How to Use Data Science to Get Business Results

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How to Use Data Science to Get Business Results

Nora Ghaoui shares an article that explains how to get business results from managing data science initiatives.

Data science can be a valuable tool for solving business problems, but the companies that I work with make little use of data science methods. There is a sense that the discipline is a black box to be left to the experts. That is a missed opportunity for creating business value.

Data science initiatives can be managed in the same way as other business initiatives. Business leaders who learn (a little bit) about data science can get better business results.

Read the details below. Contact me if you would like to know more.

Business results

When you look at the statistics being reported, most data science projects are failing to deliver tangible business results. While the interest in data science and machine learning has been growing since 2012, only 20% of analytics insights are expected to deliver business value through 2022[1], over ten years later. So the problem is widespread, and not improving.

Senior leaders are missing the opportunity to create value from data for two reasons. One is unfamiliarity, since many of the techniques are evolving rapidly, and non-experts cannot keep up. Another is a belief that data science is so complex that business leaders cannot hope to understand it. Both of these reasons need to be tackled, since they lead to a hands-off approach where a team of experts is brought in to figure things out. Meanwhile the executives are not clear on what’s going on, and are not sure if anything will come out of it.

From the view of a non-expert, here are some basic things that can help a business leader to start understanding what data science is, how it works, and what it can do. Obviously, there is a lot more detail, which is often covered in “data science for executives” courses, and business leaders would do well to educate themselves on the subject.

 

Key points include:

  • Making predictions from patterns
  • Analytics – past and future
  • Business objectives

 

Read the full article, Managing data science initiatives to get business results, on VeridiaConsulting.com.