Case Study|Food & Beverage

A national food manufacturer lifted labor productivity 11% and drove soup-line throughput up 33% to a record 1,300 cases per shift, proving the ceiling was discipline, not capacity.

National Food Manufacturer
Results at a Glance
11%
Labor Productivity Gain
33%
Throughput Increase
10%
Direct Labor Cost Reduction
Executive Brief

As demand grew, this national food manufacturer ran into a wall: its operational practices, systems, and execution rhythms had not kept pace with rising complexity, and the constraints were systemic, not equipment-driven. Supervisors lacked lean exposure and formal training, shifts started without clear priorities, downtime went untracked, handoffs were weak, KPIs were undefined, planning ran on spreadsheets that surfaced shortages too late, and safety incidents were elevated. Over a focused 26-week engagement, POWERS installed consistent downtime measurement, deployed its Digital Production System (DPS) to diagnose efficiency, and built a tiered Management Operating System with shift-start assessments, Action Lists, standardized huddles, supervisor standard work, and real-time visibility, while strengthening material planning, capacity modeling, and capital decision discipline. The result was an 11% gain in labor productivity, a 33% throughput increase on the soup packing line to a record 1,300 cases per shift, a 10% reduction in direct labor costs, roughly $750,000 a year in identified savings, and recordable safety incidents cut from an average of four per month to about half of one.

Frontline Leadership · MOS · Supply Chain
The Situation

Demand was climbing, but the way the plant ran had not. The barriers were not in the machines; they were in the routines, the data, and the discipline that never got installed.

This is a well-established, nationally recognized food manufacturer operating multiple production sites and producing several hundred SKUs. For years its volume could be absorbed by experience and effort. But as demand grew, the manufacturer hit real scalability constraints, because its operational practices, systems, and execution rhythms had simply not kept pace with the complexity the business now carried.

The barriers were systemic rather than equipment-driven, and they reinforced one another. Supervisors and leads had limited lean exposure and no formal leadership training, so shifts often started without clear priorities or direction and daily meetings lacked structure and follow-through. Slow shift startups caused recurring lost production, yet downtime was not consistently tracked or analyzed, so the losses stayed invisible. Communication between shifts was weak, with little accountability for performance carryover, and action plans were informal and inconsistently followed. Department-level KPIs were undefined or unused, and there was no consistent Management Operating System or real-time operational visibility to anchor decisions.

The problems extended into planning and risk. Manual, spreadsheet-driven planning caused frequent material shortages that were discovered too late, and paper-based maintenance work orders were inconsistently closed, limiting any insight into chronic issues. Safety recordable incident rates were elevated, with little proactive identification of latent risks. What leadership needed was not a one-time fix but a system: stronger execution discipline, continuous-improvement capability, and operational infrastructure that could make results sustainable as the business continued to scale.

The Diagnosis

Six structural gaps producing the same outcome from six directions.

Frontline leaders without the tools to lead

Supervisors and leads had limited lean exposure and no formal leadership training, leaving them unequipped to drive consistent execution on the floor.

Shifts that began without direction

Shifts often started without clear priorities and daily meetings lacked structure and follow-through, while slow startups caused recurring lost production that downtime tracking never captured.

Handoffs that dropped accountability

Communication between shifts was weak with little accountability for performance carryover, and informal action plans were followed inconsistently, so problems carried over unresolved.

No system, no visibility

Department KPIs were undefined or unused, and with no consistent Management Operating System or real-time visibility, leadership could not see performance as it happened or act on it.

Planning and maintenance running blind

Manual, spreadsheet-driven planning surfaced material shortages too late, and paper maintenance work orders were inconsistently closed, hiding chronic issues from anyone trying to fix them.

Safety risk left latent

Recordable incident rates were elevated, with little proactive identification of the latent risks that drive them, so exposure persisted shift after shift.

What POWERS Did

Gave a scaling manufacturer real-time visibility and the discipline to act on it.

POWERS began by making the invisible measurable. It established consistent downtime measurement, recording, and analysis, then deployed its Digital Production System (DPS) to diagnose efficiency and surface productivity opportunities. What DPS exposed reshaped the work. Cycle-time studies revealed imbalances on the highest-running SKU and let the team reduce packing-line headcount 35%, from 17 to 11 people per shift, while setting a more demanding rate standard. The data also caught recurring micro-stops and replenishment delays of up to two minutes occurring 26 times per shift, together costing nearly an hour of production every shift. On the soup packing line, those insights drove a record within a month, and frozen packing operations that had been running near 50% capacity utilization were pushed as high as 97% once upstream and flow adjustments took hold.

In parallel, POWERS built the operating system the plant had been missing. A tiered meeting structure became the heartbeat of a true Management Operating System, with standardized shift huddles, handoffs, daily direction setting, and weekly reviews. Shift-start assessments gave every shift a clear beginning, structured Action Lists assigned ownership, due dates, and follow-through, and supervisor standard work was defined and coached on the floor. Risk reporting and behavior observation were tied to Gemba walks so safety risks were identified before they became incidents, turning frontline leaders into the people who ran the system rather than worked around it.

POWERS also rebuilt the planning and decision discipline behind the floor. ERP posting interfaces were improved and digital maintenance work order management replaced the paper system, restoring insight into chronic issues. Capacity modeling was introduced to validate schedules and growth plans, and material planning was strengthened using the existing ERP and MRP tools, so shortages stopped surfacing too late. Structured change management and financial business-case methods were applied to evaluate automation and capital investments, holding new spending to a sub-three-year ROI. Together the measurement, the operating system, and the planning discipline compounded into throughput, productivity, and safety gains the plant could repeat.

The Full Result

Six measurable gains, all earned through execution discipline rather than new capacity.

11%
Labor Productivity Gain

Labor productivity rose 11%, with pounds per labor hour reaching 50 against a previous high of 45, as line balancing and DPS-driven downtime analysis tightened execution.

33%
Throughput Increase

The soup packing line lifted cases per shift 33% within a month to a record 1,300 cases per shift, eliminating losses equal to three pallets a shift.

10%
Direct Labor Cost Reduction

Direct labor costs fell 10% on better line balance, higher utilization, and less unplanned downtime.

97%
Capacity Utilization

Frozen packing capacity utilization climbed from roughly 50% to as high as 97% once DPS visibility prompted upstream and flow adjustments.

$750K
Identified Annual Savings

About $750,000 a year in identified savings potential, enabled by improved capacity utilization and DPS-driven downtime analysis.

4 to 0.5
Monthly Safety Recordables

Recordable incidents fell from an average of four per month to roughly half of one as risk reporting and behavior observation took hold.

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