In the digital innovation arena, it’s clear that AI and IoT are indispensable to creating added value. How do you determine which direction to follow? And how do you go beyond what everyone else is doing? That’s where outcome-based innovation comes in. Instead of making incremental product improvements based on fragmented user feedback, you evaluate which ingredients of outcome-based innovation, enabled by new technologies, better address critical or hidden user needs. It allows you to create a completely new offering that stands out amongst the fierce competition.
How can you create new added value through outcome-based digital innovation? And when looking at software solutions, how do you connect devices to a smart, robust, and agile platform? In this blog, we’ll dive into the importance and requirements of data-driven insights. If you attended the Innovation Day of 2023, the next sentence will certainly ring a bell: data is a staple in making outcome-based innovation thrive. Why? Personalized experiences and increased intelligence are key attributes in this kind of innovation, and you can’t personalize without acquiring user insights. Let’s dive into the transformative process together!
Bypassing persistent obstacles
A wonderful example of outcome-based innovation: most medical treatments have been designed for the ‘average patient’. As a result of this ‘one-size-fits-all’ approach, treatments can be very successful for some patients but not for all. Outcome-based medicine takes into account individual differences. It gives medical professionals the resources they need to target the specific treatments of the illnesses. During the Innovation Day, we showcased how we’re helping Cochlear accelerate its innovation roadmap with outcome-based innovation.
As a manufacturer of hearing aids, it continuously aims to provide all patients with a personalized patient-centered hearing experience. How do you do this when on the one hand, there’s not enough data to start building these solutions? And on the other hand, current testing methods are very time-consuming for both patients and healthcare personnel, who are already overextended and don’t give real-time insights into the ‘normal’ experiences of hearing aid users. Stuck in the status quo, Cochlear leaped into developing its mobile research app to conduct follow-up tests from home and a system to analyze and monitor this data.
As mentioned in the beginning, outcome-based innovation allows you to go beyond small incremental innovation. But that doesn’t just ‘happen’. Before you start discussing possible product features, you need to define your goals. What’s your dream product? Your ‘North Star’ to guide you throughout the innovation process? By detailing the different use cases of your ideal product, you’re mapping the key points of your digital innovation process. Spending sufficient time on your use cases is crucial to pinpoint potential risks and powerful features, but also to align resources, customer satisfaction, and compliance with user and regulatory standards.
Bad data, bad insights
So how does this relate to data-driven insights? Well, just like in any other innovation trajectory, you first need to properly define and validate what you want to build before you start building it. The key is of course to define the data range. Innovation comes from searching for and going beyond the borders of the current frame of data. And that means opening up data to a broader real-world setting, beyond the obvious setting. Take the case of Cochlear: they want to provide all patients dealing with hearing loss, with a tailored hearing aid. However, it could only move from incremental innovation by stretching the frame of data toward real-world settings. No easy job, since every patient has different needs and wishes in different environmental settings. Which information do you need for this to work? Patient histories, environmental settings, and different lifestyles, and hearing tests in those new real-world settings, all create new data.
Yet a greater database doesn’t necessarily mean more insights. If you don’t align from the start with the information you need to provide your service, you’ll create enormous waste in your data pools. Even if you want to learn from this data, it’ll be much more complicated and time-consuming to find trends in unlabeled data (it’s glorified trash). In addition, mapping the necessary input from the start allows you to combine input and eliminate redundant information, ultimately reducing the total cost.
The path to groundbreaking innovation is paved with invaluable data. While AI and IoT form the basis of digital progress, the true differentiator lies in outcome-based innovation, as illustrated by Cochlear. A crucial takeaway from this innovation approach is the emphasis on data quality from the outset. Aligning use cases with necessary information prevents information overload and helps you avoid bad insights and unmanageable data pools. So your success will hinge on the correct use of data as the catalyst for transformative, user-centric solutions.
But wait, there’s more! In Jente’s perspective we dive deeper into the untapped potential of AI in connected devices. Want to know more about the Cochlear case? Make sure to check out our previous webinar. Curious about other insights from our Innovation Day? Dive into the insights from a product engineering or strategic thinking perspective.