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Intelligent Forecasting

A solution with precise data, at the exact moment,
applicable to inventories, storage and distribution.
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What is Intelligent Forecasting?

Artificial intelligence solution that allows the forecasting of business events in advance in order to plan improvements and actions that optimize results and meet the proposed objectives.
It uses Machine Learning algorithms to learn from the data obtained and perform inventory savings by reducing forecast errors by up to 25%.

Furthermore, as a result of the reduction of the safety stock, thousands of dollars are saved.
This solution applies to inventories, storage and distribution within industries such as retail, supply chain, and manufacturing.

Which are the applications for AI?

Recurring patterns of demand

Recurring variations in demand caused, for example, during business days, holidays or seasonality.

Business decisions

The impact of promotions (including cannibalization and halo effect) price change and changes in how products are offered.

External Factors

The impact of factors not controlled by the business, such as weather, local events and customer desires.

Unknown factors

Changes in demand not contemplated in the past, such as pandemics, openings of competitors in the vicinity, unexpected high mass events (protests).

Which are the benefits of Intelligent Forecasting?

Precise Inventories

Customer base expansion with more accurate inventory stock rates.

Higher Profitability

Increased profitability, flexibility and inventory variety.

New business focus

Business approach with strategic planning to drive operations with highly predictive forecasts.

Blog

How Intelligence Forecasting can change your business. Having information in advance can make a huge difference in anticipating events and providing better service to your clients.

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Webinar

Intelligent Forecasting. The year 2020 has been one of the most volatile ones we have experienced so far with a pandemic and a recessive global economy. Being certain of the operation and understanding the demand is no longer a way of being efficient, but a necessity to survive

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