Archive for the ‘Experimental Enterprise’ Category

Q&A: On Being Data-Driven

The best way to spread data-driven thinking through an organization is by proving that you can use data to solve a real business problem.

Managing Uncertainty

Being data-driven is the best way to manage uncertainty—but achieving that is about far more than bringing a bunch of numbers to your latest meeting.

connecting data science and business puzzle pieces

Merging Data Science and Business

Business leaders cannot afford to ignore their organization’s data—rather, that data should be used to make informed decisions. In this post, Principal Data Scientist Tom Fawcett and Professor of Data Science Foster Provost discuss how businesses can make the most of their analytical teams. Tom and Foster are the authors of Data Science for Business. What aspect […]

Becoming Data-Driven: A Conversation with Sanjay Mathur

Making truly data-driven decisions can be a daunting task. Learn the first steps businesses can take, and why the effort is worthwhile.

Building a Data-Driven Culture

By far the most difficult thing in being data-driven is getting the right data in the first place.

How to Grow Your Data Capital

How to Grow Your Data Capital

The ability to generate future potential through operating your current business is the ultimate definition of what it means to be data-driven: when value, and not solely decision-making, is being driven by data.

Ways the C-Suite Can Embrace Failure

Three Ways the C-Suite Can Embrace (Gulp) Failure

You can’t avoid failure, but you can learn to cope and make the most of it.

butterfly cocoon maturity

How Mature Are Your Data Capabilities?

In a previous post on data maturity, we discussed a company that was just embarking on a transformation: launching a new services business and building data capabilities to support that business. But what if you’re not starting from the beginning?

Measuring tape

Understanding Your Data Maturity

No two situations are the same, but we have found one truism: making a data transformation successful requires much more than simply getting the technology right.