供应链物流管理中科院 龚其国三chapter4-6

1、Planning Demand and Supplyin a Supply ChainForecasting and Aggregate Planning1Learning ObjectivesPhases of supply chain decisionsIdentify components of a demand forecast Time series forecastingEstimate forecast errorAggregate planning in the supply chain2Supply Chain DecisionsStrategy or design: Pla

2、nning:OperationForecast ForecastActual demandProduction: Scheduling, inventory control, aggregate planningMarketing: Sales-force allocation, promotion, new product introductionFinance: Plant/equipment investment, budgetary planningPersonnel: Workforce planning, hiring, layoffs3Characteristics of for

3、ecastsForecasts are always wrong. Should include expected value and measure of error.Long-term forecasts are less accurate than short- term forecasts: Forecast horizonAggregate forecasts are more accurate than disaggregate forecasts4Demand Forecast Involve Factors:Past demandPlanned advertising or m

4、arketing efforts Display position in a catalogState of the economy Planned price discountsActions competitors have taken5Forecasting MethodsQualitative: Subjective, human judgment Little historical data Experts have market intelligenceTime Series: Past demand history is a good indicator of future de

5、mandStatic; AdaptiveCausal: Correlation between demand and environment factorsSimulation: Imitate the customer choices6Basic Approach to Demand ForcastingUnderstand the objective of forecasting Integrate demand planning and forecastingIdentify the major factors that influence the demand forecastUnde

6、rstand and identify customer segments Determine the appropriate forecasting techniqueEstablish performance and error measures for the forecast7Components of an observationObserved demand (O)=Systematic component (S) + Random component (R)Level (current deseasonalized demand)Trend (growth or decline

7、in demand)Seasonality (predictable seasonal fluctuation)Multiplicative: S=L Tseasonal factorAdditive: S=L+T+ Seasonal factorMixed:S=( L+T)seasonal factor8Time Series ForecastingForecast demand for thenext four quarters.9QuarterDemand DtII, 1998III, 1998IV, 1998I, 19998000130002300034000II, 1999III,

8、1999IV, 1999I, 200010000180002300038000II, 2000III, 2000IV, 2000I, 200112000130003200041000Time Series Forecasting50,00040,00030,00020,00010,000010Forecasting methodsStaticAdaptiveMoving averageSimple exponential smoothing Holts model (with trend)Winters model (with trend and seasonality)11Static Fo

9、recasting methodsS= L TSt DtFt（L+T） Seasonality=Estimate of level for period0;Estimate of trend (per period); Estimate of seasonal factor for period t Actual demand observed in period tForecast of demand for period tFt+l= L + ( t + l ) T St+l12Estimating Level: deseasonalized demandt-1+( p / 2)2Di /

10、 2 pDt-( p / 2) + Dt+( p / 2) + For p even= i=t+1-( p / 2)Dt t+ p / 2Di / pFor p oddi=t- p / 2P: periodicity13Examplet -1+( p / 2)2Di / 2 p= Dt -( p / 2) + Dt +( p / 2) +D3i=t +1-( p / 2)= D + D4+ 2Di / 815i=214P=4, t=3Excel FileLinear Regression= L + tTDt= 18,439 + 524tDt15Estimating Seasonal Facto

11、rSeasonalCycles r -1 Si= Sjp+i / rSt= Dt/ Dtj =0= (S)/ 3 = (0.67 + 0.83 + 0.55) / 3 = 0.68+ S+ SSSS22610= (S+ S)/ 3 = (1.15 + 1.04 + 1.32) / 3 = 1.17+ S33711= (S+ S)/ 3 = (1.66 + 1.68 + 1.66) / 3 = 1.67+ S4481216Forecast for the Next Four Quarters= (L + 13T )S13= (L +14T )S14= (L + 15T )S15= (L + 16

12、T )S16= (18,439 + 13 524)0.47 = 11,868F13= (18,439 +14 524)0.68 = 17,527F14= (18,439 + 15 524)1.17 = 30,770F15= (18,439 + 16 524)1.67 = 44,794F1617Adaptive Forecasting methodsLt = Estimate of level at the end of period t;Tt = Estimate of trend at the end of period t;St = Estimate of seasonal factor

13、for period t;Ft =Forecast of demand for period t (for period t);Dt = Actual demand observed in period t;Et = Forecast error observed in periodt ;At =Absolute deviation for period t = |Et |)= (Lt+ lTt )St +lFt +l18Four StepsInitialize : L0 T0 S0；ForecastEstimate errorModify estimate19Moving AverageSy

14、stematic component = Level;Lt= (Dt+ Dt -1+ . + Dt - N +1 ) / N= Lt , Ft + n= LtFt +1= (Dt+1+ Dt+ . + Dt-N +2 ) / N , Ft+2= Lt+1Lt+120Simple Exponential SmoothingSystematic component = Level;n= 1 = L ,= LFFLD0it+1t+nttni =1= aDt +1+ (1-a )LtLt +1t +1= a (1-a）n Dn=0Lt +1t +1-n21Trend-Corrected Exponen

15、tial Smoothing(Holts Model)Systematic component of demand = Level + trend;Dt= at + b= Lt+ Tt ,= Lt+ nTt+ Tt )Ft +1Ft +n= aDt +1+ (1-a )(LtLt +1Tt +1= b (Lt +1- Lt ) + (1- b )Tt22Trend-and Seasonality-CorrectedExponential Smoothing(Winters Model)Systematic component of demand =(Level+Trend) Seasonal

16、factor= (Lt+ Tt )St +1 ,= (Lt+ nTt )St +nFt +1Ft +n= a (Dt +1/ St +1 ) + (1-a )(Lt= b (Lt +1 - Lt ) + (1- b )Tt+ Tt )Lt +1Tt +1= g (Dt +1/Lt +1 ) + (1- g )St +1St + p+123Error measuresEt= Ft- Dts= 1.25MADn100Etn= 1 E 2MSEntDnE1i=1t =1=tMAPEnA =ntbias tnnt =1i=1=biasE ;TSMADn=AnttMAD24tntNATURALGAS.c

17、omForecasting MethodMoving averageMADMAPE(%)TS Range9,71949-1.52 to2.21Simple exponential smoothing10,20859-1.38 to 2.25Holts model8,83652-1.90 to 2.00Winters model1,4698-2.74 to 4.0025Aggregate Planning at Red TomatoTools26MonthDemand ForecastJanuary1,600February3,000March3,200April3,800May2,200Jun

18、e2,200Fundamental tradeoffs in AggregatePlanningCapacity (regular time, over time, subcontract) InventoryBacklog / lost salesBasic StrategiesChase strategyTime flexibility from workforce or capacity Level strategy27Aggregate Planning28ItemCostMaterials$10/unitInventory holding cost$2/unit/monthMargi

19、nal cost of a stockout$5/unit/monthHiring and training costs$300/workerLayoff cost$500/workerLabor hours required4/unitRegular time cost$4/hourOver time cost$6/hourCost of subcontracting$30/unitAggregate Planning (Define DecisionVariables)Wt Ht Lt Pt It St CtOt=Workforce size for month t, t=1, ., 6N

20、umber of employees hired at the beginning of month t Number of employees laid off at the beginning of month t Production in month tInventory at the end of month tNumber of units stocked out at the end of month tNumber of units subcontracted for month tNumber of overtime hours worked in month t,29Agg

21、regate Planning (Define ObjectiveFunction)66Min 640W t+ 300 Htt =1t =1666+ 500 Lt+ 6Ot+ 2 I tt =1t =1t =1666+ 5 St + 10 Pt+ 30 Ctt =1t =1t =130Aggregate Planning (DefineConstraints Linking Variables)Workforce size for each month is based on hiring and layoffs= W t -1 + Ht- Lt,orW tW t- W t -1 - Ht+

22、Lt= 0for t = 1,.,6, where W 0= 80.31Aggregate Planning (Constraints)Production for each month cannot exceed capacity 40W t+ Ot4,Pt40W t+ Ot4 - Pt 0,for t = 1,.,6.32Aggregate Planning (Constraints)Inventory balance for each monthI t -1 + Pt+ Ct= Dt+ St -1 + I t - St ,I t -1 + Pt+ Ct- Dt- St -1 - I t+

23、 Stfor t = 1,.,6,where I 0 = 1,000,S 0 = 0,and I 6 500.= 0,33Aggregate Planning (Constraints) 10W t,Ot10W t- Ot 0,for t = 1,.,6.34Over time for each monthExcel FileScenariosIncrease in holding cost (from $2 to $6) Over time cost drops to $4.1 per hourIncreased demand fluctuation35Increased Demand Fl

24、uctuation36MonthDemand ForecastJanuary1,000February3,000March3,800April4,800May2,000June1,400Managing Predictable VariabilityManage SupplyManage capacityTime flexibility from workforce (OT and otherwise) Use of seasonal workforceUse of subcontractingUse of dual facilities-dedicated and flexibleDesig

25、ning product flexibility into the production processesManage inventory Component commonality Seasonal inventory of predictable products37Managing Predictable VariabilityManage demand with pricingOriginal pricing: Cost=$422,275, Revenue=$640,000Demand increase from discountingMarket growthStealing ma

26、rket share Forward buyingDiscount of $1 increases period demand by 10% and moves 20% of next two months demand forward38Off-Peak (January) Discount from $40to $39Cost Revenue Profit=$421,915,$643,400,$221,48539MonthDemand ForecastJanuary3,000February2,400March2,560April3,800May2,200June2,200Peak (Ap

27、ril) Discount from $40 to $39Cost=$438,857,$650,140,$211,283Revenue =Profit=40MonthDemand ForecastJanuary1,600February3,000March3,200April5,060May1,760June1,760Demand ManagementPricing and Aggregate Planning must be done jointlyFactors affecting discount timingProduct Margin: Impact of higher margin

28、 ($40 instead of $31)Consumption: Changing fraction of increase coming from forward buy (100% increase in consumption instead of 10% increase)Forward buy41Performance Under Different Scenarios42Regular PricePromotion PricePromotion PeriodPercent increase in demandPercent forward buyProfitAverage Inv

29、entory$40$40NANANA$217,725895$40$39January20 %20 %$221,485523$40$39April20%20%$211,283938$40$39January100%20%$242,810208$40$39April100%20%$247,3201,492$31$31NANANA$73,725895$31$30January100%20%$84,410208$31$30April100%20%$69,1201,492Factors Affecting Promotion Timing43FactorFavored timingHigh forward buyingLow demand periodHigh stealing shareHigh demand periodHigh growth of marketHigh demand periodHigh marginHigh demand periodLow marginLow demand periodHigh holding costLow demand periodLow flexibilityLow demand periodSummary