UCLA Anderson School of Management
How one of the world's top business schools secured its most valuable data — without slowing down a single faculty member
AT A GLANCE
Company: UCLA Anderson School of Management is consistently ranked among the world's top business schools. Its faculty produces research that shapes industries — intellectual property that represents not just institutional value, but the life's work of individual scholars. Protecting that work, in an increasingly cloud-driven environment, is both a technical challenge and a deeply human one.
Contacts: Howard, Chief Information Officer; Mark, Director of IT Security
Challenge: A faculty community that notices performance changes measured in milliseconds. A small security team. Previous tools that felt invasive and generated resistance. A cloud migration expanding the exposure surface. Jazz had to solve all of it — invisibly.
Outcome: Jazz deployed with a near-zero performance footprint. It surfaced sensitive data exposure scenarios — including screenshot capture — that no other tool could see. And it gave the security team back the bandwidth to focus on real threats rather than triaging noise.
THE CHALLENGE
Protecting data at a research institution means protecting things that are genuinely irreplaceable. For Anderson faculty, their research isn't a work product — it's a career, sometimes decades in the making. "Their research is their life's work," says Howard. "Losing that would be detrimental in so many different ways."
The move to cloud made this more urgent. As Anderson migrated to SaaS applications and cloud infrastructure, data that once lived in controlled on-premises environments began moving across a much wider surface. More movement means more exposure, and more opportunity for things to go wrong in ways that are genuinely hard to see.
Previous DLP deployments created a different problem. When the school installed them, faculty noticed immediately. The tools carried a surveillance quality that generated pushback. Any perceived impact on machine performance — even changes imperceptible to most users — triggered complaints from a community that values independence and expects seamless technology. "When we put software on a faculty member's machine, they know right away," Howard says. The cultural friction made those tools untenable.
And even setting aside the political challenge, the tools themselves couldn't keep up. Rules-based detection couldn't account for the behavioral context of academic work. What looked like a suspicious event for one user was entirely routine for another — and a system without that understanding generated constant noise. For a small team, working through that volume was, in Mark's word, "maddening."
"Probably what was most salient about Jazz and differentiating is the fact that it runs with a really, really small footprint."
— Mark, Director of IT Security, UCLA Anderson
THE SOLUTION
Two things set Jazz apart in Anderson's evaluation: footprint and intelligence.
On footprint: Jazz's endpoint agent runs at under 1% CPU. In an environment where faculty track performance changes they feel at a nanosecond level, invisibility isn't a nice-to-have — it's a prerequisite. Jazz works at the user-space level, capturing clipboard activity, screenshots, file movements, and application interactions without touching the performance experience faculty members expect.
On intelligence: Jazz understands data in context, not just in isolation. When a faculty member moves 2 GB of files, Jazz doesn't fire an alert by default — it asks whether this is something they do regularly, what the destination is, and whether the pattern fits their normal behavior. If it does, it's silent. If it is risky, it surfaces — and the team knows it's worth their time.
"That frees us up to do other things," Mark says. "But when Jazz does let us know something is happening, we know it's something we need to investigate."
For Howard, who thinks carefully about where to place long-term technology bets, the AI-first architecture mattered as much as the current capabilities. As Anderson's environment continues to evolve — more cloud, more SaaS, more AI tools woven into academic workflows — a platform built for intelligence from the ground up is a more durable investment than one bolted onto legacy rules infrastructure.
RESULTS
Value appeared almost immediately — and in ways the team hadn't been able to achieve before.
Early in the deployment, Jazz surfaced something no previous tool had ever detected: a user capturing screenshots of sensitive data. Screenshots are invisible to browser-extension-based DLP, invisible to network-layer tools, invisible to anything without OS-level visibility. Jazz's Context Vault caught it natively. "That's something we never would have been able to detect with any other DLP tool," Mark says.
Beyond the detection capability, the team gained something rarer: confidence in the signal. When Jazz flags something, it means something. That shift — from a tool that generated noise to one the team trusts — changed how the security function operates at Anderson.
"I can almost guarantee you will see the value in the same way that we here at the Anderson School saw value in the tool."
— Howard, CIO, UCLA Anderson School of Management
Looking forward, Howard sees Jazz as a permanent fixture in Anderson's security stack: "We have a tool that will not only do what we need today — but forecasting ahead, we see that it will grow with us and continue to be a linchpin within our security portfolio."
For academic institutions navigating the same combination of cultural sensitivity, lean teams, and rapidly expanding cloud environments, Anderson's experience points toward something simpler than the traditional DLP equation: a platform that understands your organization, not just the shape of your data.