Past Success & Projects

Overview

During a quarterly business review for a large MSP program, our team identified a persistent issue: we were consistently missing a key SLA requiring three qualified resumes within 24 hours of a requisition opening. The client questioned whether the SLA was still valuable and suggested eliminating it altogether.

Instead of accepting that assumption, I conducted a structured people analytics investigation that uncovered the true drivers of performance and led to a process change that permanently resolved the issue — while also improving hire quality.

Business Problem

 

• SLA target: 90% of requisitions must receive three resumes within 24 hours
• Actual performance: consistently below target
• Client perception: SLA may be outdated or irrelevant
• Risk: Removing the SLA could reduce speed, quality, and competitive advantage in the talent market

 

My Approach

I broke the analysis into a structured, five‑step process designed to validate the SLA’s value and diagnose the root cause of the performance gap.

Step 1: Clarify the Core Question

Does this SLA actually matter?

Before fixing anything, I needed to determine whether the SLA had meaningful business impact.

Actions

 

• Pulled three years of performance data for all hires
• Matched performance outcomes to resume submission timestamps
• Analyzed correlations between submission speed and long‑term employee performance

 

Insight

Top performers were consistently candidates submitted within the first 24 hours of the requisition opening.

Conclusion: The SLA was not only relevant — it was a predictor of higher quality. Eliminating it would have weakened the program.

Step 2: Diagnose Why We Were Missing the SLA

With the SLA validated, the next step was understanding the operational breakdown.

Actions

 

• Segmented requisitions into: Met SLA, Missed SLA
• Compared process variables across both groups
• Focused on vendor distribution patterns

 

Insight

Every requisition that met the SLA had been released to an average of 5.6 vendors. Our existing process released requisitions to:

 

• 3 vendors in Week 1
• 3 additional vendors in Week 2

 

This staggered release slowed down the pipeline and reduced early candidate flow.

Step 3: Identify the Operational Lever

The data pointed to a clear, high‑impact solution.

Insight

The issue wasn’t candidate availability — it was vendor volume at the start.

Solution

Release all requisitions to at least six vendors immediately upon receipt.

Step 4: Implement and Monitor

We updated the policy and rolled it out across the MSP program.

Outcome

After increasing initial vendor distribution:

 

• We never missed the SLA again
• Resume flow increased significantly within the first 24 hours
• Recruiters gained stronger early pipelines

 

Step 5: Translate Insights into Long‑Term Value

This project demonstrated the power of people analytics to:

 

• Validate assumptions with data
• Connect operational metrics to talent outcomes
• Identify hidden bottlenecks
• Influence client strategy
• Improve both speed and quality of hiring

 

 

 

Why This Case Matters

This project is a strong example of how I approach people analytics:

• I challenge assumptions with data
• I break complex problems into structured, solvable steps
• I translate insights into operational strategy
• I focus on both quality and efficiency
• I deliver solutions that scale and stick

 

There’s a moment in every HR career where the work stops feeling routine and suddenly feels cinematic — like the camera zooms in, the soundtrack drops, and you realize the plot has shifted.

For me, that moment happened on a DHS time‑and‑materials contract.

Every resignation email landed the same way:

Subject: Quick chat Message: I’m putting in my notice.

On this type of contract, an empty seat isn’t just a vacancy. It’s a pause in billing. A leak in revenue. A countdown clock.

For a while, that was our cycle: react, scramble, repeat.

Until one afternoon — the third resignation of the quarter — I stared at the screen and thought:

“This isn’t chaos. This is a pattern

 

 

---

 

What the Data Revealed

When I pulled the numbers, the story split into two clear arcs:

1. Senior roles were steady.

Not because they were magically immune to turnover, but because leadership had already invested in keeping them anchored. Retention incentives. Recognition. Project influence. The kinds of things that make people stay.

2. Entry‑level roles were the churn engine.

Three FTEs lost every quarter. Like clockwork.

It wasn’t random. It wasn’t mysterious. It was predictable.

And predictable problems can be solved.

---

Building a System That Anticipated Attrition

Once I understood the pattern, I shifted the entire strategy.

I studied the hiring manager’s decision rhythm — how many candidates he needed to feel confident, how many conversations it took before he said yes. That gave me the blueprint.

Then I built something new:

A living hot list.

A curated bench of candidates we kept warm, informed, and respected. No ghosting. No “we’ll call you if something opens.” Just transparency and ongoing engagement.

We didn’t interview for imaginary roles. We interviewed for forecasted attrition — the openings the data told us were coming.

And then I proposed a simple but powerful change:

Every other Wednesday would be interviewing day for upcoming turnover.

The hiring manager agreed.

And that’s when everything shifted.

---

The Moment the System Took Over

A few cycles in, the hiring manager stopped asking for résumés. He trusted the process enough to just show up.

Candidates were ready. Transitions were seamless. Billing never dipped.

We weren’t reacting anymore. We were anticipating.

It felt like the moment in a prestige drama when the team stops responding to alarms and starts running the entire operation with precision.

---

The Lesson I Still Use Today

That DHS contract taught me something foundational:

Attrition isn’t the villain. Being unprepared is.

Senior roles stayed because incentives anchored them. Entry‑level roles churned because that’s the nature of early‑career work. The difference was predictability — and predictability is power.

When you treat turnover like a forecast instead of a fire drill, you protect your revenue, your teams, and your sanity.

Sometimes the most transformative moment in your career is the quiet one — the moment you decide the story is going to end differently.