The most critical element to look for in the enterprise resource planning vendor’s artificial intelligence features is flexibility. The AI modules have to be flexible in every manner data is consumed, the AI model is run, the AI model’s predictions are used, and the time new information is evaluated. Many ERP vendors don’t offer the flexibility in their offerings.

The functionalities in the ERP platform are used in more than one way. The ERP offering must allow the analyst to modify the fields in the modeling process while setting up the AI analysis. Excluding values from individual’s fields is as essential as adding or dropping fields to get to the same AI model for predictions. If a company has only good data about one type of customer then the AI modules must let the analyst filter the field. Different modeling processes require different filtration process such as filter by date, data from the past quarter, and some models require data for years.

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Few algorithms perform better with particular types of data. People try to get technical when it comes to an understanding of the different ranges of value and think about text fields versus numeric fields, but they don’t need to go far into AI. Data scientists generally use several algorithms, combine their results and form a unique result for action.

An analyst can tweak model parameters just slightly and come up with a much more accurate model. However, it is not always fine-tuning the model; it is about making the model simpler. The model performs better if it runs faster without sacrificing accuracy. Sometimes a company wants to cause an action to an isolated prediction on an ERP is adequate. AI predictions are helpful in the way forward action plan of an organization, so the projections must be brought forth for business intelligence systems and reporting. The ERP vendor’s AI modules must allow the analyst to direct the output as needed.