Water utility revenue is in danger. With more than 35% of utilities1 experiencing year-over-year reductions in revenue, and 80% of utilities2 finding declining or flat volumetric sales, there is an increasing need for revenue assurance in the water business—particularly as the American Water Works Association reported that more than half of utilities polled felt they were incapable of covering the full cost of providing service.3
Going forward, utilities need a way to both find and maintain revenue. And while water leaks certainly result in lost revenue, there is often much more revenue hidden and lost in our utility data.
WE’RE ONLY AS GOOD AS OUR DATA
Water utilities typically bill fixed and volumetric charges based on meter reads. As such, the accuracy and precision of that read is vital to ensuring accurate production of bills and ultimately the collection of revenue. Most utilities, however, do not have a complete understanding of the accuracy or integrity of the meter read that goes in to the production of their bills.
The accuracy of a meter read varies based on many factors: age and volumetric throughput, the installation configuration, the flow rate range and the means by which that data is collected. But for billing purposes, we also need to consider parameters such as meter size, customer type, customer category and installation specifications such as fire flow. To bill correctly then, we must know everything about that meter. It is imperative that utilities understand how the meter read and the meter data combine to generate an accurate bill for customers.
The majority of our water utilities employ manual or automated meter reading (AMR) systems such as a drive-by metering systems to obtain a meter read. Manual meter reading by either utility staff or the customer themselves is fraught with the potential for errors as data is being transcribed by human hands. While AMR systems can eliminate these transcription errors, the lack of immediacy and the low fidelity or granularity of data means the potential for errors is still high. In these circumstances, the inability to determine the instantaneous condition of meter means that errors cannot be detected until well beyond the read date.
To address these issues, utilities are migrating to high-frequency meter reading through advanced metering infrastructure (AMI) platforms to provide more immediate and granular meter reads, enabling a better understanding of the integrity of their meter read data.
Age & Volume
In many utilities, meter accuracy is inferred through artificially developed rules of thumb, such as time-based or cumulative flow-based assessments. While these theories can provide some basis for action, in practice the data isn’t nearly as conclusive as it needs to be. The correlation of age and volumetric throughput to accuracy contains significant scatter—more akin to a “cloud of probability” rather than an actionable trend—and an assessment of meter accuracy on a linear trend through this data is unlikely to generate meaningful results.
The proper installation of a meter device is critical to achieving accurate reads. Elbows, bends, valves and other appurtenances can negatively affect accuracy when they are in close proximity to the meter. In cases where the pipe or flow cavity of the meter may not be full, the accuracy of the results will also be suspect. Unfortunately, most utilities have poorly documented installation records for meters and there are ample opportunities for errors to be introduced by customer changes at the meter location.
In sizing a meter, it is important to consider the anticipated normal flow profiles as well as the instantaneous flow regime expected. In applications where there are large and/or abrupt fluctuations of flow, an improperly sized meter can add up to large volumes of water lost through inaccuracies. The result: increased water losses, significant under-billing and large shortfalls in revenue.
However, meter size is not simply a function of flow. Pressure drop, fire flow requirements, and fixture units counts are a few of the other factors used to size the water service and meter.
Low Flow Rate
Meters have specific flow ranges over which a new meter can be expected to be very accurate. At low flow rates though, meter accuracy can decline rapidly. While low flow performance varies by meter size, type and manufacturer, typically flows less than 0.125 gallons per minute for small residential meters and 1.5 gallons per minute for larger commercial meters are recorded with very low accuracy. In situations where vast differences between minimum and maximum flows are expected, then typically a compound meter that incorporates a large and small meter into a single assembly is installed.
Water utility billing is often the basis for billing additional services such as refuse and sewer. Often it is also subject to spatially-driven charges such as pump station surcharges, pressure surcharges and fire protection fees. Ensuring that accounts are being billed for these additional services as well as understanding where each meter is located with respect to these spatial boundaries is critical to ensure the correct revenue is collected from each customer.
GETTING A GRIP ON METER READ DATA
An accurate meter read is not as simple as getting the number from the meter—it requires detailed knowledge of the application, meter age, meter volume, customer segmentation data, and the installation specifics for a location.
To generate truly accurate bills—and therefore maximize the utility’s revenue from its customer base—requires that utilities adopt a broader measure of accuracy, expanding the term from the meter read to the entire spectrum of meter data.
FATHOM MDM offers this service to utilities of all sizes. By combining the best in geospatial data management with revenue assurance analytics that identify sources of missing revenue in the utility, FATHOM MDM offers a rapid, scalable and flexible platform that has been proven to increase revenue. The FATHOM MDM Solution can be delivered incrementally, with each carefully designed step designed to pay for itself, and is the key to unlocking the benefits of the data rich utility—and rescuing their revenue.
1University of North Carolina, Environmental Finance Center, (http://www.efc.sog.unc.edu/sites/www.efc.sog.unc.edu/files/HughesCascadePresentation_0.pdf)
22015 AWWA State of the Water Industry Report (https://www.awwa.org/Portals/0/files/resources/water%20utility%20management/sotwi/2015-AWWA-State-of-the-Water-Industry-Report.pdf)
4Davis, S.E., Residential Water Meter Replacement Economics, LEAKAGE 2005, Halifax, Canada, 2005