Creating a Data-Driven Organization

Preface

Summary

In this book, I address two core questions:

• What does it mean for an organization to be data-driven?
• How does an organization get there?

Many organizations think that simply because they generate a lot of reports or have many dashboards, they are data-driven. Although those activities are part of what an organization does, they are typically backward-looking. That is, they are often a declaration of past or present facts without a great deal of context, without causal explanation of why something has or has not happened, and without recommendations of what to do next. In short, they state what happened but they are not prescriptive. As such, they have limited upside.

In contrast, consider more forward-looking analyses, such as predictive models that optimize ad spend, supply chain replenishment, or minimize customer churn. They involve answering the “why” questions—or more generally, “w-questions”: who, what, when, why, and where—making recommendations and predictions, and telling a story around the findings. They are frequently a key driver in a data-driven organization. Those insights and recommendations, if acted upon, have a huge potential impact upon the organization.

However, such insights require collecting the right data, that the data is trustworthy, the analysis is good, that the insights are considered in the decision, and that they drive concrete actions so the potential can be realized. Phew! I call this sequence—the flow from collection to final ...