Real-time visibility into work order execution helped the plant recover 19,000 productive labor hours and $735k in annualized productivity.
Profile: Tier-1 aerospace manufacturer, 30+ factories
Operations: High-mix industrial production with definedlabor standards and complex shopfloor variability
Scale: 150 operators at the site; ~273,000 annual laborhours
Labor Base: ~$10.5M in annual direct labor cost
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The plant operated with clearly defined labor standardstargeting 70% theoretical efficiency. On paper, the model looked sound.
In reality, operational performance was being evaluated largely throughaggregated reporting and end-of-period efficiency calculations. Supervisorscould see the outcomes of production — but not the mechanisms behind them.
Time was categorized broadly. Interruptions were discussed informally. Smallstoppages were absorbed into averages. When efficiency declined, leadershiptypically debated volume fluctuations, staffing levels, or overtime decisions.
What they lacked was operational visibility inside the work order itself — howtime was actually spent while work was being executed.
When Connect 981 introduced real-time execution tracking at the work order level, thefirst insight was immediate:
>> Expected efficiency: 70%
>> Measured real efficiency: 55%
The 15‑percentage‑point gap revealed a structural visibility problem.
Across 150 operators and nearly 273,000 annual labor hours, this gaprepresented €1.58M in theoretical recoverable productivity — time already beingpaid for but not fully translated into productive throughput.
The opportunity was not to push the workforce harder. It was to understand howwork orders were actually executed on the shopfloor and eliminate hidden lossesinside them.
>> Performance Without Operational Context
Efficiency metrics were calculated against standards, but the underlying cause sof lost time were invisible. Supervisors could see whether a job finished early or late, but not how much time was lost to interruptions, waiting, or process friction during execution.
>> Invisible Non‑Productive Time
Minutes lost to micro‑stoppages, waiting for materials, clarification, or rework accumulated across every shift. Individually these interruptions were small. Collectively they represented thousands of lost hours per year.
>> Standards Drifting from Reality
Labor standards remained static while shopfloor conditions evolved. Over time the gap between theoretical routing assumptions and real execution conditions widened.
>> Managerial Friction
Supervisors were responsible for performance but lacked granular visibility into the drivers of lost time. Performance conversations often focused on outputs rather than root causes.
The plant did not lack operational discipline. It lacked clarity.
Rather than launching a large-scale systems overhaul, thesite focused on improving execution visibility at the work order level.
>> Structured Time Classification
Shopfloor time was categorized during execution into productive work orderexecution, micro‑stoppages, waiting time, interruptions, and administrativedeclarations. For the first time supervisors could see how work ordersprogressed throughout the shift rather than only evaluating them aftercompletion.
>> Supervisory Routines Aligned with Data
Daily management routines shifted toward reviewing interruption patterns, delaycategories, and recurring stoppages. Supervisors could intervene earlier andresolve issues during execution rather than reacting after the shift.
>> No ERP Overhaul
The system was deployed as a lightweight execution layer on top of existingsystems. There was no ERP replacement and no heavy IT program, allowing theplant to focus on operational behavior change.
>> Progressive Operational Maturity
The transformation followed a progression: make execution visible,stabilize data capture, align supervisory routines, and refine standards andworkflows.
Within four months the plant had begun converting visibilityinto measurable operational gains.
>> 7% Efficiency Recovered — $735k Annualized Impact
Measured efficiency improved from 55% to 62%, recovering approximately 19,000 productive labor hours annually. Across the plant’s labor base this represents roughly $735k in recovered productivity.
Operationally, this resulted in reduced overtime pressure, improved throughput capacity without new hires, and better alignment between schedules and realexecution.
>> Targeting the Full 15% Structural Opportunity — $1.58M Potential
With the remaining gap now visible, leaders are addressing the remainingopportunity through interruption reduction, process refinement, andrecalibration of labor standards. The full structural opportunity remainsapproximately €1.58M in recoverable productivity.
Extending Visibility into Traceability The next phase includes component traceability and expiration‑date tracking toreduce inventory discrepancies and overconsumption. Plants of comparable sizetypically face $80k–$120k in annual discrepancy exposure; a conservative 25%reduction represents roughly €25k in additional annual impact.
>> Standard ReconciliationProduction managers continue aligning theoretical labor standards with realexecution patterns to sustain gains and improve planning accuracy.
>> Scalable Operational DisciplineWith execution now measurable at the work order level, the framework can extendacross additional production workflows and performance levers.
Many productivity losses are not structural inefficiencies —they are visibility gaps inside work order execution.
By making shopfloor time measurable in real time, the plant recovered $735k inannualized productivity within four months and is progressing toward €1.58M instructural potential.
No ERP replacement. No workforce reduction. No disruptive overhaul.
Just operational clarity — and disciplined execution built on visible data.
Whether you're managing 1 site or 100, C-981 adapts to your environment and scales with your needs—without the complexity of traditional systems.