Executive Summary

Mônica Alessandra Guerios; Maria do Carmo Assis Todorov

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Architecture and urbanism are configured as essential bases in an increasingly complex and challenging urban space, where the intrinsic connection between social, environmental, and technological issues demands robust and strategic planning. Large-scale architectural projects, in particular, face significant challenges in reconciling multiple interests, which can generate conflicts and negatively impact the final outcome. The ability to efficiently manage stakeholders emerges as a critical factor for the success of these ventures. The Project Management Institute (PMI, 2021) defines stakeholders as individuals, groups, or organizations that can affect, be affected by, or perceive themselves to be affected by a decision, activity, or project outcome. Stakeholder theory, introduced by Freeman (1984), revolutionized management by postulating that organizations and projects must consider the interests of all involved, not just shareholders or financiers. However, the identification, analysis, prioritization, and effective engagement of these multiple agents, considering strategic, communicational, normative, and technological aspects, remains a complex challenge.

To mitigate this impasse, Mitchell et al. (1997) proposed a stakeholder primacy model based on three criteria: power, legitimacy, and urgency. This model allows managers to define more effective engagement strategies, focusing on priorities that align with project planning and promoting common objectives among stakeholders. In large-scale architectural projects, this approach is even more crucial due to the direct interactions between architectural knowledge, legal (public bodies), technical (various areas and complexities), social (impact on users and surroundings), and environmental aspects. Furthermore, monitoring and using data for future interactions and prospective scenarios are essential (Turner, 2016). A practical example of this complexity is lot condominiums, or farm-like developments, which have experienced remarkable expansion in Brazil and globally after the 2019 pandemic. These projects, which seek to connect nature with urban amenities (Silva, 2023), often incorporate complex complementary projects, such as advanced security systems and specific automations, increasing the number of decisions and the weight of each one (Olander, 2007). A management that mediates and connects these groups is, therefore, indispensable to minimize risks, align divergent expectations, and ensure execution viability.

In this context, the Design Science Research (DSR) approach presents itself as a promising methodology. Aken (2004) states that by exploring new action-oriented solutions, the researcher assumes a participatory role. DSR aims to generate knowledge about how to act in relation to a problem (Dresch, Lacerda, and Antunes Júnior, 2015), meaning, through the information and data collected, the creation of an artifact, such as a framework, is sought to mitigate the problem. The International Organization for Standardization (ISO 21502, 2020) also emphasizes the importance of adapting practices and processes to the specific context of the project, considering factors such as size, complexity, available resources, and organizational environment. Complementarily, the Agile Methodology, with its phases called Sprints (Schwaber and Sutherland, 2020), offers agility and continuous artifact verification, setting the pace for joint decision-making. The combination of these tools allows for the inclusion and connection of practical issues, specific plans, and distinct agents. The intrinsic pragmatism of DSR, aligned with the flexibility of SCRUM, offers a robust epistemological basis for the development of an innovative solution in the management of large-scale architectural projects. Bearing in mind the exposed scenario, the general objective of this work is to analyze the challenges related to change management in large-scale architectural projects and to develop a structured framework, based on the DSR approach and the agile SCRUM methodology, that contributes to the reduction of rework, the alignment of decisions, and the improvement of communication among stakeholders. The specific objectives include identifying the main obstacles in change management based on the analysis of a real case study, mapping the perceptions of professionals working in different project phases regarding communication, demand alignment, and scope validation, structuring a prototype based on DSR and SCRUM, aimed at conflict mitigation and project review organization, and simulating the application of the *framework* in a fictitious environment to evaluate its functionality, clarity, and replicability potential.

To assist change management in large-scale projects in Architecture, the qualitative methodological approach Design Science Research (DSR) was chosen. The choice of DSR was motivated by its prescriptive and practical problem-solving orientation, which distinguishes it from purely descriptive or explanatory methodologies. DSR not only investigates a phenomenon but also proposes and builds an artifact that aims to solve a real problem, which was fundamental for the development of an applicable *framework*. After reviewing specialized literature, the need for an instrument that connected to the temporal dimension of projects, capable of traversing intermediate phases, such as meetings and validations, collecting clear information, particular elements, and continuous evaluations, was identified. The agile SCRUM method proved ideal for complementing DSR, providing the essential characteristics for the iterative process of artifact creation, testing, and validation. DSR literature raised questions about the practicality of a tool that could encompass the complexity of changes without rigidifying processes. The tool would need to adapt to different project stages, sometimes requiring agility, sometimes respecting maturation time, as in physical-financial studies and market analyses.

The context for the implementation of the *framework* was the project of a lot condominium located in the southern region of Brazil. This instrumental case study was chosen for its representativeness in large-scale projects involving a complex network of *stakeholders* and change management challenges. Situated in an urban area close to a rural area, the project is influenced by a land-related culture, with small producers and extensive grain plantations, creating a scenario of complexity and contradiction among the involved *stakeholders*. The main concerns identified in this environment included aligning expectations among partners, suppliers, and designers, lack of clear and objective communication, changes resulting from personal tastes and project references, misunderstanding of the architectural project stages and other complementary projects, incompatible schedules, inconsistent deliveries, and lack of technical knowledge about appropriate tools.

Multiple *stakeholders* from various technical areas were involved, such as foundation engineers, structural (concrete, steel, and wood), electrical, sanitary, occupational safety, air conditioning, landscaping, irrigation, lighting, consultants for industrial kitchens, window frames, swimming pools, *playgrounds*, sports and wellness areas, as well as urban infrastructure projects. A specialized company acted as the manager of all projects, reconciling them with the architectural project, generating reports of findings, and acting as the project’s *Scrum Master*.

To gather the necessary information for the *Product Backlog*, *Sprint Backlog*, *Sprints*, and *Sprint Retrospective*, and for the table’s elaboration, a mapping of general themes was carried out, based on the main difficulties and observations raised in the study’s introduction. Bardin’s (2011) methodology was employed for qualitative content analysis, allowing information to be organized into groups under a predetermined classification. This approach facilitated the acquisition of clear and in-depth data for interpretation. Additionally, the Likert Scale (1932) was used in some questions to measure favorable or unfavorable viewpoints in affirmative sentences, offering a gradation that represented the complexity of opinions, avoiding dichotomies.

Based on the principles of mutual exclusion, relevance, homogeneity, productivity, and fidelity by Bardin (2011), six analysis categories were created: Category 1 – Obstacles in Change Management, to identify recurring obstacles in complex projects; Category 2 – Communication among *Stakeholders*, to map common communication problems; Category 3 – Alignment of Demands, to understand preferences for information validation and expectations; Category 4 – Priorities by Project Stage, to clarify what each *stakeholder* considers most critical; Category 5 – Willingness to participate in the validation of the *framework*, to identify potential testers; and Category 6 – Essential qualities of a good change management tool, to collect data on expected functionalities.

Strategic questions were elaborated from these groups and applied via an online form (Appendix 1) to 11 participants, between June 8 and 17, 2025. In parallel, a flowchart was developed comparing concepts and connections between DSR and SCRUM to facilitate visualization and identify synergies. The combination of the DSR and SCRUM methodological base with the field research results allowed for the analysis of the needs, desires, demands, and recurring bottlenecks of those involved. As a result, a Large-Scale Architecture Change Management Table was developed, designed to be easily accessible, intuitive, with extensive bibliography and audiovisual support resources, low implementation cost, and adaptable to innovations. A fundamental requirement was the creation of a replicable and organized workflow, ensuring continuous alignment among *stakeholders*, mitigating communication noise, and meeting the demands of each project stage. While SCRUM makes the process adaptable, DSR brings innovation with scientific rigor. The Change Management Table was based on the first four categories of Bardin (2011). For the dimensions of Analysis and Communication, fundamental in DSR theory, and for categories 5 and 6, an “Evaluation Indicators” tab was created in the same table, with quantitative indicators (objective metrics) and qualitative indicators ( *stakeholder* perceptions). The five categories of indicators were: a) Process Efficiency, b) Impact on Costs and Deadlines, c) Technical and Design Quality, d) *Stakeholder* Satisfaction, and e) Strategic. With this section, the table transcends its function as a repository, becoming an instrument for analysis and continuous improvement.

The first significant result consisted of the creation of a macrostructure that establishes the association between the phases of Design Science Research (DSR) and the stages of SCRUM. This structure, presented in detail, clarifies the points of intersection between the methodologies, facilitating conceptual comparison and the identification of new synergies. For example, the Problem Identification phase in DSR, which seeks to identify obstacles in change management in complex architectural projects, finds a direct parallel with the alignment meetings and initial requirements gathering of SCRUM’s Sprint Zero. This synergy is fundamental, as it allows the in-depth understanding of the problem, characteristic of DSR, to be immediately translated into a backlog of prioritized requirements, as advocated by Pinto and Slevin (1987) for project success. The Design and Development phase of DSR, focused on artifact conception, is intrinsically linked to SCRUM’s iterative Sprints, where the planning, development, and review of the *framework* occur in short, continuous cycles. This iterative approach, according to Schwaber and Sutherland (2020), allows for the adaptation and refinement of the artifact in response to continuous *feedback*.

The adaptation of SCRUM elements to the case study context was equally crucial, identifying specific roles, cycles, and practices. The *Product Owner* was translated as the client or representative of the project’s main interest, while the *Scrum Master* assumed the role of process facilitator or project manager. The *Development Team* comprised architects, engineers, technicians, and consultants. The *Product Backlog* became the list of requirements and issues identified in communication and change management, and the *Sprint Backlog* the selection of priority items for each work cycle. *Sprints* were defined as short development cycles, lasting one week per stage of the *framework*. *Daily Meetings* were adapted to brief meetings or logs for progress alignment. The *Sprint Review* consisted of the presentation and partial validation of the *framework* to a simulation group of *stakeholders*, and the *Sprint Retrospective* allowed for reflection and adjustments after each test round or tool review. This translation of SCRUM elements to the architectural context demonstrates the methodology’s flexibility and its ability to integrate with *Design Science Research* processes.

Quantitative data obtained through the questionnaire revealed a demographic profile of the participants, with 54.5% men and 72.7% in the 26 to 35 age range. This predominance of young male professionals in the sample suggests familiarity with agile technologies and methodologies, which may influence the acceptance and adaptability of new management tools, as observed by Schwaber and Sutherland (2020) who highlight the importance of an agile mindset for SCRUM’s effectiveness. In terms of academic background, 54.5% held postgraduate degrees, 36.4% a degree in Architecture, and 27.3% in Engineering, indicating a high level of qualification and specialization. Professionally, 45.5% held the position of analyst, followed by coordinators with 18.2%, and 45.5% directly served as project managers. The team size distribution was balanced, with 36.4% working in groups of up to five collaborators and another 36.4% in teams of six to ten professionals. Active experience in project management was reported by 81.8% of analysts, with most having between one and five years of experience in the field.

The revalidation of demands among designers was considered more adequate in the Preliminary Design stage by 30% of respondents, or after a change of stage or important decision. This data underscores the volatility and criticality of the Preliminary Design phase, where initial definitions are frequently revised. The Construction/Execution stage was identified by 72.7% of respondents as the moment of greatest communication noise, followed by the Preliminary Design stage with 18.2%. This finding corroborates the need for a *framework* that mitigates communication problems in critical project phases, where decisions have immediate practical and financial implications. The documentation of decisions was predominantly carried out via meeting minutes and/or formal documents (36.4%) and emails (36.4%), evidencing the use of traditional resources that may be insufficient for the complexity of large-scale projects. Acceptance to participate in *framework* testing was mixed, with 45.5% indicating “maybe”, 27.3% “yes”, and 27.3% “no”, suggesting the need to clearly demonstrate the tool’s benefits to ensure its adoption.

Qualitative responses, analyzed based on Bardin’s (2011) categories and Likert’s (1932) scale, provided in-depth *insights*. In Category 1, “Obstacles in Change Management”, it became evident that the greatest noise occurs in the Construction/Execution and Preliminary Design stages, mainly related to communication and prioritization. The majority of participants agreed that change management is one of the biggest challenges in their projects. The reliance on traditional resources to document important decisions and communicate them to others, even among a young professional population, indicates a gap in the adoption of more efficient tools. The perception that, in Preliminary Design or in case of significant scope change, all involved parties should be communicated as quickly as possible, reinforces the need for an agile and comprehensive communication system. The lack of clarity regarding the impact of changes on other project disciplines and the difficulty in tracking the history of decisions were points of high agreement, which leads to rework and misalignment, as pointed out by Olander (2007) on the weight of decisions in complex projects.

In Category 2, “Stakeholder Communication”, communication was identified as a crucial point. The statements sought to understand the fluidity and obstacles, the channels used, and the existence of technical problems. Most agreed that the absence of clear communication negatively impacts project compatibility, and that messages exchanged through informal channels frequently generate ambiguous interpretations or conflicts. This finding highlights the importance of formal and structured communication channels, such as those proposed by the framework, which aim to mitigate noise and ensure clarity of information. The need for well-defined communication routines among project participants and the active participation of those responsible for strategic decisions in alignment meetings were widely endorsed, aligning with effective project communication guidelines (PMI, 2021; Rosenberg, 2006).

Category 3, “Demand Alignment”, focused on understanding stakeholder preferences for validating information and expectations. The preliminary design and preliminary study stages were identified as moments of greatest volume of conversations and potential noise. There was strong agreement on the usefulness of periodic checkpoints for revalidating demands and that the lack of confirmation between stages generates rework and misalignment. This suggests that the current process lacks formal mechanisms for continuous validation, which the framework seeks to address through its iterations and reviews. The perception that the scope of each discipline is not always well-defined from the outset and that decisions are not always formally recorded reinforces the need for a robust documentation and alignment system.

In Category 4, “Priorities by Project Stage”, the statements aimed to identify the most critical moments in each stage. The idea of having clear milestones, in addition to the official stages, to understand the real demands of the large-scale project agents was shared by all. For example, most agreed that the preliminary design should focus on the compatibility between complementary projects and issue the last compatible version of all project general plans. This highlights the importance of an integrated and collaborative approach from the initial phases, where compatibility decisions have a significant impact on subsequent costs and deadlines. The need for the Executive Project to contain a report with the record of pending issues and responsibilities, and the last information validated by all designers in situations of scope change, points to the lack of formalization and traceability in the final stages.

The construction of the artifact, the Change Management Table, began with mapping basic information such as client name, project typology and name, client code, table start and last update dates, and estimated project launch date. The main stakeholders were identified, including the architectural project, the Scrum Master, the Product Owner, and the main development team, responsible for the complementary projects. All names used are fictitious to preserve the identity of the participants. The relationship of the DSR phases with the change request information was organized in columns, following the order of the DSR phases. In phase 1, “Problem Identification”, a column was dedicated to an alphanumeric identifier code for each change request, facilitating documentary traceability and historical control, fundamental aspects in complex projects with intense information flow (ISO 10006, 2018). The “source” column recorded the institutional agent and the direct requester, formalizing the origin of the demand, a critical control factor for project success (Pinto and Slevin, 1987). The “direct impact” identified the project and/or space affected, classifying it according to the project stage (Feasibility Study, Preliminary Study, Preliminary Design, Executive Design, Construction Permit), associating the alteration with the project’s maturity and the complexity of rework. “Indirect Impacts” clarified which other projects would be affected, including revisions, contractual adjustments, and new compatibilizations. The “Reason” field summarized the reasons for the request, serving as a guide for dialogue and social validation, bridging technical, organizational, and usage perceptions.

For phase 3, “Development,” the table included “Request Date” and “Analysis Completion/Submission to Development,” ensuring temporal control of the process and reinforcing the cadence and predictability of agile methods. “Priority” established a hierarchy of treatment, distinguishing low-priority demands (postponed/discarded) from high-priority ones (which would prevent project advancement), preventing overload and aiding in resource management. Assignment to the “Development Team” designated specific professionals, conferring clarity on competencies and avoiding misinformation. The “Estimated Deadline” projected the time needed to resolve the request, and the “Resolution Date” formalized the cycle’s closure with the effective delivery of revised files. “Status” categorized the request’s stage (Implemented, Under analysis, Rejected), with rejection being part of the iterative process of artifact construction and refinement, according to DSR guidelines. Examples of requests were presented for each project phase.

The Change Management Table also incorporated an “Evaluation Indicators” section in phase 5, with quantitative and qualitative indicators. Quantitative indicators included “Scrum Master Analysis Time” (working days), “Implementation Time” (working days), “Cost Impact” (%), “Schedule Impact” (days), “Rework due to poorly defined/late changes” (%), “Changes that improved the product” (number of requests), “Clarity of communication in changes” (yes/no), “Customer Satisfaction” (scale 1-5), “Unplanned but necessary changes” (%) and “Change success rate” (%). Qualitative indicators covered “Stage with most change requests” (Preliminary Design with 92%), “Change traceability index” (%), “Accumulated cost of all changes” (%), “Changes that generated positive cost impact” (80%), “Number of reworks generated by poorly specified changes” (0%), “Corrective changes rate” (40%), “Changes understood as value-adding by end-users” (20%), “Stakeholders participating in the decision-making process” (100%), “Changes aligned with the original architectural concept” (85%) and “Process maturity index” (87%).

In the “Process Efficiency” dimension, indicating the stage at which the request was made revealed the volatility of the Preliminary Design, where procedural changes and lack of product clarity occur. The “Change traceability index” informed the percentage of documented requests, crucial for historical control. In the “Cost and Schedule Impact” category, the “Accumulated cost of all changes” and “Changes that generated positive cost impact” (80%) are vital information for the venture’s viability, requiring specialized mapping of the physical-financial impact. For the “Technical and Design Quality” dimension, the “Rework rate generated by poorly specified changes” (0%) and the “Corrective changes rate” (40%) focused on mapping ambiguities and alterations that generate revisions, distinguishing failures from planned improvements. In the “Stakeholder Satisfaction” category, “Changes understood as value-adding by end-users” (20%) and stakeholder participation in the decision-making process (100%) reinforce the collaborative perspective. Finally, the “Strategic” indicators included “Changes aligned with the original architectural concept” (85%) and “Process maturity index” (87%), measuring the coherence of the changes with the initial vision and evaluating the team’s deliberative evolution, fundamental parameters for sustainable organizational growth.

The framework validation was carried out in a simulated environment, with the accompaniment of three volunteers, due to the exploratory nature of the research and the available time. For six weeks, the table was made available via a Google Docs link and discussed analytically. The contributions highlighted the order of information, what should be collected immediately, possible improvements, and adaptations to the project typology. It became clear that the indicators should be grouped in a separate tab, but in the same table, with restricted access by password. The table itself, by synthesizing information, attenuated communication noise. The feedbacks from stakeholders and the researcher’s analysis highlighted the importance of detailed technical briefings, discussed and reviewed at each stage of the project, correlating it with hiring, information, organization, and communication requirements to avoid stoppages. In long-term projects, the discontinuity of components (e.g., tableware and fixtures) in preliminary phases is common, requiring a review of specifications. The need for a physical-financial project that accompanies the architectural project from the Feasibility Study stage, with equivalent reviews at each stage advancement, was endorsed to foresee risks of financial infeasibility and anticipate implementation difficulties. The social interactions generated by the use of the table revealed the importance of the marketing, product, and financial areas in capturing information for the indicators, especially quantitative ones, to measure the financial and product conception development throughout the process of adapting intervention requests. To improve this continuous interaction, initial tests revealed that using the table can reduce communication noise and facilitate alignment among the multiple stakeholders involved. From the perspective of Nonviolent Communication (NVC), proposed by Rosenberg (2006), the structured recording of requests allows the needs underlying each request to be explicitly stated objectively, avoiding judgments or subjective interpretations that could generate conflicts. By clearly separating facts (request and impact), feelings and needs (reason for the change), and concrete requests (status and priority), the table acts as a mediator, fostering more empathetic and collaborative dialogue. Finally, the formalization of demands through the table functions as a tool for metacommunication, allowing the group to reflect not only on the content of the request but also on how the dialogue is being conducted. This approach favors the creation of an environment of mutual trust, a condition highlighted by Lencioni (2002) as essential for the effectiveness of high-performance teams.

It is concluded that the objective was achieved with the development of a framework that integrates Design Science Research and SCRUM, offering a clear, adaptable, and practical solution for change management in large-scale architectural projects. The framework demonstrated potential to facilitate information diffusion, provide a basic plan for change management, and support financial and technical observations, serving as a starting point for validation in real contexts. The specific objectives of identifying bottlenecks, mapping perceptions, structuring the prototype, and simulating its application were fully achieved. The proposed methodological approach, with its governance, communication, and management of stakeholder interests, contributes to conflict mitigation, rework reduction, and decision alignment, promoting success and minimizing challenges in project implementation.

Bibliographic References:

Aken, J. E. 2004. Management research based on the paradigm of the design sciences: The quest for field-tested and grounded technological rules. Journal of Management Studies, 41(2), 219-246. Disponível em: https://doi.org/10.1111/j.1467-6486.2004.00430.x. Acesso em: 25 de mar. 2025.

Bardin, L. 2011. Análise de conteúdo (L. A. Reto & A. Pinheiro, Trads.; 3ª ed.). Edições 70.

Dresch, A., Lacerda, D. P., Antunes Júnior, J. A. V. 2015. Design science research: Método de pesquisa para avanço da ciência e tecnologia. Bookman.

Freeman, R. E. 1984. Strategic management: A stakeholder approach. Pitman Publishing.

International Organization for Standardization (ISO). 2018. ISO 10006:2018 – Quality management – Guidelines for quality management in projects. ISO.

International Organization for Standardization (ISO). 2020. ISO 21502:2020 Project, programme and portfolio management Guidance for project management. ISO.

Lencioni, P. (2002). Os cinco desafios das equipes: Uma fábula sobre liderança. Rio de Janeiro: Sextante.

Likert, R. 1932. A technique for the measurement of attitudes. Archives of Psychology, 140, 1-55.

Mitchell, R. K., Agle, B. R., Wood, D. J. 1997. Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts. Academy of Management Review, 22(4), 853-886.

Olander, S. 2007. Stakeholder impact analysis in construction project management. Construction Management and Economics, 25(3), 277–287. Disponível em: https://doi.org/10.1080/01446190600879125. Acesso em: 25 de mar. 2025.

Pinto, J. K., & Slevin, D. P. (1987). Critical factors in successful project implementation. IEEE Transactions on Engineering Management, EM-34(1), 22–27. https://doi.org/10.1109/TEM.1987.6498856

Project Management Institute (PMI). 2021. Um Guia do Conhecimento em Gerenciamento de Projetos (Guia PMBOK®) (7ed.). Project Management Institute.

Rosenberg, M. B. (2006). Comunicação não-violenta: Técnicas para aprimorar relacionamentos pessoais e profissionais (2ª ed.). São Paulo: Ágora.

Schwaber, K.; Sutherland, J. 2020. O Guia do Scrum. Disponível em: https://www.scrum.org/resources/scrum-guide. Acesso em: 31 de março de 2025.

Silva, J. D. 2023. A busca por mais qualidade de vida em cidades do interior proporcionando uma migração das grandes cidades como legado pós pandemia. Urban Systems – Blog. Disponível em: https://blog.urbansystems.com.br/a-busca-por-mais-qualidade-de-vida-em-cidades-do-interior-proporcionando-uma-migracao-das-grandes-cidades-como-legado-pos-pandemia/. Acesso em: 25 de mar. 2025.

Turner, R. K. 2016. Environmental economics: An introduction (2ed.). Routledge.

Executive summary from the Final Course Work of the Specialization in Project Management of the MBA USP/Esalq

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