Data-Driven EPC success in a major industrial project

Introduction

In a €250 million chemical plant project located in a large industrial area near one of the major ports of Western Europe, Matei Kevenaar, serving as Engineering Manager with one of the world’s leading EPC contractors, led a data-driven initiative that achieved unprecedented results. This three-year EPC (Engineering, Procurement, and Construction) project – executed by one of the world’s largest and most recognized EPC contractors for a major European chemical producer – finished engineering 3 months ahead of schedule with 99% of piping isometric drawings right on the first issue and a 33% smaller team in the final months. These outcomes were far from typical. Historically, piping designs required multiple revisions (often 70–300% revision rates), causing rework and delays. By implementing a data-driven way of working – centered on a live Isometric Dashboard and lean, multidisciplinary collaboration – the team eliminated nearly all rework and accelerated the project. This article explains what “project success” truly means in EPC from the client’s perspective, the key success factors applied, and how the isometric dashboard’s logic and transparency shifted mindsets to deliver measurable improvements. 

Defining project success in EPC 

Project success in EPC is ultimately defined by the client’s business outcome, not just internal milestones. The owner invests in a facility expecting it to be safely operational on time, within budget, and meeting its intended performance. In short, “having the facility running as planned” is the true mark of success. For example, issuing all engineering documents on schedule means little if the plant cannot start up when promised. From the client’s point of view, a project is successful when the new plant or unit is delivered ready for operation at the agreed time and cost and meets all functional requirements. Any schedule slip or quality problem that prevents the facility from operating as planned undermines this success.

Achieving this level of success requires aligning every phase of the project (engineering, procurement, construction, commissioning) toward the end-goal. It means no surprises at startup, no costly late design changes, and no construction delays. In practice, creating customer impact in EPC projects translates to reliable, predictable delivery. This data-driven initiative set a clear objective to deliver the facility predictably within the agreed timeframe and budget – essentially, to ensure the plant could start up on schedule for the client. This client-centric definition of success guided the team’s approach throughout.

Key success factors for reliable project delivery

Several key success factors enabled the data-driven initiative to meet and exceed its targets. These factors are general best practices in EPC, but here they were applied rigorously through a data-driven approach:

• The team kept the end objective in mind – getting the plant running by the target date. All decisions were filtered through what the client needed for a smooth startup. This mindset is exemplified by working backwards from the operational goal: successful commissioning requires efficient construction; efficient construction requires receiving first-time-right designs and materials in the proper sequence. By focusing on final outcomes (not just engineering deliverables), the project avoided local optimizations that don’t benefit the overall timeline.

• Instead of managing by guesswork or static reports, the project employed data-driven tools to monitor progress and quality on a daily basis. By pulling data from various sources and visualizing status, the team could base decisions on facts. This approach provided a single source of truth for project status, which improved communication and highlighted issues early. The use of live dashboards meant everyone saw the same up-to-date information, reducing confusion and ensuring focus on the critical tasks. Overall, the project demonstrated “the value of data-driven insights in managing complex projects”, as evidenced by improved reliability and predictability of outcomes.

• Large EPC projects involve many disciplines (process, piping, civil, instrumentation, etc.) that must work in concert. Here, multi-disciplinary coordination was enhanced through daily integrated meetings and shared dashboards. Traditional siloed workflows were broken down – the piping team, for instance, didn’t work in isolation but coordinated its design releases with input from other disciplines via the dashboard. Daily scrum sessions brought all disciplines together to review priorities and dependencies. This ensured that everyone was “focused on the right tasks” at the right time. The result was fewer disconnects and a unified pace across engineering, procurement, and construction. The importance of this cross-discipline alignment was a key lesson, highlighting “the value of transparent, up-to-date insights” to keep all parties synced.

• The project created central dashboards (in Power BI) accessible to all stakeholders, so that status and readiness of deliverables were visible to everyone. This transparency eliminated the need for endless status meetings and “chasing updates.” Instead, engineers and managers could trust the dashboard as the authoritative source. When all project data sits in one connected platform, teams avoid working on outdated information and can identify issues immediately. In this data-driven initiative, the Isometric Dashboard became the common reference point, giving instant clarity on what drawings or tasks were ready to proceed and which were waiting on prerequisites. Having this single source of truth improved communication and task prioritization, as proven on a prior project as well.

• A cornerstone of the approach was doing work right the first time to avoid iterative cycles. The team emphasized Lean principles, aiming to eliminate non–value-adding activities like unnecessary checking, rework, and waiting. In practical terms, this meant instituting a “first-time-right” approach for engineering deliverables. By ensuring all conditions were met before issuing a drawing (no missing data, no pending decisions), the need for revisions was virtually eliminated. This focus on quality-at-the-source is a Lean concept that drastically reduces downstream waste. It also required a mindset shift: engineers and designers moved from a mentality of “we can always revise later” to “we only issue when it’s truly ready.” The introduction of Lean management principles and mindset alignment sessions during the rollout helped instill this culture. As a result, the project achieved near-zero rework, validating that Lean, first-time-right execution can work even in large-scale projects.

• Borrowing from agile project management, the team held daily stand-ups (scrum meetings) and used visual to-do lists to drive execution. Rather than weekly progress reviews, issues were identified and resolved daily. This responsiveness kept the project on track. The Isometric Dashboard effectively functioned as an automated to-do list generator, with traffic-light indicators (green/yellow/red) showing task status each day. Team members always knew what was ready to work on next, which tasks were waiting on others, and where there were out-of-sequence activities that needed attention. This continuous monitoring and adjustment prevented small problems from snowballing into delays. It also kept everyone accountable on a short-cycle basis, which is a key success factor in managing complex projects.

• Another factor was the smart use of technology without over-reliance on IT. Instead of waiting for a big software deployment, the team built low-code solutions using familiar tools (Excel, Power BI) to automate workflows. This “Proof of Concept” approach meant useful dashboards were up and running quickly, and the project team could tweak them on the fly. By empowering those who best understood the processes (the engineers and managers) to develop and refine the tools, the solutions were highly practical and user-friendly. The quick adoption of these dashboards by the team shows that when tools address real needs and are easy to use, people will embrace them. The low-code strategy avoided heavy IT overhead and delivered immediate value, which is a critical success factor for digital initiatives in projects.

In summary, the project succeeded by combining technology, data visibility, lean processes, and a supportive team culture. The following sections detail how these factors came together in the development of the Isometric Dashboard, and how this innovation drove the exceptional outcomes achieved.

Implementing a Data-Driven approach in an EPC project

At the start of the EPC phase, Matei and the team identified gaps in collaboration and transparency that could hinder timely delivery. To address these, he spearheaded a data-driven way of working – meaning the project’s engineering data (especially the 3D model and its outputs) became the driving source for planning, tracking, and decision-making. The core of this approach was developing custom dashboards that extracted live data from design and schedule systems to provide actionable insights.

Using a low-code toolkit, Matei’s team built several linked dashboard applications. These included tools for P&ID (Piping & Instrumentation Diagram) IFC readiness, 3D model review readiness, module weight control, and most notably an Isometric Dashboard for piping deliverables. All dashboards were created with Microsoft Excel and Power BI, pulling data from design databases and progress tracking sheets into a central location. By leveraging familiar software, the development was quick and the outputs were easily accessible to everyone on the project (no specialized training required). The fact that these solutions were delivered as a proof-of-concept and then “quickly adopted by the project team” speaks to their practicality.

Critically, rolling out the new tools was not just an IT exercise but a people exercise. The implementation included kick-off meetings and mindset alignment sessions with the team. In these sessions, Matei introduced Lean project management principles and explained the goals of the data-driven approach. By securing buy-in early and demonstrating how the dashboards would make individuals’ work easier, resistance was minimized. (On a previous project, there had been initial pushback from some subcontractors, but once they saw improved coordination and quality, the tools gained acceptance.) On this prior EPC engagement, the team embraced the dashboards as day-to-day working tools rather than seeing them as extra overhead.

The data-driven approach changed how information flowed in the project. Instead of disparate Excel files and manual reports circulated via email, the Power BI dashboards served as the live interface for project status. Engineers updated their source data (like 3D model attributes, line list status, etc.), and those updates were reflected in the dashboards automatically. This meant at any given moment, management could open the dashboard and see exactly where things stood – which is far more efficient than waiting for weekly reports. It also meant that dependencies between disciplines became transparent. For instance, if the civil team had not released a foundation drawing needed for a pipe support, that would show up as a red flag on the relevant dashboard, visible to all. This visibility encouraged teams to collaborate proactively to clear roadblocks.

One of the most innovative aspects was integrating the dashboards into daily meetings. The project instituted brief daily scrum meetings where discipline leads would stand in front of the dashboard, review what tasks were “green” (ready to go), and which were “red” or “yellow” (needing input or not ready). This created a rhythmic feedback loop: each day, priorities were adjusted based on real data, and everyone left the meeting with a clear, updated to-do list generated by the system. By contrast, many projects rely on weekly alignment meetings and static reports, which often leads to teams reacting to outdated information. Here, the combination of daily dashboard data and agile meetings kept the project tightly coordinated and allowed for continuous course-correction. It essentially replaced the traditional project control cycle with a faster, more adaptive one.

In summary, implementing the data-driven approach involved integrating technology (dashboards) with process changes (daily scrums, lean thinking). It transformed the execution from a document-driven, reactive mode to a data-driven, proactive mode. The team could see issues coming (e.g. a prerequisite not done) and act before it caused rework or delay. This set the stage for the extraordinary performance improvements described next.

The Isometric Dashboard: mechanism and impact

Among the tools developed, the Isometric Dashboard had the most far-reaching impact on project performance. Piping isometric drawings (detailed 2D drawings of pipe spools extracted from the 3D model) are a critical deliverable in any plant project. Traditionally, producing these isometrics is labor-intensive and iterative – designers issue drawings, then reviewers mark them up with corrections, and multiple revision cycles follow. Industry norms showed revision rates ranging from 70% up to 300%, meaning each iso drawing could be revised two or three times on average before final approval. This rework consumed a huge chunk of engineering hours and often caused late changes that disrupted construction. In fact, on this project, half of all engineering hours were anticipated for piping design alone, with a large portion for isometric checking and rework. Clearly, if this process could be improved, it would yield significant benefits.

The Isometric Dashboard was designed to break the cycle of rework. Its guiding concept was “first-time-right” isometric production – get each drawing correct and complete before issuing it for construction. To achieve this, the dashboard tracked all prerequisite tasks that feed into an isometric. For each piping drawing, it monitored whether upstream inputs were finished. For example, it would indicate if the 3D model for that pipe line was fully up-to-date, if all necessary calculations (stress analysis, support design) were done, and if all related components were released by other disciplines. Only when all prerequisite items turned green would the iso drawing be allowed to proceed to issue. The dashboard interface used simple traffic light colors: tasks showed red if not done, yellow if in progress or awaiting something, and green when complete. Every day, the system updated the status of each isometric’s prerequisites, and any drawing that turned “green” (ready) could be taken up for extraction and issuing.

This mechanism enforced a strict logical sequence. It prevented out-of-sequence work, where previously a piping designer might try to issue drawings early and “fix them later.” With the dashboard, nothing got issued for checking unless all inputs were confirmed. As Matei described, the dashboard reported daily which prerequisite tasks had been completed, after which the next task became green and could proceed. If a drawing’s status was still red, the team knew issuing it would lead to errors, so they held off. This was a major mindset shift for the team: patience to only move forward when ready, instead of rushing to meet an internal deadline at the expense of quality. By making the prerequisites explicit and visible to all, discipline leads also felt accountable to deliver their part on time – nobody wanted to be the reason another team was blocked in red status. Thus, the tool fostered a sense of shared responsibility and coordination.

The Isometric Dashboard was used as a centerpiece in the daily multi-disciplinary scrum sessions. Every morning, representatives from piping, process, mechanical, structural, and other groups would quickly review the dashboard. If an iso drawing was still red, they would discuss what needed to be done and who could help. If something turned green, they queued it for issuing. This daily cadence meant issues that could cause rework were identified and resolved before the drawing was produced. Over time, this virtually eliminated the need for re-issuing isometrics. Rework was not transferred to construction either – because the drawings were correct when issued (“Issued for Construction” truly meant ready for construction). The impact was profound: the project achieved a <1% revision rate on isometric drawings, effectively 99% of isos were right the first time. Compared to the typical 70–300% revision cycles, this was unheard of. It confirmed that with proper controls and team discipline, near “zero rework” in engineering is an attainable goal, not an impossible ideal.

Eliminating rework in the design phase had cascading benefits. First, it cut down the checking effort drastically. The project no longer needed a large squad of people doing nothing but cross-checking piping drawings, since the drawings were coming out correct. In fact, the team was able to reduce the number of designated isometric checkers because the dashboard ensured quality upfront. This was a direct productivity gain – those personnel could be reallocated to other value-adding work, or the team size could be trimmed. Second, first-time-right drawings meant construction could build without interruptions. When construction crews receive drawings that later change, it causes costly field rework or schedule gaps. Here, with 99% of drawings needing no revision, the construction phase went smoother than expected. As reported, the improved collaboration and “no surprises” documentation resulted in a much smoother construction phase on site. Essentially, by doing the hard work during engineering to eliminate errors, the team de-risked the later stages of the project.

The isometric dashboard also fundamentally changed mindsets on the project. Initially, some team members might have believed that a few revisions were normal or that pushing work through faster was the way to meet deadlines. The dashboard data proved the opposite – by slowing down to wait for readiness, they actually sped up the overall delivery. People started to see that a disciplined, data-driven process could outperform the traditional rush-and-fix approach. Daily exposure to the dashboard’s indicators made the concept of “flow” and “pull” (Lean principles) very tangible: they only “pulled” an isometric when all prior steps were done, creating a smooth flow of work. Over the course of the project, this ingrained a culture of quality and collaboration. Departments communicated more to get each other what they needed. Rather than each group optimizing just its own output, they optimized the handoffs between groups. In effect, technology (the dashboard) was the enabler, but the result was a human change – the team collectively adopted a first-time-right, no-waste mindset. This cultural shift is hard to quantify, but it was evident in the results and was one of the most valuable outcomes of the data-driven approach.

Quantified results and performance improvements

The implementation of the isometric dashboard and related data-driven tools led to exceptional, quantifiable performance improvements for the data-driven initiative. Key results include:

99% First-Time-Right IFC drawings:

• The project achieved a <1% revision rate on piping isometric drawings. In practical terms, out of hundreds of isometrics, almost none had to be re-issued. This is a dramatic improvement from historical norms (which ranged up to 300% revision rates). Hitting 99% correct on first issue meant virtually no engineering rework and no construction rework due to design errors. It validated that complex designs can be done right on the first pass with the proper process controls. The reduction in drawing revisions also minimized engineering change orders and late design changes, contributing to schedule reliability.

Accelerated Schedule – 3 Months Ahead:

• The engineering phase was completed three months ahead of the contracted schedule. Finishing a quarter early on a multi-year project is a significant schedule improvement. This was largely attributable to the efficiency gains from the data-driven approach – with less rework and fewer iterative cycles, tasks were completed faster. The daily scrum approach also meant no waiting on weekly cycles to solve issues, compressing the timeline. Importantly, this acceleration was achieved without compromising quality or scope. In fact, quality improved (as noted above). The time savings in engineering provided more float for commissioning and startup, directly benefiting the client’s timeline.

Resource Efficiency – 50% Effort Reduction

• As engineering became more efficient, the project was able to downsize the engineering team by 33% over the last 9 months. Together with the 3 month earlier completion, this corresponded to a 50% reduction in engineering effort hours during that period. Essentially, the team delivered the remaining work with half the manpower that would normally be required. This efficiency gain came from eliminating wasteful activities (like repetitive checking, rewriting documents, and extra meetings). By the final phase, the streamlined processes meant each engineer was far more productive, and fewer total staff were needed to handle the workload. For the project’s bottom line, this likely translated to substantial cost savings in labor. It also freed up personnel to be assigned to other projects sooner. The ability to maintain output with a smaller team is a strong indicator of improved process performance.

Reduced overhead in checking and meetings

• Although not a single line item metric, it’s worth noting the qualitative improvements. The use of dashboards eliminated many lengthy alignment meetings and manual status reporting. The automated to-do lists and visual indicators meant that the project management no longer had to constantly “chase” information; they could spend time acting on insights rather than compiling them. The text reports that weekly reporting was replaced by actionable daily updates, and long meetings were cut down. This contributed to team morale and allowed engineers to focus more on engineering rather than bureaucratic tasks.

Smoother construction and commissioning

• While harder to measure, the ultimate proof of success is that the construction phase was executed smoothly and the facility was delivered without hiccups. The client benefited from a project that was reliable and predictable, as evidenced by their satisfaction. By hitting the schedule early and delivering quality designs, the project ensured that the facility could start up as planned – the ultimate goal of EPC success. The client’s feedback was extremely positive; they were “extremely pleased” with the outcome, which strengthens the contractor’s reputation and relationship. For the client, having the plant ready on time meant they could begin operations and product sales as intended, illustrating the true business impact of the project’s success.

These results underscore a powerful cause-and-effect: technology and data visibility, combined with a lean mindset, led directly to measurable performance gains. By making prerequisites and progress transparent (via the dashboard), the team was able to coordinate better and avoid errors, which in turn saved time and resources. Finishing engineering early with fewer people, while nearly eliminating rework, is an extraordinary outcome in the EPC industry. It shows that longstanding challenges – like chronic delays and budget overruns – can be overcome by changing how people work and what information they base decisions on.

To put it succinctly, the data-driven initiative became a case study in efficiency. It demonstrated that with the right approach, a project can improve all three corners of the “iron triangle” – delivering on scope (quality), schedule, and cost – simultaneously. Often it’s assumed that you can’t speed up a project and reduce costs without hurting quality, but here quality actually improved (fewer errors) even as the timeline shrank and hours were saved. Such balanced success is rare and was achieved through the deliberate application of data-driven, model-centric techniques and cultural change.

How technology, data visibility, and mindset shift drove success

The success of this project was not an accident – it was the result of causal mechanisms put in place by the data-driven approach. It’s important to understand how the technology, data visibility, and mindset changes led to the improved outcomes:

Preventing rework through prerequisite control

• By using the dashboard to enforce completion of prerequisites (technology), the team ensured that no task was started prematurely (process change). This prevented the classic rework cycle. Causally, if all inputs to a drawing are correct and complete, the output will be correct – thus no rework. The dashboard made the status of inputs visible daily, so issues (like a missing piece of data) were identified and resolved before proceeding. This direct feedback loop eliminated the root causes of errors. The <1% revision metric is a direct result of this mechanism. Fewer revisions meant fewer hours spent fixing things, which in turn allowed the schedule to compress and team size to shrink without loss of productivity.

Improving coordination and removing bottlenecks

• Data visibility via the single source of truth meant everyone could see where bottlenecks were forming. For example, if one department was lagging on a task needed by others, it was apparent to all. This transparency (technology) prompted team members to communicate and collaborate (mindset/behavior). Instead of working in silos, people began to think about upstream and downstream needs. The daily stand-ups reinforced accountability – no one wanted to be the reason an item stayed red. As a result, dependencies were cleared faster, and work flowed more smoothly across disciplines. The outcome was seen in the smoother construction phase and improved overall reliability. The causal chain here: shared data -> proactive coordination -> fewer delays.

Faster decision making and issue resolution

• The dashboards provided daily (continuous) insight into project metrics. Project leaders didn’t have to wait for a weekly report to spot a delay; they could see it immediately on a live chart or list. This immediacy (technology) led to a change in management approach – problems were addressed on the spot (process). For example, if an engineering task was stalled, project management could intervene the same day to allocate resources or escalate a decision. This agility is what shaved months off the schedule. In essence, data visibility shortened the feedback and control cycles from weeks to hours, which causally leads to time savings. Every small prevention of delay adds up in a project timeline.

Empowering a Lean mindset

• Perhaps one of the most significant (though less tangible) causal factors was the mindset shift among the project team. The introduction of Lean principles and the success of the dashboard approach created buy-in that “working smarter” was better than working harder. As team members saw positive results – like tasks getting done with less chaos – it reinforced the new behaviors. Engineers started taking ownership of data quality (because they knew others relied on it), and planners started trusting the team more (because they delivered on promises). This culture of trust and accountability further boosted performance. It’s a virtuous cycle: technology provided a framework for better working, early wins from using it convinced people to change their habits, and those new habits produced even better outcomes, which in turn solidified the cultural change. By project’s end, the team had internalized the data-driven, first-time-right ethos, which will carry into future projects.

Holistic improvement across phases

• The technology and mindset changes didn’t only improve engineering deliverables; they also impacted procurement and construction positively. For example, first-time-right drawings meant procurement could order the correct materials once (no reorders due to design changes), avoiding waste and delay in the supply chain. Similarly, construction sequencing was optimized because engineering delivered items in the needed order (enabled by the sequence logic in the dashboard). These cross-phase benefits are how the project achieved the ultimate goal: the facility was ready to run as planned for the client. In other words, a good engineering phase sets the foundation for a good construction and commissioning phase. The project’s use of data and lean processes in engineering ensured that foundation was solid, leading to a successful turnover to the client.

In summary, the interplay of technology (dashboards, automation), data visibility (transparent live status), and mindset (lean, collaborative culture) created a powerful engine for project improvement. Technology provided the tools and information, but people had to trust and use that information to change their way of working. Once they did, the improvements in quality and speed naturally followed. This cause-and-effect was clearly demonstrated in this industrial project: because the team embraced a data-driven mindset and had the tools to support it, therefore they achieved near-flawless deliverables and beat the schedule. It’s a compelling example of how modern project management techniques can significantly outperform traditional methods in EPC projects.

5 Lessons Learned from the Data-Driven project initiative

This project provided rich learning on how to successfully execute an EPC project with a data-driven, lean approach. Key lessons learned include:

• Utilizing project data in up-to-date data is extremely effective for enhancing coordination and quality. Dashboards and analytics can highlight problems that would otherwise go unnoticed. On this prior EPC engagement, the data-driven approach led to better decision-making and ultimately improved project outcomes. Lesson: Invest in data visibility – it pays off in higher performance and fewer errors.

• Maintaining one central source for project status and tasks greatly improves communication and focus. When everyone trusts the same dashboard, there is less confusion and finger-pointing. The project showed that a single source of truth helps prioritize tasks and keeps the multi-disciplinary team moving in the same direction.

Lesson: Ensure all team members are looking at the same data; alignment and accountability will follow.

• Complex projects succeed when all disciplines work together, not in isolation. Regular multi-disciplinary meetings (daily scrums) and transparent status sharing were crucial in this case. It taught us the importance of breaking silos – coordination across departments with daily insight prevents issues.

Lesson: Create processes (like daily stand-ups and integrated planning) that force coordination and joint problem-solving across disciplines.

• Aiming for first-time-right deliverables – doing it correctly instead of doing it over – dramatically reduces wasteful effort. By front-loading quality (ensuring prerequisites are done), the project avoided rework and saved time. This demonstrated the benefit of Lean principles in engineering: find and eliminate non-value-adding steps (like redundant checks and revisions).

Lesson: Strive for zero rework by addressing root causes early; it accelerates the schedule and improves quality simultaneously.

• The project showed that you don’t need expensive, complex software to innovate – simple, low-code tools can be very effective when tailored to your needs. More importantly, getting the team’s buy-in (mindset) is what makes any tool successful. The quick adoption of the dashboards was because the team was involved and saw the value.

Lesson: Empower the project team with accessible tools and involve them in the change. A culture open to new ideas and continuous improvement will magnify the impact of any technology.

These lessons highlight that successful transformation in project execution is as much about people and process as it is about tools. By applying these lessons – using data smartly, fostering transparency, coordinating tightly, practicing Lean, and leveraging quick-win solutions – other projects can replicate the success experienced in this industrial project.

3 Misconceptions

Beyond the lessons learned, this project also challenged some common misconceptions in the EPC industry. Here are three surprising misconceptions that the data-driven project initiative success story dispelled:

Misconception 1: “Rework is inevitable in engineering.”

• Many engineers assume that multiple drawing revisions are just part of the job’s reality. Historically, piping isometrics did undergo countless changes (70%+ revision rates were seen as normal). In this project, however, the team proved that near-elimination of rework is possible – achieving a <1% revision rate for isometrics. In other words, 99% of drawings were correct on first issue. This defies the notion that you must “draw twice to get it right.” With the right process (prerequisite checks and quality focus), first-time-right can be a reality.

Misconception 2: “Digital dashboards are too complex to implement quickly.”

• It’s often thought that introducing new digital tools will be slow, costly, and met with resistance. This data-driven initiative showed the opposite. The team built low-code dashboards using familiar software (Excel, Power BI) and rolled them out as proof-of-concept within the project timeline. They were quickly adopted by the project team after brief training and mindset alignment. This demonstrated that even during a live project, one can introduce effective digital solutions without lengthy IT projects. The success dispels the idea that only enterprise software or long lead times can yield useful project dashboards – sometimes a nimble, homegrown tool is enough to drive change.

Misconception 3: “Speeding up a project means sacrificing quality (or vice versa).”

• A common belief is that you cannot compress schedules or reduce manpower without impacting quality or thoroughness. The results in this industrial project proved otherwise. The project finished engineering three months early and with a smaller team, all while dramatically improving quality (virtually zero errors). This is a surprising outcome that contradicts the trade-off mindset. By eliminating waste and rework, the team found they could deliver faster with fewer resources and at higher quality. It turns out that efficient processes benefit all parameters – speed, cost, and quality improved together. Far from cutting corners, the project’s lean approach actually built in quality upfront, enabling later acceleration.

Each of these points shows how a real project outcome can overturn traditional pessimism in EPC. The success in this industrial project is evidence that with modern approaches, what used to be “impossible” (like 99% first-time-right or major schedule gains without extra costs) is now achievable. It encourages project professionals to rethink assumptions and be open to new methods grounded in data and lean principles.

Conclusion

Matei Kevenaar and the team’s implementation of a data-driven way of working on the EPC project stands as a landmark example of what is possible in project execution. By clearly defining success from the client’s perspective and relentlessly focusing on the end-goal (a facility running as planned), the team aligned their efforts with business outcomes. They applied key success factors – data-driven tools, transparency, collaborative workflows, and Lean-first-time-right principles – to dramatically improve performance. The Isometric Dashboard became the keystone of this strategy, effectively synchronizing multi-disciplinary tasks and eradicating rework through its prerequisite tracking logic. The causal chain was clear: better information and process discipline led to better results.

The quantifiable achievements (99% first-time-right, 3 months ahead of schedule, reduced hours) are impressive on their own. But beyond the numbers, the project’s greatest achievement may be the cultural shift it created. It showcased how embracing technology and a data-driven mindset can transform an organization’s approach to project delivery. The client reaped the rewards in a smooth, on-time project, and Matei gained first-hand experience in applying data-driven, model-based execution methods that would later inspire his consulting perspective at Buro Matei. As the EPC industry faces pressure to improve efficiency, this success story provides a blueprint: integrate your data, focus on doing things right the first time, and empower your team to continuously monitor and adapt. The result is a project that not only meets its targets, but delivers real, measurable value to the client – the true hallmark of EPC project success.

Sources

The above analysis and statements are supported by Matei Kevenaar’s documented project results and experiences, his described implementation of dashboards and lean methods on the data-driven initiative, as well as his insights on defining project success from the client’s viewpoint. The case demonstrates the effectiveness of data-driven project management in delivering reliable and high-quality outcomes in EPC environments.

This experience reflects work performed under prior employment and is referenced here as a sample case of the success that data-driven project execution can have. These and other methods and insights later formed the foundation of Matei’s consulting perspective at Buro Matei.