PERFORMANCEwhite paper:

AT PEAK

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PEAK PERFORMANCEEachweek,50%ofaretailstore’ssaleshappensduringonly20ofthestore’sopenhours.Didyouknowthat?

Yourecognizeyourpeaktimesarebusy,butwouldyoubesurprisedtofindthathalfofretailstoresaleshappenduringonlyaquarterofthestore’sopenhours?

THE50/20RULE

Whilethe50/20rulemayvaryslightlyfromretailertoretailer,observingandanalyzingretailstoreperformanceovermany

yearsandmanyclientshasconsistentlyproventhe50/20rule.

WhilethisisanindisputablefactinSpecialtyRetail,itrequiresadeeperlevelofunderstandingtoturnthe50/20principleintosomethingactionable.Itstartsbybeingabletopredictwhenthose20hourswilloccurforeachstore.

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�3BACKGROUNDBetter Schedules Drive Measurable Improvements in Performance

PEAK HOURS MATTER TO ALL RETAILERS

Thereisalsoanunfoundedtheorythatonlyhightrafficretailersneedtoworryaboutstaffingupduringthepeakhoursintheweek.Ourexperiencecontradictsthisbelief.

INCREASED PEAK COVERAGE = INCREASED SWING

Whilealowvolumestorewithasmallcontingentofassociatesmightnotseemlikeastorethatneedstofollowpeakcoverageclosely,intruth,missingapeakopportunityhasalargeimpactonresults.MultipleAssociatesworkingatonetimeisarareoccurrenceinalowvolumestore.Missingpeakcoverageinthisenvironmentleadstoalostopportunitythatcannotbeeasilyrecoupedasthevolumeoffoottrafficsimplywon’tallowforit.

Conversely,effectivelyapplyingthosefewprecioushoursthatalowvolumestoremayreceiveinexcessofminimumcoveragecangeneratesalesincreasesyoumaynothavethoughtwerepossible.

Mostcurrentretailtechnologyiscapableofanalyzinglargeamountsofgranulardatatoforecastthecustomerpatternsuniquetoaspecificstoreforanyweekoftheyear.

Fromthere,advancedschedulingtoolscancombinethisforecastedtrafficcurvewithlegislationandshiftrulestoproduceanoptimumschedulethatmirrorsthehighsandlowsofwhencustomersactuallystepacrosstheleaseline.

Thisallowsaretailertoaccuratelyscheduletherightnumberofassociatesaswellasyourbestperformingassociatesduringthepeak20hoursoftheirbusiness.Asdiverseasretailersare,andasvariedthesizeandshapeoftheirstoresare,ensuringthatthepeak20hoursarestaffedproperlyisthemosteffectivewaytodrivetop-lineperformance.

Retailers that increase peak coverage by 10% increase Swing by 4-6%.

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�4WHY DO WE FAIL?

Thesemisperceptionsindicateaculturethatseesschedulecreationasanadministrativetaskinsteadofasthevitalfirststepindrivingsales.

ALL STORES ARE THE SAME

WhileweknowthataDowntownlocationandaSuburbanMallhaveverydifferentcustomerpatterns,someretailersarestill‘setting’peakhoursforallstoreswithabroadbrush,therebyassumingeachstorehasidenticalcustomerpatterns.

WealsofindinouranalysisthatnotenoughemphasisisplacedontheseparationofSellingandNon-sellingLabor.Themosttell-talesigncomeswhensellinghoursarepulledawayfrombusytimesandreallocatedtoslowtimesinordertoperformtasks,therebycreatingaveryflatschedule.

Thislackoffocusontheimportanceofpeakcoverageleadstoschedulesthatarebuiltaroundtasks,otherhunchesoranintuitionaboutthebusinessthatisgroundedinneitherfactnorscience.

So,ifthismakessenseandthetoolsareavailable,retailersshouldbeknockingpeakcoverageoutoftheparkonadailybasisright?

Sadly,thatisnotthecase,andtherearemultiplereasonsretailersfailtoexecute.Themostcommonare:

Lack of Focus / Lack of Trust

• Reluctancetousescienceandinsteadrelyongutfeel;

• Noawarenessofpeakorabaseassumptionthatpeaksdon’tshiftbetweenstoresortimeperiods;

• Schedulingforeffectivetaskinginsteadofasatooltodrivesales.

“IKnowBetter”or,thinkingthatasimpleretailmodeldoesn’tneedtodomuchmorethancutandpastethepreviousweek’sscheduleremaincommonmistakes.Thisapproachtoschedulingignorestheevolutionofcustomerpatternsandeffectivelyleavesmoneyonthetableduringpeakhours.

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MEASURING PEAKDoescoveringthepeakhoursreallydriveperformance?

TheobjectiveofthePeakCoverageAssessmentistobenchmarkeachstoreinaretailchainagainsteachotherinordertoquantifytherelationshipbetweeneffectivepeakschedulingandperformance.

Todothis,wemustbeabletoscorebothpeakcoverageandperformanceduringPeakSegments(periods).

PeakCoveragescoresarecalculatedforeachstore,withthescore

representingthe%ofrecommendedcoverage(assuggestedbyanadvancedschedulesystem)thatwasachievedonthescheduleduringPeakSegmentsonly.

StoresaregroupedbycoveragescoresandthenYearonYearandSalestoTrafficKPIsforeachgroupareusedtocalculatetheperformancecomparative.

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KEY CONCEPTSInthefollowingassessment,PeakCoverageScoreswereusedtogroupstoresintoHighandLowPeakCoveragegroups.Thethresholdusedwas90%-thatis,ifastorescheduledatleast90%oftherecommendedhoursduringpeak,thatstorewasputintheHighPeakCoveragegroup.

TheperformanceassessmentwasthenconductedbycomparingtheperformanceofHighPeakCoverageStorestotheremainingstorestoidentifyifimprovementinPeakCoverageimpactedperformance.

KEY KPIS: VISIT VALUE (“VV”) AND SWING

VisitValueindicatesthevalueofeachcustomerenteringthestore(Sales/Traffic).AnincreaseinVVisadirectresultofanincreaseinConversion,AverageTransactionorboth.“Swing”neutralizestheeffectoftrafficonsales(%YoYSalesChange-%YoYTrafficChange).ApositiveSwingindicatesthatastoreisperformingbetterregardlessoftraffic.TheseKPIsalongwithSales,ConversionUPTandAverageTransactionareusedintheassessment.

PEAK COVERAGE AND KPI PERFORMANCE

Exclude Non-Comp Stores

Eliminate stores with insufficient historical data to evaluate a change in performance from last year to avoid skewing results.

High and Low Groups

These groups are established by force ranking the Peak Coverage Score, and then dividing the stores into two groups. High Coverage stores are stores covering 90% (or greater) of the peak recommended hours during the analysis period. Low Coverage stores are below 90%;

Peak CoverageRepresents the % of recommended coverage that was achieved on the schedule during Peak Segments only;

©2018StoreForceSolutionsInc.

�7THE FINDINGS

Moststoresthatwehaveanalyzedaresetuptocoverpeaksegmentsequally.Thefactthatsomedoandsomedonotisrelatedtoeitheragapintrainingorabeliefthatpeakcoverageisnotasimportantasotherprioritieswithinthebusiness.Thegoodnewsisgapsintrainingormisalignedprioritiescanbecoached,andiftheyare,resultswillfollow

ThegraphaboveillustratesthecommonthemebetweenHighandLowPeakCoveragestores.Lowcoveragestoresroutinelypullhoursintothemiddleoftheweek,awayfromthemajorityofpeaksegmentsontheweekends,insomecasesrepurposingsellinghourstofocusontasks.

FurtherAnalysisofLaborStatisticssuchasAverageShiftlength,PeoplePeropenHour(PPOH),Availability%andotherschedulingKPIscanhelpidentifyiftheissueisrelatedtonotbeingabletoexecute,ornotbeingwillingtoexecute.

LaborStatsAverage

ShiftLengthSchedulingFlexibility%

Avail%-Peak Sell% SPH PPOH TPLH

%FTSellHours

%FTTotalHours

High 6.63 25.2% 66.9% 53.9% $261 7.9 7.6 57.9% 55.5%Low 6.70 29.3% 65.8% 49.9% $298 7.4 8.9 54.7% 52.6%

Difference (0.06) -4.0% 1.1% 4.0% -$37 0.5 (1.3) 3.2% 2.9%

Overallthereislittledifferencebetweenthetwogroupsonthevariablesthatallowforflexibleschedulingandtheabilitytohitgoodpeakcoveragestores.Typicallyweseethatthisdoesnotappeartobeastaffcomplementissue.

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�8THE RESULTS

A 10% IMPROVEMENT IN PEAK COVERAGE % RESULTS IN A 4% INCREASE IN SWING

AnalysisafteranalysishasproventhatpeakcoveragehasacorrelationtoKPI’ssuchasSwing,VisitValue,ConversionAverageTransactionsizeandultimatelySales. VISIT VALUE

2-5% growth in visit value compared to low peak coverage stores

ATV2-5% growth in ATV compared to low peak coverage stores

CONVERSIONOver 2% growth in Conversion compared to low peak coverage stores

Swin

g

-40%-30%-20%-10%

0%10%20%30%40%

Peak Coverage %

50% 63% 75% 88% 100%

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