AMC's People Analytics Chief: Data Alone Is Only Half the Battle

AMC Theatres runs more than 500 cinemas across the United States, and the person who watches the workforce numbers behind them says AI has made reading that data easy — the hard part is making it usable. Adam Murphy, Director of People Analytics for AMC Theatres, made that case to attendees at the SPARK Talent conference. His core message: what separates a successful HR leader is not access to data but the ability to contextualize it and build tools people actually need.

For employers investing in people analytics, the presentation raised a practical adoption question. If AI can now process large swaths of workforce data cheaply, why do so many analytics projects still fail to change behavior? Murphy's answer centered on design and communication, not more measurement.

Why visualization comes before action

Technology has advanced to the point where HR leaders can track data points better than before. Murphy argued that having the data is only half the battle. Before a team can act on information, employees and managers must be able to understand it — which means expressing data in a form both groups can digest.

He drew a direct comparison to consumer software. "If you trade stocks, any stock app, right? It tells you what you need to know. It gives you an idea of what you need to do with it," Murphy said. "And that's the world we're living in with our employees, right? Those are the tools that they're used to. A lot of what I'm going to talk about today is about product and some principles in how you design and put forth data, not necessarily trying to explain data to you."

The framing is a notable shift. Murphy positioned HR data delivery as a product-design problem, the same discipline a consumer app company would apply, rather than a reporting exercise.

What are the three design rules?

Murphy offered three principles for building data tools that employees will actually use. He introduced them bluntly: "If you want to figure out how to get them to use it, get them to understand the what's in it for themselves, follow [these] three principles when designing [your data visualization]."

The principles are:

• Accessibility: Is your data available and visible when your employees need it?
• Intuitiveness: Is it easy to understand your data?
• Action-oriented: Are your employees able to work off of your data?

Each principle doubles as a test. An analytics dashboard that employees cannot find when they need it, cannot interpret without training, or cannot translate into a next step fails all three.

How does data turn into change?

Even well-designed data does not produce change on its own. Murphy cautioned against using analytics as a one-way channel for issuing new instructions. Communication works, he argued, only when everyone comes to the table.

"Performance management is not a one-way street," Murphy said. "It's not just supervisor to employee. It is employee to supervisor as well. They need to express their perceptions, what they need, and come to the table as well."

That position carries an implication for employers rebuilding performance processes: the value of analytics at a 500-plus-location operation like AMC depends less on the sophistication of the numbers and more on whether employees can see themselves in them and respond.

The takeaway

Murphy's argument, drawn from managing workforce data at one of the country's largest cinema chains, is that AI has made data collection cheap and the remaining constraint is human: tools must be accessible, intuitive and actionable, and performance conversations must run in both directions. As AI-assisted analytics spreads, employers who treat data delivery as product design — and who listen as much as they instruct — are the ones likely to see their numbers change behavior.