Stefan H. Thomke

Experimentation Works

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Don't fly blind. See how the power of experiments works for you.
When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition, experience, and big data alone don't work. What does? Running disciplined business experiments. And what if companies roll out new products or introduce new customer experiences without running these experiments? They fly blind.
That's what Harvard Business School professor Stefan Thomke shows in this rigorously researched and eye-opening book. It guides you through best practices in business experimentation, illustrates how these practices work at leading companies, and answers some fundamental questions: What makes a good experiment? How do you test in online and brick-and-mortar businesses? In B2B and B2C? How do you build an experimentation culture? Also, best practice means running many experiments. Indeed, some hugely successful companies, such as Amazon, Booking.com, and Microsoft, run tens of thousands of controlled experiments annually, engaging millions of users. Thomke shows us how these and many other organizations prove that experimentation provides significant competitive advantage.
How can managers create this capability at their own companies? Essential is developing an experimentation organization that prizes the science of testing and puts the discipline of experimentation at the center of its innovation process. While it once took companies years to develop the tools for such large-scale experiments, advances in technology have put these tools at the fingertips of almost any business professional. By combining the power of software and the rigor of controlled experiments, today's managers can make better decisions, create magical customer experiences, and generate big financial returns.
Experimentation Works is your guidebook to a truly new way of thinking and innovating.
This book is currently unavailable
365 printed pages
Original publication
2020
Publication year
2020
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Quotes

  • oldmilkahas quoted7 months ago
    If you really want to understand the value of an experiment, just look at the difference between its expected outcome and its actual result. If you thought something was going to happen and it happened, then you haven’t learned much. If you thought something was going to happen and it didn’t, then you’ve learned something meaningful. And if you thought something minor was going to happen, and the results are a major surprise and lead to a breakthrough, you’ve learned something highly valuable
  • oldmilkahas quoted7 months ago
    Twyman’s law: “Any figure that looks interesting or different is usually wrong.”
  • oldmilkahas quoted7 months ago
    categorize the different levels of understanding causality, Judea Pearl and Dana Mackenzie propose a three-tier ladder in The Book of Why.19 The first and lowest causality tier, association, is about finding regularities in observations. One event is associated, or correlated, with another if observing one changes the likelihood of observing the other. The authors place modern-day analytics and big data in this tier. The second, intervention, requires changing one or more variables and observing changes in outcomes. Experiments are such interventions. The third and highest tier, counterfactuals, includes the strongest test of causality. Instead of just asking, “Did A cause B?” a higher standard includes the counterfactual, “Would B have occurred if not for A?”
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