FoodManufacturingCompanyCaseStudy

DemandWiseCu-ngEdgeSolu3onsinDemandManagement

TheBeginningofBeginning‐to‐EndManagement

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Background

 CompanyisthelargestfoodmanufacturinganddistribuDoncompanyinIsrael.

 ShufersalisthelargestfoodretailerinIsrael. Companyoperates“directstoredelivery”vendorrelaDonshipwithShufersal: AccesstoPOSdata Controlsdeliveryandon‐shelfavailability end‐to‐endcontrolofsupplychain

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TwoChallenges

 EvaluatetheoutcomesofpromoDonsofYoplaitproductsoveratwo‐yearperiod. EsDmatesalesliRduetopromoDonsand Provideindicatorsofthereasonsforfailuresorsuccesses.

 EsDmateandforecastdemandforthesesameproductsinspecificpromoDonalpricingscenarios. EsDmatepriceelasDcityundervariouspromoDonrules EsDmateandforecastdailydemandforspecificitemsinspecificstores.

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TheOpera3onalchallenges

 Numberofstores:24 NumberofSKUs:192

 Numberofdays:455

 NumberoftransacDons:909,175

 NumberofpromoDons:4

 OtherconsideraDons: Dayofweek Seasonality

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TheResultsinThreeAreas

1.  AggregateperformanceofpromoDonsi.  BypromoDonii.  ByStoreiii.  EconomicImpactofeachpromoDon

2.  Drill‐downtolevelofSKUperstoreoranylevelofaggregaDondesired

3.  DailyforecastsofdemandinpromoDonsforeachSKUineachstore,givenaspecificpricingscenario

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AggregatePromo3onResults

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(31,549)

15,005

(25)

13,769

(2,800)

(40,000)

(30,000)

(20,000)

(10,000)

‐

10,000

20,000

2 4 5 6 Total

UnitChangePerPromo

Tnuva–AggregatePromo3onResults

 ResultsbyPromoDon:

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MoreAggregatePromo3onResults

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‐30.00%

‐25.00%

‐20.00%

‐15.00%

‐10.00%

‐5.00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

1194

1359

1925

4610

5748

7371

10143

41317

55471

55713

55900

55914

55931

55940

55964

GrandTotal

%UnitSalesChangebyStore

MoreAggregatePromo3onResults2

 ResultsbyStore:

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EconomicResults

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(231,408)

(143,298)(180,873)

(146,388)

(701,965)

(800,000)

(700,000)

(600,000)

(500,000)

(400,000)

(300,000)

(200,000)

(100,000)

‐2 4 5 6 Total

DollarOutcomesofPromoJons

EconomicResults

 EconomicImpactofPromoDons

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PromoAnalysisConclusions

 Nearly1milliontransacDonswereprocessedandanalyzedautomaDcallyatthemostgranularlevelinminutes.

 Unitsalesdecreasedmateriallyfromnon‐promoaverageinPromo2impliesfrequent,endemicout‐of‐stockevents.

 Twostores—10143and5590—experiencedthemajorityofout‐of‐stockevents.

 AllpromoDonslostmoney‐$701,965overonly8weeks.

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ForecastsandMethod

 WhatDemandWise“sees”:

DWThursdayEsDmate–promo6

DW

Saturday

EsDmate

Usualleast‐squaresesDmate

ObviousOOS

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ForecastandMethod

 DemandWise“sees”day‐of‐weekandseasonalpaierns.

 DemandWisedifferenDatesproductsandlocaDonsthatpromosimpactfromthosethatpromosdon’timpact.

 DemandWiseanalyzespriorsalestransacDonstobuildpriorprobabiliDesonwhichtoapplyBayes’Theorem

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ForecastandMethod

 ClustertransacDonsbyhistoricalpaierns Seasonality

 Withstrongpromoeffect

 Withnopromoeffect

 DayofWeek

 Promo/nopromo

 Frequent/infrequentpromo Holidays

 AppliesRelaDonalBayesianNetworktechnologieswithinclusters AcrossstoresandlocaDonsinsameperiods

 AcrossstoresandlocaDons

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ForecastDetail

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TnuvaDemandForecastPromoJon:10%‐25%Discount

1Weekofproposed4‐WeekDuraJon

ForecastDetail

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‐

500

1,000

1,500

2,000

2,500

3,000

StoreNumber

Forecastvs.AverageUnitSales

One‐weekForecast

Avg.UnitSales

Parameter: 25% discount

ROIonProposedPromo3on

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1194 1194 1925 1925 4610 4610 7371 7371 55713 55713 55940 55940

ContribuJon $(983) $(1,398) $(295) $(649) $(434) $(589) $(257) $(435) $(278) $(512) $(344) $(457)

$(1,600)

$(1,400)

$(1,200)

$(1,000)

$(800)

$(600)

$(400)

$(200)

$‐

StoreNumber

PromoROI

Parameter: 25% discount

DemandWiseForecastsYieldAc3onableInforma3on

 DemandWiseforecastsare: OperaDonal–daily,weekly,monthly,custom TacDcal–monthly,quarterly,custom

 DemandWisemodelspromoDonscenarios Price(in‐storedisplay,circular) Coupons(storeandmanufacturer) Deals(e.g.,buyonegetonefree)

 DemandWiseesDmatespriceelasDcityofdemand ConDnuous Stepwise/pricepoints

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DemandWiseTransformsDataintoAc3onableBusinessIntelligence

 Determineweeklydeliveryschedules Drivequarterly,seasonalpurchasesandlogisDcsplans DrivepromoDons

 Stockingplans PricingtacDcs  In‐StoreposiDon CompeDDveDming OpDmizeseasonaleffects(liRornoeffect)

 DriveplanogramsoRwaremodels GranularspaceallocaDontoopDmizeOSA Granularanalysisofin‐storelocaDons

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DemandWiseImpactUnderstandDemand—Sa3sfyDemand:Manageyourbusinessprocessesfromthecustomertotheproductandbacktothecustomer

 MinimizeOOSevents–achieve<5%OOS

 PlanandExecuteprofitablepromoDons–turnlossleadersintoprofitleaders

 OpDmizeinvestmentininventory

 MinimizelogisDcscosts Therightproducts Therightplaces TherightDme ThefirstDme AlltheDme

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CharlesBroming,President/CEODemandWisePartners,LLCcharles@demandwisepartners.com407‐592‐0060Orlando,FL32819

DemandWise

UnderstandDemand—SaJsfyDemandManageYourProcessesFullCirclefrom

DemandthroughFulfillment

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