Quantitative Sales Forecasting (3.3.1) Flashcards
What is Quantitative Sales Forecasting?
Data-based mathematical process that sales teams use to understand performance and predict future revenue based on historical data and patterns. Forecasting results give businesses the ability to make informed decisions on strategies and processes to ensure continuous success.
What are the benefits of Sales Forecasting?
Helps to:
-Employ appropriate amount of staff
-Accurately predict cash flow
-Accurately predict profit
-Effectively plan procurement and capacity utilization
What are the 3 main methods used in Quantitative Sales Forecasting?
- Moving Averages
2.Extroplolation
3.Correlation
What are Moving Averages?
The Moving average is calculated by using the average of several periods of time up to the present. It is a simple, technical analysis tool used to identify the trend direction of a stock. These averages smooth data so that trends may be more easily identified
How do moving averages improve Sales Forecasting?
-Raw Sales Data can be erratic and vary month to month
-Moving Averages help level this out and identify trends
Why is Moving Averages used?
This is because sometimes past sales data is too erratic for clear trends to be identified and so a moving average smoothes raw data and allows analysts to spot patterns even when sales are subject to seasonal variations
What are seasonal variations?
Variation in a series of data within one year that is repeated more or less regularly
How do you work out a 3 point moving average?
Get the 3 bits of data so e.g. monthly sales and add the first three and then divide by 3 and put it in the middle of the 3 values. Then move down one and get the next 3 values.
What is Extrapolation?
Extrapolation in business is a powerful analytical tool that enables professionals to project trends, forecast outcomes, and make informed decisions based on historical data. It involves extending known patterns into the future, allowing businesses to anticipate changes, plan strategies, and adapt to evolving environments. Can often be done simply by extending a line of best fit
How does extrapolation work?
Extrapolation is a method used in mathematics, statistics, and science to estimate values beyond a known range. It involves using existing data to predict future values or to estimate unknown values within a dataset.
How does Extrapolation improve Sales Forecasting?
It makes the Sales sold be for an extended period of time before it goes out of trend.
What are Scatter Graphs?
Where there is a link between two variables there is a correlation. Correlations may be positive or negative. Chart type that is normally used to observe and visually display the relationship between variables.
How do Scatter Graphs improve Sales Forecasting?
Scatter plot is useful for understanding if two different data points may be related. For example, a coffee shop could track sales of iced coffee vs. the temperature outside to see if there is any relationship between sales and temperature. If there is a trend, they could use this data to better plan for future high-volume sales days.
What are the different types of correlation and what do they mean?
-Positive Correlation means as one variable increases, so does the other variable (line of best fit slopes upwards)
-Negative Correlation means as one variable increases, the other variable decreases (Line of best fit slopes downwards)
-No correlation means there is no connection between the two variables (not possible to identify line of best fit)
What can be used to help work out extrapolation?
Scatter graph line extended
What are the characteristics of Moving Averages?
-Relies on past sales data
-Doesn’t include external factors
-Doesn’t account for seasonality
-Doesn’t account for dynamic markets
What are the characteristics of Extrapolation?
-Relies on past sales data
-Doesn’t include external factors
-Doesn’t account for seasonality
-Doesn’t account for dynamic markets
What are the characteristics of Scatter Graphs?
-Can give false correlations
-Tunnel vision
-Invest Money in the wrong places
-May miss accurate correlations
Is a Quantitative Sales Forecasting more effective in the short or long term?
Short term as relies on future to reflect what has happened in past but future could be unexpected
Why is it bad if someone has never done a sales forecast before?
They have a lack of experience and so don’t have and understanding about trends, tastes and competitors and so will limit their ability to accurately forecast.
What are the limitations of a Quantitative Sales Forecast?
- Seasonality-Weather
- Competition- New rivals or unexpected competitor actions
- Publicity- Positive or negative publicity
- Market changes- unexpected changes to consumer income e.g.
- Changes to legislation- Unexpected changes to law or tax structure
What is the acronym for external factors that can affect Quantitative Sales Forecasting?
PESTLE
Political
Economic
Social
Technological
Legal
Environmental
How can businesses improve the accuracy of sales forecasts?
-Conducting detailed market research
-Employing experts with excellent market knowledge
-Revising the sales forecasts frequently
-Forecasting for the short - to medium - term
