Data, your greatest allies for the future
Augment adjustes and processes data to ensure maximum performance in algorithmic forecasts. Hundrers of algorithms compete against each other to bring maximum accuracy.
How do we ensure the quality of the predictions?
Set up
Data preprocessing
Data cleaning by removing atypical extreme sales.
Data adjustment considering potential sold-outs. The number of sales made is taken into account as if there had been sufficient stock.
Augment selects the most suitable prediction method based on data analyses and their performance.
Seasonality analysis
Our core can identify extreme seasons, such as Christmas, or extremely seasonal items, like Easter eggs.
Global changes and events like COVID-19 create seasonal shifts. However, for us, nothing remains unchanged. Our software is capable of absorbing these situations and learning from them.
High Seasonality01
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Moderate Seasonality
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Low Seasonality
Identification of extreme sales and inventory stockouts.
The goal is to identify unlikely extreme sales that are not likely to be repeated and prevent them from influencing sales forecasts and inventory calculations.
Including such sales in the algorithm would result in a costly and inefficient inventory.
Augment identifies and analyzes periods when stock is not available. This data is used to calculate lost sales when a specific item is out of stock.
Adjust historical sales to obtain accurate input in the sales forecast.
Assess the losses the company incurs due to stoc-kouts and replenish intelligently.
Use past sold-outs in the module to manage the customer service level.
Know more about Augment
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Contact us
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The success of every SME
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Solutions
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Introduction
Start off on the right foot with the Augment introduction.