Where Does the Time Go?
Measuring the hidden work and rhythms of major clean-energy project development
One of my partners, a former investment-bank CEO with an intimidating presence, was known for roaming the trading floor, pulling up a chair beside a new hire, and asking a simple question: “What do you do all day?” Those who survived the moment would recite their book. He would interrupt: “No, what do you actually do?” Then he’d walk away, leaving the trader to wonder whether they still had a job.[1]
Time studies, which are foundational to business efficiency, emerged with early scientific management in the late nineteen century and have evolved from Frederick Winslow Taylor’s stopwatch-based observations to AI-driven analytics. (Zong and Guan 2024) Recent literature applies similar thinking to major energy infrastructure, measuring lead times, construction durations, and delay drivers across renewables, oil and gas, and power grids. (Clapin and Longden 2024; Hajiakhondi et al. 2025; Kabanda et al. 2021) This work increasingly recognizes that pre-investment development is inherently multidisciplinary: engineering defines technical feasibility, while commercial, financial, legal, and stakeholder processes ultimately determine whether projects proceed. (Floricel et al. 2023; Memić et al. 2023; Lam and Law 2018)
Despite growing interest in shortening project development cycles in Canada and elsewhere, three significant knowledge gaps remain regarding pre-investment timelines. First, major project studies lack quantitative, data-driven analysis of pre-investment effort across disciplines, relying largely on qualitative descriptions.[2] Second, early project development phases, such as site feasibility, permitting, offtake contracting and project financing, are under-measured due to inconsistent data definitions and limited public records.[3] Third, the literature remains fragmented across professional silos, with few cross-disciplinary studies quantifying the relative roles of technical, commercial, and financial work in shaping investment decisions.[4]
To address these gaps, this data story presents a granular, four-year analysis of a $200-million clean-fuel project in Canada, spanning January 2022 to December 2025. The timeframe closely aligns with the typical period a development-stage project remains on Canada’s Major Projects Inventory before either graduation to construction or dropping out.[5] It reveals a lived reality of development that is far from the linear progression often imagined.[6] The findings uncover a hidden rhythm, with work oscillating between high-pressure surges driven by internal currents and external shocks, and long stretches of waiting where momentum threatens to leak away. Structurally, progress follows a logistic S-curve: a slow accumulation of effort accelerates into a steep momentum phase before tapering into a long tail of fragmented coordination as the project approaches investment decisions.
Perhaps most significantly, the data story empirically confirms and quantifies the project’s multidisciplinary development mix. Commercial and finance activities emerge as the project’s backbone, accounting for roughly 50% of total logged hours over the full period. Engineering and design effort, by contrast, represents about 25% overall, peaking early at 32% as technical uncertainty is reduced, before declining to 11% as emphasis shifts toward permitting and regulatory processes. It also confirms that experience carries the load. Directors consistently contribute roughly half of all annual hours (42% to 48%), indicating that project maturation depends less on junior execution and more on senior judgment, negotiation, and institutional coordination.
The analysis draws on a detailed, item-level dataset comprising more than 16,000 entries documenting professional and technical work associated with a single energy project. [7] The dataset records hours spent on discrete work actions, ranging from communications, such as meetings and emails, to tangible outputs, including documents, spreadsheets, and presentations.
The data story is subject to several limitations. First, it is based on a single case, which constrains the extent to which the findings can be generalized to other projects, sectors, or settings. Second, effort is measured using professional activity logs, which may not fully capture offline work or informal, unrecorded interactions. Third, the project’s temporal rhythm was shaped in part by a specific set of internal and external events or shocks that warrant further study. For example, it remains unclear to what extent the prolonged lull and late uptick observed in 2025 reflect structural features of project development versus context-specific disruptions, including a period of heightened policy uncertainty, the resignation of Canada’s prime minister in January 2025, the subsequent federal election in late April 2025, and the announcement of several major government initiatives in the fall of 2025.
So, when a partner asks, “What do you actually do?”, there is now a data-driven answer for major clean-energy development. Progress unfolds in pulses shaped by both internal dynamics and external deadlines and shocks, with commercial and financial work forming the project’s structural spine. Engineering reduces uncertainty early, but senior-level experience—judgment, negotiation, and hands-on direction—ultimately carries the project to the brink of investment. If Canada wants to accelerate major project delivery, it must measure, value, and design for this reality.
Please click on the button to view the full interactive data story for dynamic charts and layered narrative. Below is a static version of the data story. Curious readers are encouraged to scroll down and read the notes.
Project development timelines are often imagined as linear, orderly progressions. The lived reality is far messier. This weekly effort index aggregates professional activity for a major clean-energy project on a normalized 0–100 scale, revealing bursts, stalls, resets, and fatigue cycles over a four-year period. Peaks correspond to moments of intense effort and momentum, while troughs reflect periods of waiting and uncertainty. The overall decline in effort suggests a transition from creation to institutionalization, as decision-making shifts to external actors and progress becomes driven by third-party approvals rather than internal dynamics.
This effort-intensity band compresses four years of work into a single strip, revealing two clear patterns. First, darker, high-intensity periods arrive in waves, driven by internal project dynamics as well as external deadlines or shocks. Second, the lighter, low-intensity weeks are not empty. They are filled with monitoring, correspondence, preparation, and informal discussions. These “light” weeks are essential to project continuity but are rarely budgeted, measured, or acknowledged. The real risk lies not in the dark-shaded periods, but in the pale stretches, where momentum can quietly leak away.
Structurally, progress follows a logistic S-curve: a slow accumulation of effort accelerates into a steep momentum phase before tapering into a long tail. The early development ramp (0%–20%) is slower because the project is still taking shape. The middle, steeper segment (20%–80%) is where execution becomes iterative and repeatable, and momentum builds so that each week adds a meaningful increment to the cumulative total. The final tail (80%–100%) flattens as deliverables near completion and remaining work fragments into smaller tasks, dependency waits, and stakeholder interactions. Effort continues, but it becomes less concentrated, and the curve’s slope steadily declines.
Recent studies of the pre-investment phases of major infrastructure projects show that the work is inherently multidisciplinary, rather than purely technical. This analysis both confirms and quantifies that mix. Commercial and finance activities form the project’s continuous backbone, accounting for more than 50% of total logged hours. Early in the process, engineering and design reduce technical uncertainty by increasing project definition, which in turn raises complexity around contracts, risk allocation, and financing. As the project matures, technical effort shifts from engineering and design toward permitting and regulatory work and project management, while commercial and finance activities remain the centre of gravity required to reach a final investment decision.
Across the four years, effort remains consistently weighted toward senior roles. Directors account for roughly half of total hours each year, reflecting the sustained demands of governance, structuring, and stakeholder coordination across the project lifecycle. Managers and associates provide steady execution support, but the overall balance does not shift materially over time. This pattern reinforces a central theme: as projects mature, progress depends less on routine tasks and process management, and more on the judgment, negotiation, and accountability carried by experienced leads.
Notes
[1] Variations of this anecdote are corroborated by several first-hand accounts.
[2] Major project development is often described as complex and multidisciplinary, yet it is rarely measured that way. While manufacturing and software development has almost certainly benefitted from quantitative analysis of effort, infrastructure pre-investment studies remain largely vague and imprecise, mostly relying on narratives, heuristics, and qualitative frameworks rather than data-driven research. (Gumber et al. 2024; Memić et al. 2023)
[3] Front‑end development is widely seen as a critical phase but it lacks clear theorizing and standardized measures of performance. As a result, development success is often conflated with overall project success. (Abdallah et al. 2022) Yet a decision not to proceed can itself be a successful outcome. The purpose of development is to resolve uncertainty at the least cost. When that process reveals misaligned risks, returns, or constraints, terminating a project preserves capital and frees up resources for other potential projects. Development success, therefore, lies not in reaching construction, but in enabling a timely, informed decision to build or to walk away.
[4] One possible explanation lies in the multitask principal-agent framework developed by Nobel laureates Bengt Holmström and Paul Milgrom. (Holmstrom and Milgrom 1991) The development of major projects is a high-risk venture dominated by principals and supported by agents. Principals are equity holders (including founders and vested employees) as well as third-party entrepreneurial actors, such as investment bankers and business developers, who perform multiple, varied tasks, many of which are difficult to observe or measure. They are typically compensated through high-powered incentives tied to a single, easily verifiable outcome, such as achieving a final investment decision or reaching commissioning. Agents, by contrast, are providers of professional services, including engineers, lawyers, accountants, and consultants. They are generally paid on an hourly or fixed-fee basis rather than through contingent or success-based compensation. These agents are trained and incentivized to maintain detailed time records, sometimes to the point of perverse behaviours, while principals tend to focus almost exclusively on the outcome itself, not on how much time it took to achieve it. This asymmetry creates the potential for a systematic, incentive-driven measurement bias, limiting the validity of cross-disciplinary comparisons in studies of project development effort and time.
[5] Based on an analysis of 851 projects first appearing on Canada’s Major Projects Inventory (MPI) between 2018 and 2020, the average duration a project remains is 4.2 years, with a median of 4.0 years. (Government of Canada 2024) Projects that entered the MPI between 2018 and 2020 would, on average, reach a decision point (construction or attrition) around 2022 to 2025. The four-year window analyzed here is consistent with the modal development duration observed in the MPI data and provides a reasonable point of reference for typical pre-investment timelines in similar Canadian clean-energy projects.
[6] The linear model is no longer seen as an accurate general description of how innovation and development work, but it persists as a simplified heuristic in the policy sphere. (Godin 2025)
[7] Each record includes a timestamped activity and was cleaned, standardized, and coded to enable quantitative analysis. Temporal fields were normalized to ensure consistent alignment across the full study period. Activities were classified by workstream (e.g., Engineering & Design, Commercial & Finance, Permitting & Regulatory, Project Management). Narrative description fields were reviewed and coded to preserve contextual detail on the nature of work performed. Quantitative effort was recorded in hours (rounded to one decimal place) and validated for completeness and internal consistency. References to specific project artifacts were retained to link recorded effort to concrete deliverables and decision processes.
References
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