Business Intelligence Article

ExecutiveBulletin

COMPUTERWORLD

OVERVIEW

BI: Prescription for Business Advantage . . . . . . . . . . . . . . . . .2

TRENDS, STRATEGIES AND RESOURCES

BI for the Masses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4Hurdles to BI Implementations . . . . . . . . . . . . . . . . . . . . . . . . .7Spreadsheet Overload? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9Users Speed Feeds to Data Warehouses . . . . . . . . . . . . . . . .11Case Study: BI Dashboards . . . . . . . . . . . . . . . . . . . . . . . . .13Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15Text Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16Predictive Analytics Grows Up . . . . . . . . . . . . . . . . . . . . . . .19Outsourcing Predictive Analytics . . . . . . . . . . . . . . . . . . . . .22

BI and the DataMatrixBusiness intelligence software and data-analysis technologies are entrenched in the enterprise, but IT managers need to takespecial care planning and managing thesesophisticated tools.

COMPUTERWORLD EDITOR IN CHIEF: Don Tennant • ONLINE PROJECTS EDITOR: Ian Lamont • EXECUTIVE

BULLETIN EDITOR: David Ramel • DESIGNER: Nancy Deutsch • DESIGN DIRECTOR: Stephanie Faucher MANAGING EDITOR/PRODUCTION: Michele Lee DeFilippo • COPY EDITORS: Bob Rawson, Eugene Demaître,Mike Parent, Monica Sambataro

Compliments of

Computerworld Executive Bulletin BI and the Data Matrix 2

Companies are awash in data.Think of all the databases, spread-sheets, e-mail messages, reports, research, meeting notes and interac-tions with customers. It’s organiz-ing, analyzing and using these disparate pools of information —the basics of BI — that can help yougain an edge over your competitors.

Granted, most BI applicationsdon’t deal with life-and-death situa-tions. But today’s tools are resultingin more innovative strategies thatcompanies use to gain a business ad-vantage. Consider the examples youwill read about in this report:

l A financial services companyhelps its clients predict which oftheir customers will be late withpayments, which will be lying whenthey say the check is in the mail and which will be likely to defaultaltogether.

l A company in the educationfield can analyze its ability to attractstudents and the success of newcampus locations and acquisitions.

l A public radio and TV broad-caster hopes to analyze promotional

campaigns and precisely target itsprogramming and focus on viewerswho are most likely to make finan-cial contributions.

l A mortgage company hopes toconvert recordings of phone callsinto a text format that can be used tostudy the behavioral patterns ofdelinquent borrowers and try toidentify customers who plan to filelawsuits against the company.

l A recreational equipment retail-er identifies good locations for newstores by finding places with highconcentrations of online and catalogcustomers. It also tailors its stores’product mixes to local market pref-erences and uncovers patterns that suggest future purchases bycustomers.

But implementing a successful BIprogram can be daunting. Industryexperts warn that it can take yearsto get the right people and systemsin place and operating efficientlyenough to generate ROI. Besidestechnical, business and process ob-stacles, there are “softer” considera-tions such as cultural and political

issues standing in your way.And it’s the people issues that can

be the most perplexing. Workers canget set in their ways and become re-sistant to change — they might notwant to give up their trusty spread-sheets for standardized BI reports.Some may have become experts inspreadsheet analysis and feel thattheir jobs are threatened by the in-trusion of BI for everybody. Man-

BI: Prescription for Business Advantage

AFEW YEARS AGO STAFFERS AT HEALTH INSURER Highmark Inc. noticed data analysis that indicatedcataracts were a predictor of future heart attacks.That didn’t seem logical, so they discounted the

information as a spurious anomaly. Subsequent medical research found that heart disease

affects oxygenation of the blood and cataracts reflected thatcondition. Highmark now offers services to prevent heart attacks among people thus afflicted.

Welcome to the world of business intelligence.

Tips for Getting BI Right

n ANALYZE how executives makedecisions.

n CONSIDER what information executives need in order to facilitatequick, accurate decisions.

n PAY ATTENTION to data quality.

n DEVISE performance metrics thatare most relevant to the business.

n PROVIDE the context that influences performance metrics.

n TAKE INTO ACCOUNT users’ feelings, and address their concernsupfront.

SOURCE: “THE BRAIN BEHIND THE BIG, BAD BURGER AND OTHER TALES OF BUSINESS INTELLIGENCE,” CIO MAGAZINE, MARCH 15, 2005

Overview


Overview

agers might not want to give up control of information they have traditionally kept to themselves.Staffers might not want to even useany BI tools, especially if they aren’tchampioned by a strong and influ-ential executive or are introducedbecause of a merger or acquisitionand don’t help them do their indi-vidual jobs better.

Several strategies can be used tosolve these human issues, such asfinding a strong executive sponsor,reaching out to users to sell them onthe concept and making sure the BIsystem is based on business anduser needs rather than on technicalconsiderations. And sometimesthese strategies are more extreme.One example: This report will detailhow a chemical company actuallytied employees’ pay to their level ofcooperation on a BI project.

But first come the technical prob-lems. Moving to enterprisewide BIcan be likened to painting a house.You might want to just grab a brushand start painting so you can quicklysee the results of your labor. But ifyou don’t spend enough time inpreparation — scraping, sanding and mixing the paint — your projectwill fail.

In BI, you might want to start gen-erating those interesting reports andquickly capitalize on the informa-tion you find. But again, your projectwill fail without proper preparation.

First and foremost in BI prepara-tion comes organizing the raw data.Knightsbridge Solutions LLC in aJanuary 2005 report listed “TakingData Quality Seriously” as the No. 1trend for the year in BI and datawarehousing.

Besides ensuring that structureddata culled from myriad databases isscrubbed and standardized andstored correctly in a data ware-house, more and more companiestoday are delving into unstructureddata from other sources.

Cutting-edge BI tools are now using data from printed documents, e-mail messages and even voice mail

and recorded telephone conversations.While data from these far-flung

sources can provide valuable in-sights, it can also pose new prob-lems. For example, one executivewarns of “vampire” data that can“come back to bite you in the neck,”such as old e-mail messages thatcould be subpoenaed during litigation.

Other risks might arise from pro-viding BI information to many moreusers throughout an organization.While this proliferation can be ben-eficial, it opens up new security

risks — especially with widespreaddissemination via the Internet onlya few clicks away. One municipalitymoved to a BI system to consolidateinformation from thousands ofspreadsheets, so it made all its em-ployees read and sign a documentdetailing proper security procedures,such as not sharing passwords.

But even with the associated in-creased risks, moving to enter-prisewide BI is clearly a growingtrend, according to many researchfirms. They say BI is growing inmarket size and is near the top ofmany CIOs’ to-do lists. This reportwill help you use BI to keep up withthem and hone your competitiveedge. It may not prevent a heart at-tack, but it just might help preventheartburn.

—David Ramel

Categories of BI tools

Different types of users require different types of BI tools. Here are descriptions of some common types of tools used in corporate environments:

n Production reporting tools: Create standard reports for groups,departments or the entire organiza-tion.

n End-user query and reporting tools: Users can create their own reportswith these tools, which require noprogramming.

n OLAP tools: These let users inputdifferent criteria to generate reportsbased on time and other variables.

n Dashboard/scorecard tools: Provide a group of performancemetrics and indicators in an easy-to-read graphical format.

n Data mining tools: Create statisti-cal models of business activity.

n Planning and modeling tools:Can be used to create businessplans and simulations.

SOURCE: THE DATA WAREHOUSING INSTITUTE, 2005

The potential gains include busi-ness process enhancements, in-creased customer satisfaction andcost reductions in areas such assales and marketing.

Organizations that have broadlydeployed BI are realizing some ofthese benefits. Sara Lee Householdand Body Care, a division of SaraLee Corp., began using QlikView BIsoftware from QlikTech Internation-al AB three years ago to create arepository for sales data. Today,field salespeople, marketers andmanagers use the product to accessa variety of information about cus-tomer interactions, buying trends,products and other data that drivessales.

The software has helped the divi-sion improve the accuracy and time-liness of demand forecasts for spe-cific products in different locations,says Gary Kahler, director of salesand operations planning at Sara Leein Exton, Pa.

Workers use the product to down-load BI data into Excel spreadsheetson their PCs, Kahler says. Managersat headquarters use the application,which runs on a Dell server, to com-pare regions by customer and prod-

uct brands over different time peri-ods, he adds. “It’s simple enough foranyone in the company to use butpowerful enough to answer anyquestions they can ask,” he says.

Kahler adds the benefits of BI aretoo “nebulous” to measure. “Weknow inherently that we have effi-ciency improvements throughoutthe organization,” he says. “Peoplework much faster and more accu-rately, and they are able to do morethan they did before. But it’s verydifficult to try to quantify the benefit.”

A Head for Business Education Management Corp., aPittsburgh-based company thatowns and operates career-orientedpostsecondary schools in NorthAmerica, uses BI products fromCognos Inc. and Hyperion SolutionsCorp. to analyze surveys of students.Christopher Kowalsky, senior vicepresident and CIO, says about 250managers in admissions, finance, education and other departmentsaccess the software to learn moreabout how Education Managementis delivering services to studentsand how it can improve operations.

With BI, the company can analyzeits financial performance, its abilityto attract students and the successof new campus locations and acqui-sitions, Kowalsky says. Althoughusers have had some training inquantitative analysis, they’re busi-ness decision-makers rather thanstatisticians, he says. Users accessthe server-based BI applications viatheir desktop computers.

Kowalsky says Education Manage-ment isn’t running metrics to deter-mine the payback on BI technologyand doubts that anyone can do thisaccurately because there are toomany factors involved. But he saysthe company has an intuitive sensethat BI has more than paid for itselfbecause the technology supportscritical business functions. “Withoutit, the business would not be prof-itable,” he says.

Ed Chen, director of IT at public

Trends, strategies and resources


BI for the Masses

BUSINESS INTELLIGENCE WAS ONCE the domain of statisticians and corporate analysts. Not anymore.BI capabilities are spreading to virtually all parts of the organization, as companies strive to put critical

data into the hands of business users who need it to do their jobs.The potential benefits of giving BI capabilities to more

employees include productivity and operational gains, saysDan Vesset, an IDC analyst. “The productivity increase comesfrom the more efficient delivery of data — getting informationto the right people at the right time,” he says. “Many companiesspend a large amount of time aggregating data and getting it to aform that’s accessible to end users and then delivering it to them.”

Get SmartHERE ARE SOME TIPS for successful deployment of BI for the masses:

n DEPLOY adequate security tools and processes to protect theintegrity and privacy of BI data.

n TRAIN employees not only how touse BI applications correctly, butalso how to report and analyze dataaccurately.

n PROVIDE BI capabilities only tothose workers who stand to benefitfrom the information gleaned.

n ASSESS vendor BI products thoroughly to ensure that nonstatis-ticians will be able to benefit fromtheir use.


radio and TV broadcaster KQEDInc. in San Francisco, says the broaduse of BI will more likely succeed ifthe technology is combined withcommon applications such as Excel.“One of the key things is usability.You have to make sure the system iseasily learned and adopted,” he says.KQED is in the midst of a six-monthpilot program in which a samplingof employees is testing BI products,with plans to make BI widely avail-able within the company. The broad-caster hopes to increase revenue byusing BI to analyze promotionalcampaigns, more precisely target itsprogramming and focus on viewerswho are most likely to make finan-cial contributions, Chen says.

Along with the benefits comesome risks. For one thing, usersmight load inaccurate data into data-bases and not understand the rele-vance of BI data. “It’s important thatpeople be trained properly and havea good command of the technology,”says Kowalsky.

Kahler agrees. He says companiesmust ensure that workers under-stand how to use BI applications sothat they don’t draw the wrong con-clusions from data because theysubmitted the wrong queries or mis-used the results.

“BI is not overly complex, but it’sso powerful that it has to be usedwith care,” he says. “There are learn-ing phases people have to gothrough to make sure they’re gettingthe information they thought theywere getting.”

For example, if a financial servicesemployee misunderstands dataabout which segment of the cus-tomer base is most likely to order acertain service, it could result intime and money wasted on a mar-keting campaign that’s aimed at thewrong customers.

One of the biggest challenges ismanaging user expectations, saysIDC’s Vesset. “When you open BI tothe masses, people get a taste ofwhat they can do and start demand-ing more and more information and

analytics,” he says. “In some cases,the IT department can’t keep upwith the requests.” Vesset says theremight also be technical issues todeal with, such as integrating BI ap-plications with existing businesssystems.

Organizations must also guardagainst giving BI tools to too manypeople, says Shaku Atre, president ofAtre Group Inc., a consultancy inSanta Cruz, Calif. If too many peo-ple use the system, companies canrun into problems maintaining re-sources and controlling usage andapplication performance. There arealso security concerns to consider,including the possibility that cus-tomer data could be compromised.“Once information is made availableto the masses, if the proper controls

are not in place, there’s a risk of datafalling into the wrong hands,” saysAtre. “Because of the Internet, infor-mation could be misused. This issomething you have to be very care-ful about.” For example, health careorganizations must secure patientinformation to comply with theHealth Insurance Portability andAccountability Act. Companiesmust also guard against critical in-formation getting into the hands ofcompetitors because so many peo-ple have access to it, says DipendraMalhotra, Atre Group’s chief tech-nology officer.

BI will grow in popularity as ven-dors link its capabilities with famil-iar tools such as spreadsheets, Atresays. “If you want to provide some-thing for the masses, look at what is


BI for Business PartnerSOME COMPANIES ARE FINDING that it’s beneficial to share BI capabilities withbusiness partners as well as with employees. To do that, they’re building Web-based“BI networks” to deliver intelligence to suppliers, consultants and others.

Carl Warren & Co., a provider of claims and litigation management services in Or-ange, Calif., is using a BI system from MicroStrategy Inc. called MicroStrategy Intelli-gence Server and sharing its capabilities with customers via an extranet. For exam-ple, customers such as Bank of America Corp. and Apple Computer Inc. can accessand analyze risk management reports or litigation files on the Web.

The BI system is customizable, so high-level executives can generate “big picture”reports, and claims managers can drill down to more specific information, says PaulPark, CIO at Carl Warren. Customers can generate reports as frequently as theywant, Park says, noting that the company provides the service to more than 700clients in the U.S.

Carl Warren uses security technology such as high-level encryption to protect thedata. Prior to implementing the system, Park says, Carl Warren was printing andshipping paper-based reports to its customers at a much higher cost than what itspends on the BI system.

Owens & Minor Inc., a Glen Allen, Va.-based distributor of medical and surgicalsupplies, uses a BI system based on WebIntelligence from Business Objects SA to help customers track and analyze all purchase orders and enable suppliers totrack and analyze the sale of their products throughout Owens & Minor’s distributionchannels.

With the application, dubbed Wisdom for WebIntelligence Supporting Decisionsfrom Owens & Minor, customers and suppliers access a data warehouse via the In-ternet to get real-time updates, says Don Stoller, director of information manage-ment. The BI extranet, launched five years ago, has improved customer satisfactionand generates additional revenue for Owens & Minor, which charges fees for an ad-vanced version of the offering that includes consulting services.


already being used by the masses,”she says.

Atre says companies that roll out BI broadly can expect to reapbenefits such as reduced costs, in-creased revenue and higher cus-tomer-retention rates. A salespersonusing BI could determine which cus-tomers are most likely to buy certainproducts, and product developerscould have greater insight intowhich products and features bringin the most revenue.

Will risks slow the deployment ofBI to the masses? Not likely, expertssay. The potential benefits of pro-viding strategic information to manyemployees outweigh the risks. “Inthe past, only the elite few had ac-cess to business intelligence,” saysHoward Dresner, a vice presidentand research fellow at Gartner Inc.“We’re really starting to see infor-mation democracy take hold, andthat’s giving everyone the insightsthey need.”


“It was a nine- to 10-year processand a heck of a big investment for acompany of our size,” says Tyler. Henotes that the chemical companymoved ahead slowly and had to con-tinually re-examine the BI model it

was putting in place. The addition of the SAS 8 soft-

ware also required Quaker Chemicalto collaborate and share informationon a global basis, prompting it to tieemployees’ pay to their level of co-

operation on the project. In addition, the company had to

create a common BI language — atime-consuming task — and speedup the collection of data, Tyler says.It also developed a homegrownquery tool to make SAS 8 palatablefor widespread use, although Tylerhas said he might replace that with aset of simplified user interfaces builtinto a SAS 9 upgrade.

Andy George, senior vice presi-dent of technology at ProfitLine Inc.in San Diego, recommends thatcompanies phase in their BI imple-mentations. ProfitLine, which man-ages billing and other administrativefunctions for telecommunicationscompanies, uses Business ObjectsSA’s WebIntelligence software to an-alyze and audit customer bills.George says that during ProfitLine’srollout, ensuring the validity of datawas a big challenge because so manypeople were accessing informationand inadvertently corrupting it.That prompted the company to puta “data czar” in charge of maintain-



Hurdles to BI Implementations

COMPANIES CAN USE business intelligence tools tomake big improvements in their operations, but numerous technical, cultural and internal-processchallenges must be overcome first, according to

some IT managers. The people and process issues can be even more daunting

than the technical ones, says Bubba Tyler, CIO at QuakerChemical Corp. in Conshohocken, Pa. For the past 10 years,Quaker Chemical has used software from SAS Institute Inc. todo data analysis and reporting. But the project wasn’t a simplematter of installing the applications and giving workers accessto them, he notes.

Analyzing Unstructured Data A LOOMING BI CHALLENGE for many companies involves try-ing to exploit various types of unstructured data to help improvecorporate performance. IT managers are pursuing ways of usinginformation such as paper documents, text files, and e-mail andvoice-mail messages for BI purposes — even though the infor-mation isn’t formatted in data warehouse tables.

For example, Niis/Apex Group Holdings plans over the nextyear to start using SAS Institute software and a homegrown toolto mine medical claims records for information, according toJody Porrazzo, director of econometric risk strategy at the insur-ance services company in Princeton, N.J.

The company already uses a SAS 9.3-based system for appli-cations such as creating pricing models for insurers. But Porraz-zo said specially trained staffers have to manually cull data frommedical claims, which can be hundreds or even thousands ofpages long. To simplify that process, Niis/Apex is developing atool that will work with the SAS software and include a set of

built-in rules for automating the process of parsing the informa-tion in claims.

H&R Block Inc.’s Option One Mortgage Corp. subsidiaryplans to custom-develop a system that can convert inbound andoutbound calls into searchable data, said Matt Slonaker, directorof business information at the Irvine, Calif.-based lender.

Option One already uses a mix of software from Oracle Corp.and Microsoft Corp. to help employees assess and manage therisks on loans, Slonaker said. Now, he added, it hopes to con-vert recordings of phone calls into a text format that can be usedto study the behavioral patterns of delinquent borrowers and try to identify customers who plan to file lawsuits against thecompany.

For instance, the application will be able to track how manytimes a borrower says the word litigate during a call and thenhelp Option One employees score the likelihood that he will takethe company to court, Slonaker said.


ing the integrity of data, he says. Information security was a major

issue for the municipal governmentof Falls Church, Va., says ShirleyHughes, the city’s chief financial of-ficer and general manager. WhenFalls Church moved from 2,200 sep-arate spreadsheets to a more consol-idated BI system, it required all em-ployees to read and sign a documentthat explained proper procedures,such as not sharing passwords. Inaddition, access to the BI system is“tightly controlled,” Hughes says.

Proper maintenance of data being

used in BI applications is so crucialthat companies should seek legal ad-vice about what can and can’t bestored on a long-term basis, says AlBrill, senior managing director oftechnology services at Kroll On-Track Inc.

The Eden Prairie, Minn.-basedcompany uses homegrown analyti-cal systems to help collect and pres-ent data to lawyers for use in court.But Brill warns of “vampire” datathat could linger in a system foryears and then “come back to biteyou in the neck.” As an example,Brill cites the possibility that old e-mail messages could be subpoe-naed during litigation.

End-user access to BI systems hasto be monitored regularly and keptcurrent, Brill adds, noting that work-ers who change jobs within a com-pany might retain the ability to ac-cess data they should no longer beable to see.

Brill describes BI as potentiallythe most important technology in-vestment that a company can make.“It deserves the kind of planningand thinking that a project that po-tentially means life and death for acompany should have,” he says. “Idon’t think there are any recipes for

success, but there are a heck of a lotfor failure.”


Where do youobtain your BI tools?

55%: Best-of-breed tools frommultiple vendors

46%: Integrated suite from a single vendor

22%: From applications we purchase

13%: We build themSOURCE: DATA WAREHOUSING INSTITUTE SURVEY(594 RESPONDENTS), 2005

Criteria for selecting enterprise

BI toolsA recent Data Warehousing Insti-tute survey of 490 organizationstrying to transform BI from a de-partmental resource to an enter-prise resource rated the followingcriteria as “highly important”:

67%: TCO

61%: Quality of vendor support

52%: Pricing (licensing andmaintenance)

52%: Vendor viability and leadership

51%: Investments of time, skilland money in current tools

30%: Vendor relationship with organization

Various studies report that 47% to64% of companies use stand-alonespreadsheets for planning and budg-eting, for example. But critics sayspreadsheets — invented as a per-sonal productivity tool — aren’t wellsuited to collaboration, data qualityor regulatory compliance. “Excel is atool of information mavericks,” saysEleanor Taylor, manager of businessintelligence strategy at softwarevendor SAS Institute Inc. in Cary,N.C.

“Besides being extremely un-wieldy for processes involving largevolumes of data and multiple users,spreadsheets often contain substan-tial, material errors, according to academic research,” notes PaulHamerman, a Forrester ResearchInc. analyst.

Companies are just starting tolook at the problems caused byspreadsheet proliferation, says Gartner Inc. analyst Michael Silver.“Some enterprises are addressing it,but most aren’t,” he says.

No one is suggesting that thespreadsheet is going away anytimesoon or that it’s a top-of-mind IT is-sue. “The subject is certainly of in-

terest and has potential for improve-ment, but in the scheme of things,it’s not high on the list of priorities,”says Joe Iannello, CIO at watchmak-er Movado Group Inc. in Paramus,N.J.

What’s the Problem? Questioning the desirability ofspreadsheets, after their widespreadacceptance over the past twodecades, is almost like questioningmom and apple pie. But for a mod-ern corporation looking for consoli-dated planning and financial report-

ing, spreadsheets pose challengesnot dreamed of when they first began popping up on PCs across the land.

Here are three of the more significantspreadsheet issues that companies haveto address:

DECENTRALIZATION. Mentor GraphicsCorp. in Wilsonville, Ore., had acentral 25MB Excel spreadsheet and1,200 budget spreadsheets acrossthe enterprise, one for every costcenter. But having numerous spread-sheets makes it difficult to collectimportant data. “Spreadsheets aregreat analysis tools, but at somepoint you start using them as a plan-ning system, and that’s where Excelstarts breaking down,” says Jan-Willem Beldman, Mentor’s enter-prise data architect.

So Mentor decided to use SAP AGsoftware as a centralized database ofaccounting transactions and Hyperi-on Solutions Corp. software as abudget-planning tool. The Hyperionsystem allows Mentor to quickly doa what-if analysis of, say, changingemployee benefits in various coun-tries. “These are things you mightbe able to model in Excel, but if youhave a lot of details, it’s much morethan you could have in a spread-sheet,” says Beldman.

COMPLIANCE. Having financial datain a hodgepodge of spreadsheetsalso makes it hard to maintain oneversion of the truth, which is impor-tant for complying with the law. Forexample, the Sarbanes-Oxley Act re-quires companies to maintain agood audit trail, and generating sucha trail is difficult to do with Excel,



Spreadsheet Overload?

IN THE BEGINNING, there was VisiCalc, the first killer appfor the PC. Lotus 1-2-3 subsequently took over, beforeyielding the throne to Microsoft Corp.’s Excel. Today,spreadsheets are so easy to use and ubiquitous that

they’ve sprouted like weeds throughout most companies. And they often hold important financial data.

But what if Mary’s sales spreadsheet differs from Tom’s and has faulty data or a modeling error? What if Tom hoardshis spreadsheet data — it’s a form of power, after all — andwon’t let go? How do you get the data from dozens of far-flungspreadsheets into a companywide planning or budgeting system that meets the latest accounting standards?

Spreadsheets aregreat analysis

tools, but at some pointyou start using them as aplanning system, andthat's where Excel startsbreaking down. JAN-WILLEM BELDMAN, ENTERPRISE DATA ARCHITECT, MENTOR GRAPHICS CORP.


Beldman says. “With financial data, the risk of

using spreadsheets is too high underSarbanes-Oxley,” says Hamerman.“Let’s say you use spreadsheets forconsolidations of financial report-ing. I think there’s a chance for er-rors to occur in the spreadsheet for-mulas in this environment. That’s arisk the company shouldn’t take.”

DIRTY DATA. “One major issue withspreadsheets is poor data quality. As you make changes or add infor-mation, your spreadsheet will haveerrors or mismatched formulas,”says Ed Chen, director of IT atKQED Inc., which operates publictelevision and radio stations in SanFrancisco.

That’s why some users are mov-ing from decentralized data held inspreadsheets to a centralized data-base. “The quality of data improvesgreatly because you have muchmore control of the different calcu-lations,” Beldman says.

Spreadsheet incompatibilities caneven cause conflicts within a com-pany. “If I have developed a spread-sheet, I trust my spreadsheet morethan yours, even if yours [is really]more accurate. That creates politicalproblems,” observes Shaku Atre,president of Atre Group Inc., a data-base and BI consultancy in SantaCruz, Calif.

Reality Check To some extent, the criticism — it’sbeen called “the demonization ofspreadsheets” — comes from ven-dors pushing their own, more ex-pensive financial software, such asbusiness performance managementsoftware. Vendors put out press re-leases with headlines like “Spread-sheets Out, Hyperion In” and “Ex-tensive Reliance on SpreadsheetsDulls CFOs’ Strategic Edge,” whilearguing that spreadsheets won’thelp companies comply with theSarbanes-Oxley Act.

“Only to a degree is that true,”says Chris Iervolino, head of ITEC

Consulting Inc. in White Plains, N.Y.He says it’s true that spreadsheetsaren’t a good corporate data store,and they aren’t good for managingprocesses like planning and budget-ing because there’s too much error-prone manual work involved. ForSarbanes-Oxley compliance, it’s eas-ier for executives to sign off on theintegrity of a financial process if it’sfully automated, without manualsteps like in spreadsheets, Iervolinosays.

“But that doesn’t mean spread-sheets are down and out,” he contin-ues. Iervolino and other observerssay the future of the spreadsheet isas a user interface for manipulatingdata extracted from a central, back-end database. “[Spreadsheets] are agreat manipulation and analysistool; they’re not such a great data-base,” says Beldman at MentorGraphics.

Besides, it would be hard tosnatch spreadsheets away from thepower users. “You’d have to pull thespreadsheets from the cold, deadhands of the analysts,” Iervolinoquips. That’s why the vendors ofeven the most sophisticated busi-ness performance management tools have interfaces for connectingto spreadsheets — it’s a market requirement.

“People can quickly become com-puter-literate [with spreadsheets].They feel empowered; their confi-dence is boosted,” Atre says.

So be prepared for resistancewhen moving to a centralized sys-tem. “Trying to get people not to

save data locally and not to do theirown spreadsheets is a cultural prob-lem based on 15 years of PC use,”Gartner’s Silver says.

Although spreadsheets have sig-nificant shortcomings, they provideenough benefits — usability, what-ifanalysis and presentation graphics— that most observers say they’ll bearound for the foreseeable future.“They will persist as an interfacethat people will continue to use tomanipulate and store data,” saysHerbert A. Edelstein, president ofTwo Crows Corp., a data miningconsultancy in Potomac, Md. “I can’tenvision a world where the spread-

sheet will disappear.” Prashant Dholakia, senior vice

president at FreeMarkets Inc., a pro-curement services provider in Pitts-burgh, isn’t so sure. Someday, largecorporations may have to consider apostspreadsheet world, Dholakiasays. “Spreadsheets can go only sofar,” he says. “Something will have toreplace it, but there’s no consensusof what that is.”


Besides being extremely

unwieldy for processes involving large volumesof data and multipleusers, spreadsheets often contain substantial,material errors, accord-ing to academic research.PAUL HAMERMAN, ANALYST, FORRESTER RESEARCH

Trying to get people not to save

data locally and not to do their own spread-sheets is a cultural problem based on 15years of PC use. MICHAEL SILVER, ANALYST, GARTNER

For example, online retailer Over-stock.com Inc. has begun connect-ing users to a real-time data ware-house it completed last month. Theproject’s goal is to help employeesgain insight into the effectiveness of the company’s online and e-mailadvertising campaigns.

Overstock is using transactionaldata management tools fromGoldenGate Software Inc. to pull in-formation directly from its businesssystems into the data warehouse,says Jack Garcella, the Salt LakeCity-based retailer’s vice presidentof data warehousing, analytics andreporting.

The data warehouse, which isbased on NCR Corp.’s Teradata soft-ware, will replace a process thatused traditional extract, transformand load tools to build reports di-rectly from Overstock’s back-endsystems. As the retailer grew, the re-ports stressed the systems and gaveemployees day-old data, Garcellasays. Now the data warehouse re-ceives Web site clickstream data inreal time, financial and product-sales data every 15 minutes and oth-er information hourly.

“When we launch campaigns now,we can look within five minutes andsee if they are producing lift or rev-

enue that would not normally havehappened,” Garcella says. “You can’twait until the next day or threehours later to get that data.” He de-clined to specify how much Over-stock is spending on the warehous-ing project, other than to say thecost is in the millions of dollars.

Harrah’s Entertainment Inc. istesting a real-time data warehousethat combines operational and his-torical customer data, says Tim

Stanley, the Las Vegas-based gamingcompany’s CIO.

The new setup is based on an ar-chitecture that Harrah’s developedin mid-2002. The company is usingadapters from Tibco Software Inc.to feed information from transac-tional systems into its Teradatawarehouse to help workers interactwith customers at Harrah’s proper-ties, on the phone or on the Harrah’sWeb site.

“It uses Teradata’s transactionaldatabase and also has direct accessto all the historical data,” Stanleysays. “You don’t have to have twodatabases talk to each other.”

Changing Needs Eric Rogge, an analyst at VentanaResearch Inc. in San Mateo, Calif.,says that because BI tools are beingused more often for operational decision-making, many companiesare finding that they need to refreshtheir data warehouses more fre-quently than on a nightly basis.

“It’s not about loading a datawarehouse so a small department ofbusiness analysts can forecast twoyears out — it’s for daily decisions,”he says.

For 18 months, Avnet ElectronicsMarketing has been using a near-real-time data warehouse that cap-tures orders and updates of logisticsdata from its back-end system every15 minutes, says Kevin Harrington,director of IT delivery for global in-formation solutions at the Phoenix-based electronics distributor.

Avnet uses tools from InformaticaCorp. to move the data into thewarehouse. Because of the integra-tion infrastructure, it took only 24hours in late July to begin populat-ing the warehouse with order andcustomer information from a com-pany that Avnet recently acquired,Harrington says.



Users SpeedFeeds to DataWarehouses

AS BUSINESS INTELLIGENCE becomes a critical compo-nent of daily operations, real-time data warehousesthat can provide end users with rapid updates fromtransactional systems are increasingly sprouting

up at companies.

WarehouseChallenges

Implementers of data warehousesmost often cite these issues aschallenges:

1. Data quality

2. Security

3. Availability

4. Data standards/consistency

5. Web-based access

6. Performance/scalability

SOURCE: IDC, FRAMINGHAM, MASS.


But not all users find they needreal-time data warehouses. MerialLtd., which makes medications forpets and livestock, last year ditchedefforts to create a real-time systemfor updating sales and inventorydata from its 33 ERP systems world-wide. Although some divisions up-dated invoicing information daily,others did so only weekly or at theend of the month, says Steve Lerner,director of information systems,global finance applications and inte-gration at Duluth, Ga.-based Merial.

In the end, the company decidedto use data warehousing tools fromKalido to pull data from its ERP sys-tems once a week. “The consensusamong the business users was thatthere was no way they were pre-pared to make business decisionsbased on sales other than on a week-ly basis,” Lerner says.


After watching the group bouncebetween the two extremes, the CIOstepped in and showed several cor-porate vice presidents and the chiefoperating officer a demo of a digitaldashboard, which pulls data frommultiple sources to graphically pres-ent select performance metrics on asingle screen. The executive grouptook to it almost immediately. Theyultimately decided to track 10 keyperformance measures, which noware accessible by all 3,000 of thehealth insurer’s employees via aWeb-based dashboard that aggre-gates data from 20 systems.

“The report enables us to focus on whether we’re carrying out our strategies and how we’re per-forming against our business goals,”says Karen Thompson-Yancey, senior director, strategic businessintegration.

What happened at BCBS is a text-book example of how to do dash-boards right. Top executives drovethe effort. They kept the dashboardsimple and made it ubiquitousthroughout the enterprise. Userseven willingly parted with theirbeloved paper spreadsheets. Here’show they did it.

Information Overload“We used to have all these reportsand we spent too much time on‘Where did you get that info?’ as opposed to ‘How is the businessrunning?’ ” says Thompson-Yancey.After the dashboard demo, “OurCFO and COO made it very clearthat it was critical for us to collabo-rate and have the same informationand not confuse the organizationwith various sources and instead tofocus on how we’re doing.”

The managers formed a small,cross-functional team representingeach area of the company. “It wasimportant to us, as part of our cul-ture, to ensure that we had sponsor-ship of our executives and to makesure it was a cross-functional, col-laborative group,” says Thompson-Yancey. “We knew the reports wehad were not getting us what weneeded. So we went off to get rec-ommendations about what informa-tion we needed to look at.”

Middle Managers Make ItThey found that getting input frommiddle managers was the key. “Thatmiddle group is critical,” she says.

“They are close enough to day-to-day operations to distinguish be-tween tactical and strategic levels ofinformation, and because they’re theones giving updates to the execu-tives in the staff meetings, they havea eye into which information execu-tives were interested in seeing.”

Moreover, she says, getting morepeople involved leads to more buy-in at every level. “When you openup a dialogue and ask people fortheir opinions, it helps get everyoneworking together.”

The group came back with a longlist of metrics, then they workedwith the executives to fine-tune it.



CASE STUDY:BI Dashboards

MANAGERS AT Blue Cross Blue Shield of Massachu-setts used to show up at their monthly meetingsarmed with several pounds of paper documents— departmental performance reports, printouts

of e-mail and PowerPoint slides and lots and lots of spread-sheets. The managers eventually agreed to lighten their loadby regularly tracking a total of 45 business performance meas-ures, which were printed out in eight-point type to fit on a single sheet of paper.

Early Questions

As the BCBS cross-functional teamtrolled for meaningful metrics, thesewere the questions they asked:

n Where are we currently gettingdata?

n What are the most importantpieces of information executiveslook to in order to run the business?

n What frequency of information dowe need — daily, weekly, monthly,quarterly? Does frequency vary depending on the information?

n Where do we want the informationto go in the organization? (The audi-ence will determine the level of detail we need.)

n Do we need the information in realtime or is it possible to have a delay?

n What’s the story we’re trying to tell?


“We needed to refine that to a top-level list of measures that reallydrive the business,” she says.

The very act of fine-tuning en-hanced collaboration and buy-inamong the business units. “As wefine-tuned the list, we got everyoneonboard,” she says. “We are all very focused on executing on thethings that will affect company performance.”

Time to TestThe next step was to test the rele-vance of various kinds of informa-tion with a few different audiences.“Give yourself enough time to getthe right information,” Thompson-Yancey suggests. “Sometimes youput things together too quickly inorder to meet a date, but unless youget it right, you’re not doing yourselfor the company any service.”

The entire project took BCBSabout six months. At the end of that time, they were looking at top-level business performance metricssuch as member satisfaction and retention, sales and financials, staffretention and IT system uptime and availability.

Because BCBS placed such a highvalue on collaboration, Thompson-Yancey says, trust in the system wasnever a problem. “They [the busi-ness people] were involved in find-ing the metrics that were most im-portant and they reviewed andsigned off on the reports we usedprior to the release of information.So we didn’t have to talk about theaccuracy of the information — justthe impact.”

“This was a group that all agreedthey’d drive this effort right fromthe top,” recalls former IT directorJim Humphrey, who then headed in-formation delivery and knowledgemanagement. “We had no problemgetting people to part with paper re-ports. They liked the idea of usingbetter technology. Today, they usethe metrics to drive the agenda oftheir monthly meetings.”

Thompson-Yancey says the BCBS

corporate culture of executive spon-sorship and cross-functional collab-oration provided the foundation forthe project’s success, but no onethinks the dashboards are done.“You’re never really there,” she says.“As the business evolves, the reportshave to evolve as well.”


Success Factors

ASSURE executive sponsorship and vocal support for the initiative.

ASSEMBLE a small, cross-functionalteam that represents all areas to be reflected in the dashboard.

HAVE A GREAT IT TEAM, and stay extremely close to them.

DON’T DO things to future users; do things with them.

PROVIDE OPPORTUNITIES to refine the dashboard reports as the projectmatures.

EVEN AS YOU’RE IMPLEMENTINGthe dashboard, keep assessing it; keep getting feedback.

KEEP ASKING, “Is it working?” “Do we have the right level of detail?”“Do we need to refine this?”

NEVER BE AFRAID to make a changeas you’re going through the project.

REALIZE DASHBOARDS are never finished. As the business evolves, dashboards must evolve too.

How does data mining work?Data mining is a subset of businessintelligence, which covers a broadrange of analytics technologies. Of-ten used for predictive modeling,data mining tools can also help or-ganizations better understand rela-tionships among variables.

One core software tool is onlineanalytical processing (OLAP), whichextracts, structures and stores ware-housed data to enable quick, multi-dimensional analysis. A dimensioncan be any variable your companytracks: customer locations, sales vol-umes, product development costsand so on. An OLAP data set ismade up of dimensions and meas-ures, which can then be used forqueries to elicit detailed data break-downs and information on associa-tions among variables. For example,a grill manufacturer could use anOLAP query to correlate grill saleswith weather conditions across vari-ous locations, to determine howheat waves affect its business in dif-ferent regions.

Who is likely to benefit from this tool? Consumer-focused companies withsizable caches of information oncurrent and potential customers,

such as retailers, are ideal candi-dates for data mining technology.Wal-Mart Stores Inc., for example, isfamed for its use of data mining toanalyze “market baskets,” the com-binations of items consumers grouptogether in one purchase. Pharma-ceutical makers rely heavily on datamining technology to track theirdrugs’ effects, while financial com-panies use it for identifying newcustomer opportunities.

What’s in it for marketers? Data mining tools can help targetnew markets and craft more attrac-tive pitches to upsell current cus-tomers. For instance, outdoor gearretailer Recreational Equipment Inc.(REI) in Kent, Wash., uses data min-ing software to parse the extensivecustomer data it collects through itsWeb site, direct mailings and 78 re-tail stores. When REI considers newstore locations, it examines orderdata to find places with high con-centrations of customers buying on-line and through the company’s cat-alogs, according to Alison Polenz,director of customer research.

The company also uses data min-ing tools to tailor its stores’ productmixes to local market preferencesand to uncover patterns that suggest

future purchases by customers. “Weknow people are involved in lots ofdifferent activities, even though theymight not have bought all the gear atREI,” Polenz says. “So we’ll send ourcycling catalog to someone whomight not have bought cyclingequipment but who probably is in-terested in cycling, based on theirother activities associated with cy-cling.” Camping is one such tip-off,she says.

Who are some vendors of this software? Major players include SAS AB, SPSSInc., IBM, Computer Associates In-ternational Inc. and Fair Isaac Corp.,and dozens of smaller specialist com-panies are also competing for newbusiness. Enterprise applicationscompanies are eager to crack themarket as well. They figure that sincethey’re already making the front-endsystems their customers use forworking with corporate data, theymight as well capture the back-endmarket for tools to mine that data.

Can you get started without ahuge investment? Yes. Upstarts such as Apollo DataTechnologies and Marketics Tech-nologies are carving out a niche bydelivering analytics as a service andworking with clients on specificmarketing problems. Such an ap-proach may be useful for test-driving data mining technology on a specific project and measuringhow well the investment pays off.However, cleaning data so that min-ing tools can uncover useful infor-mation from it can be a complex and expensive endeavor. Still, whatis the cost of cleaning data whencompared against critical customerinsight to make a new campaign orstore location succeed? In a word:priceless.



Data Mining

EVERY INTERACTION your company has with a customer or supplier likely generates a data trail —and that data provides a wealth of information formarketers. Extracting that information and getting it

into usable shape, however, requires sophisticated data miningtools. The same technology that police departments use toidentify patterns in crime data and to deploy officers accord-ingly can help chief marketing officers uncover customertrends and better focus their marketing resources.

But a new generation of text min-ing tools allows companies to extractkey elements from large unstruc-tured data sets, discover relation-ships and summarize the informa-tion. Many organizations are deploy-ing or considering such software todeal with their mountains of text, de-spite the need for specialized skills tomake implementations work.

For example, since 2000 Dow’s re-search staff has been using Clear-Research software from ClearForestCorp. in New York to extract datafrom a century’s worth of chemicalpatent abstracts, published researchpapers and the company’s own files.

“By managing the informationbetter and eliminating the irrele-vant, we’ve been able to reduce thetime it takes for [researchers] tofind what they need to read,” saysShabrang.

Text mining tools take a variety ofapproaches. ClearResearch uses aproprietary pattern-matchingmethodology to search for informa-tion, categorize it and graphicallyshow its relationship to other data.

“The software can see, discoverand extract concepts, not justwords,” says Shabrang. “It gives us a pictorial representation of the textin the documents in an easy-to-understand chart.”

Adoption Roadblocks The text mining software availablenow doesn’t yet match the accuracyof data mining tools, but vendors areimproving their products’ ability tounderstand context, which is key tomaking text mining tools effective.

“Understanding linguistics andovercoming its challenges is a hori-zon that has not been dealt withwell,” says William McKnight, presi-dent of McKnight Associates Inc., adata warehousing consulting firm inPlano, Texas. “Basic text mining ispossible, but the performance needsto be improved and the tools don’tscale well.”

Because of these limitations, textmining tools are still niche productsgenerally restricted to specific partsof an organization. But they arestarting to catch on.

“Over the last 12 to 18 months, Ihave seen a lot of interest in usingthese tools for regulatory compli-ance,” says Brian Babineau, a re-search analyst at Enterprise StorageGroup Inc. in Milford, Mass. “Butonce that seems to be under control,people will retrofit these applica-tions for other purposes, like datawarehousing and CRM.”

While there are software systemsthat analyze both structured and un-structured data, many companies

use traditional BI software on theirstructured data and then turn toseparate tools to analyze text-baseddata. Electronic Data Systems Corp.,for example, has all of its 130,000employees fill out an online ques-tionnaire about their jobs once ayear. Another three times a year,20,000 employees answer an addi-tional survey.

Some of the survey questions aremultiple choice, making it easy forEDS to plug the answers into BI soft-ware from SAS Institute Inc. in Cary,N.C., and SPSS Inc. in Chicago,where it’s aggregated, dissected andanalyzed. Some of the most impor-tant feedback, however, comes in theresponses to open-ended questions.In the past, those responses were for-warded to the line managers to drawconclusions, since they didn’t fit intoany easy-to-manage structure.

Three years ago, EDS startedlooking for a better way to interpretthose responses and harness the in-formation they contained.

“There was so much richness inthere that we needed to analyze iton a higher level and look for trendsacross the enterprise,” says GregTalkington, a human resources dataanalyst at EDS.

EDS began using PolyAnalystfrom Megaputer Intelligence Inc. inBloomington, Ind., which can mineintelligence from structured and un-structured data. PolyAnalyst isbased on an implementation of the



Text Mining

UNSTRUCTURED DATA, most of it in the form of textfiles, typically accounts for 85% of an organization’sknowledge stores, but it’s not always easy to find, access, analyze or use.

“We are drowning in information but are starving for knowl-edge,” says Mani Shabrang, technical leader in research anddevelopment at Dow Chemical Co.’s business intelligence center in Midland, Mich. “Information is only useful when itcan be located and synthesized into knowledge.”

We are drowningin information

but are starving forknowledge.MANI SHABRANG, TECHNICAL LEADERIN RESEARCH AND DEVELOPMENT, DOWCHEMICAL CO.


WordNet semantic dictionary devel-oped by the Cognitive Science Labo-ratory at Princeton University.Among other functions, PolyAnalystassigns words to subject categoriesand provides related words. Talking-ton uses PolyAnalyst for analyzingthe open-ended questions but stilluses traditional BI software for themultiple-choice questions and com-bines the information from the twoin consolidated reports.

There are separate tools that spe-cialize in analyzing either databasesor text files, but there are also tech-niques that allow the two to be cor-related. Patricia B. Cerrito, a profes-sor of mathematics and a biostatisti-cian at the University of Louisvillein Kentucky, mines hospital recordsto discover ways to improve patientoutcomes. She uses SAS Text Mineron text files, such as patient charts.But she also pulls in flat-file snap-shots of billing and pharmaceuticaldatabases and analyzes those as text,rather than as database entries.

“Where you have thousands or

tens of thousands of categories,standard categorical analysis simplywill not work,” Cerrito says. “But bytreating it as unstructured data, Ican then get some very useful infor-mation from it.”

By examining thousands of pa-tient outcomes with Text Miner, shehas found useful information — thatprescribing certain medications can

prolong hospital stays for patients,for example, and that the blood sug-ar levels of diabetes patients can becorrelated to their risk of infectionafter cardiac surgery.

The differences in how hospitalsrecord their patient information rep-resent a major barrier to gatheringaccurate medical data, Cerrito says.Although they dutifully record mas-sive amounts of data, it hasn’t beencleaned or validated, which makes itdifficult to analyze. That’s why Cer-rito uses mining software to cleanseand standardize it.

“I think my results are more accu-rate because I don’t make the stan-dard assumption that hospitals enterdata uniformly across the country,”she says.

Feeding Other Systems Heidi Collins, global IT director forknowledge management at AirProducts and Chemicals Inc. in Al-lentown Pa., is using SmartDiscov-ery from Inxight Software Inc. inSunnyvale, Calif., to organize thecompany’s internal information andmake it more readily available. “Wehave an initiative to transform theorganization from silos of businessinformation to a business-process-focused, cross-functional organiza-tion,” she says.

The company has more than 18,000employees in 30 countries and morethan 600 intranet and extranet sites.Its file servers contain 9TB of un-structured data, not counting e-mailor anything stored on local drives.

Among other things, Air Productsis using SmartDiscovery to generatea catalog and index of the datarepository so that it can be moreeasily accessed by Microsoft Share-Point Portal document managementsoftware. This catalog and the indexare stored separately from the docu-ment repository.

Air Products is also using the soft-ware for Sarbanes-Oxley compliance,content life-cycle management and e-learning. By correctly categorizingthe data, business rules can be appliedto a category of documents ratherthan to individual documents. For ex-ample, if a document relates to aspectsof operations covered by Sarbanes-Oxley, then the appropriate data-re-tention policies are applied to it.

“I call it the central nervous systemfor what we are doing with knowl-edge management,” says Collins.

The Skills Gap Installing a text miner is generally asimple process. Cerrito reports thatshe just needed to load six CDs toget SAS Text Miner running on herworkstation. Shabrang says it tookabout an hour to set up Clear-Research. The hard part is gettingmeaningful results from a processthat depends on the skill and knowl-edge of the person using the software.It takes a skilled analyst to properlyinterrogate text repositories.

In addition to having analyticskills, the user has to be familiarenough with the data set to under-stand what the results mean. For


PREDICTION

Mining the e-mail pile. “Companies are just starting to realize the valuable knowledge and intellectual prop-erty that can be found in their e-mail archives. Over the next five to 10 years, thosearchives will become fully indexed, searchable, rich databases that provide insightsabout business issues, employees and where competitive advantage resides. For example, a CEO could quickly find out what's going on in a plant in Mexico, withoutever leaving his office at headquarters.”

GREG ARNETTE, FOUNDER AND CTO, INTELLIREACH CORP., DEDHAM, MASS.

We are getting anincreasing under-

standing of what thingsare possible with textmining. But there is ahuge skills problem inthis area, which is why it hasn’t gotten muchtraction so far.ALEXANDER LINDEN, ANALYST, GARTNER INC.


example, Cerrito is a mathematicianworking on medical data. She mayfind that a particular drug frequent-ly comes up in certain settings, butshe then needs to ask a pharmacistwhat that means medically. But thecombination of her skills and thoseshe consults with is saving lives.

“We are getting an increasing un-derstanding of what things are pos-sible with text mining,” says Alexan-der Linden, an analyst at GartnerInc. “But there is a huge skills prob-lem in this area, which is why it hasn’t gotten much traction so far.”

This restricts the direct use of thetools to specialists such as Talking-ton and Cerrito. At Dow, Shabrangassists researchers in conductingsearches.

To make the functionality morebroadly available while they tackleusability problems, vendors are in-corporating text mining tools as abackground function to improve theeffectiveness of more familiarsearch or document managementapplications.


Text Mining GlossaryText miners use a variety of approaches to extract and present relevant information. Below are definitions of common methods:

CATEGORIZATION - Presents the search results in categories, rather than as an undifferentiated mass.

CLUSTERING - Grouping similar documents based on their content.

EXTRACTION - Extracting relevant information from a document — for example, pulling out all the company names from a data set.

KEYWORD SEARCH - Searching documents for the occurrence of a particularword or set of words.

NATURAL-LANGUAGE PROCESSING - Determining the meaning of written wordstaking into account their context, grammar, colloquialisms and so on.

TAXONOMY - Categorization of data according to a predefined framework, either industry-standard or customized. Some tools can automatically generate a taxonomybased on analysis of the data store.

VISUALIZATION - Graphically presenting the mined data so relationships are easier to spot and understand.

For example, LoanPerformanceuses such tools to help its clientspredict which of their customerswill be late with payments, whichwill be lying when they say thecheck is in the mail and which willbe likely to default altogether. TheSan Francisco-based firm operates acooperative database of loan pay-ment information for financial insti-tutions. Richard Harmon, seniorvice president of scoring and analyt-ic services at LoanPerformance, saysits customers, which include mort-gage servicers, use the data to en-courage on-time payments or to putdelinquent accounts on the fasttrack to foreclosure.

Predictive analytic tools are alsoused to predict outright fraud. Forexample, at health insurer HighmarkInc. in Pittsburgh, such systems areset to anticipate and block fraudu-lent claims.

The adoption of predictive analyt-ics systems is on an upswing, drivenby technology advances and the po-tential for large bottom-line bene-fits. The number of preconfiguredand proven models available for spe-cific industries and applications isincreasing, while the model-creationprocess is more automated than itonce was. That means analysts canbuild models faster — and refreshthem more frequently in response to

changing business needs. Successful models can pay off big.

At LoanPerformance, a model thatpredicts which accounts that are 90days in arrears will default savedone client $2 million in six months.The total cost of deployment was$400,000. Those types of returns areone reason why IDC research showsthe sale of predictive analytics toolsgrowing to $3 billion by 2008, whichwould be a nearly 40% increasefrom 2004. Such tools make up 25%of the business intelligence market.As the volumes of business datahave increased, the desire to extractvalue from that information has in-tensified. Fortunately, predictive an-alytics tools have become easier touse, says Harmon, allowing morestreamlined model-building work-flows and enabling analysts steepedin business issues to do more with-out the involvement of statisticians.“This is where the future lies,” hesays. “The tools are being automated.”

The biggest benefits, however, arecoming on two fronts: the inclusionof unstructured data into the predic-tive modeling process to improveaccuracy and a push to execute pre-



Predictive AnalyticsGrows Up

IN THE MOVIE MINORITY REPORT, Tom Cruise’s character relies on visions from “precogs,” people who can predictcrimes, to catch criminals before they can act. While thefilm takes place in the future, the predictive analytics

tool sets available to businesses today are bringing similar scenarios to life.

Avoiding the ‘Duh’ Factor One pitfall with predictive analytics is that it may end up predict-ing the obvious, users say.

“You can often demonstrate that the software is irrelevant. Idon’t need a statistician to tell me that someone who buys ahammer will also buy a nail,” says Lou Agosta, an independenttechnology analyst in Chicago.

Avoiding such embarrassments requires a review of inputvariables by those who understand the business, says RichardHarmon, a senior vice president at LoanPerformance. The com-pany developed an application that predicts the likelihood ofloan defaults for borrowers who are 90 days past due on a pay-ment. “You could put silly stuff in any model, like why a certaintype of house shingle could lead to a [home mortgage] default,”he says.

“You can hire intelligent people who are modelers, but if theydon’t have domain knowledge, that’s where you usually get intotrouble,” Harmon says. “The person needs to have the domainknowledge of what you are building.”

Sometimes, however, results initially dismissed as spuriousend up being important. At health insurer Highmark a few yearsago, an analysis indicating that cataracts were an indicator of future heart attacks was discounted, says Christopher Scheib,manager of decision support. But in the past year, medical researchers have discovered that heart disease affects the oxy-genation of the blood and that the presence of cataracts is a reflection of that condition. “It is indeed a predictor of heart disease,” Scheib says. Highmark now offers services to preventheart attacks among people with that condition.


dictive analytics and present resultsin real time.

Predictive analytics involve sever-al steps, ranging from identifyingand preparing target data to devel-oping a statistical model, testing iton a sample for accuracy and thenrunning it against the full data set.Results are sent to front-office sys-tems, where business logic is usedto, for example, cross-sell a cus-tomer a different product or flag aninsurance claim as potentially fraud-ulent. While most organizations cus-tomize predictive models to theircustomer bases and business chal-lenges, many processes for findingmodels have been automated.

More challenging are efforts toachieve real-time results. They fall

into three categories: enabling real-time scoring on the front end when,say, a new loan application comes in;updating the back-end databases;and accelerating the pace at whichmodels can be refreshed to dealwith changing scenarios, which canbe helpful because criminals areconstantly devising new ways tocommit fraud, for example.

Texting It Up Harmon says he was surprised athow much text mining increased theaccuracy of his predictive models.The previous model included struc-tured information such as loan his-tories, credit reports and demo-

graphics. He added textual notes en-tered by call center staffers as theyspoke with customers. “That infor-mation tends to be very, very rich,despite the fact that it tends to bevery noisy,” Harmon says. He usedtools from Intelligent Results Inc. inBellevue, Wash., to analyze linguis-tic data and identify when someonemay be lying. For example, if some-one says, “The check is in the mail,”that might be one indicator. “Whatwe’re looking for is not just thewords, but the patterns that lead toan event,” says Harmon.

“The text-alone models workedbetter than our standard models,” hesays. When Harmon mixed the textwith structured data, accuracy im-proved by 18% over his originalmodel.

J.D. Power and Associates is in theearly phases of testing text mining.The Westlake Village, Calif.-basedcustomer research firm wants to useverbatim comments from surveys tocreate an early warning system thatpredicts warranty problems for au-tomobile manufacturers.

J.D. Power is currently experi-menting with a tool from ClearFor-est Corp. in Waltham, Mass. Prelimi-nary testing has shown that writtenresponses are more useful in pre-dicting the nature of a given prob-lem than are structured, check-boxanswers, says Joe Ivers, executive di-rector of quality and customer satis-faction research.

While written comments are pro-vided to J.D. Power’s customers, thevolume of surveys makes it hard forthe automakers to identify unfore-seen problems with vehicles. Themanufacturers want to catch suchproblems before large volumes ofnew vehicles have shipped. “By thetime something appears frequentlyenough to appear to the unaidedeye, it’s too late,” Ivers says.

Nextel Communications Inc. inReston, Va., uses Enterprise Minerfrom SAS Institute Inc. in Cary, N.C.,to make predictions based on textcaptured in call center dialogues.


ToolboxREGRESSION: Fits a line to a set of historical datapoints to minimize the sum of thesquares of the distances of the datapoints to the line.

For example, if the line expressesthe relationship between independentvariables such as age, sex and in-come to a dependent variable such as sales, then it defines an equationthat can be used to forecast sales.

Time SeriesAnalyses:

MOVING AVERAGE: Each new point in the time series isthe average of some number of ear-lier consecutive data points, some-times chosen to eliminate seasonalfactors or other irregularities.

EXPONENTIAL SMOOTHING:Similar to the moving average, except more recent data points aregiven more weight.

MEMORY-BASED REASONING:Sometimes called the “nearestneighbor method,” it’s an artificialintelligence technique that can fore-cast something by identifying themost similar past cases and apply-ing that information to a new case.

ARTIFICIAL NEURAL NETWORKS:Patterned after the human brain,they’re composed of a large numberof processing elements (neurons)tied together with weighted connec-tions (synapses). They’re trained bylooking at real world examples — forexample, historical sales data andthe past values of variables that mayinfluence sales. The training adjuststhe weights, which store the dataneeded to solve specific problems,such as sales forecasting.

DECISION TREES:Sequential decisions are drawn asbranches of a tree, stemming froman initial decision point and branch-ing out to multiple possible out-comes. The trees can be used topredict the most likely outcome andto forecast financial outcomes bymultiplying costs or returns at eachbranch by the probability of thatbranch being taken.


Scott Radcliffe, director of deci-sion sciences, says the telecommu-nications company relates “keyphrases that occur during customerinteractions” with future customerchurn. It has been able to reach outto those customers before they actu-ally leave — a big concern in thehighly competitive telecommunica-tions market. For I4 Commerce Inc.,which must approve or deny an on-line transaction request in underfour seconds, real-time analytics isthe name of the game. Merchantsuse the company’s “Bill Me Later”service to offer credit to a mer-chant’s customers without the needto present credit card informationover the phone or the Internet. TomKeithly, vice president of credit andintegration at I4, says his staff used apredictive analytics workbenchfrom Toronto-based Angoss Soft-ware Corp. to develop a model thatcan score each request to identifyfraudulent transactions.

“Our credit decision occurs in realtime, and each database we go to ismaintained in real time,” Keithlysays. Inputs include credit reports,demographics, telephone numberverification and the vendor’s owninternal customer histories. As soon as a customer completes atransaction, the system updates thatcustomer’s risk score. To do that, Timonium, Md.-based I4 pulls datafrom its live Oracle database ratherthan using its data warehouse. “Weonly use the data warehouse to de-velop new versions of the [model],”he says.

Although he could use tools likeSPSS Inc.’s Clementine scoring en-gine to download data and deliverthe resulting scores, Keithly saysthat approach would have intro-duced too much latency for the re-sponse time he required. Instead, hetook the algorithms built by themodeling system, compiled them inJava and runs them on I4’s produc-tion servers. “It’s just pure math. Itoperates as logic in the productionsystem,” he says.

Real Deal A critical difference in using predic-tive analytics is the speed at whichmodels can be refreshed, Keithlysays. While the mainframe systemshe used years ago allowed model de-velopment only every two years, hiscurrent tool set allows him to re-fresh the model every 90 days. Butthat’s still not real time. For most ap-plications, the ability to refresh themodel every quarter is adequate,says Keithly. However, he sees areasin which real-time models would beuseful, such as fraud, where assump-tions must be changed in responseto changing perpetrator tactics.Keithly expects to see real-timemodeling in the next decade. “It willbe worth it as long as it doesn’t takea massive investment to make itwork,” he says. But a massive invest-ment is often required for organiza-tions to provide real-time access todata. I4 is relatively small and builtits IT systems from the ground up in2001 using state-of-the-art technol-ogy, including Solaris servers andOracle databases. For large compa-nies with older equipment and data-bases, that’s more of a challenge.

“If data is divergent across multi-ple sources and you need to bring adata warehouse together, that’s con-siderably more money,” saysChristopher Scheib, manager of de-cision support at Highmark.

Peter Heijt, vice president of mar-keting and sales at Fortis BanqueSA/NV in Utrecht, Netherlands,wants to provide real-time access todata for predictive analytics applica-tions that will improve the successrate of sales campaigns. “The invest-ment is more or less double the costof the data structure we have now indata warehouse, data mart andCRM. So the payoff has to be big.We’re looking for a 40% increase insales effectiveness,” he says. Heijt isexperimenting with a small part ofhis CRM database to see if the in-vestment is justified.

Scheib says he needs access tooutside data in real time to facilitate

decisions on how to price policies.“Prescription information we canget in very close to real time, and wecan use that to make predictionsabout health risks,” he says. “That’suseful for actuaries who are tryingto price clients in as near to realtime as they can get.”

While predictive analytics toolshave gotten easier to use, successfulenterprise implementations still re-quire collaboration among businessanalysts, statistics experts and data-base administrators, say users. “Datapreparation can be 60% of the ef-fort,” says Lou Agosta, an independ-ent technology analyst in Chicago.

But the biggest challenge may bein learning how to take full advan-tage of the opportunities that pre-dictive analytics can provide. Devel-oping the right responses is whattakes the most time, says Harmon.“Having better predictive modelshas allowed everyone to re-evaluatetheir strategies. That’s where the in-tellectual capital is spent,” he says.


Farness wants to analyze thenewspaper’s market of 1.6 millionpeople and target segments withpromotions that would have an im-proved likelihood of success. For ex-ample, she says, “if we know a cer-tain segment uses our news onlineduring the week but wants printedproducts on weekends, we knowwhat to offer them.”

In addition to using its own sub-scriber database, the Times pur-chased demographic data from twosources to apply to its survey sub-jects. To address the complexity ofintegrating that data and building asuccessful model, in August 2004,Farness turned to Apollo Data Tech-nologies LLC.

“They asked us to look at five or

six demographic questions . . . andpredict who’s likely to subscribe and what category they fall into,”says Jeff Kaplan, principal of datamining technology at Chicago-basedApollo.

To do the work, Apollo used abeta version of SQL Server 2005,which includes new data mining fea-tures, and developed a model thatuses neural network algorithms topredict outcomes. Using the embed-ded algorithms available in SQLServer was a good fit for the Times,according to Howard Mendel, direc-tor of systems development. “Theuse of SQL Server will enable easyintegration with other SQL Serverdatabases and .Net applications thatare already in use,” he says.

While Apollo did the initial dataintegration and model development,the newspaper’s IT organization willrun the algorithms against the full1.6 million prospect list using itsown SQL Server database. The datawill be processed locally and thenuploaded into a marketing databasehosted by Astech Intermedia Inc. inDenver. From there, targeted mar-keting campaigns will be launched.

“We build repeatable processesand code on our back end. Our mod-el is to build these predictive modelsand turn them over to the businessuser to play with,” says Kaplan. Hesays The Seattle Times’ IT groupplayed a “great skeptic role” as the initial test on 60,000 subjectsrolled out.

Mendel says the challenge is tocome up to speed quickly on SQLServer 2005. “We have paired to-gether experts in both database ad-ministration and application devel-opment,” he says. His staff is creat-ing scripts to automate the move-ment and processing of data, whichwill occur weekly. “Once started, weexpect the entire process of datatransfers and execution of the modelto be fully automated,” Mendel says.



Outsourcing Predictive Analytics

GETTING THROUGH a predictive analytics project typically requires the resources of business analysts,statisticians and database experts. For small andmidsize organizations that don’t have the skills or

time required to complete such projects, outsourcing may bethe best alternative. That’s the approach taken by The SeattleTimes Co., which hopes to use the technology to combat de-clining newspaper subscriptions. “If we can reduce our churnby 2% or 3%, it makes a huge difference in our profitability,”says Janet Farness, strategic research manager.

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