Extrapolation
Using past experience or past business data to forecast future sales.
Quantitative forecasting methods
Time series analysis
Use of market research data
Qualitative forecasting methods.
Delphi technique
Brainstorming
Intuition
Expert opinion
When are quantitative forecasting methods used?
What do they rely on?
When there is historical data available
They rely heavily on data and are objective.
Time series analysis
Uses evidence from past sales records to predict future sale patterns
Methods of time series analysis
Seasonal analysis
Trend analysis
Cycle analysis
Random factor analysis
Seasonal Analysis
Sales are measured on a monthly or weekly basis to examine the seasonality of demand.
Eg the sales of ice cream will be higher in the warmer seasons and lower in the colder seasons, or according to daily weather changes.
Trend analysis
This focuses on long-term data, which has been collected over a number of years. The objective is to determine the general trend of sales - rising, falling, or stagnant.
Cycle analysis
As with trend analysis, long term figures are used but now the objective is to examine the relationship between demand and levels and economic activity.
Random factor analysis
This method of analysis attempts to explain how unusual or extreme sales figures occur.
Eg. If sales of ice creams double for a two week period could this be explained by a change in weather conditions as opposed to a successful marketing campaign?
How to work out moving averages
Take the number of adjacent figures for each month, add it together and divide by the number of months.
Result is placed in the middle month.
Months in a quarter
3 months
Benefits of time series analysis
- Helps plan ahead
- Helps financial planning
- Production planning (determine right type and quantity of supplies are ordered and that the line is running at the correct speed)
- Useful in identifying seasonal variation
- Reduces risk of surprises
- Human resource planning (ensures right number and correctly qualified staff members are available)
Limitations of time series analysis
- It is not always easy to predict the future
- Historical data is not always a good indicator
- Even complicated forecasting methods may not be accurate
- Less useful for long term forecasts
- Success is not guaranteed
Surveys of consumer intentions
Making predictions by asking people directly what they intend to do in the future. The results of these surveys allow businesses to predict sales patterns, and plan for the future in terms of staffing and production levels.
Direct Sales Information
Sales staff may notice any developing trends, and they have the experience to spot market changes, and shifts in customer preferences, and attitudes.
Test Marketing
Test marketing involves testing consumers response to a product, before the full release of the product. This may involve releasing the product in a small geographical area or to a small selection of the target market.
Delphi method
Begins with the initial development of a questionnaire focusing on the problem, this is then sent out to a select panel of ‘experts’ who independently answer and send back the questionnaire. A second questionnaire is then developed, based on findings from the first, and sent to the same panel.
The members of the panel independently rate and prioritise ideas. This allows the group of experts to reach a consensus forecast on the subject being discussed
Benefits of the Delphi Method
- It is flexible enough to be used in a variety of situations and can be applied to a range of complex problems.
- Provides a structured way for a group of people to make a decision.
- Participants have time to think through their ideas leading to a better quality of response.
- The Delphi Method creates a record of the experts responses and ideas which can be used where needed.
Limitations of the Delphi Method
- The method will more than likely require a substantial period of time to complete as the process is time consuming to coordinate and manage.
- It assumes that experts are willing to come to a consensus.
- Monetary payments to the experts may cause bias.
External factors affecting quantitive and qualitative sales forecasting
- Economic (unemployment, inflation, interest rates, exchange rates, economic growth)
- Consumer Factors (Consumer tastes and fashion is always changing. Consumers are notoriously unpredictable)
- Competition Factors (A business cannot control the actions of competitors)
