Empowering Efficiency & Boosting Production with Real-Time Data: The 20% Capacity Leap

Facing the challenge of increasing production by 10-20% for a major customer without quality loss, a cheese processing company, guided by INS3, focused on real-time data use and boosting employee engagement instead of investing heavily in new equipment. By sharing key performance metrics with all production line staff, the company enhanced efficiency, cut waste, and nurtured a collaborative work culture, proving strategic improvements and teamwork can achieve significant production boosts without major capital expenditure.

Focused on the operators to achieve

10-20%

increased capacity

For this project, INS3 sends data to a Data Lake in the Cloud where they do Predictive Analytics and create Prescriptive Models – we then deliver Reports, Dashboards, Scoreboards, Alerts and KPI’s!

The Challenge

A cheese processor (INS3 Customer) sliced, shred, cut, and cubed cheese along with other products and then packaged it. The challenge presented is multifaceted and emphasizes the need for operational excellence to meet increased demand without compromising quality:

  • Increased Demand: The cheese processor must increase capacity by 10-20% to meet the demand driven by new opportunities, such as placement in our customer’s stores.
  • Efficiency and Profitability: The need to enhance operational efficiency not only to meet increased demand but also to reduce waste and giveaways by 10-20%, directly impacting profitability.
  • Quality Assurance: Maintaining the high-quality standards that the brand is known for, despite the increased production demands.
  • Operational Execution: Recognizing the potential to meet demand by optimizing existing operations rather than solely relying on expanding capacity through additional lines or new facilities.

MES Administrator

By focusing the operators on the key metrics they need to control, and keep at a high level, we are able to see continual gains in productivity across our lines, and established a culture of driving to be the best.

The Solution

Opting against relying on capital-heavy investments in new machinery for growth, the company chose to optimize existing data and enhance workforce involvement. Key insights were made readily accessible to everyone on the factory floor by distilling essential data points for improved decision-making.

At the heart of this strategy was the decision to make critical data accessible to those on the production floor. We brought the performance metrics directly to the employees who have the most significant impact on the business. To put it in action, the company installed large screens throughout the plant, including strategic locations like the break room. These screens displayed key metrics that were critical to the company’s productivity and quality goals, thereby making this information part of the daily life of the plant’s workforce.

In the next step, the company trained workers and supervisors to understand the data correctly and to understand the implications of different indicators. For example, knowing a “red” status means there’s a big problem that needs to be fixed right away.

Further, employees and supervisors received training to interpret the data accurately, such as recognizing a “red” status as an immediate issue requiring attention. To engage the workforce further, the company employed creative methods like displaying announcements and conducting trivia contests with rewards on the screens, making data interaction both informative and entertaining.

Overall, by making data easy to understand and fun to engage with, the company optimized the operational use of data and cultivated a culture of improvement and deep employee engagement.

Highlights of the Solution:

  • Data Utilization and Employee Involvement
  • Accessible Performance Metrics
  • Training for Data Interpretation
  • Engagement and Learning Strategies
Real-Time Data for Prescriptive Models

The Results

The implementation of real-time data visibility and employee engagement strategies led to tangible and positive outcomes for the cheese processor. The initiative fosters a competitive and collaborative environment among line supervisors and operators. They were now trying to avoid being in the “red”, and also compete against each other for higher scores.

INS3 Tip

Not sure where to start? Start by collecting the time and event series data. Analytics run best with a lot of correlated data and you never know the variable that will be the most important. Or if you’ve got questions, let us help.

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