3.3.1 quantitative sales forecasting

quantitative sales forecasting

statistical technique which uses historical smoothed out data to make predictions about the future

4 components that can skew data

random fluctuations, trends, seasonal fluctuations, cyclical fluctuations

ways to show trends

calculations of time series analysis, scatter graphs, extrapolation of past data- look for the trend and extend the line

moving averages

calculating the most recent 3 or 4 periods to create an average

sales figures collected at consistent time intervals

time series data

centring

find the average at 2 four quater moving averages and you place the result against the 3rd period (month / year) of the first moving average

time series analysis

only shows what is happening to data

casual modelling

tries to explain data by showing a link or relationship between sets of data. this can be shown through a scatter graph comparing two variables

extrapolation

trends in the past sales data can be continued in the future to forecast sales

SWOT factors

Strengths, Weaknesses, Opportunities, Threats

PESTLE C Factors

Political, Environmental, Social, Technology, Legal, Economical, Competition

Quantitative Sales Factors limitations

products with a short lifespan may find extrapolation misleading