A Data-Driven Approach to Reducing Yield Loss and Improving Batch Accuracy

By Stacy Feeley, Product Manager at Plex by Rockwell Automation

Key takeaways:

• Food manufacturers face significant financial and environmental costs from waste, with nearly 15% of food waste occurring during manufacturing due to yield loss and batch inaccuracies.
• Inefficiencies often go undetected because of complex variables and inadequate tracking, creating ripple effects of higher costs, inconsistent quality, and production slowdowns.
• Implementing data-driven strategies — real-time tracking, automated batch scaling, and advanced analytics — can significantly reduce waste, improve consistency, and increase profitability.

The environmental impact of waste is significant, with nearly 15% of food waste occurring during the manufacturing process. However, manufacturers also face substantial financial repercussions. These financial burdens include the costs of waste disposal, lost revenue from unsellable products, and the need for additional resources to manage waste. Consequently, manufacturers are increasingly exploring innovative solutions to reduce waste, enhance efficiency, and promote sustainability in their operations.

For food manufacturers, much of this loss results from inefficiencies in yield and batch management. Inaccurate ingredient measurements, overproduction, and inconsistent batch scaling not only increase costs but also make it harder to maintain consistent quality and meet production targets. These inefficiencies often go unnoticed or are accepted as an inevitable aspect of manufacturing. However, adopting a data-driven approach can significantly reduce them.

When small inefficiencies add up to big problems

The complexity comes from the many variables at play — ingredient quality, equipment calibration, operator decisions, and production fluctuations — all of which contribute to inefficiencies. Without advanced tracking and tracing, small discrepancies can accumulate into major issues over time.

Consider a sauce manufacturer running multiple production lines. If each batch requires 500 gallons of tomato puree and ingredient variances lead to a 3% loss per batch, the result is thousands of wasted gallons translating into significant financial loss. Without real-time data, manufacturers are typically unaware of these losses due to a lack of visibility into their inputs and outputs. To make matters worse, many manufacturers, unaware of the root cause, may compensate by ordering more raw materials and accepting batch inconsistencies as normal thereby increasing the financial impact.

Overproduction presents another challenge for manufacturers. To account for potential shortfalls, some manufacturers produce more than necessary, assuming that surplus product will be used elsewhere. However, this often leads to storage inefficiencies, increased spoilage risk, and unnecessary labor costs. For example, a bakery that consistently over-measures flour by just 2% may not notice the impact in a single batch. However, that extra usage adds up over a month or more to hundreds of pounds of wasted flour and thousands of dollars in additional costs.

Even when manufacturers attempt to adjust batch sizes to meet demand, improper scaling can lead to new inefficiencies. Incorrect scaling of ingredients can result in inconsistent product texture, taste, or quality. This is especially problematic for food brands that must adhere to strict regulatory and labeling standards, as deviations in ingredient composition can trigger compliance issues or recalls.

These challenges are made worse when manufacturers rely on outdated tracking methods, such as manually recorded data or siloed systems that don’t communicate with each other. Without a centralized, real-time view of production, it becomes nearly impossible to pinpoint inefficiencies, let alone correct them in a timely manner.

The ripple effect: costs, quality, and production bottlenecks

Yield and batch inefficiencies don’t just lead to ingredient waste — they create ripple effects that disrupt the entire production process. Increased raw material costs, unpredictable batch yields, and operational bottlenecks make it difficult to plan production effectively. When manufacturers cannot accurately track ingredient usage and batch performance, they often face:

• Higher costs: Wasted ingredients, excess labor, and increased energy use drive up operational expenses and cut into profit margins.
• Inconsistent product quality: Variability in ingredient ratios or inconsistent batch scaling can lead to differences in texture, taste, and shelf stability. For instance, if a batch of yogurt ends up with an unexpected variation in acidity due to over-fermentation or contamination with unwanted bacteria, it could lead to consumer complaints or even a recall.
• Production slowdowns: Inefficient yield management can force manufacturers to operate at lower overall equipment effectiveness (OEE). Batch inconsistencies cause frequent stops and adjustments on the production line, resulting in lost production time. A plant operating at 80% efficiency instead of 90% might seem like a small difference, but over time, that gap translates into millions of dollars in lost production capacity.

A smarter approach: leveraging data for yield and batch optimization

Manufacturers cannot afford to take a reactive approach to these issues. Instead, they need to proactively manage yield and batch efficiency using real-time data and automation. Modern manufacturing systems provide instant visibility into ingredient usage, batch performance, and process inefficiencies, allowing manufacturers to make adjustments before small issues turn into costly problems.

One great example is Summer Garden Food Manufacturing. They struggled with undetected micro-downtime events, which led to inconsistencies in their batch yields. By implementing real-time data tracking, they identified hidden inefficiencies, such as frequent machine stops that operators had not been recording. As a result, they reduced downtime, improved yield accuracy, and optimized their overall production flow.

A smart manufacturing approach also enables manufacturers to refine their batch scaling processes. Instead of relying on static batch formulas that may not scale accurately with production fluctuations, manufacturers can use automated systems that adjust ingredient ratios in real time based on actual production conditions. This level of precision ensures consistency while reducing ingredient waste and production overruns.

How manufacturers can take action

To improve yield and batch efficiency, manufacturers should focus on three key strategies:

• Implement real-time tracking of inputs and outputs. Digital tracking systems provide instant visibility into ingredient consumption and batch performance. This allows manufacturers to identify inefficiencies before they escalate, ensuring that production stays on track.
• Optimize batch scaling with automated tools. Manual batch adjustments often lead to errors. By leveraging smart batch management solutions, manufacturers can automatically adjust ingredient ratios based on real-time data, reducing waste and improving consistency.
• Utilize advanced analytics to drive continuous improvement. Machine learning and predictive analytics can help manufacturers identify patterns in yield loss, pinpoint the root causes of inefficiencies, and refine production processes over time. This not only improves current operations but also helps manufacturers anticipate and prevent future issues.

The payoff: more yield, less waste, greater profitability

The shift to a data-driven approach yields (pun intended) tangible benefits, starting with cost savings. When manufacturers have a precise understanding of ingredient usage and yield performance, they can minimize unnecessary waste and maximize efficiency, directly improving profitability. 

Consistency is another major advantage. With automated batch scaling and real-time monitoring, manufacturers can ensure that every product meets the same quality standards, strengthening consumer trust and regulatory compliance. Finally, real-time insights allow manufacturers to operate with greater agility. If an ingredient shortage or sudden spike in demand occurs, a data-driven system makes it easier to adjust production schedules dynamically, minimizing disruptions while keeping costs under control.

From inefficiency to optimization

Yield and batch inefficiencies may seem like unavoidable challenges in food manufacturing, but they don’t have to be. With the right data-driven strategies, manufacturers can transform these inefficiencies into opportunities for cost savings, quality improvement, and operational optimization.

By embracing real-time tracking, automated batch scaling, and advanced analytics, food manufacturers can move beyond guesswork, turning visibility into action, waste into efficiency, and inefficiencies into competitive advantages.

Stacy Feeley is a Product Manager at Plex by Rockwell Automation, focusing on IT/OT convergence, MES implementation, RA Solutioning, and the F&B vertical. With more than 6 years of experience in product development, sales, and MES, Stacy has developed a strong expertise in the field.