Beyond Digital Transformation: Prioritizing Process Optimization Among the Best-in-Class

During times of economic volatility, digital transformation is the key to the survival of manufacturing organizations, and enhancing process optimization is critical for thriving through times of change.

According to Aberdeen research, ‘Best-in-Class’ companies have already implemented the necessary technologies and capabilities to mitigate market disruptions, and they are now leveraging those enablers to optimize process productivity. By relying on solutions that provide greater control on the factory floor and offer real-time data visibility, top performers are setting the pace of innovation with processes and technologies that prioritize efficiency and excellence.

In this blog post, we discuss how to optimize manufacturing processes and explore what Best-in-Class manufacturers are doing to navigate today’s complex manufacturing landscape. We also reveal how they have achieved digital transformation and are embracing manufacturing process optimization—setting the stage for average and laggard companies to follow suit.

Navigating Today’s Manufacturing Complexities & Challenges

It’s no secret that manufacturing today is complex—it’s full of accelerated digital initiatives, supply chain slowdowns, increased customer demands, and many other unknowns. The most pressing challenges in day-to-day manufacturing, according to Aberdeen, include:

• Maintaining product quality levels
• Embracing the increasing pace of innovation
• Handling the rising cost of raw materials
• Dealing with growing operating costs
• Managing multiple datasets
• Customer demand for competitive differentiation
• Supply chain disruptions

Manufacturing teams are constantly searching for ways to mitigate these challenges and further optimize their operations. These challenges can be tackled during product development, on the factory floor, or in the field, but no matter where efforts are made, organizations must keep up with the pace of innovation to remain competitive.

The Best-in-Class Have Moved Past Digital Transformation & Now Embrace Process Optimization

Aberdeen’s April 2021 survey revealed that digital transformation became a priority for 67% of manufacturers throughout the pandemic. These organizations have recognized the importance of leveraging technology enablers to improve time-to-market, overall equipment effectiveness, and advanced innovation.

As one of the top business units to see massive disruption due to the COVID-19 pandemic, manufacturing divisions are a prime area for digital transformation. While disruptions to normal business operations can be frustrating, they are an ideal opportunity for change—and the Best-in-Class have already stepped up to the challenge.

Digital transformation doesn’t stop after implementation. Aberdeen’s research shows that many Best-in-Class companies are nearing the end of their digital transformation journey. They have implemented new systems and are now focused on properly leveraging their new processes and technologies to maximize their performance. Now, the Best-in-Class are concerned with integrating their new systems into workflows and utilizing them to optimize manufacturing operations. They are taking actions to increase manufacturing effectiveness, improve efficiency through Lean initiatives, and establish a “digital thread” to track product data throughout the product lifecycle. The Best-in-Class have invested in comprehensive technology enablers and capabilities to put these strategies to work. They are prioritizing process optimization, adopting solutions to gain real-time visibility across their organizations, and leveraging data management capabilities to promote data-driven decision-making.

Process ‘optimization’ involves investigating processes to determine areas for improvement and reveals opportunities to minimize waste, decrease production downtime, and increase quality. While both the Best-in-Class and all others are likely to use standardized KPIs to track performance, Best-in-Class companies take process optimization in manufacturing even further. Some of their specific efforts in their optimization of manufacturing processes include:

• Idea Gathering. Having a formal process in place to capture ideas allows teams to build on successful initiatives.
• Automated Alerts. Automated alerts based on defined conditions to enhance visibility and prevent issues.
• Real-Time Response. The ability to respond to real-time manufacturing events is critical for optimizing processes and mitigating problems.
• Production Harmonization. Automated alerts based on defined conditions to enhance visibility and prevent issues.
• Predictive Maintenance. Automated alerts based on defined conditions to enhance visibility and prevent issues.

Other companies can look to the Best-in-Class in their initiatives and follow in their footsteps to achieve similar performance levels.

Although Best-in-Class companies are ahead in digital transformation, their journey isn’t complete. After adopting new technologies and processes, manufacturers need to be constantly looking for areas to reduce costs, promote innovation, and improve time-to-market.

Leverage an MES to Model Manufacturing After the Best-in-Class

The actions of the Best-In-Class provide manufacturers with an ideal model to follow, as they are in the later stages of their digital transformation journeys and have shown that prioritizing product and process optimization is essential for establishing global business agility. By investing in manufacturing systems with real-time visibility and IIoT data management capabilities to enable data-driven decisions, like an MES/Manufacturing Operations Management (MOM) solution, companies can achieve Best-in-Class levels of performance.

Aegis’ FactoryLogix is one such MES/MOM IIoT-based platform. It enables manufacturers to realize the benefits of factory digitization and Industry 4.0 while gaining real-time visibility and control over their manufacturing operations. Contact us to learn more about FactoryLogix and the optimization of manufacturing processes.