How to apply Moving Average in Forecasting?
Forecasting with Moving Average involves analyzing the smoothed data to identify trends that can inform future projections. Although it doesn't predict specific future values, it helps in understanding the direction in which data, like sales or website traffic, might move.
Application:
Consider an online retailer looking to forecast next month's sales. Their weekly sales data for the past eight weeks are: 100, 120, 110, 130, 115, 140, 125, 150 units.
A 4-week Moving Average would smooth out weekly fluctuations and provide a clearer view of the sales trend, aiding in forecasting future sales.
Calculating for Forecasting:
To apply Moving Average for forecasting in Excel or Google Sheets:
- - Calculate the Moving Average as previously learned.
- - Plot this average on a graph to visually inspect the trend.
- - For our retailer's data, calculate the 4-week Moving Average (using steps outlined in previous concept).
- - Plot these averages using a line chart to show the trend direction.
- - Analyze the trend line to infer future sales trends.
This method, while not predicting exact future numbers, provides a trend direction useful for forecasting.
This understanding of Moving Average as a forecasting tool lays the foundation for more advanced techniques in later concepts, such as Linear Regression and Time Series Models.
Each of these methods will build upon this basic understanding, enhancing your ability to make more accurate and informed forecasts.