The GLYNT.AI Guide to Utility Data
Why utility bills are hard to automate
Utilities play a critical role in business, providing electricity, natural gas, water and waste services. Today there is an increasing need to capture data on this consumption, arising from our greater focus on reducing costs and reporting emissions.
The challenge is to get the data. Every utility has a different bill format, and governmental regulations often dictate the use of terms and phrases that are opaque and confusing.
“You can’t manage what you don’t measure.”
The numbers tell the story. In the U.S. alone there are over 2,000 electric utilities with over 52,000 different rates. Each rate schedule has different charges and metrics, leading to a different bill format. And, there are over 148,000 water utilities and 16,000 wastewater utilities in the U.S. Each of these will have 3 to 10 rate schedules (CISA, OpenEI, EIA).
While the U.S. is clearly a fragmented market, there are over 7,000 electric utilities globally and hundreds of thousands of water utilities. The huge variation in utility bills that prevents easy automation is a global challenge.
And finally, about 15% of all utility bills presented to businesses are summary bills i.e. bills that cover multiple service locations, multiple service periods, and/or multiple energy suppliers. Summary bills must be unpacked, with usage tracked back to the point of use. It takes deep expertise to untangle this complex bill format.
So, for a business looking to prepare data for emissions reporting or expense management, the key challenge is invoice variation. It is quite difficult to automate such incredible variety, or to accurately capture this data by hand. Utility bill complexity defeats DIY-type efforts.
Current approaches
Standard accounts payable (AP) systems
Whether in-house or outsourced, AP teams may use an automated invoice data capture solution, but in practice only 30% of invoices are processed without human intervention, and nearly all utility bills are thrown into an exceptions pile for manual data entry (Ardent, 2026). The utility bill format is simply too different from an ordinary invoice to be easily automated. AP systems typically capture just enough data to pay the bill, not the usage and cost data needed for expense management and investor-ready reporting.
Specialized AP providers
Because utility bills often have a short grace period between statement date and due date, many businesses have arranged for the bill to be sent directly to a specialized AP provider who will process the bill and prepare a file for payment. With a focus on quick turnaround, very little data is captured from the bill. In almost all cases, the data is processed again by a second provider for use in expense management and investor-ready reporting.
Direct data from the utility via EDI
Large utilities offer an Electronic Data Interchange (EDI) file to large customers. However, this data transmission is brittle, and needs full-time staff to monitor and support at the customer side, and the data is sparse and error-prone. This is not a universal solution.
Direct data from the utility via API
This service may be available from some utilities, but in the U.S. it remains fragmented, slow and poorly supported. There is no national standard, so each utility has a bespoke API, significantly increasing costs. Outside the U.S., use of utility APIs is more reliable and standardized.
Energy management services provider
Many businesses have two work streams for utility bills: an AP provider and an energy management services provider. The energy management company reduces energy expense and, as a byproduct, captures data. The customer does not have an independent source of data; it relies on the provider to reduce costs and track savings.
In sum
This complex landscape makes it difficult for a business to gather utility bills and prepare investor-grade sustainability data. The vendor processing the bill may not have an audit-ready workstream. Nor is it likely to capture the granular data needed to operationalize energy and water reductions. The complicated format for waste data in ESG and sustainability disclosures requires a specialized method.
Businesses are looking for a focused, purpose-built solution that will simply take the utility invoices, process them appropriately, and deliver a report-ready data file from an audit-ready system.
The checklist
Source File Capture
- Direct Utility Connector
- Automated Enterprise Connector
- SFTP
- API
Look for a service that can do all of these methods. Even within one business, multiple approaches may be needed to capture all of the Source Files.
Data Formats
- Native PDFs
- Scans
- Photos
- CSV, XLS
- JSON
Again, look for a service that can do all of these formats. No business wants to run two systems – one for PDFs, and one for other formats!
Invoice Types
- Utility Bills
- Business Invoices
- Landlord Invoices
- Data Center Invoices
- Non-English Languages
- Non-Latin Characters
Utility data can be provided by the utility, by the landlord, or others. You’ll need a service that can take in all types and handle your global footprint, too.
Types of Source Files
- Electricity
- Water
- Waste
- Energy from Non-Utility Suppliers
- IoT Sensor Data
- Sub-Metering Data
A single solution for all incoming data keeps it simple for you. And if you add IoT monitoring or sub-metering later to help with energy and water reductions, you’ll want a system that can handle this data type.
Customization
- Prepare Customized Data Formats
- Add Site Codes, GL Codes and So On
- Add Other Business Data to Integrate with Business Systems
Your data must flow into other systems to be truly useful. Look for customized formatting for seamless integrations. Plan on using sustainability data broadly across the business as it often provides additional operational efficiencies.
Technology
- Automated Data Infrastructure
- SOC 1 and SOC 2 Type II Compliant System
- Use of AI
- Built-In Customization
- No Developers Required
Look for a service provider who uses a modern suite of technologies in a highly automated system that can provide documentation on compliance. Too often, a utility data service is nothing more than manual data entry in a semi-automated system, leading to delays and errors.
Onboarding
- How Long to First Data?
- How Long to Completion?
- Does Onboarding Lay the Foundation for Data Health and Audit-Ready Data?
Look for a service with a documented onboarding procedure, so you always get the best practices from their previous customer experiences. Expect a clear project plan and onboarding completion within 90 days.
Support and SLAS
- Data Turnaround
- Data Management & Accuracy Reporting
- Clear SLAs
Look for data turnaround in days, and a library of reports showing how your data was handled and how it performed on accuracy and validation tests. These reports help with data management and with auditors.