How Misaligned Specifications Create Preventable OOTs (and Unnecessary Cost)

Sometimes OOT events occur not because the instrument cannot meet its published tolerances, but because the specifications in place are tighter than what the actual process requires. When calibration limits do not reflect real-world use or necessary accuracy, teams end up investigating OOTs that were unlikely to pose meaningful risk to product quality or performance. The result is unnecessary cost, excess documentation burden, and valuable time diverted from higher-value quality work. 

 

The Hidden Cause: Your Equipment May Be “Failing” on Paper, Not in Practice 

In regulated operations, teams often inherit manufacturer specifications or default tolerances without ever reviewing how the device is actually used. That mismatch can be a significant silent driver of repetitive OOTs. 

A device may technically fail the default or manufacturer’s calibration tolerance — even though the drift never affected the process window the company relies on. In those cases, the OOT isn’t a measurement risk. It’s a specification misalignment. 

 

How Repeated OOTs Turn Into Compounding Cost 

When a device goes OOT multiple times, most companies respond by tightening the calibration interval. At first glance, this seems like a conservative fix — shorter interval, less risk. But if repeated failures never create process risk, and if the cause is never addressed, that decision actually compounds cost without adding value: 

 

Reaction	Outcome
Device keeps failing tolerance	OOTs stack
Interval is shortened	More calibrations
No process change	Cycle repeats
Cost rises	Without reducing real risk

This is exactly the trap Tray described — dozens of devices being recalibrated four times a year when they only needed annual service, all because the specification was misaligned.  

 

A Real Example: 60% OOT Rate Reduced to 5% by Fixing the Spec 

In the transcript, Tray shared an internal case where a particular power sensor was being reported OOT 50–60% of the time. When the team reviewed actual usage, they discovered the failure was always in a measurement range that was never used in production. 

Once the specification was rewritten to reflect its true intended use, three major efficiency wins followed: 

• OOT rate dropped from ~60% to ~5% 
• Calibration interval returned from 3 months → 12 months 
• Investigation workload nearly disappeared 

The process was never at risk.  However, in blindly adjusting intervals and not assessing trends and risk, the cost absolutely did. 

 

Why This Happens So Often in Regulated Industries 

This is common in life sciences, medical devices, aerospace, and defense environments because: 

• Teams inherit OEM specs without reevaluation 
• Change control processes discourage adjusting requirements 
• “Safe” defaults are assumed to reduce risk (when they actually increase it) 
• Calibration is viewed mechanically, not contextually 

Often OOT problems aren’t calibration problems — they’re requirements problems. 

NOTE: By blindly using defaults, techs are avoiding the responsibility of assessing risk themselves. In doing so, this may decrease measurement risk, but they’re just as much at risk for higher cost, and in some cases might blindly be increasing risk if they chose the wrong measurement device. 

 

A Preventive Strategy: Match Calibration to Intended Use 

A simple method organizations can apply to reduce unnecessary OOTs: 

• Identify devices with frequent OOT history 
• Compare drift location vs actual usage range 
• If failure is outside applied tolerance → flag for review 
• Work with engineering/quality to adjust specification if justified. Here, it’s important to consider another measurement device if specifications cannot be adjusted (i.e. they were actually needed) 
• Consider (or evaluate) restoring realistic calibration interval once the device exhibits reliability within your requirements 

This approach maintains compliance while eliminating wasted effort. 

 

Learn How to Prevent “False OOTs” Before They Start 

This blog is part of a broader practical OOT series. If you want to see real examples of how this is implemented inside quality systems: 

• Watch SIMCO’s OOT webinar playlist, where Tray walks through this exact case study and how the modernization of requirements cut OOT volume dramatically. 

• If your team is experiencing repeated OOTs that never impact use, you can request a quote or consultation to evaluate whether your tolerances and intervals are aligned with real-world application.