How Manufacturers Use Big Data to Gain a Competitive Edge

Manufacturing is one of the most important sectors globally, but especially in the United States. In fact, the U.S. is expected to overtake China as the most competitive manufacturing nation in the world in 2020. Japan and Germany currently round out the top four, which is expected to continue through the year 2020. Manufacturing has benefited greatly from technology advancements, and the sector plays an important role in the blending of the digital and physical worlds.

The manufacturing landscape is also highly competitive, facing constant pressure to innovate. While advancing technology is driving the competitive landscape, it’s also providing the solution manufacturers are looking for to remain competitive, in the form of Big Data and analytics.

Big Data Drives Improvements in Manufacturing

The use of Big Data isn’t new to the manufacturing sector; it’s been making an impact for more than two decades. The benefits are clear, with manufacturers tapping into the power of analytics to improve manufacturing processes, increase output, and improve quality through the use of lean manufacturing principles.

As more sophisticated analytics enter the scene, manufacturers are able to take a more granular look at their data, rapidly diagnosing flaws in processing and implementing the right changes to influence outcomes. They can analyze historical data to pinpoint patterns and trends, recognize relationships between variables, and determine which variables have the greatest influence on a key performance indicator (KPI).

Armed with these insights, manufacturers can optimize the factors that have the most influence over the desired outcome “ whether it’s product quality, yield, or something else. Perhaps more importantly, the availability of real-time data makes it possible to test process changes and evaluate results immediately, allowing for a change of course if a change isn’t producing desired results.

Big Data Use Cases in the Manufacturing Sector

LNS Research and MESA International surveyed 200 manufacturers for the 2013-2014 Metrics that Matter’ survey, which revealed insights on how leading manufacturers approach technology trends and emerging technologies to support manufacturing process improvement. When asked how they feel companies can improve manufacturing performance by mining both plant and enterprise Big Data, between 5 and 6% of respondents indicated that they didn’t see any future use for Big Data in improving manufacturing performance. The top nine responses each had response rates of more than 30%, including:

• The ability to better forecast products and production (46%)
• Understanding plant performance across multiple metrics (45%)
• Faster servicing and support for customers (39%)
• Real-time alerts on manufacturing data analysis (38%)
• Correlating manufacturing and business performance information (36%)
• Correlating performance across multiple plants (36%)
• Mining combinations of manufacturing and enterprise data (31%)
• Predictive modeling capabilities for manufacturing data (31%)
• Improving interactions with suppliers (31%)

These responses, of course, aren’t the only ways manufacturers can leverage Big Data to gain a competitive edge. Manufacturers are heavily regulated across many industries, such as pharmaceuticals, food manufacturing, and others, and analytics proves valuable for improving quality control and enhancing compliance by identifying defects in product, processes, and suppliers, components, and parts.

Proper equipment identification and preventative maintenance are foundational elements, but tracking production yield and monitoring equipment production metrics offer numerous benefits, such as identifying patterns and issuing alerts for performance thresholds that indicate impending breakdowns, allowing for production adjustments to minimize downtime and maintain required production output. Analyzing supplier data can reveal issues in the supply chain, allowing manufacturers to make smarter decisions when selecting suppliers, reduce raw materials spending, and eliminate supply chain delays that impact profits.

As technology continues to evolve and adoption becomes increasingly widespread in the manufacturing sector, it’s quite possible that these benefits merely scratch the surface of what will be achievable in the coming years.

How Manufacturers Can Succeed in Digital Transformation

In 2017, the term Industry 4.0 is used to describe the fourth industrial revolution “ several years in the making “ built on the maturation of newer technologies that prove promising for improving manufacturing, not only across the enterprise but also throughout the product lifecycle. The Digital Transformation is underway in the manufacturing sector, and with it will come the integration of operational technology (OT) and information technology (IT), also known as IIOT or Manufacturing Operations Management (MOM) 4.0.

Successfully embracing the Digital Transformation and navigating the path to eventual MOM 4.0, manufacturers need to create a plan, put the right people in place, and acquire the necessary resources to achieve technology goals. This includes, but is not limited to:

• Establish a digital leadership team. This may include establishing a leadership role such as Head of Digital Transformation or Chief Digital Officer, but should also include representatives from each department to provide insight from various perspectives throughout the planning and implementation process.
• Implement systems that support automatic data capture. Data is the foundation of Digital Transformation, and implementing systems to streamline data collection should take place early in the process. This includes tools such as durable barcode labels, barcode scanners, and integrated software to centralize data collection and analysis from non-connected devices and high-value equipment.
• Make data readily available. Equipment operators with access to real-time metrics can readily adapt to the environment and modify processes to maximize production. Maintenance professionals can address equipment breakdowns more rapidly when data reveals the source of the problem, eliminating the need for time-consuming troubleshooting. Data is only useful when it’s usable, so make data analysis findings and actionable insights available to those who need them.
• Eliminate data silos. Too often, enterprise data exists in silos, making it impossible to effectively examine relationships between disparate variables. Breaking down silos allows for the application of data across the enterprise and also reveals how corporate-wide parameters influence quality management and compliance.
• Optimize with granular data. While eliminating data silos is crucial for modern manufacturing companies, the other side of the equation is equally important: the ability to drill-down to more granular data, down to a machine-level view, provides valuable, actionable insights for operations managers, enabling them to scale production efficiently and streamline workflows.
• Embrace change. As the manufacturing sector is in the midst of its Digital Transformation, the ability to adapt readily to emerging trends and technologies is a must for manufacturers that want to maintain a competitive edge.

The proliferation of Big Data and analytics has catalyzed digital transformations across many sectors. Manufacturing companies who fully leverage Big Data and related technologies stand to reap tremendous benefits impacting every facet of their operations, establishing a competitive advantage for driving success in 2017 and beyond.