EPC Reporting Automation: A Case Study in Time Recovery
Editorial note: this article provides operational guidance. Examples and planning signals must be validated against your organisation’s own data, controls, and delivery context; they are not a promise of client outcomes.

Every Monday morning, the project controls team at a 180-person EPC contractor in Queensland spent the same three hours doing the same thing: opening twelve spreadsheets, copying numbers into a master template, chasing three project managers for updates that were already two days late, and producing a status report that the leadership team would read on Tuesday — by which point some of the data was already wrong.
This is not an unusual story. It is the standard operating procedure at most mid-size EPC and infrastructure companies. The question is not whether it is inefficient. The question is what it actually costs, and what it takes to fix it.
The Situation Before
The company ran six concurrent civil infrastructure projects across Queensland and New South Wales, ranging from $8M to $45M in contract value. Each project had a dedicated project manager and a site supervisor. Weekly reporting was the responsibility of the project controls team — two people — who consolidated inputs from all six projects into a single portfolio status report for the executive team.
The process looked like this:
- Each project manager submitted a weekly update via email by Friday 5pm (in practice, most arrived Saturday morning or Monday)
- The project controls team manually extracted key metrics from each update and entered them into a master Excel template
- Budget data was pulled separately from the company's accounting system — a manual export and VLOOKUP exercise
- The completed report was emailed to the executive team by Monday midday
- Any errors or missing data required back-and-forth with project managers, often delaying the report until Monday afternoon
The Numbers
| Metric | Before |
|---|---|
| Weekly reporting hours (project controls) | 8 hrs |
| People involved in report production | 3 (2 project controls + 1 finance) |
| Report delivery time (from week end) | ~40 hours (Friday 5pm → Monday midday) |
| Data accuracy rate | ~82% (errors caught in review) |
| Late report frequency | 3 out of 4 weeks |
| Estimated annual cost of reporting overhead | ~$47,000 (fully loaded) |
The Assessment
The Workflow Intelligence Assessment took 35 minutes. We mapped the full reporting workflow end-to-end, identified the three manual steps consuming the most time (data extraction from project manager emails, budget reconciliation from the accounting system, and formatting the master template), and scored the automation potential of each.
The assessment produced a Workflow Efficiency Score of 31 out of 100 for the reporting workflow — indicating high automation potential. The ranked opportunity list identified weekly status reporting as the highest-ROI automation target, with an estimated implementation effort of four to six weeks and a projected time saving of 7–9 hours per week.
Key Finding
The primary bottleneck was not the report itself — it was the data collection step. Project managers were submitting updates in inconsistent formats across email, WhatsApp, and a shared drive. Standardising the input format was the prerequisite for any automation to work.
What Was Built
The implementation had three components:
- A structured weekly update form (Microsoft Forms) replacing free-text email submissions, with mandatory fields for each key metric. Project managers complete it in under 10 minutes.
- An automated data pipeline connecting the form responses, the accounting system export, and the master report template. Built on Power Automate with a Python data transformation layer.
- An AI summarisation step that reads the structured inputs and generates the narrative sections of the executive report — progress highlights, risk flags, and action items — in the company's existing report format.
Total implementation time: five weeks, including two weeks of parallel running where the automated report was produced alongside the manual report and compared for accuracy.
The Results
| Metric | Before | After |
|---|---|---|
| Weekly reporting hours (project controls) | 8 hrs | 45 min |
| People involved in report production | 3 | 1 (review only) |
| Report delivery time (from week end) | ~40 hours | 2 hours (automated Sunday night) |
| Data accuracy rate | ~82% | 97% |
| Late report frequency | 3 out of 4 weeks | 0 (fully automated) |
| Annual cost of reporting overhead | ~$47,000 | ~$9,000 (review time only) |
The project controls team recovered 7.25 hours per week. The executive team received the report in their inbox by 6am Monday — before the working week started — for the first time in the company's history. Data accuracy improved from 82% to 97% because structured form inputs eliminated transcription errors.
What the Numbers Don't Capture
The financial return — approximately $38,000 in annual overhead reduction — is the easy part to quantify. What is harder to put a number on is the quality of executive decision-making when leadership has accurate, timely data at the start of the week rather than the end.
In the six months following implementation, the company identified two project cost overruns earlier than they would have previously — one at week four of a twelve-week schedule, rather than week eight. The project manager attributed this directly to having accurate budget data available on Monday morning rather than having to request it from finance mid-week.
The Real Return
The $38,000 in direct cost savings paid for the implementation in under four months. The earlier identification of cost overruns — and the additional response time that created — is worth considerably more, but it doesn't appear on a cost-benefit spreadsheet.
What This Means for Your Organisation
This case is representative of what we see across EPC and infrastructure companies of similar size. The specific numbers vary — some companies recover more hours, some less — but the pattern is consistent: manual reporting is the highest-volume, lowest-value use of project controls time, and it is almost always the first workflow we automate.
The Workflow Intelligence Assessment takes 30 minutes. If your team spends more than two hours per week on manual report consolidation, the ROI case for automation is almost certainly positive. The question is not whether to automate — it is which workflow to start with and how to sequence the implementation.
Kumash Shah
Principal Consultant, Kresto Consulting
Kumash Shah is a Principal Consultant at Kresto Consulting, specialising in AI workflow transformation for project-based companies. With experience across EPC, infrastructure, and engineering environments, he helps organisations identify and implement practical AI solutions that drive measurable operational improvement.
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