What We Actually Learn From Experience

Steven Callander has spent years building a mathematical framework to answer the question of how people learn from experience. “Here in Silicon Valley, the expression that you learn from failure is very widespread and very intuitive. But the question is… what do you learn? How do you optimally learn from that experience?”

In this episode, Callander, the Herbert Hoover Professor of Public and Private Management and Professor of Political Economy at Stanford Graduate School of Business, explains the hidden, deceptively simple logic of correlated learning — and it may change how you think about finding the right job, the right market, or the right strategy. 

“It fascinates me and I can't stop thinking about it,” he says.  

Has theory made an impact on your life? Tell us more at ifthenpod@stanford.edu.

Related Content:

• Steven Callander faculty profile
• How to Turn Old Ideas Into Creative Solutions to Modern Problems
• What We’re Still Learning from Silicon Valley’s Bank Collapse

Chapters:

00:00 Ann Miura-Ko on learning and the search for patterns in Venture capital

02:51 Introduction

05:23 What is correlated learning?

06:40 Where does this research apply in the real world?

09:28 Brownian Motion

12:45 Steven Callander’s Framework

15:25 Examples of correlated learning when seeking expert advice

20:53 Applying correlated learning

23:57 Why correlated learning research?

24:51 Conclusion

If/Then, from Stanford GSB, features conversations with faculty that explore how their research deepens our understanding of business and leadership.

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