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Six ways leaders can build organizational muscle through data analytics

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Professor Florian Zettelmeyer explains why hiring data scientists isn't enough; leaders must know the basics to make decisions.

Florian Zettelmeyer

Videos: Data analytics for leaders

Why those in charge must understand what their data experts are telling them


It's not enough to merely employ data scientists and ask them for conclusions, according to Professor Florian Zettelmeyer. Leaders must have enough of a basic understanding of the data and how it was collected in order to make sound decisions. Zettelmeyer, Faculty Director, Program on Data Analytics @ Kellogg, KMCI, recently hosted a session focusing on why it's critical for leaders to have a working knowledge of this growing field and how they can take obtain one.

Hitting home runs with data analytics
  • Oakland Athletics General Manager Billy Beane engineered baseball’s big data moment by combining a knowledge of data science with the courage to challenge conventional wisdom and try a new approach to putting together a team. But the available data wasn't new, nor were the tools to analyze them. What made the difference was Beane's unique understanding of a leader's role in data-driven decision making.
Stepping stones into data science
  • Leaders need a working knowledge of data science so that they can lead with confidence, recognize where analytics will add value and judge the data's quality.


Judging what "good" data looks like
  • Technology such as interconnected devices and remote monitoring (e.g. "The Internet of Things"), has made it easy to quickly collect data. Therefore, managers need to know what to do with data collections and apply them wisely.

How analytics adds value
  • The first step of an analytical investigation is to specify the question, and from there leaders can determine what kind of data will provide the answers.

How to confidently lead analytics
  • To be effective leaders, managers need a working knowledge of data science. Only then will they be able to lead highly technical teams of data scientists with confidence.