Avercast LLC @avercast

Forecasting Techniques

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1.  Gather data and information regarding the future event.

2.  Analyze the data and information.

3.  Combine the analysis and judgment to make a prediction.

4.  Deploy efforts to address the future opportunity and need.

How are different forecasts constructed?

Stable Demand Pattern

If demand patterns are stable and there is sufficient historical data, then quantitative methods are better relied upon for accurate forecasting.

When Data is Scarce

With little or no historical data, such as with a new product or

technology, qualitative inputs (opinions and judgements, from

experience on similar products) are relied upon for accuracy.

Time Series

Quantitative forecasting methods require a time series, to function.

A time series is a set of data arranged in chronological order.

Observing time series data usually displays randomness, trends, seasonality and cycles.

Common Quantitative Forecasting Methods

Moving Average

Weighted Moving Average

Trend Projection

Naïve

Multiplicative Seasonal

Associative Methods (regression and correlation)

Moving Average

Moving Average forecasting takes the average over a past time

horizon touching real time.

For example, the time horizon could be one month, therefore the

forecast would be the average sales over the past month. Or, if the

time horizon were two weeks, the forecast would be the average

sales over the past two weeks, etc.

Weighted Moving Average

Weighted moving average is similar to moving average, except that

we would apply weights of importance to the products, trends, or

time horizons of most importance.

Trend Projection

The method of forecasting based upon the least squares

mathematical technique fitting the line of best fit.

Naïve Method

Naïve method simply forecasts the exact amount that was sold last period.

For example, if last December you sold 200 chairs, you will forecast 200 chairs this December. You will not take into account any other factors.

Multiplicative Seasonal Multiplicative Seasonal forecasting is a combination of randomness and trend.

Steps that allow Multiplicative Seasonal forecasting are:

1.  Compute an average sales by time horizon.

2.  Compute the overall sales average of time horizon combined.

3.  Compute the Seasonal Index per each month by dividing the each time horizons sales by the overall average.

Most Common Qualitative Methods

•Sales Force Composite: Estimates from field salespeople are “rolled up” or aggregated.

•Field Sales and Product Line Management: Aggregated forecasts from field salespeople are

reconciled with projections from product line managers.

•Executive Opinion: Marketing, production, and finance managers jointly prepare the forecast.

•Delphi: A costly but effective method where experts individually develop forecasts, share their

forecasts, and then revise their forecasts until consensus is reached.

•Market Surveys: Questionnaires or interviews given to potential customers to learn about consumer behavior.