Category:4.3 Sales Forecasting

Sales Forecasting: The process of predicting what the future sales of a firm will be. It uses a quantitative method to estimate the future sales and trends over a certain period of time. By doing this it helps the business by reducing uncertainty, helps in management in stock and cash flow, and better planning for growth.

Time series analysis: This is a quantitative sales forecasting method that predicts future sales from past sales data.There are certain aspects that need to be identified in the time series data:

Trend: A trend is a visible pattern seen after putting past sales data in. This can indicate the rise and fall of sales over a given period of time.

Seasonal fluctuations: These are changes in demand due to varying seasons in a year. An example could be that a business experiences an increase of sales at the beggining of a year and a decrease in the middle.

Cyclical fluctuations: These are variations tied to the business cycle in an economy. For example, sales can be on the rise during a growth phase, but decline during recession.

Random fluctuations: These are notable changes that stand out in a given trend.

Moving averages: This is a sales forecasting method that identifies and emphasises the direction of a trend. This helps to smooth out any fluctuations from sales data.

Calculating a moving average: Get the mean for the first sets of data then get the mean for the next sets of data, and so on and so forth.

Extrapolation: An extension of a trend line to predict future sales. A graph can be extrapolated to predict the future sales of a firm. Calculating variations: This is the difference between actual sales and trend values, can be calculated by getting the sum of the variations over the period divided by the number of years within the period.