17 From Noise to Narrative: How storytelling with project data builds trust, reduces rework, and enhances construction outcomes

Rationale for Studying the Case

Modern construction projects generate enormous volumes of data from 3D building models and schedules to safety logs and sustainability metrics yet teams often struggle to convert this “data noise” into actionable knowledge. Many projects operate with unclear benchmarks, fragmented systems, and communication silos, leading to confusion rather than clarity. Prior research from the book Building innovation by Neff and Dossick highlights a persistent tension, “Even as Building Information Modeling (BIM) and other “clean” technologies provide precise information, project teams still rely on informal, “messy” talk to make sense of complex issues.” In other words, data alone, no matter how abundant, does not guarantee shared understanding on a jobsite. This case study was undertaken to examine why this gap between data and meaning exists and how Virtual Design and Construction (VDC) practices can bridge it. By focusing on a real world VDC implementation, the study aims to illuminate how construction professionals turn raw data into a narrative that drives better coordination and decision making in practice.

Motivation for the Problem and Research Question

Despite the construction industry’s investments in digital tools, the motivation for this research stems from a simple observation: project data is only valuable if people can derive “meaning” from it. VDC teams are increasingly expected to serve as information architects and translators between technical data and project goals, yet there is limited guidance and research on how to do this effectively. Industry visionaries often engage in what Neff and Dossick call “futuring work,” telling optimistic stories about how new technologies will improve collaboration. However, realizing those promised benefits requires new practices for sensemaking on the ground. The central research question emerged through this reasoning trajectory:

“How do VDC teams effectively transform project data into meaningful narratives that enhance coordination and decision making?” 

Answering this question is important, not only to validate the intuitions of VDC professionals, but also to provide a roadmap for others seeking to harness data for better project outcomes. In short, this research is motivated by both a practical need, improving project performance through better data utilization and a scholarly need to understand the human processes that make technology work in construction.

Purpose of the Study

The study investigates storytelling techniques used in a VDC context to turn isolated facts and figures into a coherent project “story.” The underlying hypothesis is that project data becomes most meaningful, when it is framed around clear goals and audiences effectively, when data is presented as a story with context. Thus, the study set out to document what practices successful VDC teams employ to achieve this translation and why those practices work. By articulating these methods, the research expects to discuss effective strategies inculcated by VDC professionals for aligning technical information with the interests and decisions of diverse stakeholders. The ultimate goal is to contribute both theoretical insight and practical guidance by highlighting techniques that are applied currently on real projects.

Focus and Case Boundaries

This investigation focuses on a single in depth case within a digitally advanced construction environment, in order to observe data sensemaking processes in context. The case study is situated at GLY Construction, a general contractor known for its robust VDC program through Trevor Lunde who serves as Director of Virtual Design Construction and oversees the Digital Transformative Delivery Business Unit within GLY. Rather than evaluating any one software platform or BIM tool, the emphasis is on the “people and practices” behind the technology. The study homes in on how the project team interprets, utilizes, and communicates information through VDC during both planning and execution phases. Key areas of focus included: how data was considered in project execution planning, the design of dashboards and visual analytics, strategies for stakeholder engagement. By defining these boundaries, the research deliberately scoped out focus on any particular software and zeroed in on human centered VDC practices. This narrow focus ensured that observations would pertain directly to the narrative making aspect of data use. Special attention was paid to collaborative situations where interdisciplinary teams attempted to “see” and understand data together. In short, the study examines VDC teams operating in a digitally mature project setting, investigating how they make sense of complex data rather than how any single tool functions.

The data collection strategy

Primary data: Interview with Trevor Lunde

Secondary data: Class readings (Building innovation by Neff & Dossick on “futuring work,” “seeing together,” and “messy talk”)

Detailed Description of the Case and Facts

With software that generates real time data on design clashes, construction activities, logistics, and more. The team initially experienced familiar challenges: data remained fragmented and inconsistently interpreted across different stakeholder groups. For example, an owner might receive the same dashboard as a site superintendent, but each was looking for different insights. The owner for high level metrics like budget, and the superintendent for day to day metrics like crew productivity. Because the data was presented in generalized, one size fits all formats, neither party was getting a narrative tailored to their needs. The absence of contextual framing led to misalignment and misunderstandings; team members lacked a shared story about what the numbers meant for the project.

To illustrate, Trevor Lunde, recounted how early project reports would list dozens of KPIs and clash detections without explanation. Stakeholders were often overwhelmed by raw figures, a classic case of information overload. One specific example Trevor provided was the metric for crane utilization through the crane view software. Initially, the project’s digital tools tracked how often each crane was in use, but this metric “didn’t click” with the team until it was reframed as a story: the VDC team linked crane utilization to logistical readiness, highlighting periods when the crane sat idle waiting for materials or when scheduling conflicts caused downtime. By annotating the data in this way, the team could immediately grasp why utilization was low at times and take action to adjust delivery schedules. This anecdote typifies the case: raw data becomes meaningful only after being contextualized in a narrative that connected to team workflows and goals.

In another example, Trevor discussed how his team collected highly granular data during the construction of concrete columns. Instead of viewing each column in isolation, they analyzed productivity across repetitive cycles within the process of layout, formwork, pouring, stripping, and finishing and then aggregated the data at floor level. This method uncovered performance patterns and enabled more accurate scheduling and estimating on future projects. The iterative buildup of shared knowledge transformed day to day field observations into benchmarks used company wide. This small change started conversations on-site about work methods and scheduling that could improve productivity. These instances are evidence that when data is presented in the right story, it can align diverse stakeholders toward common objectives.

In summary, the cases presented a scenario where the technology was present and data was plentiful, but the meaning making initially lagged. The VDC team’s role evolved to fill this gap: translating disparate data points into a coherent story for each audience. These factual observations set the stage for analyzing the patterns and theories behind how the team accomplished this transformation from “noise” to narrative.

Data Collection Methods

This semi structured interview explored Trevor’s firsthand experiences with data visualization, dashboard development, coordination meetings, and project planning at GLY. Open ended questions were used to elicit stories and examples of how raw information was turned into shared understanding on his projects. The interview provided rich, anecdotal evidence of challenges and successes in data storytelling for instance, Trevor’s accounts of specific metrics like crane utilization and how his team reframed them (as described above). Insights from the conversation with Trevor form the backbone of the case study’s factual narrative and are cited throughout the findings.

Secondary data came from relevant course texts and literature that offer a theoretical lens on the case. In particular, chapters of Building innovation by Neff and Dossick were analyzed, which discuss the cultural and organizational shifts accompanying BIM and digital innovation in construction. These readings introduced key concepts such as “futuring work” (how practitioners craft visions of technology’s promise), “seeing together” (how federated BIM models enable teams to visualize problems collectively), and “messy talk” (the informal dialogue needed to address issues that formal tools alone cannot solve). By reviewing these texts, this study identified theoretical constructs and vocabulary that could explain the patterns observed in the GLY case. For example, the notion of “seeing together” helped interpret why the team’s use of a shared 3D model improved coordination, and “messy talk” contextualized the persistent need for face to face discussion despite high tech visualization. Additionally, the study incorporated Karl Weick’s theory of sensemaking as a framework for understanding how people construct meaning from ambiguous data. Weick’s works (1995; 2005) provide insight into the process by which individuals and groups “structure the unknown” by placing data into a conceptual framework or story. In summary, the data for this study included empirical evidence from a practitioner (Trevor’s interview) and conceptual insights from scholarly readings, enabling a well rounded analysis that connects practice to theory. Combining these sources allowed the research to not only describe what happened in the case, but also why it happened, through the lens of established concepts in VDC and organizational theory.

Patterns and Theoretical Insights

Analyzing the case data revealed several patterns in how project information was turned into meaningful narrative. These patterns align with theories of sensemaking and collaboration found in the literature. Three key themes emerged:

Sensemaking Through Narrative:

A central finding is that the VDC team’s storytelling approach reflects what Karl Weick describes as sensemaking. Sensemaking is essentially the process of turning a stream of experience or data into a structured story that people can comprehend and act upon. Karl famously defines sensemaking as transforming raw events into “a situation that is comprehended explicitly in words and that serves as a springboard into action”. In this case, Trevor and his team engaged in this process by taking abstract metrics (e.g. the utilization percentage) and framing them in plain language with context (“why is this number important?”). By doing so, they created plausible references of the project’s state that team members could discuss and respond to. Importantly, this sensemaking was a social activity: it happened in meetings, on calls, and through shared dashboards, not in isolation. Karl emphasizes that sensemaking is inherently collective, people build meaning through interaction and shared narratives. The GLY case here illustrated this vividly. For example, when the VDC team explained crane utilization in terms of logistics, it allowed everyone from site engineers to project executives to grasp the situation and coordinate actions. Trevor’s emphasis on always aligning data with a stakeholder’s goals (e.g. “What does this metric mean for you?”) reflects this model. When data tells a clear, goal oriented story, it triggers coordinated action rather than confusion. Therefore, the project data only became meaningful once it was woven into a narrative, confirming the theoretical idea that people make sense of complexity through stories.

Dashboard-Driven Accountability:

A second theme is the role of visual dashboards as real time storytelling tools that promote accountability and proactive problem solving. Rather than static reports, GLY’s VDC dashboards were living narratives of the project, updated with current data and designed to highlight anomalies or trends. Trevor described how a well crafted dashboard essentially narrates the project’s health at a glance, directing attention to where it’s needed, much like a story with protagonists and tension points. For instance, if concrete pour cycles were lagging, the dashboard’s visuals might show a red flag or drop in productivity, effectively telling the story: “we are falling behind on X.” This immediacy shifted team members from a reactive mindset (finding out issues in retrospect) to a proactive one. Coordination meetings transformed from dry status recitations into collaborative problem solving sessions because the data was presented in an accessible narrative format. One practical outcome noted by Trevor was natural accountability: when everyone can see the same story on the dashboard, responsibility becomes diffused in a positive way, team members feel collectively responsible to address issues rather than waiting to be told. Neff and Dossick’s observations about “seeing together” support this finding: the federated model or dashboard creates a shared reference point, so the team “saw the building systems together in new ways” and identified problems jointly. In this case, the transparent storytelling of data meant that, for example, a subcontractor could identify a scheduling conflict on the dashboard and bring it up immediately so everyone could see the conflict, discuss it, and resolve it. This echoes earlier research noting that solely relying on “clean” digital output can inadvertently stifle discussion; instead, combining the output with a narrative prompts the dialogue needed to solve problems. Thus, dashboards in this case were not just monitoring tools but enablers of a continuous conversation, holding the project team accountable to the story the data was telling.

Interdisciplinary Collaboration and “Seeing Together”:

The third pattern relates to how data storytelling bridges gaps between different disciplines and stakeholders. Construction projects involve architects, engineers, contractors, owners, and many others; each with their own priorities and technical languages. A frequent challenge is achieving a common understanding across these groups. The case demonstrated that narrative and visualization can serve as a kind of bridge language. By using shared dashboards and federated BIM models, the VDC team helped various specialists literally and figuratively “see together.” In the words of Neff and Dossick, “the shift from separate 2D drawings to combined 3D models allowed teams to “see the building systems together in new ways” and fostered a shared understanding of design and coordination issues”. Our case mirrored this: when the structural engineer, the MEP coordinator, and the owner’s rep all looked at the same visual data (say, a clash heatmap or a schedule risk graph), they could discuss solutions on equal footing. However, the findings also reinforce that different stakeholders assign meaning differently to the same data. The story that a scheduler sees might not be the story that a sustainability manager sees in the same chart. Trevor ’s experience underscored this point. He noted that a field superintendent might interpret a production chart one way, while an owner focuses on an entirely different metric on that chart. The VDC team’s job, then, was to adapt the storytelling to each audience without losing the single source of truth. In practice, this meant developing multiple views or filters for the data and providing commentary to each stakeholder group highlighting what matters to them. This aligns with the concept of messy talk: informal back and forth was often needed to truly translate the data across disciplines. Rather than seeing this as a failure of the technology, it illustrates that successful interdisciplinary collaboration requires both the high tech common platform and the low tech conversation. The narrative created around data must be rich enough to resonate with varied perspectives. The case confirms that when data is contextualized properly (e.g. linking a technical issue to cost implications), it aligns stakeholders and improves collaboration. In effect, the storytelling approach acted as a translator between different professional languages, ensuring that the project’s many players were on the same page.

Overall, these patterns suggest that the act of “storytelling” supported by digital tools but fundamentally, a human interpretive act is what turns construction data into a powerful driver of project outcomes. By applying theories of sensemaking, we can see that the VDC team was doing more than reporting facts; they were actively constructing a shared reality for the project team. This not only helped in solving immediate problems but also in building trust and transparency. Team members began to trust the data because it was delivered with context and purpose, and they trusted each other more as the open narrative reduced finger pointing so everyone could see issues and solutions together. Additionally, these findings tie into organizational learning. Over time, the project team got better at anticipating what data mattered, a sign that they were learning how to learn from their data, a positive feedback loop created by effective sensemaking practices.

Connection to Broader Construction Practice and VDC Implications

The insights from this case study have important implications for the larger field of construction management and VDC. First, the case underscores that digital transformation in construction is not just about technology adoption, but about narrative adoption. As Neff and Dossick observe throughout their work, implementing tools like BIM triggers a need for new practices and even new institutional norms. Our study’s findings echo this even to this day: introducing dashboards and data analytics into project workflows requires project teams to develop storytelling practices and perhaps even new roles (e.g. a “data translator” in the VDC team) to truly leverage those tools. In the long run, widespread use of data driven storytelling could prompt shifts in organizational habits. For example, regular dashboard driven meetings might become a standard part of project execution processes (rewriting institutional rules in the sense of Neff & Dossick’s model). There may be resistance at first, as people adjust to more transparency and new communication styles, but as the case showed, the benefits in clarity and trust can overcome initial skepticism.

Second, this case contributes to the growing recognition that sensemaking is a critical skill in VDC practice. It is not enough for VDC professionals to be proficient in software; they must also be effective facilitators of meaning, able to construct and communicate the “so what” of data. The tension between futuring work and actual practice, highlighted by Neff and Dossick, is essentially a call for sensemaking. The industry often talks about big data, AI, and BIM as game changers for productivity and sustainability as the future vision, but without people who can interpret and narrate data, those visions may not materialize on the ground. Our case provides a concrete example of bridging that gap: the VDC team negotiated innovation by taking the grand idea of data driven construction and embedding it in daily routines and conversations.

Furthermore, It also highlights a practical point for the industry: when setting up project execution plans, teams should explicitly plan for data storytelling, deciding early on which data will be collected and how it will be communicated. In our case, once GLY’s team made that shift (embedding key metrics into the project narrative), they saw reductions in rework and smoother coordination, because issues were caught and understood earlier. These outcomes suggest that making data meaningful is not a mere academic exercise, but has tangible payoffs: better decisions, less waste (both time and material), and improved stakeholder relationships. In a larger sense, this reflects the concept that when people are literally on the same page (or screen), they build trust. Everyone could see that decisions were based on evidence and aligned with shared goals, which is fundamental in partnering approaches and Integrated Project Delivery (IPD).

Finally, this study reinforces lessons for interdisciplinary teamwork in the digital age. The traditional silos between architects, engineers, and builders are increasingly bridged by digital models, but as we saw, it takes careful curation of information to truly bring those disciplines together. The combination of a federated model (to see together) and an open forum for messy talk (to think together) appears to be a recipe for collaboration success. As VDC becomes standard practice, project managers and BIM coordinators should foster an environment where data is not just pushed to stakeholders, but actively discussed and iterated upon. In effect, every coordination meeting becomes a small act of sensemaking where the project’s narrative is continually refined. Over time, this could lead to a culture in construction that is more adaptive and learning oriented. A culture where data is not feared or ignored, but embraced as a common story of “what is happening” and “what we should do about it.”

In conclusion

The journey from noise to narrative in this case study illustrates a pivotal shift happening in construction practice. It’s a shift from treating data as a passive byproduct of work to using data as a driving force for storytelling and decision making. Theoretical frameworks like Karl Weick’s sensemaking and the innovation model of Neff and Dossick provide a vocabulary for what we observed: teams engaging in futuring visions, collaboratively seeing problems, talking through messy details, and gradually institutionalizing new ways of working. Practically, the case shows that when a VDC team succeeds in crafting a meaningful project narrative from data, the benefits are multifold; improved clarity, accountability, collaboration, and alignment with broader goals. As the construction industry continues to digitize, the ability to make sense of noise will be just as important as the ability to generate data. In the end, the true value of tools like BIM is unlocked not by the technology itself, but by the narratives we build around the information it provides. This case study serves as a testament and guide to that principle, demonstrating how virtual construction techniques can indeed turn data noise into a narrative that drives better project outcomes.

References (APA 7th Edition)

1. Dossick, C. S., & Neff, G. (2011). Messy talk and clean technology: Communication, problem-solving and collaboration using Building Information Modeling. Engineering Project Organization Journal,
2. Neff, G., & Dossick, C. S. (2011). Making BIM work in practice (Course reading, Chapter 7)
3. Neff, G., & Dossick, C. S. (2011). A new model for innovation (Course reading, Chapter 8)
4. Weick, K. E., Sutcliffe, K. M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409–421 us.sagepub.com.
5. Weick, K. E. (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage us.sagepub.com.
6. Interview – Trevor Lunde (2025). VDC Specialist at GLY Construction – Personal interview conducted on May 27, 2025.