Genba Scientist: The Yamaha Case

Young Won Park () and Hiroki Kikuchi
Additional contact information
Young Won Park: Saitama University, Graduate School of Humanities & Social Sciences
Hiroki Kikuchi: Saitama University, Graduate School of Humanities & Social Sciences

Chapter 12 in Analog–Digital Transformation Strategy, 2026, pp 279-305 from Springer

Abstract: Abstract This chapter examines Yamaha Motor’s “Genba Scientist” initiative as a representative case of Analog–Digital Transformation (ADX) emerging from the production floor. Rather than implementing digital transformation through centralized IT departments or external consultants, Yamaha developed a hybrid organizational role that integrates tacit shop-floor expertise with data analytics capabilities. Genba Scientists are experienced production professionals who combine deep process knowledge with scientific and analytical methods to address operational problems. By embedding digital tools directly within production routines, Yamaha transforms digitalization from a technology-driven project into an organizational capability rooted in practice-based learning. The initiative reflects the idea that digital technologies gain meaning and effectiveness only when interpreted through experiential knowledge accumulated on the shop floor. The case demonstrates how frontline actors can translate operational experience into analyzable data structures and convert digital insights into actionable improvements. Through this hybrid role, Yamaha institutionalizes continuous learning cycles that connect analog craftsmanship and digital intelligence, illustrating how ADX emerges through co-evolution between human capability and digital infrastructure.

Keywords: Genba Scientist; Shop-floor innovation; Tacit knowledge; Data-driven experimentation; Hybrid capability (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-92-0937-8_12

Ordering information: This item can be ordered from
http://www.springer.com/9789819209378

DOI: 10.1007/978-981-92-0937-8_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().