How Micron Redefined Quality of Hire: 3 Lessons for Talent Acquisition
Find out how Micron's Jackson Teng uses people data like downstream workforce data, including retention patterns, performance outcomes, and succession signals, to redefine quality of hire and turn Talent Aquisition into a strategic function.
Hiring has often felt more like an art than a hard science. Chemistry, gut feeling, and a good first impression have long been the signals we trusted to decide who belonged in our organizations. But today, that approach isn’t enough. Hiring demands much more precision, more rigor.
During our recent webinar, "The Science of Great Hiring," I had the privilege of sitting down with Jackson Teng, Senior Director of Asia Talent Acquisition, Workforce Development & Pathways at Micron, to explore how they are rethinking what great hiring actually means.
At Micron, they’re applying workforce signals to define quality of hire, shape hiring criteria, and ultimately "underwrite" future business value. These are key lessons from an organization that’s mastered turning external talent into future business leaders.
Lesson #1: Start underwriting future business value
Most Talent Acquisition teams are measured on speed and volume—how fast they fill a role, how many hires they close. But what we heard from Teng during the webinar is how this framing sets TA up to answer the wrong questions.
"We shouldn't just be filling roles. We really should be looking at how we underwrite our future performance, retention, internal mobility, and succession—even right from the first interview."
Teng’s perspective was shaped by his time spent as an HR Business Partner, where he had direct visibility into what happened after the offer letter was signed.
"I had the opportunity to not only see who we hired, but also who stayed, who thrived, and who progressed—as well as those who quietly quit or exited. That kind of downstream view exposed something really critical: many hiring decisions may have made sense in the moment, but not necessarily all of them created long-term value for the business."
That experience changed what Teng looks for in new hires. Beyond skills and experience, the questions he's now asking include: does this candidate show learning velocity and agility? Will they thrive in Micron's performance culture a few years from now, as the business evolves?
Micron is now treating people data as business data, and this is helping TA ask the right questions about what talent they need not just today, but in the future. This fundamentally changes the role of TA to move from one of filling roles as quickly and efficiently as possible, to strategically underwriting future business value.
It's a shift more TA teams are working toward—and it's exactly what Visier is built to support, giving teams the workforce intelligence to connect hiring decisions to long-term business outcomes.
Hiring lesson #2: Use downstream data to inform upstream hiring decisions
This lesson seems intuitive, yet all too often the downstream data TA needs to make great hiring decisions doesn’t make it to the team, or isn’t used effectively.
As Teng explained, "The biggest missed opportunity is that retention data often stays as a KPI report that other functions drive, instead of how we can use it as a design input to refine our hiring strategy."
Yes, a postmortem survey is going to tell you what happened, but does it inform who you hire next?
Retention patterns, when analyzed carefully, reveal signals that should be feeding directly into how TA sources, screens, and selects candidates. A few examples Teng raised:
Which profiles disproportionately exit after one to two years
Which competencies and skill sets correlate with strong performance progression
Which qualifications or pedigrees are over- and under-selected for
Of course, these are just a few signals, but no matter what makes it into the course correction, it can’t stay at the strategy level. As Teng said, "It needs to be applied at the req level. If we see certain attrition in a specific role type, that should trigger immediate changes in how we position that job, how we make intake discussions, how we design interviews."
In a business environment where AI is reshaping skills requirements month to month, Teng sees this feedback loop from downstream into upstream as non-negotiable: "It's very important for us to continuously be looking at all this data and analytics and feed it back into our design, to continue to fine-tune our hiring strategy."
Hiring lesson #3: Define the quality of hire on broader business anchors
The final lesson Teng shared during our fireside chat: defending quality of hire (QoH) based on broader business metrics that go outside the usual HR metrics, and measure it more effectively.
As Teng acknowledged, QoH, “is easy enough to understand, but really hard to measure quantitatively.” At Micron, the solution was to move beyond a single perfect metric, and instead, to anchor QoH to outcomes the business already cares about.
Teng outlined three in our conversation:
Performance outcomes: Micron tracks performance distribution and time-to-productivity, measured through certifications and hiring manager surveys. The goal is to look beyond basic performance and to understand how quickly someone is reaching full contribution.
Retention: First-year retention is a key signal, but Jackson is careful about how it's interpreted. Instead, he wants to understand what’s driving it: "We have to peel the onion and sit down with business partners and relevant business leaders to look at which part was influenced by the quality of hire. For example, is it that we didn't provide a realistic job preview, or is it more about the onboarding experience?"
Internal mobility and leadership succession: How are employees moving internally? What are their promotion rates? Are they showing up in succession pipelines? These signals tell you whether a hire is creating long-term organizational value.
Micron has also ensured that there is an accountability structure that supports these new, broader business signals incorporated into QoH.
When TA is measured only on speed and volume, the incentive is just to close reqs. But when TA is co-accountable for performance, retention, and succession, the incentive is to get the hire right.
"Quality of hire becomes visible, actionable, and translatable to business needs—which is where we are really able to have a very strategic conversation with business leaders."
A great hiring strategy starts by breaking down silos
The three lessons Teng shared turn the art of hiring into data-driven science. What Micron has built is a closed loop: hire with the end in mind, measure against business anchors, and apply everything towards not just the next great hire, but the next great business leader.
In my experience, what makes truly great hiring possible is breaking down data silos and creating a foundation of cross-functional accountability, which Micron has done. As Teng said, "It's really important to have this kind of closed loop between all the different roles and functions within HR to really enable Talent Acquisition to show up as a strategic talent partner."
Even if there is organizational will to evolve the hiring process to drive better business outcomes a year—or five—later, it may not be possible if the data still lives in disconnected systems.
Cost-per-hire remains the only available metric because post-hire outcome data isn't connected to sourcing decisions, or retention data stays as a postmortem report instead of a design input because there's no way to connect first-year exits back to the source, recruiter, or hiring process.
These are exactly the gaps Visier closes, giving TA teams a unified view of the full employee lifecycle. By connecting sourcing decisions to downstream outcomes like retention, performance, and succession, Visier helps shape hiring strategy by what actually works for long-term retention, not just what's fastest to fill reqs.
Ready to evolve your hiring strategy?
See how companies like Electronic Arts and Providence are tapping into workforce intelligence with Visier to hire smarter and drive measurable business outcomes in Turning Insight Into Impact: 10+ People Analytics Stories That Drive Business Results.
