Two things can be true at once: I went to Sweden for a hockey analytics conference, and I came home thinking even more deeply about change management.

The Linköping Hockey Analytics Conference (LINHAC) brings together researchers and practitioners exploring hockey through data and analytics. Liz Goldstein, a Researcher at ORRO a sports analytics firm that turns game-level data into organizational decisions, and I attended after our paper on National Hockey League (NHL) player career longevity was accepted for presentation during the conference’s Academic Day. We are not hockey insiders, just two friends from UVA Darden School of Business who have teamed up on an analytics project every year since 2022. This year, the question was hockey, a natural choice given my longtime support of the Carolina Hurricanes and for their recent Stanley Cup win.

We started with a question, built a dataset, and worked through the analysis. Eventually, we applied landmark analysis—a method from biology—to NHL player career longevity. That was the novel piece, and it was enough to earn us a spot at LINHAC.

Presenting our research was rewarding, but what stayed with me most was a theme that surfaced throughout the conference. Whether the discussion focused on player behavior, coaching decisions, front-office strategy, or analytics adoption, it kept coming back to the same question: What do people do with the information once they have it?

The Data Has to Mean Something First

One presenter described walking an assistant coach through the numbers for 45 minutes, then asking if the information made sense. The coach said no. It was not because he was uninterested or because the data was flawed; he just did not know what action he was supposed to take. That story captures the premise of change management. At LS3P, change management is a structured approach to helping people move from a current state to a desired future state. Data is the starting point, not the outcome.

Across our work, we collect information about organizations, spaces, teams, behaviors, and needs. We analyze patterns and use data to build a clearer picture of what is happening today. But its value becomes visible when we sit beside a client and explain what the findings mean, why they matter, and how they can inform the next decision. That could mean helping a commercial client understand how employees use space before establishing a new workplace strategy. It could mean translating stakeholder input into planning priorities for a campus or community. It could also mean helping a project team recognize how operational patterns, organizational culture, or employee behaviors should shape programming and design.

Translation is not secondary to the analysis. It is part of the analysis. Without it, data remains interesting but inactive.

Translation Is Relationship Work, Not Simplification

It is tempting to think that making data understandable simply means removing jargon. That matters, but what I heard at LINHAC was deeper. Translation requires understanding the person in front of you. What do they care about? What are they trying to accomplish? What would help them make a better decision tomorrow?

That shift, from “here is what I found” to “here is what you need to know,” is where analytics becomes change management. It is also why LS3P’s process begins by listening. Stakeholder interviews, visioning sessions, focus groups, surveys, and programming conversations help us understand not only what people say they need, but also what matters to them and how they experience their work or environment.

People rarely change because they are handed information. They are more likely to engage when the information connects to a goal they already value, is communicated in a way they can understand, and comes through relationships they trust. For our work, that means a successful recommendation cannot be based on data alone—It must also reflect the client’s culture, language, readiness, and priorities. The same finding may need to be communicated differently to an executive team, a department leader, a facilities group, or an employee who will experience the change every day.

The Best Teams Learn Before They Talk Themselves Out of Learning

One of my favorite sessions explored how high-performing teams debrief. The framework referenced the work of Dr. Susan Wheelan, a psychologist and professor at Temple University known for developing the Group Development Questionnaire and identifying five phases of team development.

After a fast-moving game, players first answer several questions individually. They then discuss their observations in small groups before reconvening as a full team. That order matters. People take cues from one another, and when group conversations begin too quickly, valuable insights can disappear before anyone shares them. That lesson applies directly to the way we facilitate visioning sessions, focus groups, design workshops, and lessons-learned conversations at LS3P. Moving immediately into open discussion often elevates the most vocal participants while overlooking perspectives from those who process information differently or prefer time to reflect.

Individual reflection before discussion creates space for a wider range of ideas and experiences to emerge. The workshop also reinforced the importance of varying the questions we ask. When every debrief or workshop follows the same script, responses can become predictable, limiting opportunities for new insights.

Trust Has to Be Built Before the Complicated Moment

An analyst working remotely with a team in Switzerland described what made the arrangement work: not the technology, but the relationship he’d already built with the coach, and the deliberate effort to stay connected to teammates who weren’t in the room. 

That’s a client-service lesson as much as a remote-work one. It’s also why our change management work starts during programming — well before design, delivery, or move-in — rather than being bolted on at the end. Trust doesn’t appear when the work gets complicated. It has to already be there.

From Insight to Action

One of the most interesting parts of LINHAC was seeing where different organizations are in their analytics journey. Many European leagues are asking the same questions NHL teams once asked: Why do we need this? Can’t we just watch the game? Those are not data questions. They’re change management questions.

The organizations that succeed will be the ones that integrate analytics into decision-making, communication, and behavior. The same is true at LS3P. We are already collecting and analyzing valuable project data. The opportunity is turning those insights into better decisions, stronger collaboration, and meaningful action. Because access to data is not the same as understanding, and understanding is not the same as action.

For three days, I left my laptop behind and was fully present, listening, taking handwritten notes, and having real conversations over fika instead of half-watching my inbox. That experience reinforced a simple truth: data matters. Strategy matters. Models matter. But people still have to live the change. A player still has to take the shot. A client still has to make the decision. A team still has to trust one another enough to say what they actually learned.

That’s what I loved about LINHAC: hockey, analytics, people, change management, and the Carolina Hurricanes in the Stanley Cup Finals, all in one place. It reminded me that the future of analytics is not just more data. It’s better translation, stronger relationships, and more intentional action.

Because the numbers only matter if people know what to do with them.