Sales forecasting Details Flashcards
Sales may be forecast in…
-Quantity of products
-Total revenue earned
Steps businesses may take if sales are expected to grow(hint: ensuring this extra demand is met)
-Inventory levels can be expanded
-Additional staff may be recruited
-Production capacity may be increased
-Prices can be increased(so profit can be maximised in the case that companies will not be able to meet the expected demand)
Actions that may be taken if a decline in sales is forecast
-Reducing promotion
-Firing staff
-Reallocating or selling spare land and capital
Types of sales forecasting methods
-Causal models
-Time series analysis
-Qualitative techniques(e.g. market research)
Main variations in data from time series analysis
-Seasonal variations
-Cyclical variations
-Random variations
Benefits of sales forecasting
-Based on past data(hence should be theoretically more valid)
-Better capability to make decisions
-Effective future planning
Limitations of sales forecasting
-Not enough data(especially for new companies)
-Does not account for unpredictable events/rapidly changing markets
Use of simple linear regression
allows businesses to estimate how a dependent variable(e.g. sales) changes as the independent variable changes
Features of simple linear regression
-the dependent variable
-the independent variable
Steps for simple linear regression
-Creating scatter diagrams to plot data from two variables
-Sketching a line of best fit
-Extrapolating the data to make predictions
Benefits of scatter diagrams
-Easy to plot
-Easily show non-linear patterns
-Depict the relationship between two variables(good for visual learners)
-Easy to observe and interpret the pattern depicted
Limitations of scatter diagrams
-Cannot provide the exact extent of correlation
-Cannot take more than two variables into account
-Cannot reflect qualitative data
How is the moving average calculated?
(NB: You don’t need to know this for the exams)
it is calculated by adding up all the data points during a specific period and dividing the sum by the number of time periods
