Demand Forecasting forecasts future demand based on historical sales data.
To fit the best forecast, we select from several mathematical and statistical models:
There is a built-in machine learning algorithm to select the best method for your data.
Launching the App
To launch Demand Forecasting:
Log into AIMMS PRO. The SC Navigator Applications menu appears.
Click Launch App on the Demand Forecasting tile.
These have been created in Data Navigator.
After loading the data, you are lead to the Home page where you are able to see details about your dataset, and the properties of the forecast made in a previous period.
The app cleans your data automatically when you load your dataset(s).
Go to Data Cleaning to check the results, make manual changes, or accept the proposed data. When you accept all the proposed data changes, the app calculates the forecast and takes you to the Forecast Results page.
If the raw data is good enough, you can navigate directly to the Forecast Results page.
The calculated forecast can be reviewed and edited here.
Read more about forecast editing features on the Forecast Results page.
You can review the aggregated forecast for each level here.
Read more about forecast editing features on the Summary Totals page.
You can manually select a forecast method and recalculate the forecast for each record.
Read more about selecting forecast methods on the Forecast Methods page.
Export the data
After you finish your forecast planning, you can navigate to the Export Results page and save your data.
Continuous work on results
Working on historical or forecasted demand can be time consuming as a demand forecaster, as here the time series and trends are important and not only the KPIs. If you need to have a break, or continue the work the next day you can save your current state using Save Current State page action on Data Cleaning or Forecat Review pages.
When you save your current state it means that next time when you will load your configuration and dataset your saved changes will be loaded automatically. The app notices the user about this via dialog message.
Your current state is only saved for you. If another user starts working on the same configuration and dataset, s/he starts from the original data and can save his own state.
Based on the data amount that we are working with saving a scenario could take some time. Demand Forecasting informs the user when the saving is done.