Embracing Your Digital Transformation Journey

Man and woman wearing yellow safety vests viewing something on a tablet.

October 26, 2023

What digitization projects are you waiting to finish at your plant or organization? Digital transformation is the integration of digital technologies into plant operations, and it’s not just a monolithic process; it’s a journey for all of us. This shift revolutionizes how data becomes available to operators and decision-makers, adding unprecedented value across the production environment. Digital transformation has multiple advantages, such as eliminating data silos, improving product quality, enhancing asset productivity, and significantly reducing unplanned downtime. As each organization starts its course toward a better facility, we find ourselves in different stages. It’s important to understand that you can’t leapfrog into the more advanced stages of digitization without a solid foundation. Finding a comfortable spot in one phase and focusing on mastering it is also perfectly fine.

As you make your way on the road to digital transformation, remember that industrial analytics is a cornerstone and crucial for companies wanting to optimize their manufacturing processes. It enables manufacturers to collect data from multiple devices and sources throughout a plant, offering actionable insights that lead to operational improvements. In an increasingly competitive environment, digital transformation and smart manufacturing are essential for survival and growth, and industrial analytics is a critical component of this change. A partner like Interstates can help you maintain momentum at whatever milestone you find yourself at. Explore the six main stages of digital transformation and what they could look like at your organization.

Modernization | Laying the Foundation

Modernization serves as the foundation of the digital transformation journey. At this stage, organizations working with legacy machinery and basic digital control systems, including outdated field devices and Human Machine Interface (HMI) panels, recognize they need to do some upgrades. Data collection at this point in the journey is relatively simple, involving basic operational data from machines, system health metrics, and the initial digital conversion of analog signals. The challenges addressed at this stage include reducing manual interventions by leveraging automation, extending the lifespan of machinery, and setting the foundation for future digital expansion. The benefits of modernizing your machinery are remarkable: reduced downtime due to fewer manual interventions and human errors, more energy-efficient systems, and potentially lower maintenance costs. Going even further, the role of employees shifts from manual monitoring to supervisory and problem-solving tasks, allowing them to add more value to the organization.

Connectivity | Exploring Your Network Infrastructure

After the first leg of the journey, connectivity begins. It involves the implementation of Ethernet and other industrial protocols, Industrial IoT devices, and robust network infrastructure. Data collection, including real-time machine data, system status updates, and sensor readings, becomes more advanced in this stage. Challenges addressed in this stage include rectifying data silos and improving real-time data accessibility. Moreover, the connectivity stage emphasizes security and standardization. Data validation checks, redundancy mechanisms, and regular security audits become essential components of the digital system.

Visibility | Progressing Forward with Data Insights

You can think of visibility as the scenic overlook on a long road trip. When you finally get there, it’s exciting. It’s the stage in the journey that shows organizations what digital transformation can offer. Technologies at this stage include advanced HMI panels, data visualization tools, and supervisory control and data acquisition systems. At this stage, more elaborate forms of data like production metrics, performance KPIs, quality metrics, and environmental and safety metrics can be collected and viewed. This wealth of data offers a comprehensive understanding of production processes, helping to identify inefficiencies and bottlenecks. Real-time data availability helps process engineers and stakeholders make smarter decisions. Enhanced visibility equips employees with actionable metrics, facilitating quick problem-solving and fostering a goal-oriented approach.

Transparency | Improving Compliance and Risk

You’ve hit some major sites and milestones along the digitization trip; now it’s time to get into the details. The transparency stage involves even more complex systems, such as manufacturing execution systems (MES), integrated enterprise resource planning (ERP) solutions, and cloud-based data storage. Data collection shifts towards process flow data, material traceability, and employee performance metrics. Challenges addressed include consistent product quality, offering an end-to-end view of operations, and central data storage for insight sharing across sites and levels in the organization. The transparency gained from digitization makes compliance processes simpler, risk management more effective, and issue identification and resolution proactive.

Predictability | Starting a Proactive Approach

Reaching the predictability stage of your digital transformation journey means you are almost to your final landing spot on this trip. Predictability is the advanced stage where predictive analytics tools, machine learning models, and advanced sensors come into play. Data collection focuses on condition monitoring metrics like power usage and quality, vibration, temperature, and even cybersecurity log data. The benefits are significant: reducing unplanned downtime, maximizing asset longevity, minimizing waste, and bolstering cybersecurity. This stage necessitates a shift in employee skill sets, including data interpretation and understanding predictive analytics, marking a shift from reactive to proactive thinking.

Prescriptive | Responding to Market Changes

Now we reach the peak of the digital transformation journey—prescriptive solutions. Advanced AI algorithms, decision-support systems, and automated feedback loops are typical prescriptive technologies. The data collected optimizes production pathways and machine settings, and root cause analysis shows you precisely what went wrong and where. Challenges like resource optimization and process refinement are continuously addressed, enabling agile responses to market shifts and competitive threats. However, this stage also comes with a cautionary note: over-reliance on automation may reduce human oversight, leading to unforeseen consequences.

Digital transformation is a multi-stop journey that offers unique value at each stage. Whether modernizing legacy systems or adopting advanced AI algorithms for prescriptive analytics, each phase of the transformation comes with its own set of technologies, challenges, and benefits. The end goal is a digitally mature organization capable of agile, data-driven decision-making. But remember, each organization’s path is unique, and finding the right pace and stage that aligns with your specific needs and objectives is the best way to start the journey.

As you begin down this road, discover how we can walk alongside you each step of the way.