Case Study|Food & Beverage

A meat packing industry leader added $5.8M to the bottom line and reversed a 75-week ham yield decline, lifting yield from a 99% to a 104% eight-week running average, roughly 3 million more pounds a year, by running on a unified schedule instead of shifting hot lists.

Meat Packing Industry Leader
Results at a Glance
$5.8M
Annualized Savings
99% to 104%
Ham Yield
22%
Product Giveaway Reduction
Executive Brief

Demand was skyrocketing but unpredictable, straining operational systems, processes, and behaviors that had worked for years, just as a generational management transition prepared to take 20-plus years of frontline experience out the door. Ham yield had been declining for 75 straight weeks, lost time was nearly equal to production time, and a 'whatever it takes to get it out the door' firefighting culture ran from the top floor to the shop floor with the holiday season bearing down. Over a 28-week engagement, POWERS installed a unified production schedule and capacity model, rationalized 90 low-volume, low-margin SKUs, and built frontline leadership skills, short-interval scheduling, and lost-time root-cause discipline. The work hit break-even at week 16 and, by week 27, delivered $5.8 million in annualized savings, reversed the yield slide from a 99% to a 104% eight-week running average, and cut product giveaway 22%.

Equipment Reliability · Frontline Leadership · MOS
The Situation

Demand was outrunning the plant, but the deeper problem was a business still trying to scale on paradigms, hot lists, and firefighting that no longer fit the volume it was being asked to ship.

Demand for the client’s products was skyrocketing, but it was also unpredictable, and that combination put steady pressure on operational systems, processes, and behaviors that had been built and refined over many years. Management was trying to scale on paradigms that had worked for a long time, relying on the same systems, processes, and behaviors as they always had, and those approaches no longer held up at the volume the market was now asking for. The result was an operation that simply could not reliably satisfy its customers, with the holiday season approaching and an urgent need for more throughput.

Underneath the demand pressure sat a deeper structural problem. The company was absorbing a generational management transition: managers and frontline leaders with 20-plus years of tenure were preparing to retire and take their hard-won experience with them, and there were no One Point lessons learned captured at the execution level to hold any of that knowledge in place. Ham yield had been in steady decline for 75 weeks. Lost time was nearly equal to production time. And a ‘whatever it takes to get it out the door’ firefighting culture ran from the top floor to the shop floor, where heroics substituted for a system.

What leadership needed was not another push of effort or one more heroic holiday season. It needed a way to plan and forecast resources reliably, an established production schedule to replace the constant scramble, operational visibility into how the plant was actually performing, and frontline leaders equipped to hold the line after the most experienced people walked out the door. That meant building an operating system, not patching a single process, so performance could hold under peak demand rather than only on the plant’s best days.

The Diagnosis

Six structural gaps producing the same outcome from six directions.

An ERP no one could plan against

The client could not reliably plan or forecast resource requirements because its new ERP system was inaccurate and not trusted. Decisions ran on workarounds instead of dependable data, so resourcing was a guess.

Hot lists in place of a schedule

The operation ran off constantly shifting hot lists rather than an established production schedule. Priorities changed by the hour, and the plant chased whatever was loudest instead of what was planned.

Firefighting and excess changeovers

The plant was in a constant state of production firefighting, running changeovers more frequently than optimal. Reacting to the moment cost capacity and added avoidable downtime on every line.

No unified production schedule

The operation fundamentally lacked a single, unified production schedule to align planning and the floor. Without one source of truth, scheduling and execution pulled in different directions.

No KPIs to show plant performance

There were no operational KPIs or reports to indicate how the plant was actually performing, even as yield slid for 75 weeks and lost time ran nearly equal to production time. Problems compounded out of sight before anyone could act on them.

Performance never reviewed at the line

Past performance was never evaluated at the process or line level, just as a generational transition threatened to take 20-plus years of experience out the door. Nothing was learned, captured, or improved where the work was actually done.

What POWERS Did

Replaced hot lists and firefighting with a unified schedule, a capacity model, and daily yield discipline.

POWERS started where the work happened, conducting line balance and SMED observations alongside production supervisors to see how the lines actually ran and where capacity was being lost to excess changeovers and firefighting. That floor-level view fed a SKU rationalization that purged 90 low-volume, low-margin items, simplifying the mix the operation had to schedule and produce. In parallel, POWERS worked with the planning department to build a capacity model for the operation, giving the business a credible way to plan and forecast resources that the shifting hot lists and the distrusted ERP could not provide.

With a clearer picture of true capacity, the focus shifted to execution and the leaders who run it. POWERS delivered training, development, and on-the-floor support for frontline leadership, the same leaders the generational transition was about to test, and improved short-interval scheduling, follow-up, and barrier identification at the supervisory level so issues were surfaced and closed rather than worked around. Lost-time capture was developed down to root cause, with concrete actions attached, replacing a culture where performance was never examined at the process or line level with one that learned from it.

The discipline held even when conditions turned against it. When the Omicron surge drove 25% absenteeism, POWERS ran line balances and staffed lines to minimum staffing so the plant kept producing through the disruption rather than reverting to chaos. Across the 28-week engagement, these moves compounded: a unified schedule and capacity model replaced the hot lists, frontline routines replaced heroics, and yield discipline replaced giveaway. The work reached break-even at week 16, and by week 27 the cumulative effect showed up in both the yield curve and the bottom line.

The Full Result

Six measurable gains, earned through a unified schedule and frontline discipline rather than new capital or added headcount.

$5.8M
Annualized Savings

Measured at week 27 of a 28-week engagement that had already reached break-even by week 16, the savings reflect compounding yield, scheduling, and uptime gains rather than a one-time cut.

99% to 104%
Ham Yield

Ham yield rose from a 99% to a 104% eight-week running average, about 3 million additional pounds a year, reversing a slide that had run for 75 consecutive weeks.

22%
Product Giveaway Reduction

Product giveaway, the overweight given away against spec, fell as tighter standards and short-interval control closed the gap between target and actual.

83% to 92%
On-Time Performance

On-time performance climbed as a unified schedule and a focus on customer due dates replaced the constantly shifting hot lists that had set priorities.

18% to 9%
Operational Downtime

Operational downtime was halved through start-up focus, maintenance rebuilds, and lost-time root-cause analysis that attacked recurring losses instead of reacting to them.

45%
Scheduling Accuracy Gain

The variance between pounds scheduled and pounds produced collapsed under a new capacity model and a SKU rationalization that purged 90 low-volume, low-margin items.

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