Top 10 Techniques For Building Effective Performance Dashboards

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1 Tp 10 Techniques Fr Building Effective Perfrmance Dashbards S much data, s little insight...2 Techniques fr Effective Dashbards Chse the right type f dashbard Dashbard cntent: Use best practices but dn t frget the users The gal is Actinable Business Intelligence Psitin dashbards int an integrated reprting framewrk Cnsistent screen visualizatin eases user navigatin Prvide smart drilldwns f data Data surcing dne right: Dn t frget the plumbing Prvide simulatins fr decisin supprt Dcumenting data anmalies User Feedback...6 Gerald J Kpecky jerry_k@bmsmail.cm Raghavendra Dutt B raghav_d@bmsmail.cm BLUE MARLIN SYSTEMS, INC. Business Intelligence Divisin Dver, NJ USA Tel: Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 1

2 S much data, s little insight Large scale ERP implementatins ver the last decade have resulted in an explsin f crprate data. It seems every actin, n matter hw trivial is captured digitally and stred smewhere n a crprate cmputer. Unfrtunately, this has led t a prliferatin f large and cmplex reprts as analysts attempt t gain meaningful views f their business prcesses. Perfrmance Dashbards have becme ppular tls in recent years fr executives and analysts t mine cmpany data fr useful insight. Regrettably, in the mad rush t create them, ad-hc develpment appraches have largely prevailed with IT departments (in mst cases) using the latest and slickest tls withut strategic cnsideratins t industry relevant analytics, scalability r best practices. Techniques fr Effective Dashbards This dcument presents 10 key techniques fr building effective dashbards. It is based n industry research as well as experiences with custmers wh have avided imprmptu methds and taken the time t develp and deply their dashbards in a structured manner. 1. Chse the right type f dashbard Make the infrmatin yu prvide actinable. A smart way t d this is categrize yur dashbards by target audience: Type Audience Key Features Analytics and alerts are fcused n crprate, business Strategic Senir Executive Team units, key custmers and prduct lines KPIs ften included fr strategic initiatives Evaluatin perid is typically weekly r mnthly KPIs measured against planned perfrmance f departmental Tactical Departmental Heads /majr business prcess, e.g. Prcurement Early warning indicatrs fr timely interventin Drill dwn capability fr exceptin analysis Evaluatin perid daily r weekly Analytics measured against planned perfrmance f key Operatinal Functinal Area user functinal area, e.g. Prductin Line Users can create Ad-hc metrics fr their area Drill dwn reprts fr exceptin analysis Evaluatin perid daily, per shift r real-time Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 2

3 2. Dashbard cntent: Use best practices but dn t frget yur wn experts Perfrmance dashbards primarily include: Metrics: Usually perfrmance data such as Revenues, Cmmissins and Open Orders, and Key Perfrmance Indicatrs (KPIs): Metrics tied t crprate targets r industry benchmarks such as On-Time Delivery percent, Plant Utilizatin, Order fill rate and s n. In additin, these metrics and KPIs are usually available at varius levels such as crprate, gegraphy, business unit, custmer and material. Perfrmance analytics fall int any ne f the fllwing majr categries: Industry specific: These are metrics and KPIs specific t yur industry; example Return n Ad Spend (ROAS) in the travel industry Wrld class: These analytics apply t all industries; Example Inventry turns Cmpany specific: These are unique t yur cmpany Several grups such as Supply Chain Cuncil, Eurpean Shipper s cuncil, SUGEN (SAP user grup executive netwrk) can be used t reference benchmarks. In additin, yu must ask business experts frm within yur wn cmpany t validate these and perhaps add yur wn internal nes t the dashbard(s). 3. The gal is Actinable Business Intelligence Perfrmance dashbards have ne verarching bjective t prvide decisin supprt infrmatin t yur audience. This can be dne in several ways: GAUGES AND DIAL These can efficiently shw metrics with varius actinable threshlds t cmpare current values against budget r prir perid values LINE AND BAR GRAPHS These can be used t quickly spt trends in metrics and KPIs Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 3

4 BUBBLE CHARTS Use these t crrelate data acrss multiple perids and variables. In this figure, the bubble size indicates the clsing stck while custmer rders and prcurement are pltted fr multiple perids. 4. Psitin dashbards int an integrated reprting framewrk The dashbard types discussed abve have different audiences but must fit int an verall reprting framewrk in rder t be effective. Here are sme key guidelines: Setup an Analytics Library: Crprate KPIs and measures shuld be based n a centralized library f definitins shared acrss all dashbard types. This will ensure a single versin f the truth irrespective f the type. Synchrnize Perfrmance Milestnes: Ensure unifrm plicies fr evaluating when t red-line r celebrate perfrmance. The same alerts at strategic levels will be seen at the relevant peratinal and functinal levels (hpefully sner). Develpment Tls: Since several tl vendrs target IT and end-users, it is nt uncmmn t find multiple dashbard tls being used in a cmpany. It is imprtant t select a single rbust develpment kit that is scalable t the grwing crprate requirements. A main factr fr such selectin shuld be the integratin with transactin data. 5. Cnsistent screen visualizatin eases user navigatin Every dashbard tl cmes equipped with a standard set f cntrls dials, gauges, widgets, bars and charts. Yur crprate dashbards, althugh different in their details shuld have a unifrm layut, clrs and themes fr easy end-user navigatin. Sme suggestins: Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 4

5 Layut: Set aside sectins f the screen fr different metrics, KPIs and simulatins. Once this is dne, make sure t use this layut n each dashbard. Data Filters: Reserve a screen area t allw users t analyze data by perid, rganizatinal hierarchies r ther key drill dwn nde. Data density: Real estate n the screen is precius and there is a temptatin t stuff a lt f infrmatin n it. Use tabs t grup data and avid screen verlad. 6. Prvide smart drilldwns f data Dashbards are nt replacements fr detailed reprts. Yur gal is t present data in a frmat that allws users t quickly identify perfrmance issues withut wading thugh minutiae. Sme best practices are listed here: Drilling dwn t detailed reprts are advisable nly fr Tactical and Operatinal dashbards Strategic dashbards shuld shw analytics nly n a Tp n basis, e.g. Order Fill rate fr Tp 10 custmers 7. Data surcing dne right: Dn t frget the plumbing Figure: Behind every great dashbard is a highly efficient ERP data pipeline Sluggish system respnse has killed many a slick dashbard since end users expect split secnd respnses as they slice and dice their data. Design cnsideratins fr high perfrmance surcing include: Data Warehuse: This is the single mst efficient mechanism t stre yur transactin data aggregated int an analytics-friendly frmat. Perfrmance dashbards are executed against warehuse bjects such as data cubes t instantly display KPIs and trends. Data Quality: Several vendrs such as ORACLE, SAP and IBM ffer tls that scrub data befre lading int the data warehuse. These are best used when integrating data frm multiple surces, especially external feeds. In such cases, use such tls yur users will thank yu Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 5

6 Calculating Analytics: The rule with ding cmplex calculatins is simple d as little as pssible in the dashbard tl and let the warehuse d the heavy lifting. This means ding the math either during the warehuse uplad frm ERP r in the query builder. 8. Prvide simulatins fr decisin supprt Mst dashbard develpment tls prvide cntrls that allw data simulatins. When multiple inputs can affect perfrmance, simulatin allws users t tweak them individually t instantly bserve the results. Figure: Dashbard Simulatr fr Travel Industry. Sliders allw analyst t view impact n prfit by changing Ticket price, Passenger cunts (PAX) and Cst. 9. Allw users t dcument data anmalies In sme cases, the reasn fr a sudden change in a metric r KPI may be due t a knwn. Fr example, a sudden drp in manufacturing utput may be due t planned line maintenance. In such cases, the plant shuld be able t attach a brief explanatry nte t a dashbard analytic that is visible t all users. 10. User Feedback Cngratulatins, yu ve cmpleted yur dashbard! Nw what? The nly truism is that change is cnstant and dashbards need t be reviewed peridically. Pll yur users t ensure that: Analytics are current Alert threshlds have nt changed Drill dwn reprts are still current Yur audience is still using them! Blue Marlin Systems 2010: Prtins f this dcument may be reprduced nly after apprpriate citatin f the surce Page 6