The pressure is on operations to increase efficiency and throughput. According to the Boston Consulting Group (BCG), the consumer packaged goods (CPG) industry has seen a one billion unit-volume decline since 2019. The consulting firm reports the decline is concentrated in the “at-home staples” sector, with a 2-4% decline between 2022 and 2023 alone.

“Innovation is needed to tackle more since food companies are not launching fast enough and missing margin,” says Arnold Kogan, managing director and partner, Boston Consulting Group (BCG), during the The Connected Worker: Manufacturing Summit conference in October, outside of Chicago.

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With the increasing use of middleware platforms, food manufacturers face challenges in managing data abundance and producing essential and accurate digital key performance indicators (KPIs) or overall equipment efficiency (OEE) metrics. So what are the key challenges for operators? And is data latency an issue for food brands as Industry 4.0 matures?

“It (data analytics) depends on which data you need and the frequency needed to solve problems (on the line),” added Oliver Ganschar, head of digital product management and innovation at Kraft Heinz, during a fireside data analytics chat session at The Connected Worker conference. “Sometimes you need data in an hour or at the end of a shift. OEE is a measure that can be viewed each hour, day or review when you have opportunities.”

The data analytics discussion drove home the urgency in improving KPIs at Kraft Heinz. “When you think about the opportunities in yield and improvement in certain applications, such as filling or valve management, it's millions of dollars,” Ganschar adds.

The discussion covered many alignment challenges, and the main one, not surprisingly, is agreeing on the problem to be solved. “KPIs become a choice about what meaningful data can be consistently collected across shifts and with constant turnover,” says Katie Bellott, director of product marketing at Redzone Software. “Plants may also have a misunderstanding of OEE and the goals of different shop floor solutions; for example, Manufacturing Execution Systems (MES) versus OEE systems versus Connected Workforce Solutions (CWS). Bellot adds “opportunity losses can be tracked to changeovers, slow running, and rework.”

Comprehensive data visibility enables accurate assessments, but challenges remain. “Data silos between automation, MES and enterprise systems make it hard to establish a unified view of plant performance,” says Georges Mankarious, segment marketing director, factory automation at Emerson. “Machines range in complexity, and therefore the data needed to track OEE is inconsistent and requires a heavy level of domain and user expertise.”

Other challenges, of course, include limited engineering resources to build visibility to operators and corporate. “Many facilities lack dedicated data analysts or automation engineers, making it difficult to interpret raw machine data or build meaningful KPIs,” says Ray Buchko, president of RapidVisionPak, a Middleby Company. “Facility engineering teams are typically small, focusing on uptime and maintenance rather than data strategy.” Middleby leverages platforms such as Rockwell Automation's FactoryTalk Optix to produce clear contextualized machine data.

Which KPIs and Digital Strategies Are Working?

As digital strategies emerge and alignments on metrics occur, which KPIs are leaders choosing? “We’re seeing the best plants define theoretical maximum production rates (Tmax) for individual lines based on an initial Tmax of their rate-defining assets (or constraints) on each line and applying that rate universally to identical lines,” Bellott adds.

However, applying uniform metrics is a challenge. “On a schematic, two lines in two plants may look identical, but outcomes may be influenced by differences in conditions (like warehouse temperatures) or infrastructure (like compressor capacity) or personnel (low versus high tenured teams),” Bellot says.

Workforce issues, such as inexperienced leaders, tenure and language barriers, add to inconsistent metrics. “Workforce turnover and skills gaps mean operators often interpret metrics differently, reducing data reliability,” Mankarious adds. Emerson’s Movicon supervisory control and data acquisition (SCADA) platform can centralize monitoring and enable operators to visualize OEE and other data points in real time.

Data Standardization Affords Big Swings

In addition to data being shared via OPC and MQTT industrial networking protocols, manufacturers are taking big swings with digital twin technology. Harvard Business Review recently documented Unilever and Microsoft’s partnership pilot using the Azure platform to enable Unilever’s digital twin model of a physical plant environment to emulate production and analyze metrics. Unilever captured production data, such as temperatures and production cycle times, and fed it into its digital twin platform. Using this digital twin technology across 300 factories, Unilever Manufacturing System found a 3% increase in OEE, a 5% rise in labor productivity and an 8% reduction in costs, according to the report.

In addition, Unilever’s data standardization efforts are paying dividends with its AI pilot programs. A pilot project at one of its Poland plants focused on improving the efficiency of industrial liquid systems for ice cream applications, reducing machine cleaning times by 20%, cutting utility use by 10%, and saving €100,000. According to Unilever, this pilot is one of the most successful pilots to come out of 100+ Accelerator, a partnership created by Anheuser-Busch InBev and co-sponsored by Unilever, Coca-Cola, Colgate-Palmolive and Danone.

While Unilever ramps digital KPI initiatives, many large and mid-size brands are modernizing by integrating digital OEE processes. According to Redzone’s 2025 Benchmark Report, the first step for companies once software is in place is automated benchmarking of their baseline OEE, and the baseline OEE of the 1,500 factories in the report was 47%.

“That means that regardless of how profitable they are or their On-Time In-Full (OTIF) score, the average manufacturer is taking effective advantage of less than half of their manufacturing opportunities on each line each day,” says Bellot.

Kraft Heinz connected all essential machine assets in less than two years, as the company underwent a digital transformation across its enterprise.

“Plants are driving this transformation,” Ganschar says. “So you need to have dedicated owners, promoters who believe in their journey and know the process because they are educating you and people in the corporate environment.”

“The factories that make the most improvement are those that are the most transparent about their KPIs, including OEE, and understand that OEE is revealing opportunities for improvement,” Bellot adds.