Article October 13th, 2023
by Petri Rönkkö, Business Area Head, Forest, Manufacturing and Services
Democratization of industrial data as a driver of change
It’s worth dispelling the misconception that specialized data experts are a prerequisite for industrial data analysis. These experts are often in high demand, but they might only sometimes know what’s happening on the factory floor. In the future, tech-savvy business and manufacturing process experts will independently analyze the data, significantly expanding data utilization opportunities within manufacturing organizations when coupled with well-structured data. Will you embrace change and stay ahead, or risk falling behind in this ever-evolving digital era?
The global COVID-19 pandemic showed how crucial technology is for businesses. It changed how we work and greatly impacted how people think and act. It’s like a big shift in how businesses and individuals do things, happening in all industries. And the change is here to stay.
This shift also changes how factories and other manufacturing industries work. The fourth industrial revolution, also known as Industry 4.0, has been leading the way companies manufacture, improve, and distribute their products for more than a decade. It’s all about digitizing the industrial sector by combining operational technologies and IT. By using modern technologies, digital tools, automation, data analysis, and the Internet of Things (IoT), manufacturing companies are efficiently moving toward a fully connected and integrated digital manufacturing environment.
Yet, democratizing industrial data is the newest driving force behind this revolution. This shift is reshaping the industrial landscape by making advanced tools, digital capabilities, and data more accessible to a broader array of individual users. In the future, tech-savvy individuals will play a pivotal role in fostering innovation, enhancing competitive advantages, and driving efficiency gains in the industrial landscape through data analysis. This wave is about to begin, prompting manufacturing companies to take it on now to stay caught up to their peers.
Data is no longer exclusive to data experts
Rapid technological advancements in the industrial landscape have enabled value-adding datasets by transforming data collection, storage, and analysis. Industrial businesses can leverage real-time data to create better and smarter processes in much easier ways than earlier.
Thus, in today’s data-driven industrial landscape, the difference between those who lead and those who lag is how well they collect and utilize data across the company. A report from the World Economic Forum’s Global Smart Industry Readiness Index Initiative looked at hundreds of industrial companies with a foundation that followers are still thinking about using the latest tech to improve how they make things while pioneers are already using real-time data to make their processes work together seamlessly. According to Gartner, these innovators have rates of innovation up to 80% higher than the rest.
The challenges usually occur when organizations lack specialized data experts, seeing them as a prerequisite for all data analysis. But this is not the case anymore: data shouldn’t just belong to data experts in the future. These experts are often in high demand, but their expertise may not necessarily extend to understanding the intricacies of factory floor operations.
As data democratizes, becoming more accessible to all, it empowers individuals across various departments within a company to utilize and analyze it. Leveraging the benefits of modern technology, manufacturing organizations can provide both production workers and business professionals with user-friendly data tools. This enables them to improve processes and outcomes without requiring specialized data expertise. By involving a broader range of people, not just traditional IT experts, in internal IT development, the establishment of modern operational methods and the pursuit of efficiency in daily factory operations become achievable goals.
Three must-win battles
To fully benefit from data democratization, it’s crucial to eliminate data silos. They are a common challenge in manufacturing organizations, where various departments, machines, and systems generate and store data in separate and incompatible formats. These silos block the movement of data within an organization, making it less useful; it prevents manufacturing organizations from obtaining a complete picture of their operations, performance, and opportunities for improvement. Consequently, advanced data analytics can be challenging due to the lack of connectivity between data sources and systems and in-house knowledge about machine interfaces. By breaking down these barriers through data source and system integration, as well as by using modern tools for data visualization, manufacturing organizations can unleash the full potential of their data resources.
We should also harness the knowledge of factory workers who have valuable insights but may not always share them. One way to accomplish this is through automation rather than dedicating time to manual data tasks. It’s estimated that approximately 25% of a factory worker’s day is consumed by the manual collection, processing, and reporting of data. This occupies a significant portion of their time and hinders disseminating valuable silent knowledge throughout the organization. To democratize data, it’s essential to leverage modern technology to collect real-time data from different parts of the production process.
The third important consideration is whether the data is easily understandable or resembles a foreign language. This is a common issue because various departments within a company might employ different terminology to describe the same data concepts. To democratize data, it’s essential to ensure it is presented in an easily understandable format. Achieving this involves constructing high-quality data models capable of capturing real-time data and translating it into a common language accessible to all individuals working with the data. One commonly used technological approach for achieving this goal is using digital twins. These are like virtual copies of real things, helping organizations make sense of data derived from the production line. For example, a digital twin can assist in examining raw data and its real-time implications on factory operations, enabling organizations to test various ideas for enhancing production efficiency using data.
Start from comprehensive technology and data strategy creation
To empower your journey toward success, the first step is to adopt a strategic approach encompassing technology and data.
A robust technology strategy goes beyond mere tech management; it’s about anticipating future tech needs and aligning them with your company’s broader business goals rather than merely reacting to external changes. It enhances internal transparency and identifies where your investments will yield the most value, accelerating the adoption of new technologies.
A well-crafted technology strategy is far from a static plan copied from industry reports; it adapts to the current landscape and evolves when promising technological innovations emerge. It harnesses cutting-edge technologies to offer real-time insights into your operations and supply chains, enabling your organization to swiftly respond to shifts in market dynamics, customer preferences, and other external factors. By embracing technology and integrating it with your strategic objectives, your company can position itself to thrive in an ever-changing business environment.
A well-defined technology strategy should include a holistic data strategy as well. Seamless information exchange between corporate management and production remains a central challenge. This underscores the importance of blending Information Technology (IT) and Operational Technology (OT). The convergence of these once-disparate realms forms the foundation of a holistic data strategy, yielding substantial benefits. Today, success hinges on integrating IT and OT. A holistic data strategy rooted in this fusion empowers confident decision-making, fuels innovation, and ensures competitiveness in a dynamic era.
Embracing the change leads to increased success
Democratization of data can serve as a driving force in the industrial sector: it will foster more agile innovation, enhance competitive advantages, and drive efficiency gains in factories. Embracing this transformation empowers organizations to thrive in a rapidly evolving business landscape. However, ensuring success hinges on the capacity to learn and grow in response to emerging opportunities. Thus, in today’s fast-paced digital landscape, where technological and data-related advancements challenge established practices, it’s crucial to recognize that the ability to adapt and be flexible will surpass the value of predictability and cost-efficiency.
Additionally, it’s worth dispelling the misconception that specialized data experts are a prerequisite for all data analysis. These experts are often in high demand, but their expertise may not necessarily extend to understanding the intricacies of factory floor operations. This is where putting modern, easy-to-use data tools into the hands of production workers and business professionals can yield the greatest benefits for the company. Modern self-service analytics empowers business and process experts to analyze data independently, significantly expanding data utilization within organizations when coupled with well-structured data.
Industrial companies must take immediate action to stay competitive within their industry. By harnessing the benefits of modern technologies and the widespread availability of data, these organizations can engage a more diverse set of individuals, extending beyond the traditional information system experts. This expanded participation can drive internal IT development, foster the creation of modern operational approaches, and advance the aim for daily factory operations efficiency.
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