Revisiting AMI’s Business Case

Building a Smarter Water System through More than Metering

By Andrew Chastain-Howley

Advanced metering infrastructure (AMI) is a star attraction in the world of metering. Utility managers who hope for greater accountability and efficiency in customer billing may see it as a panacea. Although AMI carries many benefits, there’s much more to metering-system improvement than investing in AMI. Taking steps to fully examine the existing system prior to implementing AMI often yields a greater return on investment. 

Getting the Most from Your Current Metering System

Almost all utilities in North America have customer metering systems. These systems vary significantly in complexity and meter-reading methodology, but most utilities still rely on manual or drive-by readings.

Utilities with drive-by automated meter reading (AMR) systems generally read meters at a frequency that ranges from quarterly to monthly. Meter-reading frequency even varies within some utilities; some might read the lowest-volume meters quarterly and the highest-volume meters more often. AMI allows more-frequent readings. But how often the data is collected isn’t as important as how the data is used.

Utilities that use metering data exclusively for billing are missing the mark. Even quarterly data can be used effectively to analyze anomalous datasets that help utilities identify important metering issues such as failing meters or chronic leakage within a property. Although more frequent readings – such as monthly or hourly readings collected through AMI – make it easier to identify metering issues, utilities with less-sophisticated metering systems can analyze data using programs that utility staff are comfortable with. Such programs include Excel, Access, and other web-based applications, which enable wider sharing and collaboration. Utilities that use higher-order datasets, such as those developed through hourly or more-frequent AMI data, need to use different tools to extract full operational intelligence from the collected data. 

Many utilities don’t fully or regularly document or evaluate meter failures and customer billing issues. Leading utilities, however, report on meter-failure trends and record data such as meter age, throughput, manufacturer, model, size, service-line age and material, and pressure at the service connection as a minimum. Evaluation of such a dataset enables some level of prediction for future failures, provides feedback for new meter purchases, and connects infrastructure data to additional databases such as meter accuracy testing. As a result, these utilities can evaluate meter inaccuracy and other apparent water losses throughout their systems. More information about water losses and meter accuracy is available in AWWA manuals M6 (Water Meters – Selection, Installation, Testing and Maintenance) and M36 (Water Audits and Loss Control Programs).

Black & Veatch.

Add Analytics & Data Integration

Approximately 63 percent of survey respondents for the Black & Veatch 2020 Strategic Directions: Water Report currently use AMR or AMI, but only 25 percent of the survey respondents see these technologies as elements of a digital water initiative and only 20 percent think their utilities are effectively leveraging all the data they collect.  These statistics highlight the importance of optimizing existing metering systems to prepare for upgrading to AMI and creating a smarter water system. Even AMI systems will be glorified meter-reading systems if additional functionality is not enabled prior to or during AMI implementation.

It makes sense to establish analytical programs and the associated data integrations before investing in AMI or another metering and networking upgrade. This will allow utilities to understand the accuracy of the existing system how an upgrade will improve it and to enable validation and reduction in errors or estimations. It will also improve documentation of key data variances, such as meter serial and identification numbers or units of measure, for systems integrations. A basic version of a meter data-management system to address these needs might suffice; it isn’t always necessary to install the highly structured, complex packages used by the largest utilities.

A metering system can gain a wider software scope through connection to a customer information system (CIS), which acts as the customer data source of record and generally is the primary billing mechanism. Most utilities can maintain consistency in their CIS or other billing systems throughout the life of an upgrade. Data connectivity may change, but the data format, frequency, and outputs usually stay constant throughout the implementation of AMI. A full understanding of inputs should precede consideration of a system upgrade.

Connecting analytics to the billing-system data output can show what more is needed or possible before adding any new software to the mix. Integration tools can help utilities combine added software products to permit use of the most suitable datasets.

In many cases, utilities that implement metering upgrades or AMI systems choose to use only the vendor’s software to manage and provision data beyond the billing-system connection. This may be the best decision for the short term, but often it is not the best long-term solution because narrowly scoped software isn’t necessarily designed to accommodate the various other work items that a water utility needs to connect to. Such software may not allow utilities that want smarter water systems to realize the widest possible array of benefits. 

Some analytics and data integration tasks can be completed prior to an AMI implementation to help utilities with existing metering systems efficiently and effectively prepare. As an example, figure X shows review of meters with zero flow recorded on a monthly basis to benchmark a possible risk factor when transitioning to AMI and to drive analysis of possible existing failing meters. Advanced analysis and data integration might encompass any of or all the following: 

  • Spatial location of infrastructure
  • Meter repair and replacement history for all components associated with each meter
  • Condition of metering and service-line infrastructure
  • Failure rate of existing meters, registers, and (if appropriate) meter-interface units
  • Meter multipliers for larger meters
  • Standard variations of use by meter size and customer classification
  • High-use alerts
  • Field validation of anomalies, and recording and reporting of trends

How Will My AMI Investment Pay Off?

Considering an investment – and return on investment – in AMI is complicated but necessary. Business-case factors and resulting decisions vary with system size and layout. For example, utilities that serve rural areas may have a completely different model due to comparatively long distances traveled for manual or drive-by readings as well as network location differences that make some network structures more viable. What makes business sense for one utility may make very little sense for another.

Figure 1 – Data management analyses of monthly data prior to transition to AMI.

Before implementing a full AMI program, it’s also important to consider metering-system accuracy. AMI deployments are often packaged with meter replacements, which is reasonable bundling for utilities that are ready to move to the next level and have poorly performing meters. However, utilities may not need AMI to improve meter accuracy. How to improve meter accuracy and how much return on investment (ROI) to expect from AMI are really two separate matters. 

Many in the water industry see AMI as a way to increase income. But AMI is really a capital improvement with a direct financial return on investment best linked with existing meter-reading and billing costs and improved customer service. Think of AMI like a treatment plant, which has a specific benefit to customers without a specific way to recover construction costs; AMI doesn’t always have a specific cost benefit or return on investment. In most cases, ROI analysis based strictly on financial terms (not including secondary or soft benefits) shows AMI programs to be neither cost-neutral nor cost-negative. Packaging AMI with meter replacements and other improvements allows projects to show favorable ROI, but making such conversations more transparent helps utilities more clearly consider the value of all the benefits of an AMI program compared to focusing only on the value of a meter-accuracy upgrade.

True AMI benefits – such as reduced ongoing staff risk, reduced carbon footprint, improved billing, and granularity of data (which unlocks many other possibilities) – should be part of internal and external performance-measurement reports and dashboards. As with any dataset, knowing what happened before a change is important to create the baseline for future comparison. Activating datasets before initiating a metering upgrade is therefore very important.

Consider Gaps Before You Leap

Upgrading to AMI offers water utility metering systems that currently are not performing optimally the potential to make a leap in technology and make operational improvements prior to that leap. To do this as effectively as possible, utilities need to fully understand their existing systems and infrastructure. Although readings are more frequent, the data collected from AMI systems is very similar to the data collected from manual systems. So optimizing the data structures and analysis to prepare for more-frequent reads with AMI is even more important. Once the right structures, analyses, and associated reporting are in place, utilities can feel comfortable and confident in moving ahead with AMI.

Andrew Chastain-Howley is a director in the Global Strategic Services Group with Black & Veatch’s water business. He has more than 28 years of experience in the fields of data analytics, advanced metering, water loss and water conservation.

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