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Forecasting

Forecasting. By Steve Quiat CPIM, CSCP Hunter Douglas, Inc. Who Am I: Steve Quiat. Work as a Business Process Analyst for Hunter Douglas, Inc. Worked in manufacturing for over 35 years. Worked in production and materials planning for 20 years.

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Forecasting

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  1. Forecasting By Steve Quiat CPIM, CSCP Hunter Douglas, Inc.

  2. Who Am I: Steve Quiat • Work as a Business Process Analyst for Hunter Douglas, Inc. • Worked in manufacturing for over 35 years. • Worked in production and materials planning for 20 years. • Taught classes on Production Planning, Purchasing, MRP, SOP, and other functions. • APICS certified: CPIM, CSCP • Email: steve.quiat@hunterdouglas.com

  3. Today’s Discussion: Agenda • Purpose of Forecasting • Prerequisite to Forecasting • Forecasting Definition and Assumption • Forecast Methods • Statistical Forecasting Concepts • SOP Process

  4. Purpose of Forecasting • Provide basis for an operations and procurement business plan.

  5. Forecast Prerequisites • Develop Inventory Management Strategies: • Requires extensive attention. • Different strategies for different inventory categories. • Examples • Good strategies should simultaneously reduce inventory and improve service levels. • Forecasting is not appropriate in some cases.

  6. Forecast Prerequisites • SOP Process • Formalize your process for Sales and Operations Planning: • Key players & upper management must participate • Discuss forecast deviations and resulting adjustments.

  7. Forecast: Definition and Assumption • A forecast is a prediction of the future. • By definition, the forecast is always wrong. • If the forecast is always wrong, why do it?

  8. Forecast Methods • Aggregate [customer] forecasts. • Consensus: qualitative and quantative inputs. • Statistical forecast: • Last Period. • Average. • Simple Moving Average (smoothed average). • Weighted Moving Average. • Exponential Smoothing (and modified) • Delphi Method: Multiple rounds of consensus of experts. • Market Research

  9. Exponential Smoothing • Basic Concept: • Weighted average of the previous forecast and and previous actual [consumption]. By weighting one more than the other, you rely more on the most recent period, or all previous periods. • The raw data sequence is often represented by {xt}, and the output of the exponential smoothing algorithm is commonly written as {st}, which may be regarded as a best estimate of what the next value of xwill be. When the sequence of observations begins at time t = 0, the simplest form of exponential smoothing is given by the formulas[1] • where α is the smoothing factor, and 0 < α < 1. Source: Wikipedia

  10. Modifications To Exponential Smoothing : • Seasonality • Trend • Others

  11. Summary • Purpose of Forecasting: Business Plan • Prerequisites to Forecasting: Good Inventory Strategies Formal SOP Process • Forecasting Definition and Assumption: • Predition of Future • Forecast is always wrong (measure the error) • Forecast Methods • Statistical Forecasting Concepts

  12. Thank You for Coming.

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