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AFSI - Case Study


Implementation of operational KPIs

In a factory manufacturing 700 tonnes of fresh product per week, a new labour and yield tracking models implemented and improved the operational contribution by 4p/kg which equated to £1.5M year on year.


First step was to review all standards against the original master data, the machinery capacity, and the actual performance in the factory.

The standards were adjusted to reflect what could be achieved, based on standard manning, machine capacity and industry standard overall equipment effectiveness (OEE), rather than historic performance. Raw material selection was set up to improve the slicing yields and the planning function was given raw material and finished stock targets, based on life and sales data, to attain.

An operational meeting with a review of KPIs was implemented and held once per shift, a weekly management meeting with the individual KPI owning mangers was implemented, and a monthly sales and operations meeting, with the relevant commercial mangers and planning stakeholders, was implemented.

KPIs were agreed with the individual area managers and the site continuous improvement (CI)  team reported variance to standard weekly.

The shop floor followed the KPIs with short interval control (SIC) meetings, labour plans, stock control and focus on the agreed KPIs.


Planning & service level improvements

A large fresh retail producing factory, was experiencing difficulties with attaining customer service levels.

The target service level was 99.5%. However, several weeks it was far below the target at 95-96% attainment, with some lines only achieving 75% completion and in some instances even lower.

(customer service levels were measured as: delivered cases/retail order e.g.,

750 delivered 1000 ordered, = 750/1000 = 0.75 ~ 75%)

There were a number of issues causing attainment failure e.g.,

  • Running out of raw material – stocks depleted

  • Retail orders coming in significantly over forecast, exhausting manufacturing capacity

  • Running out of dry goods, running out of ingredients

  • Equipment failure 

There were several things that needed to be rectified in order to stabilise the service levels.

The equipment failure had a very big impact on ability to deliver, but as there was no scope to replace the equipment, the planning run rate expectations were changed to mirror the average baseline performance. The planning function was expecting a standard efficiency of 85% but the baseline performance was 70-75%.

 Efficiency performance per SKU was set up in the CI department and then planning would plan the SKUs based on the previous months average performance.

In addition to this, the planning cycles were changed. The planning department would plan one day out, which would often cause issues with raw material surplus or shortage, so the raw material ordering was changed to a weekly order based on a 14 days plan. All the ordering of materials, dry-goods, raw materials were set up against forecast consumption based on standard BOM (bill of material) usage, so we could forecast reordering more accurately.

The planning program was dated, so we replaced that with a new excel database and we set up a monthly S&OP (sales and operations) meeting where the commercial managers were invited to look at their forecast and order performance. Lastly, stock targets for raw material, ingredients, dry goods and finish product stock were implemented at SKU level. Each SKU would have a finished stock target, that was based on life of the product and the SKU volatility.

Within six months the service levels were stabilised. The site went from being close to losing business due to poor services level performance, to being one of the most reliable suppliers. Service levels were recorded as 100% delivery the site's largest customer for several months.

 The service level were from the customers' reports, and not sites, to remove any subjectivity


Redesign of shoulder butchery specification


In a UK meat manufacturing business, there were several different shoulder specifications, which were created to accommodate different levels of fat in the final products, for example: 20%, 10% or 2%.

The 2% specification was causing a lot of yield and quality issues since intramuscular fat level of some shoulder muscles is above the 2% specification target, which caused quality issues that then resulted in excess trimming.

Firstly, the selection of carcasses for the individual jobs were allocated at random, so the first step in improving the performance, was to rebalance the use of the grades.

(The selection of carcasses, for the individual grade makeup, was updated in a separate exercise.)


In this case the driving primal (attracting the highest premium) was the middle. Logically, the selection was set up so the leaner pigs would go for the leaner cuts following the P2 grading of the loin, but even with very lean loin probes*, the 2% was difficult to attain and it resulted in a lot of trim and fat as by-products, which devaluated the overall return of the shoulder primal.

Instead of trying to achieve 2% as an output of the whole shoulder, a combined specification was created, where lean muscles were removed from the 20% specification, which then afforded a residual 2% muscle mix. As most of the meat was used for further processing, in a minced or size reduced format, it did not compromise the final product quality to have individual muscles instead of a whole deboned primal. Finally, by working through the overall lean meat percentage (LM%) for each grade, it was identified how much 2% muscle mix could be removed from each individual grade and still attain the 20%  fat target of the 20% specification.

The outcome was reduced complexity, reduced labour requirements (as trimming of the 2% specification was not required to the same extent) and a reduction in overall residual trim and fat. As the 10% was now being butchered from the correct grades, with the correct LM%, there was no longer a requirement to trim them for fat either. The overall profit improvement of the project was approximately £0.5/pig.

*In the UK the carcass grading predominantly relies on one lumbar loin probe (P2),  which is measured in line with the final floating rib, where the thoracic and lumbar vertebra meet. Though this measure is indicative of the fat levels of the loin, and a decent tool for bacon production, the measure does not provide accurate information about the rest of the carcass, limiting the grading technique benefit for forecasting the fat content of the shoulders.

Pace line shoulder butchery
Value eng. case study
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