Marco Antonio Pereira Querol, Renata Matsmoto

Formation of planning groups and data collection in a Change Laboratory

Introduction

Formation of planning groups and data collection in a change laboratory. Learn Change Laboratory (CL) planning strategies: forming strategic, methodological, and operational groups, and collecting mirror data to foster expansive and sustainable learning.

Abstract

This article discusses strategies for planning a Change Laboratory (CL), with a focus on the formation of planning groups and the collection of mirror data. Planning is organized into three levels: (i) strategic, composed of researchers and decision makers, which aligns the intervention with organizational objectives; (ii) methodological, bringing together experienced and novice researchers, with an emphasis on method and peer learning; and (iii) operational, which involves researchers and participants in reflecting on the sessions and adapting the actions to practice. As for data collection, different methods can be used, such as interviews, shadowing, field visits and participant observation, in addition to workshop records, documents, questionnaires, videos, or the collection carried out by the participants themselves. Mirror data, by reflecting the reality of the activity, is fundamental to fostering discussions and promoting expansive learning. It is concluded that the methodological and operational groups strengthen the sustainability of learning, allowing their continuity beyond the sessions.

Review

This article presents a valuable contribution to the practice and theory of Change Laboratory (CL) interventions, specifically by articulating a structured approach to planning and data collection. The delineation of planning into three distinct levels – strategic, methodological, and operational – offers a clear and practical framework for researchers and practitioners. The emphasis on the composition and purpose of each group, from aligning interventions with organizational objectives to fostering peer learning and adapting actions to practice, highlights a comprehensive and stakeholder-inclusive planning strategy crucial for the success and embeddedness of CL processes within complex organizational settings. This multi-level grouping approach, particularly the integration of researchers, decision-makers, and participants, provides a robust model for managing the intricacies of CL design and implementation. A significant strength of the article lies in its thorough discussion of data collection methods, underscoring the critical role of "mirror data." The broad array of proposed methods, including interviews, shadowing, field visits, and various forms of documentation and participant-collected data, demonstrates a commitment to capturing the multifaceted reality of the activity under scrutiny. The conceptualization of mirror data as fundamental to fostering discussions and promoting expansive learning is particularly insightful. By reflecting the actual dynamics and challenges, mirror data moves beyond mere information gathering to become an active catalyst for critical reflection and the co-construction of new solutions, aligning perfectly with the core principles of expansive learning theory central to the Change Laboratory methodology. Overall, this article offers a highly relevant and well-structured set of strategies for enhancing the effectiveness and sustainability of Change Laboratory interventions. The authors' conclusion regarding how methodological and operational groups strengthen the continuity of learning beyond the immediate sessions points to a profound understanding of long-term organizational development. While the abstract presents a robust conceptual framework, a full-length article detailing empirical examples of these strategies in action, including potential challenges encountered and solutions developed, would undoubtedly further enrich its practical utility. Nevertheless, this work provides an essential conceptual foundation for scholars and practitioners aiming to design and execute impactful Change Laboratory processes.

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