A product’s disposition is baked into its origins. The entire lifespan of a product—how long it lasts until it breaks or becomes obsolete, the maintenance it needs along the way, and even the way it is disposed of—all arise out of a probability cloud that is generated during the product’s design phase. Companies can’t predict the exact outcome for any of the products they create, but they can understand what’s most likely to happen based on data from the design and manufacturing processes. This is where PLM and DFM converge with Big Data.
Data is not a magic bullet, however. Data can’t help manufacturers if the right people don’t have access to it. Data can’t help you if it’s low-quality, and data can’t help you if there’s not enough of it. Therefore, a successful company doesn’t just analyze data well—it also optimizes data sharing. Here’s how market leaders can wield data to succeed in an increasingly complex manufacturing environment.
Big Data Integration with DFM has Been a Long Time Coming
To a certain extent, DFM has already been integrated with Big Data since the early 2000s. This was when OEMs began to employ the idea of “mass customization,” allowing customers to select a mass-produced product with certain characteristics tailored to their personal needs. Big Data is used to select an array of product combinations that consumers might want and manufacturers needed to design their products with that array of customizations in mind.
There is so much more that can be done, however. Mass customization started fifteen years ago, but it was only the beginning of a wave of increasing product complexity. In the Aberdeen Group study, “Maximizing Product Design in a Complex Manufacturing Environment,” our respondents noted that their products had become up to 30% more complicated in just the last two years. In order for companies to ensure that their more complicated products are as reliable, they must begin integrating data-driven PLM.
The Move to Data-Driven PLM
Big Data is going to have huge effects on product life-cycle management. The Internet of Things, just a single data point in a whole spectrum of advances, is already having an incalculable effect. For example, manufacturers are going to be able to use sensors embedded in their products in order to proactively identify and schedule maintenance needs. This process will be invaluable not just for maintenance, but also for compliance and regulatory monitoring. Lastly, these sensors will capture customer usage data, giving companies the feedback necessary to tweak and update their products for enhanced customer loyalty.
Integrating the data captured from the IoT has the potential to revolutionize PLM, but that shiny future isn’t quite there yet. In a study from Aberdeen Group entitled “Optimizing Product Lifecycle Management Using Big Data Analytics,” we determined that nearly 20% of companies consider data management to be an obstacle to the design process, and that 30% believe that data silos are an important challenge. However, only 60% of companies in the Follower category were using a product data management solution.
Integrating the Trifecta
Design for manufacturing now relies on big data—in just one example, companies are using customer feedback in order to generate customized product designs en masse. PLM will shortly rely on big data—embedded sensors in customer devices will allow manufacturers to refine their products and schedule maintenance. Done right, this is a perfect scenario for manufacturers. Done poorly, it’s a negative feedback loop, in which the IoT drives more complex products, more complex products become more unreliable, and no one can make sense of the data being generated.
How do OEMs avoid this negative outcome? All of our research suggests that the answer is collaboration. From design, manufacturing, maintenance, and analysis from the earliest stages, every stakeholder needs to be involved, talking to one another, and looking at the same data. This is much easier said than done, of course. For more information on how the leaders of the field manage this exercise, check out the Aberdeen report, “Maximizing Product Design in a Complex Manufacturing Environment.”