The Real Cost of Manual EPD Data Collection

Where the hours actually go

Manual EPD prep is a relay race across functions. Someone pulls utility bills, someone else reconciles SAP exports, another chases suppliers for mill certs, and a PM stitches version control together. Context switching and rework creep in like pop‑up ads. Thats time you do not get back.

Reliable benchmarks for this internal effort are scarce by design because every factory, data estate, and PCR differs. Treat your own last three EPDs as the only dataset that matters.

Log it once and get a baseline

Pick three recent EPD projects. For each, capture who touched data, what they did, and how long it took. Do it retroactively from calendars and email trails if needed, then track a live project for four weeks to fill gaps. Keep the log tiny so people actually use it.

A simple, repeatable log structure

• Task name and artifact gathered
• System of record and where the file ended up
• Person and role
• Start time and stop time
• Rework minutes and why it happened

Two reviews later you will see the hotspots. Typical culprits are supplier outreach loops, unit conversions, and missing lot‑level detail that forces a second pass through the shop floor.

Turn hours into dollars, fairly

Convert time to cost with publicly available pay data so finance trusts the math. Median hourly wages in U.S. manufacturing‑relevant roles are a good anchor, for example $58.39 for industrial production managers and $48.63 for industrial engineers, with environmental scientists at $38.49 per hour (BLS OOH, 2024, BLS OOH, 2024, BLS OOH, 2024).

Load those wages to reflect true employer cost. Benefits represent about 29.5 percent of private industry compensation in December 2024, so a quick loaded rate is wage divided by 0.705, or wage multiplied by roughly 1.42 (BLS ECEC, 2025).

A quick calculator you can copy

Use this lightweight model. Keep it in a shared sheet so assumptions are visible.

Internal cost per EPD = Σ(role hours × median hourly wage × 1.42)

Example illustration only

• Production manager 12 h × 58.39 × 1.42
• Industrial engineer 16 h × 48.63 × 1.42
• Environmental scientist 10 h × 38.49 × 1.42
• Product manager 6 h × your wage × 1.42

Sum it. That is your baseline internal cost before any external consultant or verifier sees a file. Adjust hours to your logs and swap wages with company‑specific rates if you have them.

What causes delay and rework

Manual collection usually contends with three frictions. Source systems that were never designed for LCA evidence, supplier data that arrives as PDFs with inconsistent units, and approval chains where a tiny detail needs a plant manager’s signoff. Each friction adds touches and calendar time. The LCA itself may be clean yet the pre‑model pipeline keeps slipping.

What good automation should displace

Automation is not magic. It should do specific jobs that your highest value people currently do by hand.

• Pull structured data from ERP, MRP, energy meters, and QMS with field mappings that match the PCR scope
• Normalize units, apply QA checks, and flag missing fields so rework happens once, not three times
• Maintain an auditable trail so third‑party verification questions are answered in minutes, not days

If a platform or service cannot demonstrate those three movements on your actual data, it will not reduce your baseline cost.

Evaluate platforms on internal labor saved

When budgets are already committed to consulting retainers, the business case hinges on displaced internal labor and avoided delay. Ask vendors to estimate touches removed per artifact and show it live on one product. Tie their claim to the hours you logged. If a connector removes three supplier chaser emails per declaration and eliminates one plant walkthrough, your model will show the impact without any hype.

Budget for the renewal cycle too

Your baseline is not a one‑off. Collections repeat for renewals, product changes, and new plants. A small internal friction multiplied by every renewal becomes a large number. Recording touches now prevents “we forgot how hard this was” next year.

Make the case to finance in three slides

Slide 1 shows the baseline table with roles, hours, and loaded rates plus your total internal cost per EPD. Slide 2 maps specific manual steps to the automation features that replace them. Slide 3 runs two scenarios that reduce only the steps you can prove. Finance teams respond to what is measured and attributable.

Tie the math to specs and revenue

Buyers on projects with carbon targets prefer products that come with third‑party verified EPDs because the accounting is clear. When internal friction drops, more SKUs get covered faster, and bids stop stalling while data is hunted down. That improves win rates without racing to the lowest price. We have seen that the time you free in R&D, product, and the plant is the real dividend, because those teams focus on what moves spec decisions.

The payoff

Quantify your manual baseline once, translate it with public wage data, and test automation against your real bottlenecks. If the internal hours fall in your logs, the business case writes itself. If not, keep the baseline and revisit. Either outcome makes the next EPD easier and faster, which is the point.