The Great Lock-In: Why 90% Retention Might Be a Warning Sign

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Hi Friends,

Retention numbers across the board are looking better than they have in five years.

If you look at your company’s HR dashboard today, voluntary turnover has likely drifted down toward pre-pandemic levels. The emergency exec meetings about mass attrition that defined 2021 and 2022 are in the past. Executive teams are reviewing 90%+ retention metrics, taking a win, and declaring that employee engagement initiatives have finally paid off.

Before you celebrate, there is a more uncomfortable analytical question we can ask:

Did we become better or is leaving too risky?

And when we put the data into context of economics, we learn something interesting.

We haven't really solved retention issue.

Instead, we found 'The Great Lock In'

What does the data tell us?

To understand where we are in 2026, we have to look at the full trajectory of the last five years.

During the peak of the Great Resignation in late 2021, the U.S. monthly quit rate hit an all-time high of 3.0% (roughly 4.5 million quits per month).

Annualized voluntary turnover in many tech and professional services organizations routinely cleared 20% to 25%.

I remember those days in tech. We were doing anything to make sure our engineers do not jump ship for competitors.

Today, data from the U.S. Bureau of Labor Statistics (JOLTS) shows the monthly quit rate has plummeted to 1.9% (around 3.1 million quits per month). That is not just lower than the 2021 peak; it sits below pre-pandemic baseline norms.

On the surface, an executive summary looks clean:

• Voluntary quits are down ~36% from their historical peak
• Layoffs remain relatively subdued at 1.7 million per month
• Overall annual retention rates have climbed back into the 88%–92% "green zone"

Did we return to balance?

People Analytics requires us to dig deeper and look at the denominator.

Hires have dropped to 5.1 million per month (a hiring rate of 3.2%), down significantly from the post-pandemic hiring frenzy. Job openings have drifted down from a peak of 12 million to 7.3 million. The ratio of job openings per unemployed worker has compressed from a hyper-competitive 2.0 down to 1.05.

Even the Non-Farm Payroll on Friday came in way below expectation: 27k on the expectation of 90k jobs!

Employees aren't staying because they are deeply engaged.

They are staying because external market has dried up!

Retention Is Not Happening Evenly: The K-Shaped Divide

The biggest mistake a People Analytics team can make right now is reporting a single, company-wide retention metric. A single 90% retention figure masks a severe K-shaped split across employee populations:

The Upper Arm: The High-Judgment Bottleneck

For specialized, deep-domain roles—senior software architects, specialized data engineers, and high-margin operational leads—retention remains surprisingly fragile.

Macro analysis of over 75 million job postings by Revelio Labs shows that while required skill checklists on postings dropped 25%, required baseline experience for analytical roles jumped from 2 years to 5+ years.

The market loves these hires and a lot of my more senior level colleagues are enjoying great job mobility and get snatched up as soon as they hit the market.

The Lower Arm: "Trapped Retention"

For generalist roles, mid-tier managers, and routine operational staff, voluntary quit rates have frozen.

Broad software development job listings dropped from 25% to 16% of overall tech postings.

These employees are experiencing "trapped retention"—they remain in their seats not out of organizational loyalty, but because external job-switching wage premiums have stopped, and replacement hiring has slowed to a trickle.

If your retention rate improved from 82% to 90%, but that 10% attrition was concentrated entirely in your senior domain experts while your legacy generalists stayed, your organizational capability actually degraded.

Follow the Money: Debt Markets and Household Risk Aversion

Retention does not happen in an HR vacuum.

It is deeply connected to financial markets and capital allocation decisions made in the C-suite and at your own kitchen table.

1. The Corporate Side: High Capital Costs & Refinancing Pressure

For nearly a decade, cheap corporate borrowing funded broad headcount expansion. Today, corporate debt refinancing pressure remains high. Deloitte’s restructuring outlook highlights that the proportion of corporate borrowers with interest coverage below 1.0x has reached ~13%, while operating cost inflation stays elevated.

When CFOs face higher interest rates on corporate debt, labor is no longer treated as a scaling engine—it is scrutinized for immediate margin contribution. Companies are enforcing strict "skill density" standards, freezing broad generalist hiring, and redirecting capital toward tech infrastructure. Fewer new requisitions mean fewer external exit options for your workforce.

2. The Employee Side: Household Financial Pressure

On the worker side, macro financial conditions have significantly muted risk tolerance:

• U.S. credit card debt and consumer borrowing costs sit near historic highs
• Household mortgage obligations and elevated cost-of-living constraints make job-hopping far riskier than it was in 2021
• The wage premium for switching jobs—which peaked at record levels during the Great Resignation—has narrowed dramatically, approaching parity with staying put

When the financial reward for changing jobs vanishes and the economic downside of being "last in, first out" at a new company increases, employees stay put.

The People Analytics Problem

Confounding internal initiatives with external macroeconomic subsidies is not the way to go at the executive table.

When your voluntary turnover drops from 18% to 10%, your team might present a slide attributing the success to your new onboarding program, career pathing framework, or hybrid work policy.

To test whether your internal programs actually worked, you have to untangle internal sentiment from external market forces. Let me propose:

If external labor liquidity drops by 40%, your retention rate will improve automatically—even if your internal employee experience got noticeably worse.

Relying on "unearned retention" creates 3 problems:

1. Unmanaged Underperformance: Low voluntary attrition allows low-producing legacy roles to linger, blocking career progression for high-potential junior talent
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2. False Security: You stop fixing real managerial, workload, and compensation issues because the surface metrics look healthy
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3. The Sudden Liquidity Shock: The moment interest rates ease, hiring reaccelerates, or external capital opens up, your best people leave all at once because the underlying dissatisfaction was never resolved

What Should People Analytics Teams Actually Measure?

To stop falling for the retention illusion, People Analytics teams should adjust their measurement framework:

1. Segment Retention by Experience Depth & Domain Skill: Never report a single retention number again. Track retention separately for high-judgment domain experts (5+ years context) versus generalist execution roles
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2. Benchmark Internal Turnover Against External Quits: Compare your voluntary quit rate trend directly against JOLTS industry-specific quit rates. If your turnover dropped 20% but your industry quit rate dropped 35%, your relative retention actually underperformed the market
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3. Track the "Regrettable vs. Non-Regrettable" Ratio: Focus on the proportion of exits that represent high performers or critical talent. An overall retention rate of 90% is a failure if 100% of your attrition comes from top-quartile performers
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4. Monitor Internal vs. External Wage Growth: Track the spread between your internal merit increases and external market hiring offers. When external premiums widen, your retention rates are about to be tested
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5. Measure Internal Mobility Velocity: Look at promotion and lateral movement rates. If external mobility is frozen, robust internal mobility is the only way to prevent high-potential employees from feeling trapped

When leaving becomes easy again, will your best people stay because they want to, or will you realize they were just waiting for the door to unlock?

K

Whenever you’re ready, there are 2 ways I can help you:

#1

If you’re still looking to get started in People Analytics, I recommend starting with my affordable course:

​Practical People Analytics: Build data-driven HR programs to 10x your professional effectiveness, business impact, and career. This comprehensive course will teach you everything from building an HR dashboard for business results to driving growth through more advanced analytics (i.e., regression). Join your peers today! ​
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#2

If you are looking for support in your human capital programs, such as engagement, retention, and compensation & benefits, and want to take a more data-driven approach, contact me at Tskhay & Associates for consulting services. Or simply reply to this email!