By Sarah Nicastro, Creator and Editor in Chief, Future of Field Service

There are certain environments where “good enough” simply isn’t good enough.

Fenway Park is one of them.

When you think about a venue like Fenway – its history, its visibility, the sheer volume of people it hosts – you begin to understand that service delivery in that context isn’t just about uptime. It’s about precision, orchestration, and an almost obsessive level of diligence.

In last week’s podcast conversation with Greg Parker, Vice President of America’s Life Cycle Solutions at Johnson Controls, recorded on-site at Field Service Next West, He shared a bit about what it actually takes to deliver on that level of expectation. And a shocking statistic: how his team has achieved 95% remote resolution of issues.

What stood out to me wasn’t just that number, though. It was the execution of what has to fundamentally change from traditional break-fix service to make a number like that possible.

One of the most striking points Greg shared is that, on average, organizations don’t even have visibility into roughly 25% of their assets.

Think about that for a moment. Service leaders are being asked to guarantee outcomes, reduce costs, and elevate customer experience – all impossible feats with a blind spot that large.

This is the core flaw of reactive service models: you can’t manage what you can’t see – so you’re stuck with sending a technician to diagnose the issue. At Fenway, that type of process simply wasn’t viable. Shifting to a proactive model required Johnson Controls to establish real-time visibility into every asset – but that was just the start. Here are five lessons Greg shared from the company’s work with Fenway.

#1: Remote Resolution Isn’t a Technology Story – It’s an Orchestration Story

It would be easy to attribute a 95% remote resolution rate to technology alone, but that would miss the point – and do a disservice to the effort involved.

What Greg described is really about orchestration – bringing together connected assets, centralized command, field operations, and intelligent data in a way that works seamlessly.

At the center of this is a managed service model supported by a centralized team that monitors and manages asset performance in real time. When something deviates from expected behavior, alerts are generated, prioritized, and acted upon – often without ever dispatching a technician.

And here’s what they found: many of those issues are simple. A connectivity glitch. A configuration issue. A reboot.

In a reactive model, those same issues would still trigger a truck roll – adding cost, delaying resolution, and frustrating the customer.

The difference isn’t in the complexity of work changing, but what’s mde possible with increased awareness.

#2: AI Doesn’t Replace Humans, It Empowers Them

Another important nuance in the approach Greg described is how AI is being used.

There’s a lot of discussion today about AI-powered automation replacing human decision-making. But in high-stakes environments, including stadium security, that’s not where customers (or providers) are comfortable yet (and maybe ever).

Instead, Johnson Controls has taken what Greg calls a “human in the middle” approach.

AI is used to curate, prioritize, and contextualize data – essentially teeing up the right information so that human operators can make faster, better decisions.

This does two critical things:

• It allows a relatively small team to scale without linear headcount growth
• It reduces both false alarms and human error by improving the quality of decision-making

In other words, AI isn’t removing humans from the equation; it’s making them exponentially more effective.

And that’s a far more practical (and powerful) application than many of the headlines suggest.

#3: You Can’t Deliver Outcomes Without Designing for Them

One of the most important lessons from this transformation is that you don’t stumble into outcome-based service – you have to design for it.

Greg described the need to map managed services end-to-end, from order intake through execution to billing. Every step in that value stream must be aligned, because gaps – no  matter how small – compound quickly in execution.

In fact, some of the most critical issues his team uncovered before launch were what he described as “minor bugs.” The kind of things that might be overlooked in a traditional rollout, but that would ultimately prevent the organization from delivering on its commitments at scale.

This is where many service transformations fall short: Organizations underestimate the operational rigor required to deliver consistently against new service models.

#4: The Service Contract Is Changing, Whether You’re Ready or Not

Perhaps the most significant implication of everything Greg shared is what it means for the future of service agreements.

When you have the visibility and capability to proactively manage assets, the entire basis of the customer relationship changes.

Customers are no longer willing to pay for your inefficiency – for truck rolls that may or may not resolve the issue, for downtime caused by a lack of insight, or for reactive service that could have been prevented.

Instead, they’re expecting outcomes. And increasingly, they’re expecting those outcomes to be guaranteed.

Greg put it simply: connected assets and the data they provide are becoming table stakes. Not a differentiator; not an add-on. A requirement.

That raises an important question for service leaders: Are your capabilities evolving at the same pace as your customers’ expectations?

#5: Not All Service Environments Are Created Equal

One final point that’s worth emphasizing is the level of diligence required in high-density, high-visibility environments like Fenway.

Serving a stadium with 80,000 people in one place isn’t just a scaled-up version of another vertical, it’s fundamentally different. The tolerance for failure is lower. The consequences are higher. And the margin for error is virtually nonexistent.

What that demands is a level of planning, testing, and execution that goes beyond standard approaches. It’s a reminder that as service organizations scale, they also need to consider customer segmentation – recognizing that different environments require different levels of rigor.

Stepping back, what this story really illustrates is the broader shift happening across service industries and customer segments:

• From reactive to proactive
• From visibility gaps to data-driven insight
• From labor-dependent scaling to technology-enabled productivity
• From transactional service to outcome-based partnerships

The 95% remote resolution rate is impressive, but it’s ultimately a byproduct of these deeper changes. And while that specific target may not be attainable in every customer example, the shifts Greg retold are valuable across the board.

For organizations that haven’t yet embraced how service is evolving, the gap isn’t just operational; it’s strategic. The expectation for what service should deliver has already moved forward, and companies like Johnson Controls are doing the work to keep pace – those who don’t (or won’t) risk irrelevance in the near future.