Ulrich B. Hansen is the CEO of APX10. He can be reached at [email protected].
Over the past 30 years, water specialists in the Nordics have adopted a forward-looking approach to digital asset management and data-driven decision-making. These countries’ proactive integration has led to the establishment of best practices utility leaders in the United States can learn from to improve CAPEX spending, lower OPEX costs, and guarantee streamlined and resilient service.
According to the 2021 Infrastructure Report Card, monumental challenges exist for U.S. drinking water, stormwater, and wastewater systems. A glimpse into the complex difficulties prompts concern, notably:
- Water utilities are losing an estimated 6 billion gallons of treated water each day in the U.S.
- Wastewater utilities are operating at an average of 81% of their design capacity.
- Stormwater systems are confronting chronically underfunded maintenance on 3.5 million miles of storm sewers, 270 million storm drains, and 2.5 million stormwater treatment assets.
Having reliable drinking water, stormwater, and wastewater distribution systems is not just a necessity for private households; It also has a great impact on the industrial sector, which is heavily dependent on freshwater. As a direct or indirect consequence of future service disruptions, ASCE projects a cumulative decline of $2.9 trillion in gross domestic product by 2039 if the gap between required and actual investments in infrastructure is not addressed.
The pressing need for investment in aging infrastructure as well as limited budgets are forcing municipalities to not only replace network infrastructure, but also modernize operation with data analytics to leverage smarter, predictive, and cost-effective technologies. Digital asset management and predictive analytics represent two subsectors of the crucial transformation; however, many water utility professionals are unaware of their potential.
Definition, Methodology & Implementation
Digital asset management is a process that leverages data to manage long-term planning for the purchase, deployment, and decommissioning of infrastructure assets. Predictive analytics is a tool used in digital asset management that gathers data through real-time machine learning, modeling, and data mining to understand, analyze, and forecast diverse scenarios. These prognostic planning frameworks clarify challenges and opportunities that may arise as utility decision makers weigh lifecycle costing and value engineering.
In the Nordic countries, data-driven decisions have increased utility efficiency substantially. In Denmark, for instance, strict regulation has made it one of the most efficient and resilient in the world over the last 30 years by compelling the water sector to adopt leading-edge technology. Recently, the Danish sector progressed from simply benchmarking operating costs into intelligently developing a total financial benchmarking model (TOTEX). This approach includes both OPEX and CAPEX to compare the utilities on financial efficiency.
Consequently, a number of water utilities, with small budgets and operations resembling those in the U.S., were forced to further reduce their infrastructure investments by at least 1.5% per year. This economic constraint compelled them to prioritize and improve investment planning, and they relied heavily on digital asset management to accomplish this goal.
In Norway, digital asset management and the data|APX platform are used to optimize utility economy and resilience. A great example is the Norwegian utility - Nordrefollo – which jumpstarted the process of adapting digital asset management by simplifying the complex in a three-step process that
- Captures data;
- Analyzes data; and
- Enhances those data insights.
This sets up management and operators with proactive, dynamic, and actionable intelligence for precision reinvestment priorities.
Using the platform, Nordrefello’s digital asset management adoption onboarding process was completed in two weeks, and the organization introduced and trained to work digital software within the first month. Furthermore, the always critical data cleansing process was semi-automated and Nordrefollo was able to bring down a planned 12-month process to only 1.5 months.
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Reducing Leaks & Minimizing Non-Revenue Water
Through a complete criticality overview of the infrastructure for drinking water, wastewater and stormwater, Nordrefollo’s investment planning pipeline is now being refined to minimize high leakage and non-revenue water volumes. This holistic planning is optimizing Nordrefollo’s external water procurement, ultimately reducing the cost of drinking water by more than 50%.
The Danish utility ARWOS is another great example of how digital asset management and predictive analytics enable service in the real world. This southern Danish utility experiences many hurdles comparable to problems in the U.S., such as extreme weather occurrences, deficient infrastructure, and restricted budgets.
One of the most pressing concerns at ARWOS is to limit overflows and infiltration to decrease their OPEX, as the difference from a year with high precipitation compared to a year with low levels of rainfall is approximately USD $1.5 million. However, the cost itself is not the only strain. It can be equally demanding to identify the location. As part of the solution, ARWOS integrated data|APX to support the utility’s decision-making and prioritization of reinvestment decisions. Using the platform, ARWOS has been able to locate annual savings in the range of USD $250,000 due to the identification of rainfall-derived inflow and infiltration, all within the first year.
Asset Management
The platform provides an overview of ARWOS assets criticality based on their own existing data and public data. ARWOS uses the platform to assimilate multiple datasets such as GIS data, CMMS data, SCADA data, IoT data, and CCTV data to make it easy to pinpoint critical areas. The addition of the platform helped reduce inspection costs, minimize risk of failure for critical assets, and prioritize areas to refurbish.
In the Nordics, it is consensus that a simple and intuitive approach to asset management among water professionals is required to update and scale operations. There are too many fragmented spreadsheets, personal know-how, and data silos that would instead benefit from a holistic platform that allows for better-supported management decisions. A platform like data|APX has dynamically involved Nordic water utility leaders in the development of the solution to assimilate their best practices. U.S. utility leaders are then able to utilize the utility know-how from the various Nordic countries, regardless of geography.
Transferring Knowledge Overseas
Since at least 2014, Nordic and U.S. water professionals have exchanged best practices and technologies in the water and wastewater sector. Digital asset management with predictive analytics is one of the areas where U.S. utilities will profit with time, capital, and efficiency gains from the experiences in the Nordic water sector.
In the U.S., many small-and-medium utilities face extremely tight budgets. They should rest easier knowing certain straightforward, cost effective, and flexible data analytics solutions exist to combat these economic constraints. These data analytics solutions do not require numerous consultations, onboarding, or big investments to get started.
By leveraging existing data like CCTV data, SCADA data or other available data streams, a utility can generate the savings with the right tools like those widespread in the Nordics. These tools build upon deep understanding of utility data and can serve a fundamental role in the data-driven transformation and ROI of drinking water, wastewater, and stormwater utilities and systems in the U.S.
