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.comsteve.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 1.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 2.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 {x t }, and the output of the exponential smoothing algorithm is commonly written as {s t }, 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] [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.