How to earn an A in Data Science

Data is changing the world, and it’s happening rapidly.

The IBM Center for Applied Insights has studied this revolution through a series of experiments. The goal of this data revolution? To capture the transformative power of data and analytics to make smarter, quicker and more analytically informed decisions. For our first test, we examined a new role emerging in the c-suite: the chief data officer (CDO). Through our observations, we concluded that when it comes to emerging roles, like that of the CDO, one of the few constants is change. CDOs are assembling their organizations around an enterprise-wide data strategy, activating the use of data in new ways, and building more data-driven cultures.

In a subsequent experiment, we sought to detect the catalysts for creating value through data in organizations led by these highly skilled data leaders. We discovered that, by controlling three variables (making data a priority, developing from within, and freeing all the data), companies steered by data leaders were able to yield value.

Like any good scientist, we followed up with one last test. This time, we aimed to discover a success formula for effectively integrating a data science capability within organizations.

We began our experiment by interviewing data scientists and their executive colleagues about their business case for investing in a data science capability. In the words of one data scientist in the media industry, “When you ask me what the value of data science is, it’s almost like explaining the value of water to a fish.” Others alluded to their data science capability as being a fundamental element for the organization to be competitive and differentiated in the future.

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These in-depth interviews highlighted common themes, confirming our hypothesis:

Leading firms are integrating data science capabilities within their organizations to capture the untapped potential of data science as a source for competitive advantage. Yet, many enterprises are challenged to successfully integrate a data science capability for sustained value and to measure its value for the organization.

In our final report, Breakthrough experiments in data science: Practical lessons for success, we share several accounts of real business impact generated by data science. As predicted, we found that enterprises implementing these capabilities are observing business benefits from increased revenue to improved efficiency and effectiveness. Although it isn’t always easy, these wins build credibility and drive demand for greater capacity.

What is their formula for success?

Each organization has found a substantial way to infuse data science into culture, design a data science capability, equip with the right technology, and showcase results.

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In the coming months, the team and I will examine these topics in more detail.

Check out the full report for more of these organizations’ stories and recommended actions.

For related research from the IBM Center for Applied Insights, visit the CDO Insights page.

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