How to Get Useful Data from Your Smart Products




In a previous post on the topic of smart, connected products (SCP) and design intent, we talked about how working with a significant number of vendor and supplier components (like sensors and transmitters) can impact your product definition.  The key takeaway? You’ll need a process that combines bottom up, top down, and middle out design methodologies to effectively design SCPs.

But there’s more to planning smart products than figuring out where to place components. Connecting our products to the internet provides enormous opportunities for gathering data, which leads to better products and higher customer satisfaction. But what data do you collect, and when? In this post, we look at the data — what to measure, when, and why.

The Past

In traditional product development, we typically gathered data at two different phases: prior to product launch, and after customer use.

After detailed design, analysis, and prototype manufacturing, product development typically enters into a testing and qualification phase. This involves subjecting our products to the environments –and the extremes of the environments –they could experience during operation and use by customers. Testing might involve:

  • Tensile testing machines, transducers, and strain gauges to calculate stress.
  • Environmental chambers and thermocouples to measure temperature.
  • Shaker tables to subject products to vibration.
  • Non-destructive testing (NDT) techniques such as electromagnetic inspection, ultrasonics, and dye penetrant.
  • Simulated user damage, such as drop- and tumbler-tests.

Upon qualification, the object enters into production. At that point, there may be engineering change notices (ECNs) to address manufacturing issues, but we often don’t receive much data until our customers report information to us, such as:

  • Field reports of defects, damage, malfunction, and operational issues.
  • Returned artifacts.

In between manufacturing and customer complaints, there’s a huge gap in our product’s lifecycle during which we have no insight or data at all. How often was the product used? Under what conditions? Did it perform as expected? Are there opportunities we hadn’t thought of during design?

Those are exactly the kinds of questions SCP and the Internet of Things can help answer.

The Present and Future

Creo Product Insight

A smart, connected product streams data back to the engineering team for use in a future design with Creo Product Insight.

With SCP, we need to change our way of thinking about product performance to include the total customer experience. We want to measure data from all life cycles phases, and from products that are working properly, not just the ones with problems or defects. Connected products can provide data from these neglected life cycle phases:

  • The sales process. Does our product interact with the customer during the sales process, and if so, how? Can we correlate product demonstrations to sales success? Can we use this information to update our sales campaign midstream?
  • Installation. Can the customer implement the product without any problems? If not, can we revise the product to eliminate any issues?
  • Operation. How do our customers use our products? What use cases are most popular? Are they different than our assumptions? What new product features can we extrapolate from the current use cases?
  • Sustainment. How can we update our products in the field to extend the service life? Can we provide feedback to the customer regarding maintenance?
  • Retirement. What can we learn about our products’ end of life and how our customers dispose of them? What recycling or refurbishment opportunities are available?

Design intent is all about building flexibility into our products to adapt to the changes that result from additional data. To build design intent into smart, connected products during the product development process, we need to ask ourselves the following questions:

  • What sensors should we embed in our products to measure how our customers use them? How often do we relay that information back to us?
  •  Do we record and analyze every interaction? What kind of sample rate are we going to take from our sensors?
  • How much data is too much data to collect? Information overload –gathering too much information –can be just as detrimental as not collecting any at all.
  • Do we provide our customers with the capability to communicate with us? If so, what kind of interface are we using –voice, visual, tactile, or other? Do they communicate with us directly through the product itself, via a website, or through an app on the customer’s smartphone?
  • Does the customer interface incorporate machine learning and artificial intelligence?

IOT changes the way we think about our products: we need to figure out how to hear our customers –and then truly listen to them. Customer satisfaction occurs when results exceed expectations. By measuring data throughout the product life cycle, we’ll create better products that evolve to meet changing needs and wants, and become market differentiators or best-in-class.

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