Taught classes on Production Planning, Purchasing, MRP ... Forecast Prerequisites Develop Inventory Management ... Formalize your process for Sales and Operations ... – PowerPoint PPT presentation
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_at_hunterdouglas.com
3 Todays 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 formulas1