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Sales Forecasting, Strong Positive, Negative, Weak Positive, None - Coggle…
Sales Forecasting
Limitations
'Correlation doesn't always mean causation' too often relationships can appear by chance, it takes judgement to decide the cause and effect or whether its merely down to chance.
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in dynamic markets, change happens rapidly making extrapolation often misleading
Extrapolation
We assume that past trends will continue, thereby we automatically do in series of data, the long-term trend identified in time series data is extended into the future.
Predicting by projecting past trends into the future, marked on the scatter graphs of how that would look.
However this focus on past trends can be innacurate, short term assumptions may be correct however, if the businesses is ongoing a 'blip' and long term the upward movement will dominate, it wont be as accurate.
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Moving Averages
to identify a underlying trend in a set of data, a moving average is a quantitative method used in a set of raw data.
CALCULATION
its calculated first by adding 3 or 4 months if data then dividing by 3 or 4 to work out an average for that group of data, then working your way down the table this time not using the first month you used but the 2nd,3rd and then the 4th.
Alike the example table as followed, there is a sales column and a centred total and then room for either a ' three period moving average' or a ' four quarter moving average' depending if you are assessing 3 or 4 months; this will depend on whether your product or brand is seasonal ( 4 months) or whether this does not apply.
Scatter graphs
We then take all the data figures we have collected through the moving averages and then them to create a scatter graph demonstration over the original data, using a line of best fit. ( a line which can be drawn through a series of data to look for a trend)
Plotting the relationship between two variables on a scatter graph can provide great insight relating ti the extent at which the products interlink.
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Purpose
To predict future sales, plan budgets, organise distribution, plan sales campaigns and make strategic changes.
Using statistical techniques to analyse existing data in order to provide information on likely or current decision making.
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