Forecasting

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Forecasting Cube Representation
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New Product Demand Forecasting
• New product demand forecasts for the longerterm horizon tend to be the responsibility of marketing departments. In the shorter term, demand forecasts tend to be assimilated from sales force estimates. There are no specific formal methodologies within demand planning for forecasting new products sales.
Forecasting
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Agenda
• Concept • Application • Q&A
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Concept
• Factors influencing the demand • Basic demand patterns • Basic principles of forecasting • Principles of data collection • Basic forecasting techniques • Seasonality • Sources and types of forecast error
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Basic principle of forecasting
• Are rarely 100% accurate over time • Should include an estimate of error • Are more accurate for product lines and families • Are more accurate for nearer periods of time
• Market Testing Methods
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Operational Forecasting
• Operational Forecasting is the process of pulling together the three sub-processes. • This includes the process of selecting appropriate modeling and forecasting methods which can be one of the most difficult aspects of forecasting. The first factor is whether the demand is purely time-dependent or causal, ie demand is affected by demand drivers. • The issue is whether the data is stationary, trended and/or seasonal. The variance and auto correlation functions are extremely useful in this instance.
• Seasonality index Period average sales =---------------------------------------------Average sales for all periods
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Sources and types of forecast error
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Demand Planning
• There are four main sub-processes:
– Baseline Forecasting – Event Forecasting – New Product Demand Forecasting – Operational Forecasting
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Factors influencing the demand
• Factors
– – – – General business and economic Competitive factor Market trends Firm’s own plans
• Sources
– – – – – Customers Spare parts Promotions Intra-company Other
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Basic forecasting techniques
• Qualitative techniques • Quantitative techniques • Extrinsic techniques • Intrinsic quantitative techniques
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Seasonality
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The following graph illustrates how these process areas interact:
supply chain planning demand creation processes marketing planning customer development planning etc. demand planning Baseline forecasting Event forecasting New product Demand planning Operational forecasting Demand management financial planning Other Business processes
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Basic demand patterns
• Characteristics
– Trend – Seasonality – Random variation – Cyclical variation
• Patterns
– Stable vs. dynamic – Dependant vs. independent (forecast or not)
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Pyramid Forecasting
• A fundamental issue with any implementation of a demand planning process is the determination of the proper level at which the forecast should be created. • We all know that it may be easy to predict annual category or brand sales volumes, but we also agree that not much action can be taken based upon that prediction. • On the other hand, a daily forecast by item and location may very difficult to produce but it will be invaluable in the determination of the best finished goods deployment plan from production sources to regional distribution centers.
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Pord data in terms needed for the forecast • Record circumstances relating to the data • Record demand separately for different customer groups
• Pyramid Forecasting
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Baseline Forecasting
• Is used to determine long-term underlying demand, without the influence of instantaneous or transitory events. • Includes only the regular or systematic components of the demand pattern. To determine baseline forecast, the systematic components of the history are identified and extrapolated.
• Two types’ errors
– Cumulative variation – Random variation
• Countermeasure
– Make a judgment about the reasonableness of the error – Make contingency plan – Set safety stock
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Event Forecasting
• Is the process of forecasting additional volume sales and cannibalizing standard lines at times of short term and /or immediate effect events. Promotions are the most common event. • Consumer off-take