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From ERP to Machine Learning and Back

I have been implementing and managing Enterprise Resource Planning (ERP) systems for several years. My ERP journey started at the FIU Computer Science department where I was working on a degree in Computer Science and had taken a few courses in Artificial Intelligence (AI). One day, I visited the Dean of the department seeking advice on what courses to take next to improve my IT knowledge and enhance my career. The Dean, a knowledgeable individual, advised me that “rather than re-inventing hot water, I should learn to use systems and applications already created by others”. I followed his advice and instead of working on a master’s degree in Computer Science with concentration in AI, I began learning and working with ERP systems at my job then as an IT Manager.

What is ERP?

Enterprise resource planning is a process used by companies to manage and integrate the important parts of their businesses. Many ERP software applications are important to companies because they help them implement resource planning by integrating all the processes needed to run their business with a single system.

Working on and learning about ERP became my passion. But ERP systems are broad and typically large, and it is not possible to know all about them, so you need to concentrate on certain areas of the system. I choose to learn the technical aspects and a couple of functional areas: distribution and manufacturing. I also learned to implement them and eventually became an ERP Project Manager. I have managed Epicor, SAGE, and Infor (Baan and LN) implementations.

Implementing ERP Systems

Implementing ERP systems is a lot of fun, you deal with different scenarios and business organizations. You also deal with lots of data and make decisions based on such data. You even try to make predictions (examples are Demand Planning and Demand Forecast) based on data with various degrees of success. The most successful models typically use intelligent algorithms. But data is just data and ERPs are information-hungry beasts. As information is data with a purpose, you first must make sense of that data before it can be used by the system.

And that is one of the reasons why I have enrolled in AI Machine Learning: from Data to Decisions, an online class with MIT Professional Education. According to the curriculum, this class will take me from understanding data, making predictions, making decisions, to understanding the results. I think I could become a more effective ERP implementer if I could help make better and more intelligent decisions. I look forward to sharing my progress with you.

After that, my next stop will be at Intelligent Supply-Chain. I feel there are plenty of opportunities at better understanding, classifying, and optimizing supply-chain data.

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