10 docs tagged with "Sales Forecasting"

Now that our forecasting is complete, we can compare the forecasts with IBP and get the difference in accuracy and errors.

The dashboard for presenting the results of this project was made programmatically using the Tremor framework of React Javascript. The web app was made using the NextJS framework and TypeScript.

Delivery data

Choosing a good evaluation metric for our problem is important. How accurate our estimate is depends on what metric we are using, and depending on the situation, different metrics can be the most suitable.

After cleaning and preprocessing the data, we created the relevant and important features for forecasting.

Now that we have the cleaned dataset with the appropriate features, we can finally perform forecasting. This forecasting is just regression, with the exception that train data must be sequential upto a date and test data must be the sequence following that.

This project is a Work in Progress.

This was a project started as an experiment to see whether using covariates like weather and economic indicators provide better forecasts than simply using historical data.

There are several steps followed for preprocessing the data.

When the forecast accuracy got from our method is compared to IBP forecasts, we get some brands for which we have significantly higher accuracy/lower errors. We would like to improve the accuracy even further for these brands.