As an engineer, I enjoy quantifying parameters, documenting requirements, and understanding problems at a deeper level; but before delving into the details it’s important to take a step back and ensure your company is taking on the appropriate level of risk and reward with its emerging medical device technology.

Striking a balance of customer ignorance and customer input is a delicate one, particularly with nascent technologies. Tools like Voice of Customer, House of Quality, downselection matrices, and customer input are an important part of a successful design process. This is particularly true when you’re coming out with the next ultrasound probe, and you need to know what shape, ergonomic features, BoM cost, and ultrasound frequency is needed for your target indications, patient needs and what cost the payer will tolerate.

Where it gets tricky is with disruptive technology, such as when you’re designing a novel ultrasound tool that no one has ever seen or used. In these cases interpretation of what Voice of Customer data means needs context and interpretation. For example, we worked with a doctor who asked all of his colleagues about using a new safety device. The response was resoundingly defensive to the prototype, even though the product would actually decrease workflow steps and make the user of the device safe – there is generally a resistance to change.

So how do we collect meaningful user data for the use of novel technologies? Assuming we pass the litmus test of having a technology that really truly works and solves a meaningful problem, we get creative. Here are a few ideas:

1. As we’re catering to new adopters, pick a related technology and understand it thoroughly. With disruptive technology you don’t necessarily need to stand out on industrial design efforts (though there may be some reasons for doing so). What about parent technologies works well? What doesn’t? Where have others succeeded or failed? How have they solved some of the problems that you are currently encountering? When you’re already trying to solve some large technical challenges, don’t introduce additional product risk on peripherals that may not be better than incumbents.

2. Collecting customer feedback on related technology can feed directly into your design. For instance, when designing a cart for an imaging system, look at all of the imaging carts of similar technology and/or use environment. Think about the impact that your technology will have on the layout of the interface and try to mitigate any introduced risks. Ask if there are any additional problems being encountered that may be addressed with your technology and consider introducing them as part of the design.

3. Collect feedback on preliminary designs early. When users don’t realize they’re using a new technology, except for enhanced information, you may have just succeeded. Where confusion exists, understand if this is an anomaly or if something has been missed. Consider a device we were developing that required a photo of the patient be taken as part of the workflow. An early prototype camera orientation relative to the patient seemed to add 10lbs. This may not seem like a big deal, but for some people it was very off-putting and decreased the perceived value of the device even though technically all requirements were met.

4. Go through the process of defining your customer requirements and use these as a part of your design criterion, but don’t be afraid to ignore the results. To quote a recent report from the University of Stanford’s paper QFD and the Designer: Lessons from 200+ Houses of Quality, “QFD is a powerful and popular tool but it should not be the sole focus of the design efforts.”

There are great examples in history such as Henry Ford’s quote ‘If I had asked people what they wanted, they would have said faster horses’ that speak to the fact that defiant minds are able to conceptualize embodiment that customers actually want. This can lead to epic failures – like the Saab 9000 prototype car, where the steering wheel was removed and replaced with a joystick – good on ergonomics, bad on control. Alternatively, these can lead to resounding successes that are separated from the pack at the time – such as Apple.

I often find myself dealing with emerging medical device technology that offers significant advantage and benefit over what is already out there. Determining methods to best define what the customer wants with these types of technologies can be challenging as many of the methods published just don’t fit early stage work. I hope my tips above help others and would love to hear ideas and suggestions from readers on how they solve this problem.