Thinking about building your industrial analytics app in-house? To succeed you need the right team, and strong IT-OT collaboration.
In my previous post about Build vs Buy, which discussed when it makes sense to design your own analytics application or buy an existing product, I had mentioned that for the Buy strategy the right team needs to be in place. In this post, we will talk about the team structure and more closely examine the different types of data scientists emerging in the industry. The team needs to be a mixture of IT (Information Technology) and OT (Operational Technology) for the initiative to succeed. One cannot operate without the other. A clear corollary is that if IT is the heart then OT is the brain. The following roles are essential for the success of the analytics initiative:
The reason I have defined the above hierarchy and roles for the Buy strategy is because there is no magic bullet in the market which will solve all problems at the click of a button. There needs to a clear intent from the side of the organizations which are planning to implement analytics solutions. That intent can only be seen if there is a right mix of IT and OT and both parties have some skin in the game for the final success of the initiative. One without the other is like taking away the brain or heart. The body cannot function without either.
Abhishek is a data junkie who lives and breathes solving customer problems using analytics. He has a breadth of experience - from implementing large-scale enterprise data warehouses to helping manufacturers analyze asset behavior and predict failures. Due to his business background, he has a unique ability to understand functional requirements and translate them into technology solutions. He is part of the customer success team and leads solution engineering initiatives, traveling all over the world to explain how Progress DataRPM can help companies save millions of dollars.
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