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Energy and sustainability managers are stretched thin—and not always because they’re busy implementing energy efficiency upgrades or innovative sustainability initiatives, but because they’re bogged down in administrative drudgery.
From chasing down utility bills across dozens of accounts to crunching consumption data in spreadsheets, a huge portion of an energy manager’s time is spent on manual tasks that don’t directly reduce a single kilowatt-hour of usage or unit of emissions. Real estate organizations waste hundreds of hours annually on manual utility bill processing—time that could be spent on strategic energy initiatives.
Lauren Trapp (sustainability manager) and Brandon Money (energy manager) from AFL told us that automation cleared their plates and enabled them to tackle more strategy projects like Scope 3 emissions and waste management. Brandon said software allows him “to focus more on our overall Scope 1 and 2 reduction strategy, capital investment strategy…on site solar installations, [and] capital budgeting… and [spend] less time punching numbers into Excel.”
This busy work not only saps productivity, it also contributes to errors and missed opportunities. It’s no wonder that according to the World Economic Forum, only about 9% of companies have fully embraced software tools for managing their energy and sustainability data—the vast majority still rely on spreadsheets and manual effort.
Fortunately, energy management software providers are getting really good at handling the “dirty work” of energy management—the tedious, time-consuming workflows required to gather and organize data and keep on top of energy expenses—so that energy managers can refocus on higher-value projects.
We’ve covered a lot of ‘sexy’ capabilities of energy management software before (most notably in our Buyer’s Guide to Energy Management Software), but we haven’t yet celebrated the basic dirty work that energy managers don’t need to do anymore. Instead of spending hours wrangling utility data or preparing reports, energy managers can spend their time implementing efficiency projects, optimizing systems, and planning sustainability strategy.
Kris Zebrowski, former energy manager at Cushman Wakefield and now Customer Success Manager at Atrius, found that automation enabled him to focus on the work that actually saved energy. “All of that was gone, and we could really focus on the work of identifying outliers, looking for energy conservation measures, and doing what I consider the fun part of energy management.”
Critically, integrating software into energy management workflows goes beyond labor savings and having more fun, it’s enabling tasks at a scale that would be impossible to handle manually. Gridium’s VP of Product and Cofounder Adam Stein emphasizes that trying to perform detailed energy analysis across a whole building portfolio without digital tools simply doesn’t pencil out:
“In a practical sense, no, it’s not possible … I suppose you could do [it] manually. Would you? Would you trust it? If you were trying to do this across a portfolio, it would be an enormously daunting task. So no, practically speaking, this is not something you could do on your own.”
This article dives into how software is transforming the day-to-day job of energy management. We’ll examine five “dirty jobs” that modern energy management platforms handle—from utility data wrangling to tariff analysis—and how offloading these tasks to digital tools is freeing up energy professionals to concentrate on the impactful work of actually improving buildings’ energy performance.
Along the way, we’ll highlight real-world insights from experts at Gridium, Arcadia (which acquired the utility data specialist Urjanet), Atrius from Acuity Intelligence Spaces, and Backpack Group, and we’ll ground the discussion in the realities of what software can and can’t do today.
The foundation of any energy management program is having access to timely, accurate utility data. Every month, energy managers need to compile data on electricity, gas, water, and other utilities for each site—usage, costs, demand charges, taxes, you name it.
The problem is, this data usually comes from a patchwork of sources: different utility companies (each with their own billing format or website), third-party suppliers, and perhaps on-site generation meters. The data is often scattered across paper bills, PDFs, and online portals, in inconsistent formats that are a nightmare to consolidate. As Gridium’s Adam Stein points out, “utilities are not presenting their data in a way that is convenient to use. If you manage a portfolio of real estate, you probably have many utility accounts, and your data is scattered across those accounts and not in a structured format.”
In the U.S. alone, there are over 3,000 electric utilities, each with different billing systems and data access methods. Simply retrieving all that information and standardizing it can consume an enormous amount of time and effort. Even if a utility offers an API like Green Button, an individual energy manager isn’t likely to write their own software to pull that data together.
This is why many energy teams are now leveraging utility data automation services. Companies like Arcadia have built platforms to streamline and aggregate billing data billing data from virtually any utility. In Arcadia’s case, their platform covers 95% of residential and commercial accounts in the US and data from 9,500+ utilities across 52 countries, all delivered via API in a unified format.
Instead of an energy manager logging into dozens of different utility websites each month, the software connects to each account (handling all the login credentials behind the scenes), pulls the latest bills and meter readings, and ingests them into a single database. The data is normalized into a consistent data model—unit conversions handled, rate components separated, correct labels applied—so that utility data looks and behaves the same way, regardless of source. This work is a huge time suck—A study from EnergyCAP estimates its customers save on the order of 23–37 hours of staff time per month by automating utility bill capture—which makes the ROI calculation stark.
It’s telling that even other energy software vendors often don’t reinvent this wheel—they piggyback on specialized utility data acquisition platforms. Atrius and Backpack Group, for instance, integrate with Arcadia’s Plug API rather than building their own utility scraping tools from scratch. By outsourcing the heavy lifting of utility data aggregation to a dedicated provider, they spread the cost across many clients and ensure coverage of thousands of utilities.
Utility data is often incomplete or inconsistent in ways that make it unreliable for energy managers who rely on it for reporting, budgeting, and decision-making. Gaps in usage data, incorrect unit conversions, and misaligned reporting formats can all create problems that ripple through an organization’s energy strategy.
In AFL’s spreadsheet days, data quality and completeness were constant headaches. “There was… human error, had to go back and forth with people so many times… it was very frustrating and just inefficient because… we could all be doing better things with our time,” Lauren Trapp admitted. Manual data management not only wastes time but also causes staff burnout and lost opportunities. Rather than leaving energy teams to hunt down discrepancies manually, modern energy management software also automates the error-checking process, flagging anomalies before they create bigger issues.
“We have data quality checks in place—does your bill total add up correctly? If not, it spits out an error so you can fix it before it causes bigger issues,” explains Atrius’ Sustainability Product Manager Chelsea Davis. Their system also proactively monitors for missing data. “If something doesn’t match historical trends, we flag it so the energy manager doesn’t have to find out the hard way,” she adds. These safeguards ensure that gaps in utility usage data are identified early, preventing reporting errors and compliance headaches down the line.
For organizations that integrate real-time meter data, Atrius takes validation further by cross-referencing actual interval readings with utility billing data to ensure alignment. “If a customer has sub-metering in place, we can compare that against the utility bill data to catch anomalies before they get billed incorrectly,” Davis explains. This means that energy managers don’t just have to trust that their data is accurate—they have real-time verification that their reported energy use actually reflects what was consumed.
Since energy management data comes from multiple sources, vendors must make sure the units, reporting structures, and timeframes align so that energy managers can work with a consistent, error-free dataset. Without this kind of automated validation, discrepancies—such as a meter reporting in kBTUs instead of MMBTUs, or missing days in a billing period—could easily lead to faulty conclusions about building performance.
Once the data is aggregated and checked, software vendors then add additional context to enable the data to be useful in the energy management process. As an energy manager, you might interact with analytics, alerts, or reports, which require a lot of behind-the-scenes work to normalize, structure, and enrich utility data so energy managers can actually use it to make decisions.
Backpack Group’s Daniel Kaplan explains how their system uses a structured data model that enables real-world use cases. “Once we have everything in a nice little package, we can then build upon it,” he says. “We structure the data for ENERGY STAR Portfolio Manager, for tenant vs. owner-paid breakdowns, for emissions reporting, for projects and capital planning. Once the blocks are there, we can use them however we need to.” Instead of leaving energy managers to wrangle raw utility bills and spreadsheets, the software standardizes everything into a format that can be applied across different reporting and analysis needs.
This work goes beyond just the energy meters themselves. The software maps energy consumption to tenants, spaces, equipment, and even operational data from building automation systems. “Utilities is one arm of our data model,” Kaplan says, “but so is tenants, spaces, equipment, projects, documentation, and even operational data like building automation system inputs and weather data. This way, energy managers can analyze energy consumption in context.”
The system can map everything correctly without manual intervention by automatically pulling in building characteristics from leasing documents, space plans, or previous reports. “All the property team needs to do is upload a stacking plan or leasing documents,” Backpack Group’s Cody Bond explains. “We have a rules engine that takes that information and maps it where it needs to go.” This kind of automation removes the guesswork from reporting and ensures compliance data is accurate—without hours of manual spreadsheet work.
Ultimately, the biggest value software provides isn’t just utility bill collection—it’s making data usable. Energy managers don’t just need numbers; they need insights. By structuring energy, property, and equipment data in a way that’s actionable, software platforms ensure that energy managers spend less time wrestling with data and more time turning insights into energy-saving projects.
A significant chunk of energy management work doesn’t involve engineering—it involves accounting and finance. Every year, energy managers are asked to develop utility budgets and forecasts for their facilities. Every month, they have to approve or accrue bills, and often allocate costs to different business units or tenants. These tasks can be mind-numbingly boring but also sneaky complex. Utility costs are not a simple linear function of usage; they involve fixed charges, demand charges, tiered rates, fuel cost adjustments, and other components that can change unpredictably.
For organizations with many sites, budgeting energy spend for the next year is like shooting at a moving target, complicated by volatile energy markets and regulatory changes. “If you are an energy manager who has to come up with a budget every year—we will generate a budget for you based on top of [your historical] data. That’s just a very basic thing, but it’s not easy to do manually,” notes Gridium’s Adam Stein. “Especially if you’ve got supply charges and distribution charges coming from different places.”
In deregulated energy markets, this is even harder because the supply portion (the commodity price of electricity or gas) might be contracted separately from the delivery (utility) portion; each has its own rate structure and both need to be forecasted. Software can crunch years of utility data, account for seasonality, rate changes, and usage trends to automatically project a forward-looking budget—sparing energy managers from endless spreadsheet tweaking and giving finance teams a data-driven estimate of future costs with a few clicks.
Another accounting headache is accruals—booking the cost of energy consumed in a month before the actual bill arrives. As Stein explains, “often you have to file your energy expenses at the end of the month in your accounts payable system, and you don’t actually have the bill yet… you need to file expenses at the close of the month, even if you don’t have [the bill]. We have your interval data, we have your most recent bill, we can do a reasonably good job of estimating those costs for you.” When the real bill comes, the software can reconcile it against the accrual and flag any major differences.
Automating this accrual process is a huge relief for energy managers working with finance departments on tight monthly closes. Stein puts it bluntly: otherwise “you are sitting there trying to download PDFs from different utility accounts and cutting and pasting the values into spreadsheets – that’s the world you’re in. We shouldn’t sleep on [how important] this is.”
Before the bill actually get paid, energy managers (and their accounting departments) lean on software providers to make sure it’s correct. Utility billing errors are more common than most energy managers realize. Utilities process massive volumes of billing data, often using complex rate structures that leave room for mistakes. A misapplied demand charge, an incorrect tariff classification, or even simple clerical errors can all lead to thousands of dollars in unnecessary costs. Historically, energy managers had little choice but to trust that their bills were accurate or spend hours combing through line items in search of discrepancies. But now, energy management software automates the auditing process, flagging billing errors before they become costly problems.
Gridium has built its platform to do just that—identifying when a building is being overcharged, billed under the wrong tariff, or hit with avoidable fees. Stein explains how their system reconstructs utility bills to check for accuracy. “We model utility bills using our rate engine, applying historical interval data to see if the billed amount is correct,” he says. “If there’s a major discrepancy, we flag it for the customer.” Instead of relying on manual audits, software continuously monitors for errors, ensuring that overcharges don’t go unnoticed for months or even years.
“Bill audit opportunities aren’t as frequent, but when they happen, they can be lucrative,” he explains. “A utility billing mistake could be worth tens of thousands in refunds.” For organizations managing multiple properties across different utility territories, these errors can add up quickly, making automated bill audits an essential tool for financial oversight.
Beyond catching errors, software ensures that billing corrections actually get made. Gridium’s platform tracks billing disputes and resolutions, ensuring that energy managers not only catch overcharges but also recover their funds.
Brandon Money from AFL emphasized the importance of being able to audit the historical utility data. “Having robust data…data that’s auditable and traceable is key” as sustainability reporting expectations rise, and “it’s definitely important to have your data in a good system because spreadsheets just aren’t going to cut it.” In hindsight, moving away from Excel to energy management software was not just helpful but necessary for credible, ready-for-audit data.
Automating these bread-and-butter tasks is foundational. It doesn’t have the glamour of AI optimizing your chiller plant, but it might save as much or more time and money in practice and lay the groundwork for bigger energy initiatives to be taken seriously.
One of the more technically complex tasks in energy management is making sure each facility is on the optimal utility tariff or rate plan for its usage profile. Large commercial and industrial users often have options when it comes to utility tariffs: different rate schedules with varying demand charges, time-of-use pricing, peak vs off-peak differentials, etc.
Choosing the best one (or negotiating a custom rate) can yield significant savings, but manually figuring out the ideal tariff is a daunting analytical challenge. You’d have to take a year’s worth of interval data (hourly or 15-min usage), then calculate what that usage would cost under each eligible tariff—which could be dozens of permutations—and compare the outcomes. Historically, this was done occasionally by hiring a specialized consultant or by very laboriously running data through Excel. As a result, many buildings stayed on whatever default rate the utility assigned, even if a better (cheaper) rate was available for their pattern of use.
Today, energy management software can perform digital tariff optimization continuously and in a fraction of the time. Sam Moskal of Arcadia explains that their platform connects three data elements—the customer’s billing data, their interval meter data, and a database of all available tariff structures—to automate the entire analysis.
The software first validates the current bill by re-calculating it from the interval data and the current tariff, then it simulates the customer’s bill under every other applicable tariff or rate option, using the interval load profile to account for demand peaks, TOU periods, etc. The result is a clear identification of the cheapest rate for that historical period. This can reveal if the customer has been on the wrong tariff.
In practice, many commercial customers are on suboptimal tariffs simply because utilities don’t always proactively move them to the best rate. In California, for example, some buildings have saved tens of thousands per year by switching from a general TOU rate to a more appropriate “peak day” tariff once their usage patterns were analyzed by Gridium’s’ tariff optimization algorithms.
They’ve published many case studies demonstrating this, such as at Lincoln Property Company where they found a $75,000 rate change opportunity. It’s common for these analyses to find 5–15% cost reduction opportunities—gold that would remain hidden without crunching the numbers.
What’s really powerful is that software can run these tariff comparisons continuously, not just as a one-time study. Utilities frequently update their tariffs—new optional rates are introduced, prices change with regulatory approvals, pilot programs come and go. A digital platform can keep the tariff library up to date and periodically re-check your cost against new or modified rates. If a better option emerges, the system can alert the energy manager to consider a switch.
This kind of continuous rate optimization was virtually unheard of when it required human effort; no analyst is going to manually recompute bills for dozens of sites every month. But with automation, it’s feasible to revisit the rate decision every billing cycle or every quarter. Arcadia’s team notes that unlike traditional consulting that might take 6–8 weeks to produce a one-time report, their automated rate engine can do it every month and flag if changing conditions (like a new peak demand pattern or a tariff change) mean you should change rates. Essentially, software shifts tariff optimization from a project to a continuous process.
Tariff optimization might not reduce carbon emissions or kWh, but it directly boosts the bottom line, and it’s exactly the kind of high-value analysis that busy energy managers rarely had time to tackle before. Now the “robot” does it for you.
For any energy manager working in a city or state with a benchmarking or building performance ordinance (which is now dozens of major cities and several states in the U.S.) or for an organization that creates annual sustainability reports, complying with ENERGY STAR Portfolio Manager reporting requirements has become a yearly ritual—and often a dreaded one.
ENERGY STAR Portfolio Manager (ESPM) is the EPA’s online tool for benchmarking building energy and water performance. It’s a great tool, but feeding data into it correctly can be surprisingly labor-intensive. You need to input each building’s total energy usage (often by manually entering monthly totals for each utility), along with detailed operational characteristics (square footage, occupancy, space types, weekly hours, number of computers, etc.).
Getting all this data right is crucial to obtain a valid ENERGY STAR score or meet local law requirements. Doing it by hand for a large portfolio is tedious and prone to errors. In Seattle, for example, building owners have been fined for submitting inaccurate benchmarking reports just as they would for failing to report at all. It’s not just a data entry task; it requires understanding Portfolio Manager’s conventions and often digging for information about each building.
Energy management software is making this process far smoother through Portfolio Manager automation. Many utilities claim to offer automatic data upload to ESPM (via web services), but in practice these often only cover single utilities and can be clunky or incomplete. Software vendors have instead built integrations between the utility and Portfolio Manager to automate the flow of data and ensure its quality.
Essentially, these tools take the same utility data discussed earlier (often already aggregated in their platform) and push it to the Portfolio Manager system on behalf of the customer. When it comes time to do the annual benchmarking submission, an energy manager can simply review and hit submit, and the software essentially syncs your data to the Portfolio Manager, eliminating transcription errors and saving time.
However, the trickiest part of Portfolio Manager compliance isn’t just the meter data—it’s the property use details. Portfolio Manager requires you to input how each space is used (office, retail, data center, etc.), with specific parameters for each space type. If you have a complex building, determining and entering these details can become a deep rabbit hole. “The property use side—there could be 10 plus good answers for any given building… You could spend 100 hours in the FAQs to fully understand this,” says Cody Bond of Backpack Group.
Users often feel unsure if they did it right (“Is a professional engineer going to come through and disagree with everything I’ve done?”). To solve this, some software vendors are using expert systems and rule engines. For example, Backpack Group developed a rules engine that asks the property team a series of simple questions (or pulls info from a “stacking plan”—basically the floor-by-floor tenant layout) and then maps that to the appropriate Portfolio Manager input.
Instead of the energy manager manually figuring out how to classify a multi-use building’s areas into, say, “Office – Unrefrigerated Warehouse – Retail,” the software’s decision tree does it for them.
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All the property team might need to do is upload a lease document or fill a short form with tenant types and square footages, and the system will decide the best way to input that into ESPM.
Even with automation, there is recognition that this process might never be 100% automated— vendors pair the software with human expertise. For instance, Backpack Group’s team still reviews the outputs and handles edge cases, acknowledging there’s a need for expert oversight for tricky buildings.
The difference is that instead of each energy manager individually struggling through the Portfolio Manager interface and guidance, the software vendor centralizes that expertise and builds it into a tool that benefits all their customers. This “spread the cost across many” model means one team of experts figure out how to properly account for, say, a building with solar panels plus battery storage in Portfolio Manager (which has some esoteric rules), and then that logic is coded so every client with similar setup gets it right.
The importance of getting Portfolio Manager data right is growing as cities move beyond just benchmarking to Building Performance Standards (BPS)—mandates to improve energy efficiency or emissions over time. “We’re seeing the same thing all over again with building performance standards… reporting around that is very complicated, because the data is just hard to get,” notes Stein.
Some jurisdictions are now requiring not just annual ENERGY STAR scores, but verification of energy and carbon reductions, which ups the stakes. Missing tenant data or incorrectly categorizing a building in ESPM could even lead to financial penalties in these cases (e.g., New York City’s Local Law 97 fines buildings that don’t meet carbon intensity targets).
By automating and validating the inputs, software helps ensure compliance data is accurate and complete. As Stein observed, when Gridium takes over ENERGY STAR reporting for a new customer, they often find the historical data was “just bad… all your old stuff is wrong”, because previous manual entries were inconsistent. With software doing the heavy lifting, those errors can be corrected going forward, and energy managers can be confident that a compliance deadline won’t turn into a fire drill.
As more cities and states adopt benchmarking and performance laws (by one estimate, at least 25% of U.S. commercial floorspace is now benchmarked in Portfolio Manager), this kind of automation is swiftly moving from a nice-to-have to a must-have tool in the energy manager’s kit.
The final dirty job on our list veers into the domain of energy procurement—an area that in deregulated energy markets can be as complex as Wall Street trading, and just as administratively burdensome.
Large organizations often procure their electricity or natural gas from third-party suppliers or through contracts separate from the local utility’s default service. This means energy managers (or their procurement departments or consultants) have to negotiate contracts, manage contract renewals, and develop purchasing strategies (fixed vs. index pricing, block purchases, green power purchases, etc.).
Doing this for one facility is one thing; doing it across a portfolio of dozens or hundreds of sites in multiple regions becomes a massive undertaking. Each contract might have different start/end dates, pricing structures, and risk profiles. Keeping track of market prices and knowing when to lock in rates requires constant vigilance. It’s easy to see how procurement can eat up huge amounts of time and still lead to suboptimal outcomes if not done rigorously.
Energy management software companies are now stepping up to assist with digital procurement advisory. By leveraging the detailed usage data they already collect, these platforms can analyze a customer’s load profile in conjunction with market price curves and help formulate an optimal procurement plan. “What we’re doing is taking the customer’s interval data and pricing it under different scenarios—including just buying from the utility as a baseline—then plugging in futures prices to see what third-party supply would look like, how much you’d pay for hedges, etc., to come up with a plan that balances cost versus risk,” explains Gridium’s Adam Stein.
In essence, the software can simulate outcomes of various procurement strategies: staying fully indexed to market, hedging a portion of usage at fixed rates, trying alternative suppliers, etc., and compute the expected cost and risk of each. This was once the realm of energy consultants producing long reports; now some of it can be done dynamically with software that draws on up-to-the-minute market data.
One notable trend is the integration of procurement functionality via acquisitions. Arcadia, for example, recently acquired a company called RPD Energy—a leader in renewable energy and customized procurement deals. By folding RPD’s capabilities into its platform, Arcadia aims to automate more of the energy purchasing process for customers. Sam Moskal from Arcadia noted that traditionally RPD (and similar brokers) operated in a consultative, somewhat manual fashion, but the goal now is “automating that, making it even faster, so we can serve customers at scale.”
It’s important to note that human expertise still plays a role—these tools augment, rather than replace, energy procurement professionals or consultants. The contracts still need to be signed, and market intelligence (like regulatory changes or supplier credit risk) must be interpreted. But much of the data crunching and coordination can be offloaded.
Gridium, for example, provides advisory services around procurement in deregulated states, using interval data analysis to guide whether a client should buy from a third-party and how to structure that deal. Stein mentions they often see very good savings from such analyses, especially in times when market prices present opportunities. The software essentially provides the analytics backbone, while the energy manager or advisor uses those insights to make informed decisions.
Many organizations have learned the hard way that an expired energy contract can mean a budget blowout; software with a calendar and workflow can prevent that with simple prompts and even handle many steps of the transaction process.
In summary, managing energy supply has traditionally been a high-stakes, complex job that often required separate consultants or brokers. Now, the same energy management platforms handling your utility bills and analytics are increasingly able to handle energy purchasing analyses as well. One could say the software becomes your energy broker’s assistant, constantly watching the markets and your contracts, so you can avoid nasty surprises and capitalize on opportunities to cut costs or buy cleaner energy.
From data grunt work to financial calculations to complex analysis, software is taking on the dirty jobs of energy management, and the impact on the profession is profound. Energy management software today not just about fancy dashboards—it’s also about eliminating drudgery.
The platforms we’ve discussed act like a tireless junior analyst, bookkeeper, and data technician all in one—collecting and cleaning data, checking for errors, producing budgets and reports, optimizing tariffs, streamlining compliance reporting, and prepping procurement decisions. This allows energy managers and facility teams to redistribute their time to the initiatives that truly require human insight and creativity: identifying energy conservation measures, engaging occupants and operators in efficiency efforts, evaluating new technologies, and steering organizational sustainability strategy.
This shift comes at a critical moment because there’s a well-documented workforce shortage in facilities and energy management. With fewer hands on deck, automation isn’t a luxury—it’s necessary to maintain and improve building performance.
Outsourcing the drudgery of energy management to software could also help address one of the biggest challenges we face in scaling up efficiency and decarbonization—the sheer manpower gap to implement improvements across millions of smaller buildings. By augmenting each energy professional’s capability, the industry can do more with fewer people.
Even organizations that don’t have a dedicated energy manager on staff can now pursue energy-saving programs, because software makes it feasible for, say, a property manager or sustainability coordinator to manage energy data and spot opportunities in their spare time.
In practice, the most successful approach is often a hybrid one: let software do what it’s great at (fast data processing, routine tasks, pattern recognition) and let humans do what they’re great at (strategic thinking, stakeholder engagement, nuanced decision-making). Energy managers who use these tools find they can elevate their role. Instead of being seen as “the person who wrangles the utility bills,” they become strategic leaders driving projects that cut costs and carbon. The software fades into the background as a silent partner ensuring nothing falls through the cracks.
All the property team might need to do is upload a lease document or fill a short form with tenant types and square footages, and the system will decide the best way to input that into ESPM.
Even with automation, there is recognition that this process might never be 100% automated— vendors pair the software with human expertise. For instance, Backpack Group’s team still reviews the outputs and handles edge cases, acknowledging there’s a need for expert oversight for tricky buildings.
The difference is that instead of each energy manager individually struggling through the Portfolio Manager interface and guidance, the software vendor centralizes that expertise and builds it into a tool that benefits all their customers. This “spread the cost across many” model means one team of experts figure out how to properly account for, say, a building with solar panels plus battery storage in Portfolio Manager (which has some esoteric rules), and then that logic is coded so every client with similar setup gets it right.
The importance of getting Portfolio Manager data right is growing as cities move beyond just benchmarking to Building Performance Standards (BPS)—mandates to improve energy efficiency or emissions over time. “We’re seeing the same thing all over again with building performance standards… reporting around that is very complicated, because the data is just hard to get,” notes Stein.
Some jurisdictions are now requiring not just annual ENERGY STAR scores, but verification of energy and carbon reductions, which ups the stakes. Missing tenant data or incorrectly categorizing a building in ESPM could even lead to financial penalties in these cases (e.g., New York City’s Local Law 97 fines buildings that don’t meet carbon intensity targets).
By automating and validating the inputs, software helps ensure compliance data is accurate and complete. As Stein observed, when Gridium takes over ENERGY STAR reporting for a new customer, they often find the historical data was “just bad… all your old stuff is wrong”, because previous manual entries were inconsistent. With software doing the heavy lifting, those errors can be corrected going forward, and energy managers can be confident that a compliance deadline won’t turn into a fire drill.
As more cities and states adopt benchmarking and performance laws (by one estimate, at least 25% of U.S. commercial floorspace is now benchmarked in Portfolio Manager), this kind of automation is swiftly moving from a nice-to-have to a must-have tool in the energy manager’s kit.
The final dirty job on our list veers into the domain of energy procurement—an area that in deregulated energy markets can be as complex as Wall Street trading, and just as administratively burdensome.
Large organizations often procure their electricity or natural gas from third-party suppliers or through contracts separate from the local utility’s default service. This means energy managers (or their procurement departments or consultants) have to negotiate contracts, manage contract renewals, and develop purchasing strategies (fixed vs. index pricing, block purchases, green power purchases, etc.).
Doing this for one facility is one thing; doing it across a portfolio of dozens or hundreds of sites in multiple regions becomes a massive undertaking. Each contract might have different start/end dates, pricing structures, and risk profiles. Keeping track of market prices and knowing when to lock in rates requires constant vigilance. It’s easy to see how procurement can eat up huge amounts of time and still lead to suboptimal outcomes if not done rigorously.
Energy management software companies are now stepping up to assist with digital procurement advisory. By leveraging the detailed usage data they already collect, these platforms can analyze a customer’s load profile in conjunction with market price curves and help formulate an optimal procurement plan. “What we’re doing is taking the customer’s interval data and pricing it under different scenarios—including just buying from the utility as a baseline—then plugging in futures prices to see what third-party supply would look like, how much you’d pay for hedges, etc., to come up with a plan that balances cost versus risk,” explains Gridium’s Adam Stein.
In essence, the software can simulate outcomes of various procurement strategies: staying fully indexed to market, hedging a portion of usage at fixed rates, trying alternative suppliers, etc., and compute the expected cost and risk of each. This was once the realm of energy consultants producing long reports; now some of it can be done dynamically with software that draws on up-to-the-minute market data.
One notable trend is the integration of procurement functionality via acquisitions. Arcadia, for example, recently acquired a company called RPD Energy—a leader in renewable energy and customized procurement deals. By folding RPD’s capabilities into its platform, Arcadia aims to automate more of the energy purchasing process for customers. Sam Moskal from Arcadia noted that traditionally RPD (and similar brokers) operated in a consultative, somewhat manual fashion, but the goal now is “automating that, making it even faster, so we can serve customers at scale.”
It’s important to note that human expertise still plays a role—these tools augment, rather than replace, energy procurement professionals or consultants. The contracts still need to be signed, and market intelligence (like regulatory changes or supplier credit risk) must be interpreted. But much of the data crunching and coordination can be offloaded.
Gridium, for example, provides advisory services around procurement in deregulated states, using interval data analysis to guide whether a client should buy from a third-party and how to structure that deal. Stein mentions they often see very good savings from such analyses, especially in times when market prices present opportunities. The software essentially provides the analytics backbone, while the energy manager or advisor uses those insights to make informed decisions.
Many organizations have learned the hard way that an expired energy contract can mean a budget blowout; software with a calendar and workflow can prevent that with simple prompts and even handle many steps of the transaction process.
In summary, managing energy supply has traditionally been a high-stakes, complex job that often required separate consultants or brokers. Now, the same energy management platforms handling your utility bills and analytics are increasingly able to handle energy purchasing analyses as well. One could say the software becomes your energy broker’s assistant, constantly watching the markets and your contracts, so you can avoid nasty surprises and capitalize on opportunities to cut costs or buy cleaner energy.
From data grunt work to financial calculations to complex analysis, software is taking on the dirty jobs of energy management, and the impact on the profession is profound. Energy management software today not just about fancy dashboards—it’s also about eliminating drudgery.
The platforms we’ve discussed act like a tireless junior analyst, bookkeeper, and data technician all in one—collecting and cleaning data, checking for errors, producing budgets and reports, optimizing tariffs, streamlining compliance reporting, and prepping procurement decisions. This allows energy managers and facility teams to redistribute their time to the initiatives that truly require human insight and creativity: identifying energy conservation measures, engaging occupants and operators in efficiency efforts, evaluating new technologies, and steering organizational sustainability strategy.
This shift comes at a critical moment because there’s a well-documented workforce shortage in facilities and energy management. With fewer hands on deck, automation isn’t a luxury—it’s necessary to maintain and improve building performance.
Outsourcing the drudgery of energy management to software could also help address one of the biggest challenges we face in scaling up efficiency and decarbonization—the sheer manpower gap to implement improvements across millions of smaller buildings. By augmenting each energy professional’s capability, the industry can do more with fewer people.
Even organizations that don’t have a dedicated energy manager on staff can now pursue energy-saving programs, because software makes it feasible for, say, a property manager or sustainability coordinator to manage energy data and spot opportunities in their spare time.
In practice, the most successful approach is often a hybrid one: let software do what it’s great at (fast data processing, routine tasks, pattern recognition) and let humans do what they’re great at (strategic thinking, stakeholder engagement, nuanced decision-making). Energy managers who use these tools find they can elevate their role. Instead of being seen as “the person who wrangles the utility bills,” they become strategic leaders driving projects that cut costs and carbon. The software fades into the background as a silent partner ensuring nothing falls through the cracks.
All the property team might need to do is upload a lease document or fill a short form with tenant types and square footages, and the system will decide the best way to input that into ESPM.
Even with automation, there is recognition that this process might never be 100% automated— vendors pair the software with human expertise. For instance, Backpack Group’s team still reviews the outputs and handles edge cases, acknowledging there’s a need for expert oversight for tricky buildings.
The difference is that instead of each energy manager individually struggling through the Portfolio Manager interface and guidance, the software vendor centralizes that expertise and builds it into a tool that benefits all their customers. This “spread the cost across many” model means one team of experts figure out how to properly account for, say, a building with solar panels plus battery storage in Portfolio Manager (which has some esoteric rules), and then that logic is coded so every client with similar setup gets it right.
The importance of getting Portfolio Manager data right is growing as cities move beyond just benchmarking to Building Performance Standards (BPS)—mandates to improve energy efficiency or emissions over time. “We’re seeing the same thing all over again with building performance standards… reporting around that is very complicated, because the data is just hard to get,” notes Stein.
Some jurisdictions are now requiring not just annual ENERGY STAR scores, but verification of energy and carbon reductions, which ups the stakes. Missing tenant data or incorrectly categorizing a building in ESPM could even lead to financial penalties in these cases (e.g., New York City’s Local Law 97 fines buildings that don’t meet carbon intensity targets).
By automating and validating the inputs, software helps ensure compliance data is accurate and complete. As Stein observed, when Gridium takes over ENERGY STAR reporting for a new customer, they often find the historical data was “just bad… all your old stuff is wrong”, because previous manual entries were inconsistent. With software doing the heavy lifting, those errors can be corrected going forward, and energy managers can be confident that a compliance deadline won’t turn into a fire drill.
As more cities and states adopt benchmarking and performance laws (by one estimate, at least 25% of U.S. commercial floorspace is now benchmarked in Portfolio Manager), this kind of automation is swiftly moving from a nice-to-have to a must-have tool in the energy manager’s kit.
The final dirty job on our list veers into the domain of energy procurement—an area that in deregulated energy markets can be as complex as Wall Street trading, and just as administratively burdensome.
Large organizations often procure their electricity or natural gas from third-party suppliers or through contracts separate from the local utility’s default service. This means energy managers (or their procurement departments or consultants) have to negotiate contracts, manage contract renewals, and develop purchasing strategies (fixed vs. index pricing, block purchases, green power purchases, etc.).
Doing this for one facility is one thing; doing it across a portfolio of dozens or hundreds of sites in multiple regions becomes a massive undertaking. Each contract might have different start/end dates, pricing structures, and risk profiles. Keeping track of market prices and knowing when to lock in rates requires constant vigilance. It’s easy to see how procurement can eat up huge amounts of time and still lead to suboptimal outcomes if not done rigorously.
Energy management software companies are now stepping up to assist with digital procurement advisory. By leveraging the detailed usage data they already collect, these platforms can analyze a customer’s load profile in conjunction with market price curves and help formulate an optimal procurement plan. “What we’re doing is taking the customer’s interval data and pricing it under different scenarios—including just buying from the utility as a baseline—then plugging in futures prices to see what third-party supply would look like, how much you’d pay for hedges, etc., to come up with a plan that balances cost versus risk,” explains Gridium’s Adam Stein.
In essence, the software can simulate outcomes of various procurement strategies: staying fully indexed to market, hedging a portion of usage at fixed rates, trying alternative suppliers, etc., and compute the expected cost and risk of each. This was once the realm of energy consultants producing long reports; now some of it can be done dynamically with software that draws on up-to-the-minute market data.
One notable trend is the integration of procurement functionality via acquisitions. Arcadia, for example, recently acquired a company called RPD Energy—a leader in renewable energy and customized procurement deals. By folding RPD’s capabilities into its platform, Arcadia aims to automate more of the energy purchasing process for customers. Sam Moskal from Arcadia noted that traditionally RPD (and similar brokers) operated in a consultative, somewhat manual fashion, but the goal now is “automating that, making it even faster, so we can serve customers at scale.”
It’s important to note that human expertise still plays a role—these tools augment, rather than replace, energy procurement professionals or consultants. The contracts still need to be signed, and market intelligence (like regulatory changes or supplier credit risk) must be interpreted. But much of the data crunching and coordination can be offloaded.
Gridium, for example, provides advisory services around procurement in deregulated states, using interval data analysis to guide whether a client should buy from a third-party and how to structure that deal. Stein mentions they often see very good savings from such analyses, especially in times when market prices present opportunities. The software essentially provides the analytics backbone, while the energy manager or advisor uses those insights to make informed decisions.
Many organizations have learned the hard way that an expired energy contract can mean a budget blowout; software with a calendar and workflow can prevent that with simple prompts and even handle many steps of the transaction process.
In summary, managing energy supply has traditionally been a high-stakes, complex job that often required separate consultants or brokers. Now, the same energy management platforms handling your utility bills and analytics are increasingly able to handle energy purchasing analyses as well. One could say the software becomes your energy broker’s assistant, constantly watching the markets and your contracts, so you can avoid nasty surprises and capitalize on opportunities to cut costs or buy cleaner energy.
From data grunt work to financial calculations to complex analysis, software is taking on the dirty jobs of energy management, and the impact on the profession is profound. Energy management software today not just about fancy dashboards—it’s also about eliminating drudgery.
The platforms we’ve discussed act like a tireless junior analyst, bookkeeper, and data technician all in one—collecting and cleaning data, checking for errors, producing budgets and reports, optimizing tariffs, streamlining compliance reporting, and prepping procurement decisions. This allows energy managers and facility teams to redistribute their time to the initiatives that truly require human insight and creativity: identifying energy conservation measures, engaging occupants and operators in efficiency efforts, evaluating new technologies, and steering organizational sustainability strategy.
This shift comes at a critical moment because there’s a well-documented workforce shortage in facilities and energy management. With fewer hands on deck, automation isn’t a luxury—it’s necessary to maintain and improve building performance.
Outsourcing the drudgery of energy management to software could also help address one of the biggest challenges we face in scaling up efficiency and decarbonization—the sheer manpower gap to implement improvements across millions of smaller buildings. By augmenting each energy professional’s capability, the industry can do more with fewer people.
Even organizations that don’t have a dedicated energy manager on staff can now pursue energy-saving programs, because software makes it feasible for, say, a property manager or sustainability coordinator to manage energy data and spot opportunities in their spare time.
In practice, the most successful approach is often a hybrid one: let software do what it’s great at (fast data processing, routine tasks, pattern recognition) and let humans do what they’re great at (strategic thinking, stakeholder engagement, nuanced decision-making). Energy managers who use these tools find they can elevate their role. Instead of being seen as “the person who wrangles the utility bills,” they become strategic leaders driving projects that cut costs and carbon. The software fades into the background as a silent partner ensuring nothing falls through the cracks.
Energy and sustainability managers are stretched thin—and not always because they’re busy implementing energy efficiency upgrades or innovative sustainability initiatives, but because they’re bogged down in administrative drudgery.
From chasing down utility bills across dozens of accounts to crunching consumption data in spreadsheets, a huge portion of an energy manager’s time is spent on manual tasks that don’t directly reduce a single kilowatt-hour of usage or unit of emissions. Real estate organizations waste hundreds of hours annually on manual utility bill processing—time that could be spent on strategic energy initiatives.
Lauren Trapp (sustainability manager) and Brandon Money (energy manager) from AFL told us that automation cleared their plates and enabled them to tackle more strategy projects like Scope 3 emissions and waste management. Brandon said software allows him “to focus more on our overall Scope 1 and 2 reduction strategy, capital investment strategy…on site solar installations, [and] capital budgeting… and [spend] less time punching numbers into Excel.”
This busy work not only saps productivity, it also contributes to errors and missed opportunities. It’s no wonder that according to the World Economic Forum, only about 9% of companies have fully embraced software tools for managing their energy and sustainability data—the vast majority still rely on spreadsheets and manual effort.
Fortunately, energy management software providers are getting really good at handling the “dirty work” of energy management—the tedious, time-consuming workflows required to gather and organize data and keep on top of energy expenses—so that energy managers can refocus on higher-value projects.
We’ve covered a lot of ‘sexy’ capabilities of energy management software before (most notably in our Buyer’s Guide to Energy Management Software), but we haven’t yet celebrated the basic dirty work that energy managers don’t need to do anymore. Instead of spending hours wrangling utility data or preparing reports, energy managers can spend their time implementing efficiency projects, optimizing systems, and planning sustainability strategy.
Kris Zebrowski, former energy manager at Cushman Wakefield and now Customer Success Manager at Atrius, found that automation enabled him to focus on the work that actually saved energy. “All of that was gone, and we could really focus on the work of identifying outliers, looking for energy conservation measures, and doing what I consider the fun part of energy management.”
Critically, integrating software into energy management workflows goes beyond labor savings and having more fun, it’s enabling tasks at a scale that would be impossible to handle manually. Gridium’s VP of Product and Cofounder Adam Stein emphasizes that trying to perform detailed energy analysis across a whole building portfolio without digital tools simply doesn’t pencil out:
“In a practical sense, no, it’s not possible … I suppose you could do [it] manually. Would you? Would you trust it? If you were trying to do this across a portfolio, it would be an enormously daunting task. So no, practically speaking, this is not something you could do on your own.”
This article dives into how software is transforming the day-to-day job of energy management. We’ll examine five “dirty jobs” that modern energy management platforms handle—from utility data wrangling to tariff analysis—and how offloading these tasks to digital tools is freeing up energy professionals to concentrate on the impactful work of actually improving buildings’ energy performance.
Along the way, we’ll highlight real-world insights from experts at Gridium, Arcadia (which acquired the utility data specialist Urjanet), Atrius from Acuity Intelligence Spaces, and Backpack Group, and we’ll ground the discussion in the realities of what software can and can’t do today.
The foundation of any energy management program is having access to timely, accurate utility data. Every month, energy managers need to compile data on electricity, gas, water, and other utilities for each site—usage, costs, demand charges, taxes, you name it.
The problem is, this data usually comes from a patchwork of sources: different utility companies (each with their own billing format or website), third-party suppliers, and perhaps on-site generation meters. The data is often scattered across paper bills, PDFs, and online portals, in inconsistent formats that are a nightmare to consolidate. As Gridium’s Adam Stein points out, “utilities are not presenting their data in a way that is convenient to use. If you manage a portfolio of real estate, you probably have many utility accounts, and your data is scattered across those accounts and not in a structured format.”
In the U.S. alone, there are over 3,000 electric utilities, each with different billing systems and data access methods. Simply retrieving all that information and standardizing it can consume an enormous amount of time and effort. Even if a utility offers an API like Green Button, an individual energy manager isn’t likely to write their own software to pull that data together.
This is why many energy teams are now leveraging utility data automation services. Companies like Arcadia have built platforms to streamline and aggregate billing data billing data from virtually any utility. In Arcadia’s case, their platform covers 95% of residential and commercial accounts in the US and data from 9,500+ utilities across 52 countries, all delivered via API in a unified format.
Instead of an energy manager logging into dozens of different utility websites each month, the software connects to each account (handling all the login credentials behind the scenes), pulls the latest bills and meter readings, and ingests them into a single database. The data is normalized into a consistent data model—unit conversions handled, rate components separated, correct labels applied—so that utility data looks and behaves the same way, regardless of source. This work is a huge time suck—A study from EnergyCAP estimates its customers save on the order of 23–37 hours of staff time per month by automating utility bill capture—which makes the ROI calculation stark.
It’s telling that even other energy software vendors often don’t reinvent this wheel—they piggyback on specialized utility data acquisition platforms. Atrius and Backpack Group, for instance, integrate with Arcadia’s Plug API rather than building their own utility scraping tools from scratch. By outsourcing the heavy lifting of utility data aggregation to a dedicated provider, they spread the cost across many clients and ensure coverage of thousands of utilities.
Utility data is often incomplete or inconsistent in ways that make it unreliable for energy managers who rely on it for reporting, budgeting, and decision-making. Gaps in usage data, incorrect unit conversions, and misaligned reporting formats can all create problems that ripple through an organization’s energy strategy.
In AFL’s spreadsheet days, data quality and completeness were constant headaches. “There was… human error, had to go back and forth with people so many times… it was very frustrating and just inefficient because… we could all be doing better things with our time,” Lauren Trapp admitted. Manual data management not only wastes time but also causes staff burnout and lost opportunities. Rather than leaving energy teams to hunt down discrepancies manually, modern energy management software also automates the error-checking process, flagging anomalies before they create bigger issues.
“We have data quality checks in place—does your bill total add up correctly? If not, it spits out an error so you can fix it before it causes bigger issues,” explains Atrius’ Sustainability Product Manager Chelsea Davis. Their system also proactively monitors for missing data. “If something doesn’t match historical trends, we flag it so the energy manager doesn’t have to find out the hard way,” she adds. These safeguards ensure that gaps in utility usage data are identified early, preventing reporting errors and compliance headaches down the line.
For organizations that integrate real-time meter data, Atrius takes validation further by cross-referencing actual interval readings with utility billing data to ensure alignment. “If a customer has sub-metering in place, we can compare that against the utility bill data to catch anomalies before they get billed incorrectly,” Davis explains. This means that energy managers don’t just have to trust that their data is accurate—they have real-time verification that their reported energy use actually reflects what was consumed.
Since energy management data comes from multiple sources, vendors must make sure the units, reporting structures, and timeframes align so that energy managers can work with a consistent, error-free dataset. Without this kind of automated validation, discrepancies—such as a meter reporting in kBTUs instead of MMBTUs, or missing days in a billing period—could easily lead to faulty conclusions about building performance.
Once the data is aggregated and checked, software vendors then add additional context to enable the data to be useful in the energy management process. As an energy manager, you might interact with analytics, alerts, or reports, which require a lot of behind-the-scenes work to normalize, structure, and enrich utility data so energy managers can actually use it to make decisions.
Backpack Group’s Daniel Kaplan explains how their system uses a structured data model that enables real-world use cases. “Once we have everything in a nice little package, we can then build upon it,” he says. “We structure the data for ENERGY STAR Portfolio Manager, for tenant vs. owner-paid breakdowns, for emissions reporting, for projects and capital planning. Once the blocks are there, we can use them however we need to.” Instead of leaving energy managers to wrangle raw utility bills and spreadsheets, the software standardizes everything into a format that can be applied across different reporting and analysis needs.
This work goes beyond just the energy meters themselves. The software maps energy consumption to tenants, spaces, equipment, and even operational data from building automation systems. “Utilities is one arm of our data model,” Kaplan says, “but so is tenants, spaces, equipment, projects, documentation, and even operational data like building automation system inputs and weather data. This way, energy managers can analyze energy consumption in context.”
The system can map everything correctly without manual intervention by automatically pulling in building characteristics from leasing documents, space plans, or previous reports. “All the property team needs to do is upload a stacking plan or leasing documents,” Backpack Group’s Cody Bond explains. “We have a rules engine that takes that information and maps it where it needs to go.” This kind of automation removes the guesswork from reporting and ensures compliance data is accurate—without hours of manual spreadsheet work.
Ultimately, the biggest value software provides isn’t just utility bill collection—it’s making data usable. Energy managers don’t just need numbers; they need insights. By structuring energy, property, and equipment data in a way that’s actionable, software platforms ensure that energy managers spend less time wrestling with data and more time turning insights into energy-saving projects.
A significant chunk of energy management work doesn’t involve engineering—it involves accounting and finance. Every year, energy managers are asked to develop utility budgets and forecasts for their facilities. Every month, they have to approve or accrue bills, and often allocate costs to different business units or tenants. These tasks can be mind-numbingly boring but also sneaky complex. Utility costs are not a simple linear function of usage; they involve fixed charges, demand charges, tiered rates, fuel cost adjustments, and other components that can change unpredictably.
For organizations with many sites, budgeting energy spend for the next year is like shooting at a moving target, complicated by volatile energy markets and regulatory changes. “If you are an energy manager who has to come up with a budget every year—we will generate a budget for you based on top of [your historical] data. That’s just a very basic thing, but it’s not easy to do manually,” notes Gridium’s Adam Stein. “Especially if you’ve got supply charges and distribution charges coming from different places.”
In deregulated energy markets, this is even harder because the supply portion (the commodity price of electricity or gas) might be contracted separately from the delivery (utility) portion; each has its own rate structure and both need to be forecasted. Software can crunch years of utility data, account for seasonality, rate changes, and usage trends to automatically project a forward-looking budget—sparing energy managers from endless spreadsheet tweaking and giving finance teams a data-driven estimate of future costs with a few clicks.
Another accounting headache is accruals—booking the cost of energy consumed in a month before the actual bill arrives. As Stein explains, “often you have to file your energy expenses at the end of the month in your accounts payable system, and you don’t actually have the bill yet… you need to file expenses at the close of the month, even if you don’t have [the bill]. We have your interval data, we have your most recent bill, we can do a reasonably good job of estimating those costs for you.” When the real bill comes, the software can reconcile it against the accrual and flag any major differences.
Automating this accrual process is a huge relief for energy managers working with finance departments on tight monthly closes. Stein puts it bluntly: otherwise “you are sitting there trying to download PDFs from different utility accounts and cutting and pasting the values into spreadsheets – that’s the world you’re in. We shouldn’t sleep on [how important] this is.”
Before the bill actually get paid, energy managers (and their accounting departments) lean on software providers to make sure it’s correct. Utility billing errors are more common than most energy managers realize. Utilities process massive volumes of billing data, often using complex rate structures that leave room for mistakes. A misapplied demand charge, an incorrect tariff classification, or even simple clerical errors can all lead to thousands of dollars in unnecessary costs. Historically, energy managers had little choice but to trust that their bills were accurate or spend hours combing through line items in search of discrepancies. But now, energy management software automates the auditing process, flagging billing errors before they become costly problems.
Gridium has built its platform to do just that—identifying when a building is being overcharged, billed under the wrong tariff, or hit with avoidable fees. Stein explains how their system reconstructs utility bills to check for accuracy. “We model utility bills using our rate engine, applying historical interval data to see if the billed amount is correct,” he says. “If there’s a major discrepancy, we flag it for the customer.” Instead of relying on manual audits, software continuously monitors for errors, ensuring that overcharges don’t go unnoticed for months or even years.
“Bill audit opportunities aren’t as frequent, but when they happen, they can be lucrative,” he explains. “A utility billing mistake could be worth tens of thousands in refunds.” For organizations managing multiple properties across different utility territories, these errors can add up quickly, making automated bill audits an essential tool for financial oversight.
Beyond catching errors, software ensures that billing corrections actually get made. Gridium’s platform tracks billing disputes and resolutions, ensuring that energy managers not only catch overcharges but also recover their funds.
Brandon Money from AFL emphasized the importance of being able to audit the historical utility data. “Having robust data…data that’s auditable and traceable is key” as sustainability reporting expectations rise, and “it’s definitely important to have your data in a good system because spreadsheets just aren’t going to cut it.” In hindsight, moving away from Excel to energy management software was not just helpful but necessary for credible, ready-for-audit data.
Automating these bread-and-butter tasks is foundational. It doesn’t have the glamour of AI optimizing your chiller plant, but it might save as much or more time and money in practice and lay the groundwork for bigger energy initiatives to be taken seriously.
One of the more technically complex tasks in energy management is making sure each facility is on the optimal utility tariff or rate plan for its usage profile. Large commercial and industrial users often have options when it comes to utility tariffs: different rate schedules with varying demand charges, time-of-use pricing, peak vs off-peak differentials, etc.
Choosing the best one (or negotiating a custom rate) can yield significant savings, but manually figuring out the ideal tariff is a daunting analytical challenge. You’d have to take a year’s worth of interval data (hourly or 15-min usage), then calculate what that usage would cost under each eligible tariff—which could be dozens of permutations—and compare the outcomes. Historically, this was done occasionally by hiring a specialized consultant or by very laboriously running data through Excel. As a result, many buildings stayed on whatever default rate the utility assigned, even if a better (cheaper) rate was available for their pattern of use.
Today, energy management software can perform digital tariff optimization continuously and in a fraction of the time. Sam Moskal of Arcadia explains that their platform connects three data elements—the customer’s billing data, their interval meter data, and a database of all available tariff structures—to automate the entire analysis.
The software first validates the current bill by re-calculating it from the interval data and the current tariff, then it simulates the customer’s bill under every other applicable tariff or rate option, using the interval load profile to account for demand peaks, TOU periods, etc. The result is a clear identification of the cheapest rate for that historical period. This can reveal if the customer has been on the wrong tariff.
In practice, many commercial customers are on suboptimal tariffs simply because utilities don’t always proactively move them to the best rate. In California, for example, some buildings have saved tens of thousands per year by switching from a general TOU rate to a more appropriate “peak day” tariff once their usage patterns were analyzed by Gridium’s’ tariff optimization algorithms.
They’ve published many case studies demonstrating this, such as at Lincoln Property Company where they found a $75,000 rate change opportunity. It’s common for these analyses to find 5–15% cost reduction opportunities—gold that would remain hidden without crunching the numbers.
What’s really powerful is that software can run these tariff comparisons continuously, not just as a one-time study. Utilities frequently update their tariffs—new optional rates are introduced, prices change with regulatory approvals, pilot programs come and go. A digital platform can keep the tariff library up to date and periodically re-check your cost against new or modified rates. If a better option emerges, the system can alert the energy manager to consider a switch.
This kind of continuous rate optimization was virtually unheard of when it required human effort; no analyst is going to manually recompute bills for dozens of sites every month. But with automation, it’s feasible to revisit the rate decision every billing cycle or every quarter. Arcadia’s team notes that unlike traditional consulting that might take 6–8 weeks to produce a one-time report, their automated rate engine can do it every month and flag if changing conditions (like a new peak demand pattern or a tariff change) mean you should change rates. Essentially, software shifts tariff optimization from a project to a continuous process.
Tariff optimization might not reduce carbon emissions or kWh, but it directly boosts the bottom line, and it’s exactly the kind of high-value analysis that busy energy managers rarely had time to tackle before. Now the “robot” does it for you.
For any energy manager working in a city or state with a benchmarking or building performance ordinance (which is now dozens of major cities and several states in the U.S.) or for an organization that creates annual sustainability reports, complying with ENERGY STAR Portfolio Manager reporting requirements has become a yearly ritual—and often a dreaded one.
ENERGY STAR Portfolio Manager (ESPM) is the EPA’s online tool for benchmarking building energy and water performance. It’s a great tool, but feeding data into it correctly can be surprisingly labor-intensive. You need to input each building’s total energy usage (often by manually entering monthly totals for each utility), along with detailed operational characteristics (square footage, occupancy, space types, weekly hours, number of computers, etc.).
Getting all this data right is crucial to obtain a valid ENERGY STAR score or meet local law requirements. Doing it by hand for a large portfolio is tedious and prone to errors. In Seattle, for example, building owners have been fined for submitting inaccurate benchmarking reports just as they would for failing to report at all. It’s not just a data entry task; it requires understanding Portfolio Manager’s conventions and often digging for information about each building.
Energy management software is making this process far smoother through Portfolio Manager automation. Many utilities claim to offer automatic data upload to ESPM (via web services), but in practice these often only cover single utilities and can be clunky or incomplete. Software vendors have instead built integrations between the utility and Portfolio Manager to automate the flow of data and ensure its quality.
Essentially, these tools take the same utility data discussed earlier (often already aggregated in their platform) and push it to the Portfolio Manager system on behalf of the customer. When it comes time to do the annual benchmarking submission, an energy manager can simply review and hit submit, and the software essentially syncs your data to the Portfolio Manager, eliminating transcription errors and saving time.
However, the trickiest part of Portfolio Manager compliance isn’t just the meter data—it’s the property use details. Portfolio Manager requires you to input how each space is used (office, retail, data center, etc.), with specific parameters for each space type. If you have a complex building, determining and entering these details can become a deep rabbit hole. “The property use side—there could be 10 plus good answers for any given building… You could spend 100 hours in the FAQs to fully understand this,” says Cody Bond of Backpack Group.
Users often feel unsure if they did it right (“Is a professional engineer going to come through and disagree with everything I’ve done?”). To solve this, some software vendors are using expert systems and rule engines. For example, Backpack Group developed a rules engine that asks the property team a series of simple questions (or pulls info from a “stacking plan”—basically the floor-by-floor tenant layout) and then maps that to the appropriate Portfolio Manager input.
Instead of the energy manager manually figuring out how to classify a multi-use building’s areas into, say, “Office – Unrefrigerated Warehouse – Retail,” the software’s decision tree does it for them.
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