Posted on 2022-01-04
Description
Having troubles predicting your sales with your business being impacted by seasonal factors? This analysis gives you the ability to predict your future sales by taking into account all your seasonal parameters - holidays, events, commercial impacts... add them as constraints for the model and it will return related sales forecast.
We recommend to perform this analyis in a timeline matching the product lifecycle, for example, at the stock arrival date. It can either be an automated analysis sent periodically through mail or a regular process pushed to your favorite supply chain ERP/demand planning tool
Analytics status
- Available
Business benefit
The major positive impacts to be expected by running this analysis are essentially on :▪ total turnover
▪ sell-through rate
Data inputs (mandatory)
We'll be using historical sales data containing the following information :▪ Date : historical timestep of observation (could be daily, monthly, weekly…)
▪ SKU :SKU ID, item identification number
▪ Revenue : sales in quantity or revenue
Data Output
You get the predicted sales per SKU in the format you needTechnical description
This analysis is made using a procedure called Prophet. It is forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects.Limitations
It works best with time series that have strong seasonal effects and several seasons of historical data.
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