The Power of Data in Manufacturing

In the era beyond Industry 4.0, digital technologies are transforming manufacturing, with data at the heart of this revolution. Unified workflows, which require accurate and comprehensive data, provide end-to-end visibility throughout the manufacturing process. This plays a crucial role in driving innovation, improving decision-making, and enabling proactive management.

In this article, we’ll explore the significance of data and its role in fostering innovation and facilitating data-driven decision-making through guided insights. Such insights empower companies to operate more efficiently.

Understanding “Good” Data Versus “Bad” Data Versus “Dark” Data

The quality and relevance of data is paramount in manufacturing. Effectively distinguishing good data from bad or dark data lays the foundation for successful data-driven manufacturing. Good data is accurate, consistent, timely, and relevant, providing a reliable basis for analysis and decision-making. Bad data often refers to incomplete and outdated data that leads to inaccurate conclusions and ineffective actions. Dark data is information that organizations collect and store, usually in operational technology (OT) or IoT devices, but do not use in any manner to drive insights for decision-making, leading to inaccurate, flawed, or often biased decision-making. Below are three key factors to consider when working with data:

• Accuracy: Good data must be precise and correctly represent the real-world conditions it measures, leading to accurate conclusions and actions.
• Timeliness: Data should be complete, current, and up to date to be effective. Using outdated or incomplete data might not capture the present conditions, potentially leading to misguided decisions.
• Relevance: Data must align with the specific needs and goals of the manufacturing process. Irrelevant data clutters the analysis and obscures actionable insights.

Data quality requires robust data governance frameworks, regular audits, and continuous monitoring to detect and correct anomalies. Good data is the cornerstone of effective unified workflows and end-to-end visibility.

Data as the Foundation and Fuel for Innovation

In modern manufacturing, many refer to data as the new “oil,” an essential resource that powers advanced technologies. Unified workflows depend on a robust data infrastructure to ensure a seamless flow of information across all stages of the manufacturing process, including but not limited to sensors, ERP systems, CRM platforms, and machines.

This provides critical insights through advanced data analytics, including AI and machine learning, which are necessary for optimizing processes, developing new products, and enhancing overall operational efficiency.

Data is not just a passive resource but an active driver of innovation. By leveraging data, manufacturers can develop new products, optimize processes, and enhance customer experiences to stay ahead of the curve by continuously improving and innovating to meet evolving market demands.

Benefits of Data-Driven Decision-Making

Data-driven decision-making transforms manufacturing by providing actionable insights that guide strategic and operational choices. Data-driven decisions are more accurate, objective, and reliable, leading to better outcomes and enhanced competitiveness. Below are some common benefits of using data-driven insights:

• Increased efficiency: Data analytics pinpoint bottlenecks and inefficiencies, fostering targeted improvements.
• Improved quality: Real-time monitoring and predictive analytics maintain high-quality standards and minimize defects.
• Enhanced agility: Data provides the agility required to respond quickly to market changes, customer demands, supply chain disruptions, and other external factors.
• Cost reduction: By optimizing resource utilization and minimizing waste, data-driven decisions reduce operational costs.
• Customer satisfaction: Data insights help tailor products and services to meet customer needs, driving satisfaction and loyalty.

With data-driven decision-making, manufacturers can move beyond intuition and experience, relying on concrete evidence to guide their actions to optimize operations, enhance product quality, and increase customer satisfaction.

Data-Centric Computing and IT/OT Integration

Data-centric computing, such as cloud and edge with the integration of IT and OT, is a vital component of modern manufacturing systems for realizing the full potential of unified workflows.

Interoperability and robust security are critical for IT/OT integration, enabling seamless communication and unified workflows between systems, which helps prevent breaches and safeguard data integrity. This supports seamless data flow and real-time analytics, driving operational excellence.

The collaboration between IT and OT allows manufacturers to harness advanced analytics, IoT, and AI technologies, transforming raw data into actionable insights and strategic advantages.

Guided Insights and Proactive Management

High-quality data underpins workflows, guiding manufacturers with predictive and prescriptive analytics that support proactive management. This shift from reactive to proactive strategies is crucial for achieving operational excellence and staying ahead of the competition.

With the right data and tools — such as real-time monitoring and strategic planning — manufacturers can anticipate and resolve issues before they disrupt operations, leading to fewer interruptions and better overall performance.

Conclusion

In the age of smart manufacturing, data is more powerful than ever. Embracing unified workflows and leveraging data for complete visibility can drive innovation, enhance decision-making, and support proactive management.

By focusing on data quality, integrating IT and OT systems, and tapping into the power of data analytics, manufacturers can transform their operations, boost efficiency, and deliver exceptional value to their customers. Moving toward a data-driven future involves more than just adopting new technologies; it's about creating a cohesive, data-centric ecosystem that helps manufacturers thrive in a competitive and rapidly evolving market.

Learn more about how Splunk can positively impact data across manufacturing organizations here.

Sarah Lee is Research Director for IDC Manufacturing Insights and is responsible for the IT Priorities & Strategies practice. Sarah’s core research coverage includes IT investments made across the manufacturing industry and manufacturers' progress with digital transformation. Based on her background covering the manufacturing space, Sarah’s research also includes an emphasis on the technology enablers that help manufacturing executives make better-informed operational decisions.