Member Spotlight

Carter Dougherty, EVP, Analytics – AMS

AMS provides advanced online water quality monitoring solutions with a strong focus on delivering accurate, real-time data utilities can rely on to improve their treatment processes and operations. For more than a decade, we have combined proven analyzer technology with continuous remote monitoring and a comprehensive data quality assurance program to help utilities move from simply collecting data to acting on it with confidence.

The industry talks a lot about “digital transformation,” but in reality many utilities still struggle with unreliable or incomplete data. What’s holding the sector back from making data truly operational 24/7? And who needs to change: utilities, vendors, or both?

The water industry has undergone a significant shift over the last decade. With ‘digital transformation,’ utilities are now generating enormous volumes of real-time water quality data, and with that comes an important question: can you trust the data?

One of the key challenges is that online instrumentation has too often been designed simply to generate data, with insufficient emphasis on validating or contextualising it beyond routine calibration. Reliable operational decision-making requires more than raw numbers; it requires confidence that every datapoint is trustworthy.  Without that, data risks becoming something utilities collect, rather than actively used, in order  to improve operations.     

Addressing this gap requires change on both sides. Utilities are increasingly moving away from treating online monitoring as a one-off capital purchase and toward seeing it as part of an integrated operational capability. At the same time, there is a growing expectation that solution providers are accountable not just for equipment performance, but for the reliability and usefulness of the data it produces.

Operational data only becomes valuable when utilities can trust it in real time, 24/7. That means data quality needs to be continuously assessed alongside the measurement itself, not treated as a separate exercise limited to periodic calibration checks.

But technology alone is not enough. When unexpected results occur, they need to be investigated in an operational context rather than simply flagged or ignored. Making data truly operational requires ongoing engagement, interpretation, and shared accountability between utilities and solution providers.

Ultimately, the industry is moving toward a model where trusted data is supported not just by instrumentation, but by continuous validation, operational insight, and collaboration. That is what turns data into something utilities can confidently operate with.

As we move toward Data-as-a-Service and outcome-based models, data availability is becoming just as important as data accuracy. The opportunity is clear, but what needs to come together for the industry to fully realise the value of always-on, trusted data?

For Data-as-a-Service (DaaS) models to scale, utilities, regulators, and technology providers need to align on long-term operational value rather than focusing primarily on upfront equipment costs. The real opportunity lies in what continuous, high-quality data enables: more efficient treatment processes, improved compliance confidence, and better use of limited operational resources.

In this context, data reliability is just as important as measurement accuracy. Together, they underpin decisions that can reduce chemical and energy use, improve workforce efficiency, and help prevent compliance issues before they occur.

Achieving consistently high availability is not without cost. It requires robust instrumentation, continuous system monitoring, advanced analytics, and the capability to interpret and act on data in near real time.

Where DaaS models are gaining traction is in shifting the focus from owning infrastructure to accessing assured operational insight. As that shift continues, the key question for utilities becomes less about the purchase model and more about whether the data is dependable enough to run critical operations on.

Digital water only works as well as the partnerships behind it. What does a real high-performing collaboration between utilities and solution providers look like, and where do most successful partnerships get it right?

The utilities that achieve the greatest success are usually those that view solution providers as strategic operational partners who bring scientific expertise, operational insight, and ongoing support, not just instrumentation vendors.

High-performing partnerships start with a shared understanding that digital solutions are not about deploying technology or making a one-time purchase; they are about delivering operational outcomes. 

The strongest partnerships are typically characterised by three things. First, clear alignment on the operational challenge being solved, whether that is reducing treatment costs, improving compliance confidence, increasing resilience, or managing workforce constraints. Second, both sides commit to continuous engagement rather than a “deploy and disappear” model. Third, a willingness to embrace a more data-driven operating culture and use continuous insights to guide decision-making.

Where the best partnerships really stand apart is in their ability to collaborate effectively through the inevitable learning curve that comes with innovation. Success depends on responsiveness, accountability, and a readiness to refine system usage after implementation.

If you were starting your career in water today, what would you be most eager to challenge, rethink, or completely rebuild, and why?

That’s a great question. I would probably challenge how we think about data systems altogether.

The water industry is now at a point where the technology exists to fundamentally rethink how utilities operate. We can generate continuous, real-time insights across treatment and distribution systems, yet many organizations still operate with workflows and procurement models built for a much earlier era. I would like to help accelerate the transition to truly data-driven operations.

I would also challenge the tendency to evaluate technology primarily on upfront capital cost rather than long-term operational value. In many cases, the least expensive solution on day one can ultimately prove the most costly when downtime, maintenance, compliance risk, and operational inefficiencies are taken into account. The industry has an opportunity to shift toward valuing reliability, resilience, and actionable data outcomes alongside measurement accuracy.

Perhaps most importantly, I would want to help rebuild the connection between data and operational confidence. Utilities are facing increasing pressure from aging infrastructure, workforce shortages, stricter regulations, and more complex source water challenges. Continuous, reliable, trusted data can help operators move from reacting to problems toward anticipating and preventing them. That shift has the potential not only to improve efficiency and compliance, but also to make the industry more attractive to the next generation of engineers, scientists, and operators who want to work in a modern, technology-enabled environment.