As recently as 18 months ago, most of the conversations manufacturing companies were having with us at Stratecast’s Big Data & Analytics (BDA) practice focused on their interest in predictive maintenance: identifying degrading parts or performance in equipment so they can be repaired or replaced before they shut down production lines. Manufacturers that have installed sensors on their manufacturing equipment can collect data, and perform predictive analytics against that data, to avoid breakdowns on the production line, as well as other delays and bottlenecks. This is the definition of predictive maintenance in manufacturing, and it parallels similar activity that first occurred in the telecommunications industry long ago. By detecting so-called performance faults, Communications Service Providers (CSPs) began to proactively identify problems that were likely to occur, and thus to repair or replace a piece of networking equipment before it broke down and interrupted communications services. Manufacturers are now beginning to follow this same sound business practice.
As beneficial as this is, however, predictive maintenance impacts only one area of a manufacturer’s operations. BDA has the potential to leverage data collected through the Internet of Things (IoT)—and 40 other areas—to do much more across the enterprise. Today, manufacturers are beginning to use BDA to synergize data from all sources to create opportunities and value across the enterprise, as highlighted in the gold text boxes along the right edge of the graphic.
Figure: How BDA and IoT Can Create both Operational and Business Benefits
By using BDA to synergize IoT and all types of data across the organization, manufacturers can achieve what to many is the Holy Grail: commercial decision insight, where device and system data helps drive business decisions about potential product features and markets. Aggregated over time, BDA can help identify trends so companies can anticipate and plan for the future. The opportunities this creates include:
• Manufacturing to Meet the Market. Manufacturers must integrate IoT and other production-focused data with the wide range of other data sources at their disposal—such as warranty, call center, and social media data—to get early warnings of perceived and actual problems. One example: learning through social media analytics that a planned product design is unpopular with a key target market, and plugging that information into product development and production processes to change the product before it hits store shelves.
• Using Test and Production Data to Optimize Products and Processes. Manufacturers can benefit tremendously from test data generated during R&D processes. While testing is often seen as an obstacle to getting products out the door, test data can improve productivity by helping to streamline processes and reduce waste; combining test data with production data helps shape better products and drives more efficient processes once products are in production.
• Optimizing the Supply Chain. Despite three decades of supply chain improvements, many manufacturers still name variable demand as the biggest obstacle to achieving goals: it is extremely difficult to get the right product to the right place at the right time, and at the right price. By incorporating true demand signals, leading indicators, and other causal factors, BDA can sense and in fact help shape demand.
• Staying Connected throughout the Product Lifecycle to Create Sales Opportunities. In the past, many manufacturers could simply “ship it and forget it”: they developed and shipped products, often through distributors, and never came into contact with the product again unless there was a warranty issue. Today, however, BDA and the IoT are creating new revenue potential by helping manufacturers stay connected with cars, appliances, electronics and more, long after the sale. Parts can be inspected with optical sensors or cameras, then tagged and followed digitally throughout the supply chain, and while in use by the customer. For example, some manufacturers are developing connected sporting equipment, such as baseball bats that record information on the amount of usage the bat receives and can assess a user’s swing, where he or she is contacting the ball when hit, and more. Staying connected with users throughout the product lifecycle can help manufacturers create subscription services, sell add-ons, or sell related products based on lifestyle.
• Staying Connected throughout the Product Lifecycle to Create Service Opportunities. Smart products can create new service opportunities by gathering diagnostic and prognostic data and sending it to the manufacturer. For example, vehicles equipped with sensors can feed performance data to the manufacturer; the manufacturer analyzes that data and delivers actionable information through an app or dashboard on the customer’s smartphone. That actionable information can include warnings that an issue is developing and request that the customer head to the nearest dealership for a specified repair. The BDA system must coordinate with all parties to ensure that when the customer arrives, the dealership knows the situation, and is prepared to take action on arrival. For example, the system can identify the right parts needed for a repair before a service technician even sees the vehicle. This not only saves customer, dealership, and manufacturer time and expense, it also builds customer loyalty.
• Democratizing and Mobilizing Data to Help People Perform Better, too. BDA done right empowers employees with the information they need, when and where they need it, to do their jobs better. The old models that locked up data inside IT “glass walls” have been obsolete for a long time. The key is to analyze data from all sources, and distill it into specific actionable insights; then, either proactively push it out, or make it readily accessible to both business and technical users.
When it comes to deploying BDA solutions to effectively leverage data from the IoT and all sources, some companies are blowing away the rest of field. Manufacturers such as Lenovo, BUNN, Sub-Zero, and others, working with providers such as GE, Mesh Systems, and SAS, are reaping benefits that include:
• Cutting service incident rates, issue detection times, and energy costs in half
• Reducing contact center calls by 30-50 percent
• Obtaining double-digit efficiency gains
• Reducing warranty costs by 15 percent
• Realizing operational savings of millions of dollars
Clearly, while data is at the core of predictive maintenance, the benefits of a comprehensive BDA strategy transcend predictive maintenance to lend benefits across the manufacturing enterprise. Smart manufacturers truly get it, and are reaping the rewards.