4.3 sales forecasting Flashcards
Sales forecasting
quantitative technique used to predict a firm’s level of sales revenue over a given time period (month, year etc) using previous data
why is Sales forecasting important in business
prediction of the future sales is accurate, the risks of business operations and business strategic decisions would be much reduced.
examples of when and where sales forecasting is employed
The operations department would know how many units to produce and what quantity of materials to order and how much stock level to hold.
The marketing department would be aware of how many products to distribute and whether changes to the marketing mix are needed.
Human resources workforce plan would be more accurate.
Finance could plan cash flows with much greater accuracy and make accurate profit forecasts.
Strategic decision-making such as developing new products or entering new markets would become much better informed.
Time series analysis
predicts future sales levels from past sales levels, identifying trends patterns and variations. data will be plotted in a scatter plot, a line of best fit drawn and the trend will be extrapolated.
what is a extrapolation
involves basing future predictions on past results. When actual results are plotted on a time-series graph, the line can be extended, or extrapolated, into the future along the trend of the past data.
This simple method assumes that sales patterns are stable and will remain so in the future. It is ineffective when this is not true
inexpensive and effective method you can use to predict future values and trends in data.
Benefits sale forecasting
drive strategic planning in a business. For example, it can use sales forecasts to make more informed decisions about growth and expansion plans.
It enables organizations to predict, identify, and prepare for likely opportunities and threats, such as cyclical, seasonal or random variations (see next slide).
It helps firms to plan for the future, and to minimize uncertainties (risks) of the future.
Sales forecasts help businesses to identify sales trends, which helps to improve its operational efficiency.
Learning from the past can strengthen an organization.
Trend
underlying movement of the data in a time series.
Seasonal variations
regular changes in demand at different times of the year (for example with a peak before Christmas in the Western world).
Cyclical variations
linked to the business cycle in the country’s economy (for example with a recession).
Random variations
unpredictable changes that may occur at any time and will cause unusual sales figures (for example exceptionally poor weather or negative public image following a high profile product failure).w
what type of trends exist
Cyclical variation
Random Variation
Business cycle
seasonal variation
Limitations of sales forecasting
Extrapolated results can be inaccurate as they ignore changes in the external business environment that are beyond the control of a business.
Trends can be hard to identify, especially in businesses that experience fluctuations in their sales.
The use of simple linear regression in sales forecasting requires extrapolation from historical data, which can be inaccurate. Major problems can occur in the future that are not reflected in past sales figures.
Seasonal, cyclical and random variations in data can be difficult to predict and affect the accuracy of the sales forecast.
Sales forecasting has limited use for some businesses, such product-orientated organizations (which do not rely on market research to sell their products), those in rapidly changing markets (such as the fashion industry) and new businesses (which have no previous sales data to draw upon).
Links to BMTs that apply to Sales Forecasting.
SWOT: To what extent do external threats faced by a business affect the accuracy of sales forecasting?
Descriptive statistics: The mean, mode, median, range, and standard deviation are all statistical techniques used to analyse sales forecasting data. Discuss how the use of descriptive statistics can improve decision making in organizations.
Simple linear regression: Discuss how the use of simple linear regression can help businesses to make more accurate sales forecasts and strategic business decisions
Simple linear Regression includes
Scatter diagrams
Lines of best fit
Correlation/ Extrapolation
Line of best fit
A line through scatter plot of data that best express
