Predict demands and control stocks

When the large flow of data collected is handled correctly, companies are able to use it to have greater control over market changes and thereby improve the forecasting of their demands.

From the insights extracted, they will be able to anticipate when certain products will be most sought after by consumers and when there is a drop in demand.

For example, through Big Data analysis, a company with multiple branches can closely monitor the launch of a given product. She is able to track which points this product is coming out more and even if in some place no sales were made. That way, you can get in touch and ensure that the team resolves the situation.

With these forecasts, it is possible to better control production, avoiding waste of resources with stopped products and also the loss of business due to not having them available.

Improve delivery logistics
As well as improving inventory control, data science is a great ally in logistics decisions. Through efficient analysis, companies are able to discover the best routes, have greater precision in the delivery time, avoiding setbacks and using the most efficient means of transport for each situation.

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For example, using the data collected from the GPS of a delivery truck, it is possible to generate a constant report of how long the delivery is taking to reach the buyer. In addition to being very useful for customers, it helps companies to identify patterns that can be used to optimize delivery strategies.


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