Digital BrainFest 2013 World Café – Digital Analytics

The Digital Analytics World Café session was a great opportunity for practitioners who face similar challenges to connect and share ideas about cultivating analytic talent and using analytics to drive business outcomes.

Companies recognize that it takes more than just tools and technology to make sense of data; it takes people. Our group discussed several perspectives for acquiring and developing talent to meet the need for strong analytic support. Two big themes emerged:

• Refiningtheskillsetswelookfor

• Growingpeople’sindividualbrands

While comfort with numbers is still requited, the softer qualities of intellectual curiosity, the ability to tell a story, and sell recommendations internally are increasingly important. This talent is retained when managers invest in the individual brands of their analysts, helping establish them as “experts” and “thought leaders” beyond the project of the day. Additionally, analysts need a clear career path about what it takes to advance along the track. It is important to stretch them and allow them to “fail” in a safe environment, provide coaching from those who have “been there,” and reward achievement.

Many people in the group could relate to being “data rich and insight poor.” The ability for analytics to drive business insights and outcomes can be hindered by distrust of the data, lack of metric understanding, unclear or misaligned KPIs, and static reporting that doesn’t come with recommendations or an action plan. So how do you overcome these limitations? The group suggested a number of ideas:

• Governancetaskforce/committeewithexecutivebuy-incangoalongwayinidentifyingdataintegritygapsand“cleaningup”reporting.

• Evangelizingquickwinswithtangiblebusinessimpactshelpsengenderdata-informeddecisionmaking.Companieswithagiledevelopmentcyclesfocusedonincrementalgainshavemoreopportunitiesforthesequickwinsasanalystscanweighinontests,campaigns,anddesignconceptswithoutasmuchpoliticalfriction.

• Analystswhocantellcompellingstoriesandemployinteractivevisualization(asopposedtoflatslidepresentations)canbemuchmoreeffectiveandinfluentialwiththebusiness.Ofcourse,everydeep-diveanalysismeansthebusinessmustthinkthrougharangeofactionsandoptions.

These things don’t happen overnight, but consistent application of these types of ideas can foster a healthy data-informed culture.

Overview:

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• Inadditiontothescienceofcrunchingnumbers,analystsshouldbecoachedintheartofstory-telling.

• Weneedtochangewhatwelookforincandidates.Can’tjustrecruitquant-jocks;needcuriosity,practicalbusinesssense,andabilitytocraftacompellingstoryfromdata.

• Retentioncomeswithhelpinganalystsdeveloptheirownbrand.Investincertifications,skilldevelopment,andpracticalexperiencethatestablishthemasan“expert”or“thought-leader.”

• Managersneedtobecognizantofanalysts’variousstrengths,weaknesses,andcareerpathgoalsandcommittedtodevelopingthemthroughprojectassignments,coaching,androleallocation.

• Establishanalystcareerpaths–theyneedtohaveatracktoadvancealong(withvisibilityintowhatgetsthemtothenextstage).Supportwithcoachingandmentoring.

• Organizationscanlookforuniversityinvolvementopportunitiestoidentifytalentandestablishapipe-line.Theseincludeguestspeaking/lecturing,academicprojectsponsorship(e.g.,casestudy),professionalmentoring,internshipprogram,etc.

• Stretchandpushanalystsandsetupasafeenvironmentforthemtofailandlearn.

• Recognizecontributionandachievement.

• Needtogrowpeoplewithguidancefrompeoplewhohavedoneitbefore.(Makesureyouhaveandutilizestrongmentors/coaches).

• Artofstorytelling:mustbeabletocraftacompellingstoryfromthedatatomakeaclearpointandrecommendation.

• Curiosity:Alwayslookingtounderstand“why”and“whatif.”Healthylevelofskepticismtonottakeeverythingatface-valueandtrytolookdeeper.

• Passion:Findsexcitementandfulfillmentinfiguringoutcomplexproblems.

• InternalSelling:Inadditiontocraftingsound,logicalanalyses,mustbeabletotapintothepsycheoftheaudiencetoconvince/inspirethemtotakeaction.

• Clearly,thenumberonehurdleislackoftrustinthedata.

• Timeismonopolizedbydatafixing;notimeforcreativebusinessanalytics.

• Lackofagreementaroundwhatthekeymetricsareandhoweveryoneshouldlookatthemetrics.

• FocusedonthewrongKPIsandanemphasisonvanityKPIs.

• Noteveryoneunderstandswhatdifferentmetricsmeanandhowtointerpretthem.

• Differentaudiencesarereceptivetodifferenttypesofanalyses.Theanalysisisnotalwaystailoredtotheaudience’sstyle;therefore,itmaynotresonate.

• Analyseslackacall-to-action.Itisnotclearwhatactionthebusinessshouldtakebasedonthedataoranalysis.Inthesecases,theanalysisbecomesjustan“academicexercise.”

• Largeprojectsaremoresusceptibletopolitics;shiftdevelopmentandanalysiscycletoamoreagileapproachfocusedonmorefrequent,incrementalchange.Itiseasiertogetpeopleon-boardwithsmall,incrementaltests/analysesthatprovevalue.Chalkupafewofthese“quickwins”togaintrustasabusinesspartner.

• Developataskforcefocusedondatagovernancetoachieveexecutivebuy-inandoperationalcomfortwithdataintegrity.

• Regularlysharelearningsandbestpracticesacrosstheorganization.

• Changetheformatforsharingdataandanalysis.ShiftfromstaticPowerPointslides,charts,andtablestowardinteractivevisualization.Thisreinforcesthestory-tellingaspectandmakestheabstract“real”forexecutives.

• Asananalysisisbeingplanned,thebusinessshouldestablishwhatrangeofactionsitispreparedtotakebasedontheresults.Thebusinessneedstobereadytomobilizeforaction.

Question 1: How can talent best be developed, acquired, and grown to meet the drastic increase in demand?

Question 2: Within an organization, what limits the capacity for analytics to drive or impact business outcomes?

What are the domain and behavioral skills that most contribute to an excellent analytics resource?

How can these limits effectively be overcome?

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