By Jamal Syed, HEXstream president and CEO

I have been working in the analytics space for more than 35 years, and during that time I’ve had the opportunity to see how the role of data in decision-making has evolved. I remember when analytics was simply static output generated by COBOL jobs. Over time, those outputs became more descriptive reports, and eventually dashboards and KPIs emerged to provide greater visibility into operations. Each step in that journey made data more accessible and more useful, and each represented meaningful progress for our industry.

However, there has always been an underlying limitation.

Dashboards and KPIs are very effective at answering known questions. They allow users to drill down from summary information to detailed data, but only along predefined paths. When a new question arises—something outside those predefined paths, the typical response is to build another KPI or another dashboard. That approach served us well for many years, but the environment utilities operating today is far more dynamic than it was even a decade ago.

With the advent of artificial intelligence, the paradigm has begun to shift in a fundamental way. If implemented correctly, analytics is no longer just about viewing data—it is about interacting with it. Instead of navigating through layers of reports and dashboards, users can ask a question in plain language and receive an immediate answer. In many ways, this
represents the most significant transformation in analytics since the introduction of dashboards themselves.

At the same time, it is important to recognize that delivering this kind of experience requires more than simply adding AI to an existing system. It requires a disciplined data model, strong governance, and careful training of the underlying platform. Technology alone does not solve the problem; architecture and design do. Without that foundation, the promise of conversational analytics remains difficult to achieve in practice.

This is where many current outage analytics solutions begin to show their limitations.

Most of these solutions rely on rigid data models that restrict the ability of users to explore their data beyond predefined workflows. In addition, many are developed by software vendors who understandably design their analytics tools to work primarily with their own outage management systems. While that approach makes sense from a product perspective, it can limit flexibility for utilities operating in complex and evolving environments.

Another important reality is that, although utilities share many common operational challenges, no two utilities are exactly alike. Each organization has its own reporting requirements, operational priorities, regulatory expectations, and customer communication needs. These requirements also change over time. A fixed analytics platform, no matter how sophisticated, cannot anticipate every future scenario or requirement.

At HEXstream, we have always believed that analytics is not a one-time implementation or a completed project. It is an ongoing process—one that must continuously adapt as the business evolves and as operational demands change. That philosophy has guided much of our work over the years, and it ultimately led us to make a significant decision in the past few months.

We chose to rebuild Utility360—a platform with solid analytics foundation that can cater to all traditional analytics needs and can also provide advanced analytics capabilities.

Our new Utility360 platform, now live and available for demo, is an AI-enabled outage analytics platform built on a pre-trained utility data model designed specifically for operational environments. It provides a strong analytical foundation that can be implemented in weeks rather than months or years, reducing the time and effort typically associated with large-scale analytics deployments. More importantly, it is designed to be configurable to each utility’s unique operational and reporting needs, allowing organizations to adapt the platform as their requirements evolve.

Our goal was to create an enterprise-level solution capable of supporting the complex demands of large Tier-1 utilities, while also making advanced analytics accessible and practical for mid-sized and smaller organizations. In other words, we wanted to build a platform that combines robustness with flexibility—one that can grow alongside the utilities it serves.

What excites me most, however, is not the technology itself. It is what becomes possible when utilities can interact with their data naturally and intuitively—when operators can ask questions in the moment and receive immediate answers, when leaders can identify emerging risks before they escalate, and when decisions are guided by timely insight rather than delayed by information gaps. In those moments, analytics moves from being a passive reporting tool to becoming an active part of daily operations.

We are entering a period where analytics will no longer sit on the sidelines of utility operations. Instead, it will play a direct role in how utilities manage outages, allocate resources, communicate with customers, and maintain system reliability. Systems will increasingly learn from operational patterns, adapt to changing conditions, and support faster, more informed decision-making across the organization.

In the years ahead, the most successful utilities will not simply be those with the most data. They will be the ones that can transform that data into actionable insight—quickly, reliably, and continuously.

That is the future we are working toward. And that is why we rebuilt Utility360.

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