How to Make Data Experiments Powerful

Easy Implementation Steps for Analytics Project Management

This article provides two clear examples of how managers can move their projects and organizations to become data-savvy organizations. The fun of this Analytics article is that an example is from an industry that you wouldn’t think of being open to IOT and Big Data!


Experimentation is powerful when it deepens managerial intuition. The first example asks teams to runs lots of tests and to ask how each one impacts the organizations key performance indicators (KPI’s.)  So the team has to look at all the “touchpoints, the task completion, metrics, more deeply than have they had in the past. Managers can quickly test their insights, either validating their thinking or sending them back to think more, then swiftly bring changes to scale.This really changes the team culture and how they look at analytics.


Experimentation is powerful when the organization has unique data. The next example looks at a laundry operations that has a unique set of data and opportunities for introduction of IOT to collect data. “This organization has made it easy, both technically and culturally, for managers to test ideas and learn from them.”


This is an easy read and a big win for project managers looking for examples of how to implement Analytics Projects.

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