s drugperformance data in some situations than Astra-Zeneca itself did. This gave them a distinctadvantage in negotiating payments. It also made itdifficult for AstraZeneca to get its drugs repre-sented on national and country formularies, the allimportant drug approval lists from which physi-cians prescribe medications. How did AstraZenecarespond to this competitive disadvantage? It builtup its own analytics program, partnering withIMS Health in Europe and U.S.-based HealthCore,a clinical outcomes research subsidiary of healthinsurer WellPoint Inc. The partnerships havebecome a crucial tool in AstraZeneca’s negotia-tions with payers.In some markets, once a company finds a uniqueway to use data to gain an advantage, competitorsquicklyjumponthebandwagonandleveltheplayingfield. Simplyobtaininganadvantagefromanalyticsisnot enough in these cases; insights must be revital-ized again and again to sustain a competitive edge.The story of the OaklandAthletics offers a tellingexample. In 2002, despite being handicapped withthe most significant salary constraint in MajorLeague Baseball, Oakland A’s general manager BillyBeane built a winning team through an innovativeuse of analytics. He bucked conventional wisdomand began looking at previously ignored player sta-tistics. This story — popularized in Michael Lewis’sbook Moneyball: The Art of Winning an UnfairGame and the movie starring Brad Pitt — ends on ahappy note, with the A’s winning their division andgoing to the playoffs.13But over time, other teams copied Beane’s meth-ods, and the A’s lost the competitive edge they hadinitially gained with analytics. It was only after teammanagement created new analytical metrics thatthe A’s returned to the playoffs in 2012, after a five-year hiatus.14The moral: Organizations need to findnew ways to apply analytics to refashion the advan-tage they gain from data.Analytics is not just about generating insightsand getting those insights to the right people.To sus-tainthelong-termsuccessofdata-driveninnovation,it is necessary to continually revise one’s analyticalapproach in order to generate insights that lead tonew innovation and competitive advantage.The Analytical InnovatorsWhile many companies are begin-ning to cultivate benefits fromtheir use of analytics, organiza-tions that are getting the mostvalue have a distinct approach. In this section, weintroduce the Analytical Innovators, contrast theirbehaviorswithothercompaniesanddiscusshowthesedifferencesmattertoorganizationalperformance.TheconceptofAnalyticalInnovatorsemergedwhenwecombinedresponsestotwoof oursurveyquestions,oneaboutcreatingacompetitiveadvantagewithanalyt-icsandoneaboutusinganalyticstoinnovate.15WethenCASE STUDY: Caesars EntertainmentAnother dimension of the analytics revolution is balancing intuition with ana-lytical insights. Decision-makers, especially in the context of strategicjudgment, often need to strike the right balance between a course of actionsuggested by data and a different course of action indicated by intuition. Onone hand, there is a clear sense in which the distinction between intuition anddata is false: Many judgments must be made about which data to use andhow to interpret it in order for data to become insights in the first place. Buton the other hand, as analytical insights grow in number and influence withinan organization, the need to put these insights into a broader context will be-come even more important.Caesars Entertainment Corporation is a case in point. Led by chairman andCEO Gary Loveman — a former Harvard Business School professor with adoctorate in economics from MIT — Caesars was offered the chance to bidon a gambling concession in Macau, China, in 2006. The asking price of theconcession was $900 million. Loveman, who had established a reputation forhimself by profitably using analytics to fine-tune customer segments andbuild effective loyalty programs, ran the numbers but couldn’t produce a valu-ation anywhere near $900 million. He declined to bid. The global financialcrisis hit the next year — but not in Macau, which enjoyed a growth explosion.Caesars bought a golf property in Macau in 2007 for close to $600 million inthe hopes of turning it into a gaming property. Unfortunately for Caesars, nomore gambling concessions have been (or are likely to be) issued to foreigninvestors. One of Caesars’ competitors is now profiting more from its proper-ties in Macau than from its properties in Las Vegas.Loveman has been open about his missteps in Macau. “You had to have akind of intuitive courage, and I am not well-suited to those kinds of decisions,”he said in 2010.i “Big mistake. I was wrong, I was really wrong.”
  9. 9. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 7groupedrespondentsintothreedistinctlevelsof analyt-ics sophistication according to how they responded toboth questions.(See Figure 2:Analytical Innovators —ASmallGroupofAnalyticsLeaders.)Analytical Innovators are those respondentswho strongly agree that analytics has helped im-prove their organizations’ ability to innovate andsay that analytics has helped create a competitiveadvantage to a great extent. Analytics Practitionersare utilizing data, mostly to address tactical andoperational issues, but are not innovating with ana-lytics at the same level as Analytical Innovators.AndAnalytically Challenged organizations are strug-gling to use data beyond basic reporting andmarketing applications.Analytical Innovators are distinguished by sev-eral key characteristics: their mindset and culture,their actions and their outcomes.Mindset and CultureMore than other companies, Analytical Innovatorshave developed an analytical mindset that supportsthe use of data and analytics across a wide range ofcorporate activities.They tend to view data as a coreasset; they challenge the status quo; they believe inthe possible; and they are open to new ways ofthinking.Data as a Core Asset: It’s Cultural Several execu-tives in our interview series described data as a coreasset — in their companies, analytical insights arepart of the culture of the organization and are uti-lized in strategic decisions, both large and small.Analytics determines products and services, projectsuccess or failure, and the allocation of resources.Employees, whether data-oriented or not, utilizethese insights in their decision-making processes.Neel Sundaresan, senior director and head ofeBay Research Labs, describes the role of analyticinsights at eBay:Everybody in the organization — whether youare a technical person, a researcher or an engi-neer, a product manager, a businessperson, oran analyst — has to be data-driven. Now, noteverybody has to look at data, but everybodyhas to understand data at some level. A lot ofdata is coming from the behavior of millions ofpeople on our site. So, being able to understandand get your head around that data is reallyimportant.You can think of it as an attitudechange in all grades of people.”Michael Johnson, director of the utility for caredata analysis at Kaiser Permanente, describes howanalytics permeates healthcare delivery:With our electronic medical record system,we’ve become much more data driven and an-alytics oriented. Pretty much every actor in thecare delivery system is using the same recordand entering information in the same place.That allows us to do some remarkable thingswith regard to thinking about where and howmembers should receive care, and how to im-prove the flow of information, while at thesame time lowering costs.New Ways of Thinking Sixty percent of Analyti-cal Innovators“strongly agree” that they are opento new ideas that challenge the status quo, a viewthat is weakly represented among other companies.(See Figure 3: Open to New Ideas.)A perfect example of an Analytical Innovatorcompany with this mindset is online dating The evolution of analytics has changedhow the company thinks about everything it does,according to its CEO, Mandy Ginsberg:Everything that we do is driven by analytics.We literally test every page, every new feature— there’s nothing that we do where we don’tunderstand the impact of what we’ve has become much smarter inthe past four years.We’ve grown the data andanalytics team considerably compared to someof the other areas of our business. We realizedFIGURE 2:ANALYTICALINNOVATORS —A SMALL GROUPOF ANALYTICSLEADERSRespondentsare at variouslevels of analyticssophistication.AnalyticalInnovatorsAnalyticalPractitionersAnalyticallyChallenged11%29%60%
  10. 10. 8 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C Sthat we needed to double down in this area,and we started getting smarter and smarterabout has been around for 18 years,and that is both a benefit and a curse becausewe had old infrastructure and old ways ofdoing things, and had to adapt, versus a com-pany like Zynga who is so fresh and new andeverything they do is as a data driven company.In fact, I would say a company like Zynga is adata company that happens to do games. We’rea dating company that happens to be good atanalytics, but it went in that reverse order. It’sshocking how far we’ve come.Analytical Innovators use different languagethan other types of companies to talk about analyt-ics. In response to an open-ended survey question,Analytically Challenged managers often referred totheir analytics capabilities in terms of “we can’t” or“we don’t.” Analytics Practitioners frequently de-scribed their analytics capabilities in practicalterms, such as solving problems or increasing effi-ciencies. In stark contrast, Analytics Innovatorsdescribe their analytics capabilities in terms of “rei-magining”or“rethinking.”Key ActionsCompared to the other groups,Analytical Innovatorsreportthattheyusemoreof theirdata,useittoobtainmore timely answers,collaborate more with analyticsand are more effective throughout the informationvalue chain. In short,Analytical Innovators use dataand analytics much differently than everyone else.Getting Real-Time Answers and DevelopingProducts More Quickly We asked respondents torank the top three uses of analytics in their organiza-tions and found that the groups diverged on severalkey applications.ForAnalytical Innovators,the No.1use of analytics is to make real-time decisions. Forother groups, the top answer was reducing costs.Thenext top use of analytics among Analytical Innova-tors is increasing customer understanding, followedby accelerating the development of new products.(See Figure 4: Analytical Innovators Use AnalyticsDifferently Than Other Companies.)Sam Hamilton, vice president of data at PayPal,describes how analytics has influenced that compa-ny’s real-time decision making:We have gone from report creation that takesweeks or months to deliver, to self-service,real-time data analysis.And we have gone from dataanalysis done by a small group of analysts todata-driven decisions throughout PayPal,doneby most of the staff.All of this has progressivelyshrunk the latency of time to value of data.In our interviews, we asked executives fromcompanies that had many of the earmarks of Ana-lytical Innovators how analytics was influencingtheir product development life cycle. The com-ments of eBay’s Neel Sundaresan were typical:Increasingly (Internet-based) products are gettingimproved and improvised as they get used.Asthese products get used at scale,they generate a lotof user behavioral data.This provides the oppor-tunity to enhance these products as users use themand create analytics-driven learning products.Think about the product life cycles now andthose from a few years ago. Before you wouldprobably have a product release every year,everytwo years, and you’re waiting for the next revi-sion to be released with enhancements,whereasnow it’s just happening all the time. Releases?There is no well-defined product release.Use More of Their Own Data Analytical Innova-tors use more of their data than other companies.They are nearly three times more likely to say theyuse a great deal or all of their data than AnalyticallyChallenged organizations do, which are the least ef-FIGURE 3:OPEN TO NEW IDEASMost Analytical Inno-vators strongly agreewith the statement:My organization isopen to new ideasthat challenge thestatus quo.AnalyticalInnovatorsAnalyticalPractitionersAnalyticallyChallengedStronglydisagreeSomewhatdisagreeSomewhatagreeStronglyagree“My organization is open to ideas andapproaches that challenge current practices.”0% 20% 40% 60% 80% 100%
  11. 11. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 9fective at using analytics for competitive advantageand innovation. More generally, we saw a strongcorrelation between how much a given companyuses analytics to create competitive advantage andadvance innovation, and how much of their datathat company uses. (See Figure 5: Analytical Inno-vators Use More of the Data They Collect.)LinkedIn is among the few companies that uti-lizes virtually all of its data. Every web request thecompany gets generates a transaction, and everytransaction has some information and value associ-ated with it, according to Deepak Agarwal,LinkedIn’s director of relevance science:While carefully respecting the privacy of ourLinkedIn members’ data, every single bit ofinformation is eventually used. The raw datagets transformed in very complex ways, allow-ing for members’ data to remain private andanonymized. There are many different ana-lysts and data scientists who analyze this data,create different groupings of the data, createdifferent aggregates of the data, look at differ-ent kinds of numbers on different usersubpopulations and then glean insightsfrom them. That’s what ultimately goes intoimproving the relevance of our products.More Effective Throughout the InformationValue Chain Analytical Innovators are also moreeffective than other companies at each step of theinformation value chain. (See Figure 6: Effective-ness Across the Information Value Chain.)Compared to Analytically Challenged organiza-tions, Analytical Innovators are more than twice aseffective capturing information, nearly three timesas effective at analyzing information and threetimes as effective at using insights to guide strategy.Beyond the basics of capturing and analyzinginformation, Analytical Innovators are much morelikely to support their analytics activities with an in-tegrated approach to information management thatdisseminates insights to customer-facing employeesand to partners and suppliers. Analytical Innova-tors bolster their efforts to share knowledge andinsights through champions who promote bestpractices.And they are much more likely than othergroups to have these key supports in place. (See Fig-ure 7: Analytical Innovators Have More Supportsfor Analytics.)Outcomes: Power Shiftsto Those with InsightOne distinguishing characteristic of Analytical Inno-vatorsisalsoacompellingthemethatemergedduringour research: Analytical Innovators report a powershift in their organization because of their use of50%40%30%20%10%0%ReduceenterprisecostsImproveresourceallocationsPercentage indicating this activityas a main use of analyticsIncreasecustomerunder-standingMakereal-timedecisionsIdentifynewmarketsAcceleratedevelopmentof newproducts /servicesAnalytical InnovatorsAnalytical PractitionersAnalytically ChallengedAnalyticalInnovatorsAnalyticalPractitionersAnalyticallyChallengedNotmuchSome A greatdealAllof itHow much of the data generated by yourorganization does your organization use?0% 20% 40% 60% 80% 100%FIGURE 5:ANALYTICAL INNOVATORS USEMORE OF THE DATA THEY COLLECTAnalytical Innovators tend to know why theyare collecting data and how to use it.FIGURE 4:ANALYTICAL INNOVATORS USE ANALYTICSDIFFERENTLY THAN OTHER COMPANIESMaking real-time decisions is the No. 1 use of analyticsamong Analytical Innovators, compared to cost reduc-tion for other groups.
  12. 12. 10 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C Sanalytics. This is a significant finding, in that powershifts can be disruptive. They often call into questionexperience and intuition that managers and employ-ees have built up over years.We found that the morean organization uses analytics to build competitiveadvantage and to innovate, the more likely it is to sayanalytics has shifted its power dynamics.Our survey revealed that Analytical Innovators“strongly agree” or “somewhat agree” four timesmore than Analytically Challenged organizationsthat analytics has shifted the power structure withintheir organizations. (See Figure 8: Analytics Shiftsthe Power Structure. )That power shift can take a number of forms.A C-suite champion may give new analytics talent thepower to innovate.Or analytics and analysis may starttoinfluenceinvestmentdecisions,shiftingpowerfromone group or executive to another. For example, atNeiman Marcus,analytics was once consumed exclu-sively by midlevel managers. Now, with consistentproject successes,analytics outcomes are regularly re-ported to the board and senior executives.Accordingto Jeff Rosenfeld, vice president of customer insightand analytics at Neiman Marcus, this has created ashiftintheall-importantfundingdecisionprocess:Having a culture, which has evolved over thelast couple of years, based more on data, hascaused us to make smarter decisions. No ques-tion. There is a long list of examples of changeswe’ve made to the website, or customer experi-ence, or changes we’ve made to promotionsthat were based on rigorous analytics and teststo understand what’s most profitable for thebusiness.  How we choose to allocate our mar-keting dollars has shifted by substantial dollarfigures, based on analytics.Those who have control over data, and the abil-ity to analyze that data, move to the forefront in theorganization — in fact,it is suddenly very cool to bethe geek. (Researchers Tom Davenport and D. J.Patil peg data scientists as having,“The Sexiest Jobof the 21st Century.”)16Chief marketing officers are among those who arebenefitting from data analytics. In a 2012 survey of100 CMOs,17over 89% say that social data has influ-encedtheirdecisions.Theauthorsof thestudyoffereda particularly intriguing conclusion: CMOs are usingsocial data to drive discussion in the C-suite andthereby elevate themselves“as owners of the brand-consumer relationship.”This suggests that CMOs areusing social data to enhance their influence andimprove their personal brand within the organiza-tion. For CMOs, social data is not merely aboutinsight;it is a new source of legitimacy in the C-suite.Many executives focus on the question of how toget more value from their data. But for some com-panies — perhaps even many companies — this50%40%30%20%10%0%CapturinginformationAggregating/integratinginformationPercentage indicating that their organiza-tion is very effective at each activityAnalyzinginformationUsinginsights toguide futurestrategiesAnalytical InnovatorsAnalytical PractitionersAnalytically ChallengedFIGURE 6:EFFECTIVENESSACROSS THEINFORMATIONVALUE CHAINAnalytical Innova-tors are moreeffective at capturingand analyzing data,and utilizing insightsfrom that data thantheir AnalyticallyChallenged or Ana-lytical Practitionercounterparts.FIGURE 7:ANALYTICAL INNOVATORS HAVE MORESUPPORTS FOR ANALYTICSAnalytical Innovators are much more likely to supportanalytics with more resources and processes.50%40%30%20%10%0%Analyticschampionspromote bestpracticesData insightsshared withstakeholdersPercentage “strongly agreeing” theirorganizations have these supportsCustomer-facingemployees haveaccess to insightsto help drive salesand productivityAn integratedapproach toinformationmanagementAnalytical InnovatorsAnalytical PractitionersAnalytically Challenged
  13. 13. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 11approach emphasizes the wrong issue. It misses akey part of the relationship between data and value:the connection between how much data is valuedand how much value data can deliver.Indeed, the more data is valued by an organiza-tion, the more value it can usually deliver. This isnot merely about making investments in analytics(which can go wrong), but about conferring poweron analytics and creating a culture in which analyt-ics is part of how decisions get made.At Wells FargoCompany, this means that the organization is rely-ing more on analytics to make decisions, asignificant shift, according to Pascal Hoffmann, for-mer vice president of digital banking strategy:When you look at the decision making process,it has become more quantitative and more sci-entific than it used to be a few years back. It’s aslow transition triggered by smart people alongthe way, where you have existing processes andestablished thinking. Some people want tochallenge the status quo and look harder at theevidence on how the decisions are made, andwhat decisions are made. They come up withevidence that shows that there is a better way togo about making decisions; that there is a bet-ter decision than the one that was made in thepast. And because they have the evidence andthey can build a case with hard science anddata, they get paid attention to. Senior management support is almost alwayscritical to developing the kind of data-driven cul-ture that embraces evidence-based ideas that runcounter to the status quo. At casino giant CaesarsEntertainment, for example, analytics is beingdriven through the organization by a team of ana-lytics missionaries who are being integrated intosenior management teams at the property level.This has been a difficult change in managementprocess that has required support from corporateexecutives at headquarters.Summing up the Analytical InnovatorsAnalytical Innovators exist across industries, vary insizeanddifferinhowmuchdatatheycollect.However,they share several important characteristics. Mostshareabelief thatdataisacoreassetthatcanbeusedtoenhance operations,customer service,marketing andstrategy.Across the information value chain, they aremore effective with their analytics than other groups.They use this effectiveness to act more quickly: to de-liver faster results, to make real-time decisions and toaccelerate the development of products or services.They also tend to have strong management supportfor analytics-based decision making,which undoubt-edly supports (or reflects) a greater willingness toaccept data-driven ideas that challenge the status quo.In turn, this creates more opportunity for managerswith valuableideastoadvocatefortheirorganization’ssuccess—andtoenhancetheirowncareerprospects.On Becoming anAnalytical InnovatorIn the previous section, we examined theflagship characteristics of the AnalyticalInnovators. In this section we examine theremaining companies — the AnalyticallyChallenged and the Analytical Practitioners — andwhat these organizations can do to become morelike Analytical Innovators.The Analytically ChallengedThe Analytically Challenged, 29% of our surveyrespondents,are less mature in their use of analyticsand have not been able to derive as much value fromthem as the other groups.18Few have achieved acompetitive advantage with analytics, and evenfewer have benefitted in the area of innovation.Thisis a stark difference compared to all other surveyrespondents, most of whom are deriving someAnalyticalInnovatorsAnalyticalPractitionersAnalyticallyChallengedStronglydisagreeSomewhatdisagreeSomewhatagreeStronglyagree“Analytics has shifted the power structurewithin my organization”0% 20% 40% 60% 80% 100%FIGURE 8:ANALYTICS CANSHIFT THE POWERSTRUCTUREAnalytical Innova-tors report a powershift in their organi-zations at a muchhigher rate thanother groups.
  14. 14. 12 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C Scompetitive advantage and are using data to inno-vate. (See Figure 9: Analytically Challenged ReportFewer Benefits from Analytics.)Analytically Challenged organizations have fourdistinct characteristics that separate them fromtheir more analytically advanced peers:1.Data deficiency2.Weak information value chain3.Lack of collaboration4. No burning platformData Deficiency Analytically Challenged companiesaredistinguishedbythestateoftheirdataandwhattheyare (or aren’t) doing with it. Unlike other companies,this group has generally not capitalized on big datatrends,andtheirdatamanagementabilitiesarelagging.One survey respondent in the Analytically Chal-lenged category noted:Analytics are only meaningful if the quality ofthe underlying data is unassailable. Until thereis sufficient attention paid to data governanceand quality assurance, analytics will remainlittle more than a lofty goal.Data issues are a nonstarter for the effective use ofanalytics. If the data the organization is using isn’t atleast reliable, accurate, timely and adequate, theresults of analytics will be meaningless. Andupstream, senior managers who prefer to drive deci-sionsontheirintuitionwillhavecausetobeskeptical.Weak Information Value Chain Another definingcharacteristic of the Analytically Challenged is theirineffectiveness at the analytics tasks that make up theinformation value chain, particularly compared toother organizations. Fewer than half (42%) of therespondents in this category report being effective atcapturing information, and the capabilities in otherareasareevenweaker,withinformationdisseminationatamarkedlylow21%.Accordingtoonerespondent:We are collecting mass quantities of data.However, there is no specific plan in place toactively utilize the data and only a vague con-cept of why we need it. … In other words, noreal plan.We are capturing data just in case.Lack of CollaborationIf we do not improve on our collection, integra-tion, analysis and productive use of informationacross data silos, we will destroy our business.This quote from a survey respondent, an ITexecutive at a European bank, gets to the heart ofanother characteristic common among the Analyti-cally Challenged: lack of collaboration across theorganization. Silos have long been identified as abarrier to the use and management of informationfrom both a data and a cultural standpoint.As com-panies have amassed more data from disparatesources, systems across organizations have emergedthat are not always integrated. Different functionalareas have built their own data stores, and ITdepartments have often been hamstrung in tryingto keep up with it all.Another respondent said:Too many nonintegrated silo systems is a hugeproblem for implementing better analysis andusing the existing information as a competitiveadvantage.Technology can improve, if not fix, the issue ofdata integration. However, more difficult to addressare organizational silos spawned from a culture thatlacks collaboration. One respondent in the Analyti-cally Challenged group notably lays out sharpcriticism of senior management:I find the corporate political climate surround-ing analytics to be one of smiling deception.Many EVP level managers … are threatenedby analytics. I fear that self–interest … is thebiggest hindrance. Organizational dynamicsAnalytics creates acompetitive advantagePercentage indicating a“moderate” or “great” extentAnalytics hashelped innovationPercentage “strongly” or“somewhat” agreeingAnalyticallyChallenged16%12%85%82%All OtherRespondentsFIGURE 9:ANALYTICALLYCHALLENGEDREPORT FEWERBENEFITS FROMANALYTICSAnalytics is noton the executiveagenda in Analyti-cally Challengedorganizations.
  15. 15. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 13are always at the core of enterprise solutionadoption. … I fear it probable that manyofficers may be shackled and apprehensive,caught on the sucker’s side of the Prisoner’sDilemma.19No Burning Platform The fourth characteristic ofAnalytically Challenged companies is that theyappear to have no key driver to use analytics — noreal burning platform compelling them to make theforay into analytics, let alone to improve their datamanagement. Without something threatening tospur them to action and leave the status quo, therewill not likely be much change. As one AnalyticallyChallenged survey respondent noted:Everyone believes that if we’ve managed so farand so well without a robust strategic approachto data analytics, we can go on doing so in thefuture as well.These companies are clearly change-resistant. Atelling example: Only 13% of the Analytically Chal-lenged strongly agree that their companies are opento approaches that challenge current practices, com-pared to 60% of Analytical Innovators who feel thatway.Evidently,manyAnalyticallyChallengedorgani-zationsarefeelingnopressuretodothingsdifferently.Another respondent from this group offered:Unfortunately, the pain of declining profits andmarkets will have to take the lead before man-agement will seriously look to analytics as asource of competitive advantage. No pain, noanalytics seems to be the business model.Supporting this notion is our finding that only29% of the Analytically Challenged organizationsindicate that analytics is a top-down mandate,com-pared to 55% of all other respondents. There is acase to be made that not only are these organiza-tions analytically challenged but they are alsoanalytically apathetic.Moving Forward with AnalyticsAnalytics in the organization has a hugefuture. I’m very interested in where big datagoes over the next few years. My organizationdoesn’t get it at this point; there are some pock-ets of the company where teams are pushing forincreased analytics, but the C-suite doesn’t yetsee the value.This survey response seems to capture the atti-tude of many respondents in the AnalyticallyChallenged group, who expressed general frustra-tion with their organization’s view on data andanalytics. The obstacles they face due to data defi-ciency, a weak information value chain, lack ofcollaborationandnoburningplatformareformidable.Though it is unlikely that a company will prog-ress from Analytically Challenged directly to beingan Analytical Innovator, the data advocates in theseorganizations can help ignite change. The missionfor the individual who wants to be an analytics cata-lyst: Lead analytics change by showing value.We’ve identified three key issues stemming fromthe characteristics noted above that individuals canbegin to address: technology latency, lack of collab-oration and inertia.Technology Latency. The Analytically Challengedare stymied in their progress by core data issues,fromupstream at the capture, quality, integration andaccess phases to downstream, where data is analyzedand disseminated. To address these areas, companiesmust invest in improved infrastructure, processesand technology skills. Wholesale change of thesecompetencies across the organization is impossiblewithout executive commitment to data. Therefore,improvement must start at the localized level.Action items for the analytics catalyst: Identify asmall but important issue that will benefit from theuse of analytics. Use the resources that can be foundin the organization and highlight what needs to bebrought in from the outside. Find the internal geeks— those who are hungry for analytical work — andtake a seat at their lunch table.Gather credible,timelyand accurate data. Make use of the available analyti-cal technology, and focus on identifying solutions toyour issue that have a clear and measurable impact.Lack of Collaboration. The silos in the organiza-tion,whether built from data stores or managementprotectionism,are a major impediment to the effec-tive use of information. Talk about breaking down
  16. 16. 14 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C Sthese silos is not new.But enterprise-wide change inthis arena could require a substantial informationinfrastructure investment, not to mention a dra-matic culture shift.However,collaboration can startto occur at the individual level.Action items for the analytics catalyst: Reachacross the hall to those who have data that is impor-tant to addressing your issue. Enlist their helpas partners in increasing the value of their data in de-cision making. Build ongoing relationships byincludingthemintheprocessmovingforward.Facili-tatediscussionsamongpeersindifferentdepartmentson bringing data together to address specific chal-lenges. Give to get — share information of value toother departments to encourage reciprocity.Inertia. Unfortunately, Analytically Challenged or-ganizations are constrained in their use of analyticsby their executives’ unwillingness to change the sta-tus quo. These executives see no need for largeinvestments in the infrastructure, systems and tal-ent necessary to drive decisions with analyticsbecause they believe that what they have been doingis working just fine. They are suspicious of data,particularly if it contradicts their intuition. So far,there has been no life-threatening event to their or-ganization that has spurred thinking beyond thestatus quo. Outside of creating a burning platformto ignite a need for changes in decision making,those advocating the use of analytics simply mustprove its value, one small win at a time.Action items for the analytics catalyst: Developan executive communication strategy for your ana-lytics use case.To increase the credibility of the effort,engage your cross-sectional team to participate.Translate the analytical results into business insightsand recommended actions. Show a clear ROI interms of cost reduction, improved operations or in-creased revenue.Focus discussions on improving thebusiness issue rather than on the method.The Analytics PractitionersThesecondandlargestsegmentweidentifiedthroughthe survey responses is the Analytics Practitioners,which represent 60% of respondents. These compa-nies have made significant progress in their analyticsjourney, and many are reaping strong benefits. How-ever, the key metric that separates them from theAnalyticalInnovatorsisoutcome.RecallthattheAna-lytical Innovator group consists of those respondentswho indicated that the use of analytics has provided acompetitive advantage to a great extent and stronglyagreed that analytics has helped them innovate. TheAnalytics Practitioners have not achieved this highlevel of competitive advantage and innovation fromanalytics. But they have matured well beyond theAnalytically Challenged on their path to being data-driven. (See Figure 10: Analytics Practitioners UseAnalytics more to Compete than Innovate.)Underpinning the differences between this largegroup and Analytical Innovators are three charac-teristics:1. Just-good-enough data2. Operational focus on analytics3. Fragmented analytics ecosystemJust-Good-Enough Data Unlike the AnalyticallyChallenged, Analytics Practitioners have made sig-nificant advances in the area of access to useful datathis past year,with a corresponding increase in theirconfidence about the data, likely stemming fromimproved accuracy and timeliness. As surveyrespondents noted:Analytics are only as the good as the data. Bestpractices for data management, integrationand governance are necessary for analytics tosucceed. Otherwise, the adage “garbage in, gar-bage out” applies. Then analytics gets a badname and decision making is done via man-Analytics creates acompetitive advantagePercentage indicating“to a great extent”Analytics hashelped innovationPercentage “strongly”agreeingAnalyticallyChallenged8%2%33%9%100%100%AnalyticalPractitionersAnalyticalInnovatorsFIGURE 10:ANALYTICSPRACTITIONERSUSE ANALYTICSMORE TO COMPETETHAN INNOVATEAnalytics Practitio-ners have maturedbeyond the Analyti-cally Challengedbut are not yetclose to AnalyticalInnovators.
  17. 17. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 15agement intuition rather than based on factsoriginating in the data.We operate in extremely complex markets thatare very difficult to model,so the reliability ofthe data,analysis or insights is often challengedby the decision makers.We still have a way to go.Let’s be clear: This group still has room for im-provementintermsof dataproficiency.ButAnalyticsPractitioners have achieved a level at which they areable to make use of their information to help runtheir businesses.In their own words:Today, accessing data is not an issue, but thechallenge lies in structuring the data, manag-ing the data and making the data more usable,which will enable quicker decision making.We have the data in pockets and currentlymanually piece a lot of it together, but havebeen making great progress in first aligningdata so we speak the same language across theglobal operations, then connecting data, andfinally creating dashboards and tools to pro-vide the right data to the right people.Operational Focus on AnalyticsAnalytics are mired in “automating theexisting” rather than innovating a brighterperformance future. It is a culture problemthat will not be mitigated until a real leader-ship change occurs.Asthissurveyrespondentpointsout,AnalyticsPrac-titioners tend to be focused more on day-to-dayoperational use of analytics, as opposed to using it todriveinnovationandchangethebusiness.Thisisclearlysupportedbythesurveyresults,whichshowthatthetoptwo uses of analytics among this group, similar to theAnalytically Challenged,are reduction of enterprise costsandimprovementinresourceallocations.Comparethesetothepriorityusesof theAnalyticalInnovators:makingreal-timedecisionsandincreasingcustomerunderstand-ing.OneAnalyticsPractitionerrespondentnoted:We have to teach the enterprise to “behave”differently with data and move from atransactional to an insight mindset.The balance of using analytics and intuition inkey decisions is another example of the operationalfocus of Analytical Practitioners. In decisions in theareas of budget allocation, financial forecasts, sup-ply chain management and allocating employees’time, Analytics Practitioners and Analytical Inno-vators use a similar balance of intuition andanalytics. However, for more strategic insights suchas identifying target customers, enhancing cus-tomer experience and establishing strategy for theorganization, Analytical Innovators are much morereliant on analytics than the Practitioners.Fragmented Analytics EcosystemAnalytics are HUGE in my company. … Untilrecently, though, it was held in the hands ofvery few people. To the point where we worriedabout the proverbial “what if they get hit by abus” scenario. The past 12 months have beenfocused on integrating and trying to give dataaccess to more people.As seen in this comment, the third key differen-tiator of the Analytics Practitioner and their moreanalytics-savvy counterpart is their fragmentedapproach to the execution and use of analytics inthe organization. Additional fragmentation is evi-denced by differences in where companies are intheir integration of information management andbusiness analytics. While fully 85% of the Analyti-cal Innovators indicate that an integrated approachis a core part of their business strategy, only 59% ofthe Analytics Practitioners report the same. Onerespondent’s view of the future of analytics empha-sizes this point:In the future, analytics will transition fromsimple information gatherers and maintainersto influential thought-leaders that are inte-grated parts of teams across the organization.In the meantime,a pervasive issue still exists:inef-fective dissemination of key insights to employees.We found that companies generally seem to strugglemost with the dissemination of some components ofthe information value chain. This is quite definitelythe weakest link for the Analytics Practitioners. Onesurvey respondent from this group said:
  18. 18. 16 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C SThe need internally is to have access to action-able insight with data at the right level ofgranularity — when it is needed.What’s more, only 14% of Analytics Practitio-ners report increasing by“a great deal”their deliveryof actionable insights to frontline employees overthe past year, as compared to 35% of AnalyticalInnovators. That, coupled with the 16% of Analyti-cal Practitioner organizations that “strongly agree”that their customer-facing employees have access toinsights, gives rise to a sort of insight fragmentation— analytics is being conducted to drive decisions,but the results are not being shared among thosewho might be in the best positions to drive change.In the words of one respondent:A data-driven decision culture is at its beginningof being developed across the organization. Itwill be effective only if it is being embraced at alllevels and everyone is empowered to access it.Moving Forward with AnalyticsThe current operational and tactical use of analyticsbyAnalytics Practitioners is not unexpected for com-panies getting their feet wet in the use of analyticstechnology. Many companies have only recentlymade the foray into data-driven decisions and arestill experiencing growing pains.It’s clear that,unlikesome in the Analytically Challenged segment, theseorganizations do see value in information, and theyare earnest in trying to use it to their advantage.One Analytics Practitioner respondent noted:Analytics are the essential tool in the toolbox.The analytics are not THE answer, but the an-alytics should inform us to reach or formulatethe answer. A growing trend for our company isthe ability to capture information from a widerange of sources, use standard metrics and an-alytics to glean some knowledge and thenensure that this knowledge is appropriatelydisseminated. This is a trend and a need withinour company ... it is a work in progress.This optimism about the use of analytics wasstrong among the Analytical Practitioner group.Unlike the general feeling of “we can’t” among theAnalytically Challenged, this group showed a defi-nite sentiment of “we’ll try.” The mission foranalytics evangelists who want to step up their orga-nization’s use of analytics: Expand analytics relianceby demonstrating strategic possibilities.In order to develop the ability to“reimagine thepossible” with game-changing insights, at leastthree issues must be addressed: due data diligence,dashboard dependence and denial of access.Due Data Diligence. A key differentiator betweenthese organizations and those taking analytics to thenext level is the data itself. It’s a matter of data qual-ity, access and management. Analytical Innovatorsare leading the charge in tapping new sources ofdata. Analytics Practitioners should take note andlearn from them.Action items for the analytics evangelist: Con-duct a data audit. Do a quality check on the data youare using to drive decisions.How long have you beenusing the same data sources? Identify gaps in whatyou have and what you need, and consider how datafrom unconventional sources (e.g., social media)might provide a new perspective on your business.Dashboard Dependence. Business intelligencetechnologies brought the ability to watch day-to-dayoperations on bright and shiny dashboards andmonitor actual results against KPIs. But what’s hotnow is the ability to predict what’s going to happenand to find patterns in data that lead to not-so-obvi-ous conclusions. Analytics Practitioners who wantto step beyond the tactical and operational uses oftheir data need to sharpen their analytical skills andcast a net for analytics talent. If you are going tomake the move to Innovator,be prepared to invest.Action items for the analytics evangelist: Takestock of your own analytical prowess. Do you oryour staff have the right skills to employ sophisti-cated analytical techniques? Search for talent thatcombines an understanding of your business with apassion for data exploration and technical skills.Denialof Access.To help drive innovation,AnalyticsPractitioners must do a better job at disseminatingkey insights to the right people at the right time.Ana-lytics should be approachable — easy to access,simple and intuitive – in order to spur innovation
  19. 19. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 17from all levels in the organization.As one respondentsaid,“Analytics must be in the DNA of every empow-ered employee.”Action items for the analytics evangelist: Takestock of your organization’s information access anddistribution. Are employees stifled in their jobsbecause they don’t have the appropriate informa-tion to make decisions? Connect with peers aboutinformation dissemination, and developing strate-gies that help empower workers with insight.ConclusionThe analytics revolution is still at an earlypoint in its development. Many compa-nies are still struggling to figure out how,where and when to use analytics. Despitetheir analytical prowess, less than half of AnalyticalInnovators report that they are “very effective” atcapturing data, analyzing and integrating it, andusing analytical insights to guide strategy. Similarly,less than half of Analytical Innovators strongly agreethat they share data with key stakeholders and havean integrated approach to information management.Even so, Analytical Innovators are much morelikely to be able create a competitive advantage fromanalytics than their counterparts in the other twogroups.Inpart,thisisamatterof definition.AnalyticalInnovators are those respondents who say their com-paniesareusinganalytics(toagreatextent)tocompeteand innovate. However, the key lessons that we haveidentifiedfromstudyingthisgroupisthat:(a) their orientation to data and analytics is muchdifferent than other groups. How AnalyticalInnovators think about analytics, how they sup-port the development and dissemination ofanalytical insights, and what they do withanalytics are very different compared to the ap-proaches taken by the Analytically Challengedand Analytics Practitioner groups(b) We have boiled down these differences intothree characteristics:i.A widely shared belief that data is a coreasset that can be used to enhance operations,customer service, marketing and strategyii. More effective use of more data for fasterresultsiii. Support for analytics by senior managerswho embrace new ideas and are willing toshift power and resources to those who makedata-driven decisionsThese are the main characteristics of companiesthat are, today, leading the analytics revolution.We hope that a better understanding of the Ana-lytical Innovators will yield benefits for companiesthat are looking not only to create business valuefrom analytics, but also for a more innovative wayto compete in their markets.REFERENCES1. “The New Initiative on the Digital Economy,” pressrelease, MIT Sloan School of Management, n.d., P.C. Evans and M. Annunziata, “Industrial Internet:Pushing the Boundaries of Minds and Machines,” GEReports, November 26, 2012.3. Evans, “Industrial Internet.”4. R. Bean and D. Kiron, “Organizational Alignment Is Keyto Big Data Success,” January 28, 2013, “Governor Patrick Announces New Initiative toStrengthen Massachusetts’ Position as a World Leader inBig Data,” press release, Commonwealth of Massachu-setts, May 30, 2012.6. ”Governor Patrick Announces New Initiative.”7. A. Pentland, “Reinventing Society in the Wake of BigData,” August 30, 2012, Tweeted by Joel Cherkis on 10/21/12: J. Manyika, M. Chui, et. al, “Big Data: The New Frontierfor Innovation, Competition and Productivity,” May 2011, Capgemini Consulting and MIT Center for Digital Busi-ness, “The Digital Advantage: How Digital LeadersOutperform Their Peers in Every Industry,” November 5,2012, T.H. Davenport and J.G. Harris, “Competing on Analytics:The New Science of Winning” (Cambridge, MA: HarvardBusiness School Press, 2007).12. E. Brynjolfsson and A. McAfee,“Big Data, The Man-agement Revolution,” Harvard Business Review 90(October 2012): 61-67.13. M. Lewis, “Moneyball: The Art of Winning an UnfairGame” (New York: W.W. Norton, 2004).14. L. Melnick,” Moneyball Strikes Again: How to Use An-alytics for Sustained Competitive Advantage,” October 3,2012, The two questions were:(a) To what extent does information and business
  20. 20. 18 MIT SLOAN MANAGEMENT REVIEW • SAS INSTITUTE INC. MORE FROM MIT SMR ON DATA ANALYTICSS P E C I A L R E P O R T R E I M A G I N I N G T H E P O S S I B L E W I T H D ATA A N A LY T I C Sanalytics create a competitive advantage for yourorganization within its industry or markets?(b) To what extent do you agree with the followingstatement? Analytics has helped improve my orga-nization’s ability to innovate.Managers that checked “great extent” for both questionswere placed in the Analytical Innovators category.16. T.H. Davenport and D.J. Patil, “Data Scientist: TheSexiest Job of the 21st Century,” Harvard BusinessReview 90 (October 2012): 70-76.17. “Chief Consumer Advocate: How Social Data ElevatesCMOs,” white paper, Bazaarvoice and the CMO Club,Austin, TX, July 25, 2012.18. Respondents in Analytically Challenged companiesdiffer demographically in subtle but important ways fromother survey participants. They tend to be in less seniormanagement positions and have a slightly higher likeli-hood than other survey participants to work in operationalfunctions. These demographic differences might be a con-tributing factor to their evaluations of their organizations asless analytically mature.19. The prisoner’s dilemma refers to a non-zero-sumgame that shows why two people may choose to betrayeach other even if cooperation is in their best interest.It’s based on the premise that two isolated prisonersinvolved in the same crime have the independentopportunity to either collaborate with each other byremaining silent or sell the other prisoner out. Each com-bination of possibilities results in a different outcome,with the best for both stemming from cooperation. Thesucker’s side is the prisoner who remains silent but isbetrayed by the other prisoner.i. K.T. Greenfeld, “Loveman Plays ‘Purely Empirical’ Gameas Harrah’s CEO,” August 6, 2010, deepen our understanding of the challenges and opportunities associated with the use of business analytics,MIT Sloan Management Review, in partnership with SAS Institute Inc., has conducted its third annual survey, towhich more than 2,500 business executives, managers and analysts responded from organizations locatedaround the world. Our analysis includes individuals in 121 countries and more than 30 industries. Participatingorganizations also ranged widely in size, from those organizations reporting under $250 million in revenues tothose with $20 billion and over in revenues. Respondents included MIT alumni and MIT Sloan Management Re-view subscribers, SAS clients and other interested parties.In addition to these survey results, we interviewed academic experts and subject matter experts from a num-ber of industries and disciplines to understand the practical issues facing organizations today in their use ofanalytics. Our interviewees’ insights contributed to a richer understanding of the data and the development ofrecommendations that respond to strategic and tactical questions senior executives address as they implementanalytics within their organizations. We also drew upon a number of case studies to further illustrate how orga-nizations are using business analytics as a competitive asset.In this report, the term “analytics” refers to the use of data and related business insights developed throughapplied analytical disciplines (e.g., statistical, contextual, quantitative, predictive, cognitive and other models) todrive fact-based planning, decisions, execution, management, measurement and learning.ANALYTICS The use of data and related insights developed through applied analytics disciplines (for example, statistical,contextual, quantitative, predictive, cognitive and other models) to drive fact-based planning, decisions, execution, man-agement, measurement and learning. Analytics may be descriptive, predictive or prescriptive.DATA-ORIENTED CULTURE A pattern of behaviors and practices by a group of people who share a belief that having,understanding and using certain kinds of data and information plays a critical role in the success of their organization.ABOUT THE RESEARCHDEFINITIONS
  21. 21. MORE FROM MIT SMR ON DATA ANALYTICS REIMAGINING THE POSSIBLE WITH DATA ANALYTICS • MIT SLOAN MANAGEMENT REVIEW 19DeepakAgarwal, Director, Relevance Science, LinkedIn CorporationBrunoAziza,Vice President,Worldwide Marketing, SiSense Inc.Bruce Bedford,Vice President, Marketing Analytics and Consumer Insights, Oberweis Dairy Inc.Veronika Belokhvostova, Head, Global Business Analytics, PayPal Inc.Antonio Benjamin, Chief Technology Officer and Managing Director, Citigroup Global TransactionServices/Institutional Clients Group, Citigroup Inc.Marco Cardinale, Head of Sports Science and Research, British Olympic AssociationLouis Datko, Senior Research Psychologist, United States Air Force Survey OfficeJohn Eliseo,Vice President, Enterprise Content, Metadata Management, Thomson ReutersHelen Fisher, Chief Scientific Advisor, Chemistry.comDan Flood, Senior Director, Go-to-Market Supply Chain, PepsiCo North America BeveragesMandy Ginsberg, CEO, Match.comArnab Gupta, CEO, Opera Solutions LLCSam Hamilton,Vice President, Data, PayPal, Inc.Shawn Hanna, Director, Financial Analysis, Petco Animal Supplies Inc.Pascal Hoffmann, formerVice President, Digital Banking Strategy,Wells Fargo CompanyMichael Johnson, Director, Utility for Care Data Analysis, Kaiser PermanentePete Johnson, Chief Technology Officer, The Bank of NewYork Mellon CorporationRaymond Johnson, Principal Manager, Demand and Price Forecasting, Energy Supply and Management,Southern California Edison CompanySteven Labkoff, Head, Strategic Programs, Research and Development Information,AstraZeneca Pharmaceuticals LPPeter Marney, SeniorVice President, Platform and Information Strategy, Thomson Reuters Corp.Ganesh Natarajan,Vice Chairman and CEO, Zensar Technologies Ltd.David Norris, former CEO, BlueCava Inc.Jeff Rosenfeld,Vice President, Customer Insight and Analytics, The Neiman-Marcus Group Inc.Jeanne Ross, Director, Center for Information Systems Research, MIT Sloan School of ManagementArijit Sengupta, CEO, BeyondCore Inc.Neel Sundaresan, Senior Director and Head, Research Labs, eBay Inc.Laura Teller, Chief Strategy Officer, Opera Solutions LLCSimon Thompson, Director, Commercial Solutions Esri, Inc.GeorgeWesterman, Research Scientist, MIT Sloan Center for Digital Business,MIT Sloan School of ManagementACKNOWLEDGMENTSFOR MORE ON DATA AND ANALYTICS FROM MIT SLOAN MANAGEMENT REVIEWGet the complimentary monthly newsletter on Data AnalyticsThe intensifying“data deluge,”and the new analytical approaches that help organizations exploit that data,willfundamentally change how managers make decisions and innovate.Data Analytics explores the challenges ofthe data-driven world,and defines the new organizational capabilities this environment will demand.Signup.
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