Maximizing the Value of Data Exchange (Part 3): Software is the Solution

Utilities and regulators often perceive tools that help customers share their energy usage with service providers as “nice to haves,” but not critical for day-to-day customer needs. In the final post of this three part series, I explain how utilities can dramatically save deployment costs and speed to market by looking beyond custom-built solutions.

Data exchange platforms can be deployed faster and cheaper than ever.

Utility software investments like this exist in a tricky world of capex versus opex, build versus procure, and plan versus rate case. One of the major questions that is coming up in regulatory proceedings now is whether utilities should build or procure software for data exchange platforms, and if the latter, what procurement looks like.

Some of the most-used data exchange platforms in the country have been self-built or bespoke from vendors, and they haven’t exactly been cheap. Regulatory research suggests that PG&E has spent around $60 million building Share My Data and Click-Through data tools over the last 10 years. SmartMeterTexas was built for regulated utilities by an outside vendor, but was originally custom for the Texas retail choice market–while development began in 2008, testimony suggests that the costs to set up SmartMeterTexas already exceeded $90 million by 2016. More recent annual performance reports suggest that over $60 million has been spent for building and rebuilding the software, just since 2019. 

It makes sense that early implementations might have cost more to stand up when the data exchange platform concept was untested in the U.S. But we’re still seeing utilities estimate millions of dollars in capital costs for what appear to be internally built data exchange platforms–around $5 million for Ameren Illinois in its previous multi-year grid plan, $9 million for Exelon Maryland companies based on their report on Order 2222 implementation, and $11 million presented by ConEd in its latest rate case, reflecting just the latest upkeep (Exhibit IT-5). To be fair, these numbers often come from estimates created by project managers doing their best to interpret regulatory direction and perspectives from multiple internal teams. But with load flexibility taking off, there’s a more efficient approach.

Productized software solutions can offer a cheaper, “off the shelf” alternative for utilities (and ratepayers). Over the past decade, software companies have built customer, utility, and third-party interfaces on top of the Green Button Connect standard, creating a modern and replicable data exchange platform. This means that a software vendor can provide a utility with a core set of functionalities and privacy and security best practices, minimizing the need for expensive customization. A skilled vendor can tweak these functionalities to the regulatory, customer, and user environment, and deploy within months. While often treated as proprietary information in rate cases, public examples like El Paso Electric New Mexico’s implementation indicate prices in the hundreds of thousands of dollars, not the millions, for this approach (Case 21-00269-UT).

Regulators should be skeptical when utilities try to build productized software functionalities in-house, because it means that they’re having to relearn the lessons that software companies have already figured out through a decade of real-world deployments. Utilities that build their own electronic “letter of authorization” systems must build from scratch the same functionalities that are available through software as a service (SaaS): customer authorization flows, audit logs, security protocols. This time-consuming development work often follows years of stakeholder meetings outlining use cases and business functionalities. Moreover, internal development may be subject to constant reinvestment as other backend systems are upgraded, and this frequent rebuilding means that self-built systems aren’t going to be depreciated over a long enough period of time to be more cost-effective than an annual or monthly software subscription. On top of that, data users still have to customize at least some of their processes to accommodate each utility, losing out on the value of consistency.

Capital expenses can look more attractive to utilities compared to operations costs for software subscriptions, but when the differences in overall cost and quality are so stark, the subscription model will result in more value for ratepayers and greater consistency for third parties.

Currently, regulators are overseeing rate cases where utilities procure other types of software–customer information systems (CIS), meter data management systems (MDMS), distributed energy resource management systems (DERMS)–rather than building those internally from scratch. CIS and MDMS systems are great examples of commercialized software, while DERMS software tools are still evolving and may have productized versions for some variations but not others (e.g., “grid” or “edge” tools). With decades of implementations nationally, data exchange platforms are closer to the former than the latter–closer to productized than custom.

When regulators authorize utilities to build data exchange platforms instead of procure them from skilled vendors, they risk a process that will take months or years longer and cost millions of dollars more than what could be obtained through a competitive solicitation. Just like other large software solutions, data platforms should be procured based on their quality and functionality, rather than converting makeshift solutions into long-term capital investments.

Data exchange platforms punch above their weight because of the utility integration work they require, not in spite of it.

Sometimes the efficiencies that transitioning to software-as-a-service creates can get hidden among the line items in rate cases. Like other software companies, a data exchange platform vendor will typically charge certain types of costs. The most common are implementation costs for initial planning and setup, and then ongoing monthly or annual costs for continued use of the platform. There may be costs associated with customer support. How all of these costs are assessed (and whether third-party user fees can offset them) may vary based on the utility or vendor.

However, there is another chunk of costs which, while not well-explained, can sometimes be the highest line item in the development of a data exchange platform: utility implementation costs. These are the backend costs for the utility to be ready to interact with the data exchange platform–to deliver the information that data recipients require.

A data exchange platform will usually ingest and repackage data from multiple different utility systems in order to deliver it to an authorized third party. The MDMS provides interval energy usage data while the CIS provides account and billing information. However, these systems may use different identifiers for premises, customers, or meters that have to be reconciled to ensure data is transferred properly. Units or timestamps may need to be converted.

In our experience, this can represent a significant investment of time by utility teams, many of which may not have worked together in the past or who have limited context for why data exchange platforms are created. For example, in an August 2025 presentation to the Illinois Commerce Commission Data Access Working Group, ComEd benchmarked its system integration costs at $19-57 million, compared to $1-7.5 million in annual SaaS fees. ComEd’s integrated data platform represents a significantly more robust scope than the data exchange platform I’m discussing and would require more subscriptions and more data integrations, but it’s an example of how extreme the difference can be between cost categories.

A dimension of this that is misunderstood is that data exchange platforms aren’t the only reason these systems need to be integrated. Just like a data exchange platform can serve many users, system integration can benefit many utility activities. MDMS, CIS, and other systems have to communicate for a variety of reasons, like accurately billing customers on time-varying rates, setting up community solar projects, or facilitating electric retail supplier relationships. Anecdotally, our customers have also leveraged the data exchange platform for their own planning and reporting, because it involves reconciling into a single source of truth multiple data flows that they would otherwise have to manually process. But specifics about integration costs are rarely discussed in depth in rate cases, making the efficiencies created by reconciling data sources difficult to value.

Now, utilities can still reduce their integration costs specific to data exchange platforms by leveraging data flows that already exist. Data exchange platforms commonly transmit types of data, like 15-minute interval usage data, that the utility is also presenting to customers through its web portal. In other words, there can be multiple vendors whose data needs are the same in scope, timeliness, and accuracy. Unfortunately, we still see utilities build duplicative data flows for individual vendors. Where there are more data flows there are more server expenses, more integration costs, more risk of error, and more opportunities for failure.

As energy markets become more complicated and involve more actors–think distributed energy resource aggregations–ensuring that all actors involved are relying on the same, accurate source of data will promote market credibility. Often, I see utility integration costs cited as a negative or cost that dings data exchange platforms by making them seem more expensive than they actually are to deploy. A more accurate way of looking at this is that utilities need their data systems to communicate to enable market innovation. Utility systems integration is a benefit that data exchange platforms create because they do once what utilities would otherwise have to do many times over for different purposes. And if utilities recognize the efficiencies that system integration creates and do this proactively to support VPPs and time-varying rates, then it will make data exchange platforms that much easier to layer in.

Smart data exchange platform design saves utilities and customers money.

Each year we are getting closer to a crisis in energy affordability. Public utility commissions are rightfully scrutinizing every cost. Utilities are looking closely at how they can be more efficient with each dollar they spend. Customers are showing up to public utility commission hearings and voting in regulator elections.

If designed correctly, a data exchange platform is not only fundamentally low-cost compared to the major investments utilities are making in AMI and DERMS–but it drives disproportionately massive benefits in the form of efficiencies for utility staff and customers’ vendors. The time and money customers spend trying to parse their bills has been treated as an externality to utility rates. But that was before the confluence of concerns about load growth, reliability, and affordability drove 35 states and the District of Columbia to explore virtual power plants in 2025. Easy, electronic data-sharing is fundamental to helping scale up load flexibility, driving measurable benefits not just for those who choose to share their data for energy management, but also for their peers. Again–if designed correctly, with consideration to the points I’ve made in this post–a data exchange platform is a benefit for customers regardless of size or income and regardless of whether they’re using it to manage budgets, get contractor bids, or flex load.

With this much at stake, we have to stop looking at foundational tools like a data exchange platform as “nice to haves.” These are necessities if we want people to have any kind of agency over their energy costs in the future.