The rapid adoption of IoT and embedded smart sensors by equipment manufacturers combined with new connectivity options are providing easy access to a wealth of rich operational data. Increasingly, equipment manufacturers and users want to leverage the insights derived by analyzing and modeling that data to transition from reactive to proactive services. Recently, RTInsights sat down with Chris MacDonald, Head of AI and Analytics, Digital Transformation Solutions at PTC, to explore what’s driving interest in this area, the challenges companies face, and key technologies that contribute to success. Here is a summary of that conversation.
RTInsights: Why is there interest in moving to proactive services, and why now?
MacDonald: Service and aftermarket are becoming important aspects of modern manufacturing businesses. Customers are demanding greater value, and manufacturers realize that long-term closer customer relationships are more profitable and sustainable. And if they are not, at the very least, they are a way of ensuring customers return to generate consistent revenue.
You have margins on the products that are continually squeezed. Companies and executives look towards service as a place to offset margin pressure by delivering greater value, forging closer customer relationships, offering opportunities to embed solutions deeper into those customer operations and provide additional products and services that are related to their core offerings.
The problem for many manufacturers is that much of the service and aftermarket business has been offloaded traditionally to third parties, who may not do things exactly the same way or follow guidelines to a tee. Going proactive is a way to regain control. It is actually regaining visibility at the very least, and then some level of control that allows you to standardize services.
If you take service, which can have margins of 2.5x of new product sales, and you see many manufacturers generating 40 to 50% of their overall profit from the aftermarket, it's easy to see why manufacturers start with proactive insights and proactive services. That gives them the ability to listen to equipment and assets in the field and adapting operational motions to patterns they discover. A proactive approach also offers a way to protect profitability of service business. They can then offer more aggressive SLAs. If they do that, they're much more likely to win profitable business and keep it over the longer term.
RTInsights: What are the benefits of using a proactive approach?
MacDonald: I'm going to use an analogy. Let’s take a step back and think about these physical assets or smart, connected products. You have telemetry data, and potentially other data about service from systems. That’s the equivalent of being able to hear. The question becomes, what do I listen to? There's a lot of noise, so how do I pick out and listen to only what’s important?
Without even considering predictive and prescriptive analytics, think about features and statistical importance related to performance. It gives you the ability to hear clearly which notes are in or out of tune amidst the background noise.
Of course, you can always hear a scream. But usually, a scream comes from someone (or something) already in some sort of crisis, experiencing harm. So, you are dealing with problems reactively.
There's a benefit of being able to truly listen to the right things. You can start to identify performance patterns and behaviors to diagnose what’s happening. Customers expect seamless operations. They tend to penalize the manufacturers who they believe, whether it's right or wrong, caused them unplanned downtime. Hearing notes that are out of tune will allow you to address a problem before there’s a scream - from the equipment or from your customer.
Analytics deliver the diagnostic insights I was talking about. It can spot deviations from best practices or how equipment should be operated or used in an environment. Proactive services based on those analytics spot problems before they arise.
With a connected product, you get a view into what is happening in the environment where the asset is operating. Analytics, especially advanced analytics, allows that data to be processed to identify statistically relevant anomalies, patterns, and events. That ultimately provides a more objective lens into what a problem really is.