If you run C&I solar projects, you have probably had this debate internally at least once: should we keep paying consultants to run our ASTM E2848 capacity tests, or should we bring it in-house?
Having talked to enough EPCs, developers, and asset managers, I can tell you there is no universal right answer. But there is a wrong way to make the decision — and that is defaulting to "how we have always done it" without actually running the numbers.
Here is a framework that cuts through the noise.
The Three Variables That Actually Matter
1. Test volume per year
This is the single biggest driver. If you are running one or two capacity tests a year, a consultant relationship probably still makes sense — the fixed cost of building internal expertise and tooling is not worth it for occasional use.
But once you cross into three or more tests a year, the math starts to flip. At roughly $3,000 per site for external consultants, a team running five tests annually is spending $15,000 a year on something that could be standardized and brought in-house for a fraction of that cost.
2. In-house technical expertise
ASTM E2848 is not trivial. It requires understanding regression modeling, data filtering criteria, weather normalization, and how to interpret a failed test rather than just reporting one. If your team has PV or project engineers who already understand system performance — even if they have never run a formal capacity test — the learning curve to bring testing in-house is manageable, especially with the right tooling.
If your team has zero engineering bandwidth for this, an external consultant's expertise is doing real work you would otherwise have to build from scratch. That is a legitimate reason to keep outsourcing, regardless of volume.
3. Tolerance for process risk
This one gets overlooked. Custom Excel or Python-based in-house tools introduce their own risk: inconsistent methodology between engineers, version control issues, and the occasional regression error that goes unnoticed until it causes a failed audit. If you are bringing testing in-house without a standardized, repeatable process, you may be trading one risk (consultant cost and opacity) for another (internal inconsistency).
Teams that successfully bring testing in-house usually do one of two things: they invest significant time building rigorous internal documentation and QA around their spreadsheet process, or they adopt purpose-built software that enforces the standard's methodology by design.
A Simple Way to Think About It
| Low volume (1–2 tests/yr) | Moderate volume (3+ tests/yr) | |
|---|---|---|
| Low internal expertise | Consultant makes sense | Consultant, or software with guided workflows |
| Moderate-to-high internal expertise | Consultant (unless cost is a major concern) | In-house — via standardized tooling, not ad hoc spreadsheets |
The pattern: volume changes the economics, but expertise (or the right tooling to compensate for its absence) changes the risk profile. You need both favorable economics and manageable risk to justify moving away from consultants.
What Most Teams Get Wrong
They evaluate this decision purely on cost — "consultants are expensive, let's do it ourselves" — without accounting for the process risk of ad hoc internal tooling. A failed audit or an incorrectly reported test result costs far more than the money saved by cutting out the consultant.
This is the same trap that catches teams who underestimate the real cost of Excel-based capacity testing: the hidden engineer hours, silent formula errors, and missing audit trails rarely show up in the initial cost comparison.
The teams that make this transition successfully treat it as a process change, not just a cost-cutting exercise. They ask: how do we get the cost savings of in-house testing without losing the standardization and reliability a consultant was providing?
How HelioTest Fits This Decision
The reason this decision has traditionally been binary — expensive consultant or risky spreadsheet — is that there was no middle option. Purpose-built software changes that. HelioTest is built to give a team the cost profile of in-house testing with the standardization a consultant provided, by enforcing the ASTM E2848 methodology directly in the workflow.
That matters most for the two variables where in-house teams get into trouble. On expertise, guided workflows walk an engineer through regression setup, data filtering, and reporting-condition calculation, so a team that understands PV performance but has never run a formal capacity test does not have to build that knowledge from scratch. On process risk, the methodology is applied the same way on every test and every engineer, and each run produces an audit-ready report — no version-control drift, no per-engineer spreadsheet variance.
It also handles the cases that make ad hoc tooling brittle in the first place, such as multiple array orientations, bifacial modules, and GHI-only sensor setups, natively — so bringing testing in-house does not mean writing custom scripts for every non-standard site.
Key Takeaways
Whether to keep using a consultant or bring ASTM E2848 capacity testing in-house comes down to three variables: your annual test volume, your in-house technical expertise, and your tolerance for process risk. Volume changes the economics; expertise and tooling change the risk profile. You need both in your favor to justify the move.
The teams that get this right do not treat it as a simple cost-cutting exercise. They treat it as a process change — and they look for a way to capture the savings of in-house testing without losing the standardization and reliability a consultant provided.
If you are weighing this decision for your own team, HelioTest offers a free tier so you can try the in-house workflow on your own data before committing to a change.
Peter is an engineer with a PhD in renewable energy management and over a decade of experience in software development for renewable energy applications. He built HelioTest to replace the fragile spreadsheet workflows he encountered across dozens of ASTM E2848 capacity tests.
