Data & Innovation • Automotive • AWS
Intelligent Forecasting for process automation
Solution enabling the automation of demand planning processes across various business units within the company.
About the client
A leading company in the categories of fuel additives, engine additives, antifreeze, and automotive fluids with over 60 years of experience.
Today, it holds significant market share and presence due to its development of new technologies in the category of lubricating oils for gasoline engines and industrial products.
Committed to the continuous development of new and improved products for engines and the needs of its customers, whose satisfaction is its sole mission.
Needs
The client is seeking to implement a solution that allows them to automate the demand planning process for the various business units of the company.
Solution
Nubiral developed and refined a flagship product called Intelligent Forecasting. The tool is a model created with Machine Learning, utilizing both supervised and unsupervised learning techniques.
The solution learns from data and helps companies become efficient in their operations, providing accurate forecasts and minimizing forecasting errors.
Having an Intelligent Forecasting system is crucial for business success and is a central piece of digital transformation. Understanding and predicting customer demand is vital for companies to avoid stockouts, inventory issues, and maintain appropriate inventory levels.
Results
Currently, the client is primarily using Intelligent Forecasting to predict distributor demand, which has led to a 15% reduction in Forecast Error, decreasing it from 50% to 35%.
Additionally, the second application is based on understanding demand for oil packaging production, ensuring that manufacturing aligns with demand. In this regard, they have reduced stock times by 23%.
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