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In the production of capital and consumer goods, human improvement teams are challenged with optimizing value creation while ensuring resource efficiency. The established method of value stream analysis and design, rooted in lean management, has evolved to include material flow cost accounting, information logistics, and external influencing factors. These expansions significantly increased data complexity, rendering traditional pen-and-paper approaches impractical. While existing research emphasizes analyzing current value streams using real-time data and ad-hoc optimization, structured methods for value stream design and implementation strategies remain underdeveloped. To address this gap, this chapter utilizes a novel engineering and management approach—the CRISP-DM-based gamification framework. Building on this framework, a socio-technical simulation game named “North Star—The Value Stream Game” was developed, validated, and deployed, emphasizing interaction between humans and digital systems. The simulation game supports human improvement teams across both initial education and professional development, facilitating knowledge acquisition, practical skills development, and enhanced self-assessed competence. Participants can progress through defined levels of mastery from foundational understanding (level 1) to training proficiency (level 5). Furthermore, integrating large multimodal models (LMMs) enables interactive collaboration between humans and digital systems within the simulation game. Empirical results confirm the educational effectiveness of combining gamification, CRISP-DM, and LMMs, significantly reducing complexity barriers in value stream analysis and design after just one intervention. Statistically significant improvements were observed in knowledge acquisition (p = 0.002), practical skills development (p < 0.001), and self-assessed competence (p = 0.038). Findings highlight the potential of socio-technical simulation games for teaching complex methods like value stream analysis and design in a resource-constrained world.

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Large Multimodal Model-Based Simulation Game as a Socio-Technical System for Value Stream Analysis and Design

  • 章节

  • 发表日期：

    2026年

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  • Mick Geisthardt,
  • Lutz Engel,
  • Jorge Marx Gómez

摘要

In the production of capital and consumer goods, human improvement teams are challenged with optimizing value creation while ensuring resource efficiency. The established method of value stream analysis and design, rooted in lean management, has evolved to include material flow cost accounting, information logistics, and external influencing factors. These expansions significantly increased data complexity, rendering traditional pen-and-paper approaches impractical. While existing research emphasizes analyzing current value streams using real-time data and ad-hoc optimization, structured methods for value stream design and implementation strategies remain underdeveloped. To address this gap, this chapter utilizes a novel engineering and management approach—the CRISP-DM-based gamification framework. Building on this framework, a socio-technical simulation game named “North Star—The Value Stream Game” was developed, validated, and deployed, emphasizing interaction between humans and digital systems. The simulation game supports human improvement teams across both initial education and professional development, facilitating knowledge acquisition, practical skills development, and enhanced self-assessed competence. Participants can progress through defined levels of mastery from foundational understanding (level 1) to training proficiency (level 5). Furthermore, integrating large multimodal models (LMMs) enables interactive collaboration between humans and digital systems within the simulation game. Empirical results confirm the educational effectiveness of combining gamification, CRISP-DM, and LMMs, significantly reducing complexity barriers in value stream analysis and design after just one intervention. Statistically significant improvements were observed in knowledge acquisition (p = 0.002), practical skills development (p < 0.001), and self-assessed competence (p = 0.038). Findings highlight the potential of socio-technical simulation games for teaching complex methods like value stream analysis and design in a resource-constrained world.