Why energy cost accuracy is critical — and why it's so hard to achieve

The high stakes of energy cost calculations

In the world of energy management, investment decisions require a highly accurate assessment of energy savings and cost impact. Unlike other operational expenses where you might have comfortable margins for error, energy efficiency and optimization initiatives typically deliver savings in the low single digits.

When the savings from your energy initiatives are in the single-digit percentage points, your calculations must be accurate to make reliable ROI projections or verify savings from implemented projects. Even initiatives with large savings impact — like onsite solar and storage — will have skewed ROIs if your energy cost calculations are inaccurate. 

Despite the importance of energy cost accuracy, many organizations find it difficult to consistently achieve these tight tolerances using simplified calculations, manual processes, and conventional tools. The challenge is even more acute for enterprises that must achieve high accuracy across hundreds of sites with different load profiles, tariffs, and utility providers. 

Consider these sobering examples: 

1. Our review of one leading third-party tariff calculation tool revealed a median accuracy of 89% across common tariffs at large utilities.
2. A sophisticated Fortune 500 company with dedicated internal energy teams and advanced systems for rate analysis achieved a median accuracy of 86% in their cost calculations across a portfolio of over 150 sites.

An 11-14% error rate doesn't just alter projected savings — it can completely invalidate an ROI and introduce enough uncertainty to impede investment.

Best practices for more accurate cost calculations

Many organizations today use a straightforward method for calculating the financial impact of an energy project: they multiply a blended energy rate by the quantity of energy saved.

The advantage of this methodology is its simplicity, but its major drawback is a lack of accuracy. With the proliferation of time-of-use (TOU) rates, demand charges, net metering, and other complex tariff structures, it’s no longer sufficient to use a blended energy rate to calculate financial savings. Accurate energy cost analysis requires granular interval data and a sophisticated tariff calculator. 

This large discrepancy — between blended rate methodology and a more accurate approach using tariffs and interval load data – is impacting regulatory policy and leading to a tightening of industry standards.  For example, as of November 2025, the California PUC now requires that all solar developers use actual customer interval data and tariff rates when creating savings proposals for homeowners. Although this policy only applies to residential solar projects today, the inaccuracy risk is just as relevant for commercial & industrial energy projects. 

Whether you’re evaluating the ROI on a new solar project, or conducting M&V on an energy efficiency upgrade, there is a better way to evaluate financial impact:

1. Establish your cost baseline. Collect your historical usage data, across at least 12 months at granular (sub-hourly) usage intervals. Calculate total costs by applying the relevant tariff for the time period under evaluation to the baseline load profile.
2. Calculate your utility bill after project implementation. Simulate your post-implementation load profile, across at least 12 months at granular usage intervals. Apply the relevant tariff to calculate costs for the post-implementation load profile.
3. Calculate the difference between your pre- and post- implementation utility bills. Subtract the post-implementation costs from the cost baseline. 

The process is very similar when conducting M&V on a completed project: Determine the counterfactual load profile if you hadn’t implemented the project, apply the relevant tariff, and compare those costs to the actual, post-implementation utility bill. 

At first glance, this methodology seems straightforward. But let’s take a closer look at why it can be so challenging to do this accurately.

Challenge #1: Data Access

Accurate energy cost calculations require 3 key inputs: utility bills, interval data, and tariff information.  None of these are easy to obtain.

• Utility bill data is only available on an account-by-account basis, delivered via PDF with inconsistent formats, and hidden behind outdated utility portals that are difficult to navigate.
• Interval data, if even provided by the utility, is often found in a separate 3rd-party portal requiring different access permissions.
• Tariff information must be accessed from regulatory filings, with tariff books that span hundreds of pages and are nearly impossible to interpret.  

Consolidating, digitizing, and provisioning the needed data to calculate energy costs for one meter can be a daunting task. It quickly becomes unworkable when trying to do it across multiple sites.

Challenge #2: Tariff Identification

Once you have provisioned all of the required data, a fundamental requirement for any energy cost calculation is to know which utility tariff applies to a given meter. The seemingly simple requirement is far more complex than it appears:

• A single large utility might offer dozens of different tariffs
• Each tariff can have multiple versions, riders, and options
• Tariff names on bills are often cryptic abbreviations
• The same tariff might be called different names across statements and utility websites
• Archived/superseded tariffs remain on bills even after utilities publish new tariff documents

An experienced analyst might spend several hours researching a single complex meter to confidently identify the correct tariff. And that's just to identify what tariff you're currently on, not to evaluate alternatives.

Challenge #3: Rate Criteria

Once you've identified the base tariff, accurate cost calculations require navigating a maze of rate criteria — specific parameters that modify how the tariff applies to your meter. Common rate criteria that impact calculations include:

• Connection and Service Characteristics: Primary vs. secondary voltage connection, single-phase vs. three-phase service
• Operational Parameters: Contracted demand, power factor adjustments
• Geographic: Sub-utility territories or zones
• Special rate riders: Green energy, economic development, etc.

What makes this especially difficult is that many rate criteria don't appear explicitly on utility bills. They must be inferred from context clues on the statement, cross-referenced with utility tariff documents, and deduced from charge calculation patterns.

Challenge #4: Utility Data Quality

Even when you've collected all of your data and correctly identified the tariff and rate criteria, there's a fourth obstacle: the underlying data itself is frequently unreliable.

Arcadia often uncovers billing statement issues including estimated consumption totals, overlapping dates, and proration errors. It’s also not uncommon for utilities to publish incomplete interval data, with gaps due to meter malfunctions, communication failures, or utility system issues. 

These issues aren’t isolated to a small number of utilities or accounts.  In a recent review of over 1M billing statements from utilities across the US, we found that 20% of all utility statements had data inconsistencies.

When the underlying data lacks credibility, it can be nearly impossible to make financial decisions with confidence.  

Challenge #5: Calculation Complexity

Even with perfect tariff identification, complete rate criteria, and clean data, actually calculating costs accurately is extraordinarily complex.

Most C&I tariffs include time-of-use periods (rates vary by hour, day, and/or season), demand charges (charges based on the single highest usage interval within a billing period), or both. Other complicating factors include ratchet provisions that reference demand from up to 11 months ago and tiered pricing that changes based on consumption thresholds.

At Arcadia, we run cost validation analyses on 10,000 utility bills per month, and in doing so uncover all sorts of edge cases. Here are a few of the unexpected billing practices we’ve uncovered at some utilities:

• Billing systems are still based on estimates, not interval usage data, even when interval data exists.
• Peak demand measurements are rounded up, which makes a material difference for small-medium C&I sites exposed to high demand charge rates.
• Superfluous information is shown that has no impact on billing calculations. As one utility representative admitted to us when asked about a peculiar data point, “I am not sure why we include it on the bill except to confuse the customer.”

We frequently find utility calculation methods that are not documented in public tariff sheets and only appear in billing system code. These can be nearly impossible to decipher without a robust cost validation process that is tested at scale across hundreds of meters.

Challenge #6: Scale and Maintenance

All of the above challenges compound when you try to operationalize them.

Enterprise portfolios may have hundreds or thousands of facilities with multiple meters per facility, each with unique load profiles and tariff applicability. Results need to be standardized and comparable across sites to inform energy investment allocations. 

Data collection must be automated and continuous, as utilities publish 75,000+ tariff updates monthly across North America, facility usage patterns change, and portfolios change due to new locations, closed sites, and changes of ownership. 

Achieving high accuracy requires deep expertise and extensive automation, but building both is prohibitively expensive for most organizations.

What's Needed: A Different Approach

How do you verify your energy cost calculations are correct? The only ground truth is to triangulate data inputs against actual utility bills. This means you need to:

1. Calculate costs with usage data and a tariff calculator.
2. Compare to actual bills.
3. Investigate discrepancies. (Is it your calculation, the utility’s calculation, the data, or the tariff?)
4. Iterate until you achieve consistent accuracy.

Doing this for one meter is painstaking. Doing it for thousands, continuously, is nearly impossible.

Solving these challenges requires:

• Comprehensive data coverage to access bills, interval data, and tariffs for your entire site portfolio
• Automated tariff identification at scale across all tariff-meter combinations
• Comprehensive rate criteria mapping that surfaces hidden parameters
• Robust data quality validation through systematic triangulation
• Verified calculation accuracy proven through bill recreation, not just claimed
• Continuous maintenance as tariffs, portfolios, and data evolve
• Subject matter expertise to handle edge cases and complex scenarios

Most importantly, these capabilities need to work together as an integrated system—not as separate point solutions that create new gaps between them.

In our next post, we'll explore how Arcadia's Automated Tariff Assignment and Cost Validation Service address these challenges through a combination of advanced automation, proprietary data assets, and deep utility data expertise—achieving 99% accuracy at a scale that's never been possible before.