Data & Analytics, Digitization

Better decision-making with mathematical models

Daniel Gburek05/07/2020

Do you know the difference between conventional and intelligent ERP systems? Intelligent ERP systems utilize intelligent assistants to help make complex operational decisions. Instead of relying on gut feeling and past experience, you can use data-based calculation models to help you make the right decisions.

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Mathematical models help decision-makers

Intelligent assistants are based on mathematical models. Real-life problems are translated into precise mathematical formulas, allowing us to resolve issues mathematically. Inventory optimization models, for example, put critical factors such as sales expectations, service levels, warehouse specifications or information on stock replacement in a mathematical context.

Mathematical models are easy to implement in the ERP environment

Modeling is about balancing out the complexity of mathematical descriptions. Models that are too broad do not provide acceptable results because crucial details and information are missing. Models that are too fine are equally inappropriate because it is difficult to extract the key information from the abundance of dependencies.
When mathematicians develop models for intelligent ERP systems, this isn’t an issue. The ERP system provides them a clear context to work with. Since it’s embedded right in the system landscape, the model is able to obtain accurate service commitments using the available data and the associated business processes. If any relevant information is missing, the first thing to do is add it to the company software. This also ensures that all the data required for decision-making is available in the ERP system – the backbone of every company.

Dashboards deliver clear results

Prediction and optimization results can be visualized on quality dashboards. Users can easily navigate through all the information and explore the full scope of the mathematical model. The performance figures displayed are perfect for demonstrating the added value of intelligent assistants, as well as the associated savings potential and key business indicators.

Conclusion

Intelligent assistants extend the classic performance spectrum of ERP systems with the addition of mathematical methods for prediction and optimization. This enables companies to use their existing data to simplify or automate complex decisions – for example, in areas such as material management, production or sales. Intelligent assistants offer greater security and help staff make difficult decisions.

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Author:
Daniel Gburek
Solution Manager Data & Analytics | COSMO CONSULT