Effective performance management: integrate methods under ... - SAS

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Effective performance management: integrate methods under ... - SAS

November 2008Effective performancemanagement: integratemethods under one umbrellaBy Roberto MichelPerformance management—when narrowlydefined—spans so many individualmanagerial methods that few peopleseem to agree on what it is. But define it broadlywhile ignoring integration of these methods,and it risks becoming little more than a sloganfor a disjointed mix of projects.There is real promise in performance management.Companies that approach it broadlywhile linking its various methods can fulfillthat promise and avoid the usual pitfalls. “It’shelpful to think about performance managementas an umbrella concept that integratesdifferent methods within a single decisionsupportframework,” says Gary Cokins, globalproduct marketing manager for performancemanagement at SAS, a leading provider ofbusiness analytics software and services. “Butthese methods and tools need to be integrated.Many companies think about performancemanagement as just a set of dashboards, dials,and financial reports, for instance—and theyend up with siloed efforts.”A performance management frameworkmay include methodologies and supportingsoftware for activity-based cost management(ABM), balanced scorecards andstrategy maps, dashboards and key performanceindicators (KPIs), aswell as systems and measuresfor customer relationship management(CRM), supply chainmanagement (SCM), lean management,resource planning,and budgeting & forecasting.“Ideally, one method or toolshould feed the other,” saysCokins—who is APICS certifiedin production and inventorymanagement. “For example,your ABM solution shouldinform your CRM solution oryour production managementsystem if it’s apparent that costdrivers are changing, or KPItargets are being missed.”Even when various methodsAlertMoving the dials:getting pro-activePerformance management carriesa contradiction in its name. If anorganization is just monitoring dataand trying to “manage” around historicaltrends, can it fully optimizeperformance?“Performance management is notabout monitoring the dials, butmoving the dials,” says Gary Cokins,global product marketing managerfor performance management atSAS, a leading provider of businessanalytics software and services.“Performance management shouldhave initially been called performanceimprovement. It is abouttransforming data into meaningfulinformation to lead to quicker analysis,conclusions, and ultimately, tobetter decisions.”To achieve a more proactive performancemanagement framework,multiple components need to bein place, culminating in predictivemodeling and analytics thatcan help managers test and validatealternatives. These componentsinclude:• Sound transactional systemssuch as enterprise resources planning(ERP), customer relationshipmanagement (CRM), and sourcingsystems. These provide much ofthe raw data and standard reportsneeded to monitor performance.• Data warehousing and datamanagement tools. These solutionsextract transactional data from mulcont’don p. 2 cont’d on p. 2Manufacturing Business Technology


Effective performancemanagement:cont’d from p. 1under a performance management umbrellaare successfully linked, says Cokins, it’simportant to embed each method withanalytics such as segmentation analysis,and especially predictive analytics software.“Predictive modeling and analyticsis what move a company toward forwardlooking,pro-active decision making, ratherthan measuring what has happened in thepast,” he says. (See “Moving the dials: gettingproactive,” page 1, for more.)In its simplest sense, performance management—whichspans terms such as business,corporate, and enterprise performancemanagement—is the translation of plansinto results. Performance management canbe defined as the integration of operationaland financial information into a singledecision support and planning framework.The framework’s methodologies should beintegrated and embedded with analyticsto promote pro-active decision making.Finally, the entire system should work in acirculatory and simultaneous manner.SAS is a leading provider of softwarefor performance management. Its offeringstake SAS’s award-winning business intelligence(BI) technologies to a higher levelby providing more context for problemsolving. These offerings include softwarefor building dashboards and scorecards,ABM, budgeting & planning, customer andsupplier intelligence, predictive modeling& analytics, as well as data warehousingand data management. But as expertsagree, it’s an organization’s approach to thesoftware—and success in integrating techniquesand technologies within a framework—thatare most crucial to improvingperformance.United methodsSome of the component methodologiesof a performance management frameworkhave been around decades. For example,balanced scorecards first gained popularityin the mid-1990s, and BI software fordisplaying measures within a “dashboard”has also been around for years. But all toooften, these tools aren’t used in an integratedfashion around strategic goals.One problem with balanced scorecardefforts, says Cokins, is that many organizationshave failed to design and implementa strategy map as the basis for thescorecard. “The balanced scorecard andits companion strategy map from whichthe scorecard’s strategic projects and mission-criticalprocesses, KPIs, and targetsare derived, are only one methodology in aportfolio of methodologies that constitutea performance management framework,”says Cokins. “Others include profitabilityreporting, customer loyalty and value management,lean management, and driverbasedrolling financial forecasts. The problemis most organizations implement thesesequentially and in isolation of each other.There is synergy when you integrate them,and even more synergy when you imbedeach methodology with analytics, such assegmentation analysis; but especially predictiveanalytics.”Individual improvement techniques canbe of high value. For instance, ABM systemsthat reject standard cost accountingfor an approach that traces actual cost driversallow companies to truly understandwhere they are making or losing money.Moving the dials: getting pro-activecont’d from p. 1tiple systems and wipe out redundancies, allowing companies to createa clean pool of high-integrity data for modeling and analysis.• Performance management software with capabilities for managementand control of strategic objectives, as well as reporting. Someorganizations use a strategy map and a balanced scorecard to establishtheir key performance indicators (KPIs).• Predictive modeling and analytics software.This type of software capability—ideallyembedded within supporting performancemanagement applications such as activitybasedmanagement—allows managers to pose“what-if?” scenarios and test probable outcomes.Get predictivePredictive modeling and analytics software,however, is well beyond standard reportingtools, or even the more advanced ad-hocquerying tools. A reporting or query tool canbe effective at summarizing or comparing historicaldata—typically from a single transactionalsystem—whereas predictive analytics is built upon modelingcapabilities that allow companies to combine vast pools of data andtest alternative scenarios.“There are now superior application software tools that offer acomplete suite of analytic applications and data models that enableorganizations to tap into the virtual treasure trove of informationthey already possess, and enable effective performance managementcont’d on p. 4 Manufacturing Business Technology


Effective performance management:cont’d from p. 3measures. A scorecard may employ a dashboarduser interface, but the scorecard ismuch more than a dashboard—it providescontext and linkage to the strategy.Two preliminary steps to devising asuccessful scorecard effort are having theexecutive team take the time to identifyenabling projects to achieve specific objectives,and gaining buy-in from employeesto ensure they understand the strategy.“Strategy is all about change,” says Cokins.“The presence of enabling projects goes tothe heart of what distinguishes a strategicobjective from just getting better at whatyou have already been doing.”In practice, a key step is to delegateto managers the selection of measuresderived from the strategy map. “The executivescan review and adjust afterwards incollaboration with the managers,” Cokinssays. “A next step is to assure there isa blend of project-based KPIs—such asdate milestones or percentage-of-completiontargets—for the initiatives, as well asprocess-based KPIs to monitor the coreprocesses.”Many organizations also focus onbudgeting and forecasting as early componentsof a performance managementeffort. However, budgeting & forecastingshould be based on solid transactionaldata, which may need to be “cleansed” toremove issues such as redundant data.Another component of successful performancemanagement is an ABM solutionthat can move an organization awayfrom traditional accounting systems thatallocate costs using non-causal averages.“An ABM solution doesn’t allocate costs,it actually traces them based on causeand effect relationships from the costdrivers that consume resources,” says LeoSadovy, product marketing manager forSAS financial management, and a formerVP of finance at the U.S. division of alarge, global company. “ABM solutionsalso should provide managers visibility onhow changes in volume of real cost driversaffect product costs, and provide analyticaltools to predict outcomes.”Once all parts of a performance managementframework are working in unison, acompany can proactively improve performance,not just react to data. “ nMoving the dials: getting pro-activecont’d from p. 2– performance improvement – on a huge scale that is enterprisewidein scope,” says Cokins.For example, in conjunction with an ABM solution that managesactual cost drivers, predictive analytics could be used to test themost profitable order sizes or locations for where products mightbe built, taking into account factors such as the need for intercompanytransfers that might not be spotted by a typical productionplanning system.Predictive modeling and analytics also is being used to investigatewhat is known as customer lifetime value (CLV) in businessto-consumerindustries such as telecommunications, and is alsoapplicable to business-to-business supply chains. This centerson close examination of the potential future economic value ofcustomers as they progress through life stages. “The questionsinvolve which types of customers companies should retain, grow,win back and acquire,” says Cokins. “Practitioners of customerlifetime value use statistical forecasting methods to project thefuture sales volume and mix of products and services. They alsomodel the future costs of those products and services basedexisting consumption rates and future changes in their financialexpense structure. Equipped with these projections, they canbetter target which customers to provide offers, deals, discounts,up-sell, cross-sell and the like to achieve a higher yield and profitlift from their marketing and sales budgets.”There are both “descriptive” and “predictive” modeling capabilities,notes Cokins. An ABM solution that models the conversion ofexpense spending into the calculated costs of business processes,work activities, and specific outputs such as product or servicelines, is a form of descriptive modeling. A strategic map thatlinks objectives to enabling projects is another type of descriptivemodel. Predictive analytics differs by focusing on what-if scenariosand future outcomes, rather than historical data. Both types ofmodeling, however, are essential for performance management.Proactive leadershipWith modeling and analytics embedded within performancemanagement solutions, says Cokins, managers can begin tomake proactive decisions, not just “manage” after the fact. Forinstance, if the goal is to increase customer service measureswithout increasing costs, predictive analytics could be used totest alternatives, such as whether it’s better to increase inventoryheld in satellite warehouses, or do more direct shipping from acentral warehouse.“Most organizations are shifting their managerial style fromreactive after-the-fact reporting to anticipatory planning toproactively make decisions and mitigate risk and problems beforethey become larger ones,” says Cokins. “But in many cases,alternative actions need to be validated. This is where predictiveanalytics fits in. The ability to project what-if scenarios is powerfulbecause you can select the best one of the alternatives—andstrive for optimization.”nFor more informationFor general information on performance management go to:http://www.sas.com/solutions/pm/index.htmlFor more performance management whitepapers go to:http://www.sas.com/solutions/pm/index.html#section=6 Manufacturing Business Technology

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