Why Data Scientists Struggle to Deliver Business Value

Author(s): Cornellius Yudha Wijaya

Originally published on Towards AI.

And how to overcome it…

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A data science project is unique to the other as we directly develop data-driven solutions to solve business problems.

Many thought the problem would be solved if we had the machine learning model or the analysis.

How wrong is that assumption — many data science projects require more than technical applications.

In my professional experience, especially in my junior years, I made mistakes where I should have paid more attention to the business in favor of the model. This led to many failed data science projects and did not provide any value.

So, I want to share with you guys why data scientists need help to deliver business value and how to overcome them from my experience.

Let’s get into it.

I have experienced and seen many great models fail to deliver value because they are not aligned with the business objectives.

As technical people, we might like to work isolated from others and focus on our model. However, our model needs to solve the business pain point. And who knows more about business problems than business people?

When there is a lack of clear communication between data scientists and business teams,… Read the full blog for free on Medium.

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Published via Towards AI