8/29/009/7/99s. chopra / demand planning1 planning demand and supply in a supply chain forecasting...

8/29/009/7/99 S. Chopra / Demand Planning 1

Planning Demand and Supply in a Supply Chain

Forecasting and Aggregate Planning

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Learning Objectives

Phases of supply chain decisions Identify components of a demand forecast Time series forecasting Estimate forecast error Aggregate planning in the supply chain

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Phases of Supply Chain Decisions

Strategy or design: Forecast Planning: Forecast Operation Actual demand

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Characteristics of forecasts

Forecasts are always wrong. Should include expected value and measure of error.

Long-term forecasts are less accurate than short-term forecasts: Forecast horizon

Aggregate forecasts are more accurate than disaggregate forecasts

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Forecasting Methods

Qualitative Time Series

– Static

– Adaptive

Causal Simulation

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Components of an observation

Observed demand (O) =

Systematic component (S) + Random component (R)

Level (current deseasonalized demand)

Trend (growth or decline in demand)

Seasonality (predictable seasonal fluctuation)

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Time Series ForecastingQuarter Demand Dt

II, 1998 8000III, 1998 13000IV, 1998 23000I, 1999 34000II, 1999 10000III, 1999 18000IV, 1999 23000I, 2000 38000II, 2000 12000III, 2000 13000IV, 2000 32000I, 2001 41000

Forecast demand for thenext four quarters.

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Time Series Forecasting

0

10,000

20,000

30,000

40,000

50,000

97,297,397,498,198,298,398,499,199,299,399,400,1

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Forecasting methods

Static Adaptive

– Moving average

– Simple exponential smoothing

– Holt’s model (with trend)

– Winter’s model (with trend and seasonality)

Excel File

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Error measures

MAD Mean Squared Error (MSE) Mean Absolute Percentage Error (MAPE) Bias Tracking Signal

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Aggregate Planning at Red Tomato Tools

Month Demand ForecastJanuary 1,600February 3,000

March 3,200April 3,800May 2,200June 2,200

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Fundamental tradeoffs in Aggregate Planning

Capacity (regular time, over time, subcontract)

Inventory

Backlog / lost sales

Basic Strategies Chase strategy

Time flexibility from workforce or capacity

Level strategy

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Aggregate PlanningItem Cost

Materials $10/unitInventory holding cost $2/unit/monthMarginal cost of a stockout $5/unit/monthHiring and training costs $300/workerLayoff cost $500/workerLabor hours required 4/unitRegular time cost $4/hourOver time cost $6/hourCost of subcontracting $30/unit

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Aggregate Planning (Define Decision Variables)

Wt = Workforce size for month t, t = 1, ..., 6

Ht = Number of employees hired at the beginning of month t, t = 1, ..., 6

Lt = Number of employees laid off at the beginning of month t, t = 1, ..., 6

Pt = Production in month t, t = 1, ..., 6

It = Inventory at the end of month t, t = 1, ..., 6

St = Number of units stocked out at the end of month t, t = 1, ..., 6

Ct = Number of units subcontracted for month t, t = 1, ..., 6

Ot = Number of overtime hours worked in month t, t = 1, ..., 6

Excel File

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Aggregate Planning (Define Objective Function))

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Aggregate Planning (Define Constraints Linking Variables)

Workforce size for each month is based on hiring and layoffs

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Aggregate Planning (Constraints)

Production for each month cannot exceed capacity

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Aggregate Planning (Constraints)

Inventory balance for each month

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Aggregate Planning (Constraints)

Over time for each month

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Scenarios

Increase in holding cost (from $2 to $6) Over time cost drops to $4.1 per hour Increased demand fluctuation

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Increased Demand Fluctuation

Month Demand ForecastJanuary 1,000February 3,000

March 3,800April 4,800May 2,000June 1,400

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Managing Predictable Variability

Manage Supply– Manage capacity

» Time flexibility from workforce (OT and otherwise)

» Use of seasonal workforce

» Use of subcontracting

» Flexible processes

» Counter cyclical products

– Manage inventory» Component commonality

» Seasonal inventory of predictable products

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Managing Predictable Variability

Manage demand with pricing– Original pricing: Cost = $422,275, Revenue = $640,000

Demand increase from discounting– Market growth

– Stealing market share

– Forward buying

Discount of $1 increases period demand by 10% and moves 20% of next two months demand forward

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Off-Peak (January) Discount from $40 to $39

Month Demand ForecastJanuary 3,000February 2,400

March 2,560April 3,800May 2,200June 2,200

Cost = $421,915, Revenue = $643,400, Profit = $221,485

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Peak (April) Discount from $40 to $39

Month Demand ForecastJanuary 1,600February 3,000

March 3,200April 5,060May 1,760June 1,760

Cost = $438,857, Revenue = $650,140, Profit = $211,283

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Demand Management

Pricing and Aggregate Planning must be done jointly

Factors affecting discount timing– Product Margin: Impact of higher margin ($40

instead of $31)

– Consumption: Changing fraction of increase coming from forward buy (100% increase in consumption instead of 10% increase)

– Forward buy

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Performance Under Different ScenariosRegularPrice

PromotionPrice

PromotionPeriod

Percentincrease indemand

Percentforwardbuy

Profit AverageInventory

$40 $40 NA NA NA $217,725 895$40 $39 January 20 % 20 % $221,485 523$40 $39 April 20% 20% $211,283 938$40 $39 January 100% 20% $242,810 208$40 $39 April 100% 20% $247,320 1,492$31 $31 NA NA NA $73,725 895$31 $30 January 100% 20% $84,410 208$31 $30 April 100% 20% $69,120 1,492

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Factors Affecting Promotion Timing

Factor Favored timingHigh forward buying Low demand periodHigh stealing share High demand periodHigh growth of market High demand periodHigh margin High demand periodLow margin Low demand periodHigh holding cost Low demand periodLow flexibility Low demand period

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Summary of Learning Objectives

Forecasting Aggregate planning Supply and demand management during

aggregate planning with predictable demand variation– Supply management levers

– Demand management levers

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Factors Influencing Discount Timing

Impact of discount on consumption Impact of discount on forward buy Product margin

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Inventory/Capacity tradeoff

Leveling capacity forces inventory to build up in anticipation of seasonal variation in demand

Carrying low levels of inventory requires capacity to vary with seasonal variation in demand or enough capacity to cover peak demand during season

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January Discount: 100% increase in consumption, sale price = $40 ($39)

Month Demand ForecastJanuary 4,440February 2,400

March 2,560April 3,800May 2,200June 2,200

Off peak discount: Cost = $456,750, Revenue = $699,560

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Peak (April) Discount: 100% increase in consumption, sale price = $40 ($39)

Month Demand ForecastJanuary 1,600February 3,000

March 3,200April 8,480May 1,760June 1,760

Peak discount: Cost = $$536,200, Revenue = $783,520