3.3.1 Quantitative sales forecasting

Moving averages

a quantitative method used to identify underlying trends in a set of raw data

How to calculate moving averages

  1. add several months worth of raw data
  1. calculate the average for those months and centring that figure on the middle period

Forecasting using extrapolation

predicting the future by assuming past trends will continue

time series data

a series of figures covering an extended period of time

Extrapolation: predicting by projecting past trends into the future

Scatter graphs (Correlation)

Limitations of quantitative sales forecasting techniques

when there's a link between sales and another variable, the relationship can be used to forecast sales if the other variable is controllable or predictable

Links such as

sales and advertising expenditure

sales and temperature

sales and the number of stores open

sales and the level of staff bonuses available

future may not be like the past

changes on external impacts = possible significant impact on sales

external events = unpredictable e.g. changes in FTPs or new entrants

quality of forecast can be questioned by the ability of forecaster to interpret data used to generate forecast

decision making - whether a trend could continue or dip - in the long term or short term

in correlation - understanding which variables to pair up and then exploring the causality if any involved