The Lean Startup Method: Early-stage teams and hypothesis-based probing of business ideas

Leatherbee, M. and Katila, R. (2020), The Lean Startup Method: Early‐Stage Teams And Hypothesis‐Based Probing Of Business Ideas. Strategic Entrepreneurship Journal. Accepted Author Manuscript. doi:10.1002/sej.1373

Posted: 23 Jan 2017 Last revised: 17 Oct 2020

See all articles by Michael Leatherbee

Michael Leatherbee

Pontificia Universidad Católica de Chile - Department of Industrial Engineering

Riitta Katila

Stanford University; Stanford University

Date Written: October 3, 2020

Abstract

We examine a learning-by-doing methodology for iteration of early-stage business ideas known as the “lean startup.” The purpose of this paper is to lay out and test the key assumptions of the method, examining one particularly relevant boundary condition: the composition of the startup team. Using unique and detailed longitudinal data on 152 NSF-supported lean-startup (I-Corps) teams, we find that the key components of the method—hypothesis formulation, probing, and business idea convergence—link up as expected. We also find that team composition is an important boundary condition: business-educated (MBA) members resist the use of the method, but appreciate its value ex-post. Formal training in learning-by-thinking methods thus appears to limit the spread of learning-by-doing methods. In this way, business theory constrains business practice.

Keywords: Lean startup method, hypothesis-based probing, business idea, young-firm teams, MBA education, learning-by-thinking, learning-by-doing

Suggested Citation

Leatherbee, Michael and Katila, Riitta, The Lean Startup Method: Early-stage teams and hypothesis-based probing of business ideas (October 3, 2020). Leatherbee, M. and Katila, R. (2020), The Lean Startup Method: Early‐Stage Teams And Hypothesis‐Based Probing Of Business Ideas. Strategic Entrepreneurship Journal. Accepted Author Manuscript. doi:10.1002/sej.1373, Available at SSRN: https://ssrn.com/abstract=2902869 or http://dx.doi.org/10.2139/ssrn.2902869

Michael Leatherbee (Contact Author)

Pontificia Universidad Católica de Chile - Department of Industrial Engineering ( email )

Av. Vicuna Mackenna 4860
Macul
Santiago
Chile

Riitta Katila

Stanford University ( email )

Stanford, CA 94305
United States

Stanford University ( email )

Stanford, CA 94305
United States

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