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Episode 4: How to Build an Experimentation Machine and Where Most Go Wrong

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Manage episode 450107842 series 3615441
Content provided by Delphina. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Delphina or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.

Ramesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the risk aversion trap, the importance of learning from negative results, and how generative AI is reshaping the experimentation landscape.

We also talk about common failure modes and the types of things you're probably doing wrong, along with strategies to avoid these pitfalls. Plus, we discussed the role of incentives, the necessity of data driven decision making, and what it means to experiment in high stakes environments.

  continue reading

16 episodes

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iconShare
 
Manage episode 450107842 series 3615441
Content provided by Delphina. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Delphina or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Ramesh Johari (Stanford, Uber, Airbnb, and more) explores the art and science of online experimentation, especially in the context of marketplaces and tech companies.

Ramesh shares insights on how organizations evolve from basic experimentation practices to becoming fast, adaptive, and self learning organizations. We dive into challenges like the risk aversion trap, the importance of learning from negative results, and how generative AI is reshaping the experimentation landscape.

We also talk about common failure modes and the types of things you're probably doing wrong, along with strategies to avoid these pitfalls. Plus, we discussed the role of incentives, the necessity of data driven decision making, and what it means to experiment in high stakes environments.

  continue reading

16 episodes

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