Forecasting and Demand Planning

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  • Topic: Forecasting, Forecast error, Time series analysis
  • Pages : 19 (2739 words )
  • Download(s) : 267
  • Published : September 13, 2010
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Integrated Planning – Module 2

1

Agenda
• Forecasting, • Factors influencing Demand • Basic Demand Patterns • Basic Principles of Forecasting • Principles of Data Collection • Basic Forecasting Techniques, Seasonality • Sources & Types of Forecasting Errors

Forecasting can be conducted at various levels
Strategic Required for • Product life cycle • Long-term capacity planning • Capital asset/equipment/ human resource management Examples • Product line transitions • Annual volume out 3-5 years • Buy/build/lease decisions

Financial

• Budgeting • Financial reporting • Working capital management • Production scheduling • Purchasing • Resource planning • Customer service management (product allocations)

• Total annual/monthly volume • Projected product mix

Operational

• Weekly/monthly SKUlevel demand • Order size and frequency

3

Role of Forecasting in Supply Chain,
• Basis for Strategic & Planning Decisions in SCM • Decisions needing Forecast as Base • Production - Scheduling -Inventory Control -- Aggregate Planning - Purchasing

• Marketing
-Allocation of Sales-Force -- Promotion Activities -- New Product Launching

• Finance
-Plant & Equipment Investment -- Budgetary Planning

• HR
-Workforce Planning -- Recruitment - Lay-Offs
3

Forecasting Impact
Demand management
Sales history/ orders Forecasting Demand planning Sales and operations planning

Directly impacted by demand management

Production management Aggregate planning

Distribution management Inventory management Master production scheduling (MPS) BOM inventory routing

Materials requirement planning (MRP)

Distribution/transport network Shop floor scheduling and control

Capacity requirements planning (CRP)

Purchasing

Production

5

Higher forecast accuracy improves service levels at lower inventory Percent
100 99 98 97 96 95
0 94 Monthly average forecast error Excellent Far Poor 20% 40% 50% 3 1 2 Reducing forecast error will permit 1 Reduced inventory to a given service level 2 Increased service level for a given inventory level 3 Both reduced inventory and improved service level

2 4 6 Required average inventory Weeks

8

10

12

Forecasting error must be measured at different levels
Forecasting error Percent Mean forecasting error Forecasting tips

• Measure forecasting error as the
mean absolute percent error (Forecast – actual sales) Forecast

60 50 40 30 20 10 0
-12 -10 -8 -6 -4 SKU/DC (12 oz. ketchup bottle in Dallas warehouse)* SKU level (12 oz. bottle) Brand level (ketchup)

• Error of forecasting can be
measured at various levels: product family, brand, SKU, SKU/DC and will improve at higher levels of consolidation

• Frequency of measurement is
usually monthly; however, best practitioners are doing weekly forecasts

Product family level (all condiments)
-2 Manufacturing lead time -0

• Measure bias as the mean
percent error**

(Forecast – actual sales) Forecast

* Required level of detail for planning 7 ** A consistently positive or negative bias indicates a tendency to over- or under-forecast which may be easily remedied

Range of algorithms can be used
COMMON FORECAST ALGORITHMS
Model Simple Calculation/description

• Last year plus percent • Last 3 months • Experiential smoothing • Seasonality with trend

• Last year‟s same period demand* increased by a flat
percentage

• Last 3-month moving average of demand • Last 12-month moving average with most recent 2-3 months more heavily weighted

• Experiential smoothing with a seasonality factor that
weights periods differently based on relative historical demand throughout the year

• Regression

• Incorporates variables other than historical demand
(e.g., price promotional activity) to best fit historical demand patterns

• Time series
• Real-time regression using
POS data

• Uses Fourier transforms to best fit historical demand
patterns

Complex

• Modifies above models...
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