What can Manufacturing Made Smarter innovators learn from Everett Rogers?
How Innovators can use diffusion models when framing innovative ideas
Do you want your manufacturing tech to change the world? Do you also want lots of great customers?
We talk about barriers to adoption of tech, but what can the innovators do to eliminate the barriers?
We want to help you make manufacturing smarter through digital innovation; we are building a vibrant, cohesive and growing community of industrial digital technology providers, developers and users. Here is one model you could consider to maximise innovation adoption.
Everett Rogers, in his book Diffusion of Innovations, presents evidence-based models for you to frame your own ideas. If you are familiar with the bell curve of adopters divided into Innovators, Early Adopters, Early Majority, Late Majority and Laggards, then you’ve come across his work. Diffusion is all about the next group on this curve adopting the innovation. Rogers defines five key attributes that determine the uptake of new technology: Relative Advantage, Compatibility, Complexity, Trialability and Observability.
Is it a game changer?
Relative advantage is easily understood but easily over-rated by the enthusiastic innovator. This is why you have to test ideas with the right users and quantify the benefits. For most technologies, the adopter wants a significant step in function or features. Game changing innovations therefore diffuse more quickly. A word of caution, if your claims are implausible you won’t be taken seriously – it’s a bit of a tightrope. Real-time data-driven dashboards give a significant advantage over manual data collection and preparation of charts in excel. Automating repetitive pick and place tasks with a robot can easily improve speed, accuracy and reduce operating cost.
How well will it fit?
Consider compatibility with society, values and beliefs, with previous ideas, with the needs of the user, with other technologies. Technologies that are compatible with existing systems, such as PLMs or ERP systems can be appealing. Add-ons that don’t require you to stop using the old system also feel easier than starting over. Is the technology compatible with the brand? A company famous for hand-made goods might not find robotic assembly compatible with their ethos, but the same company might adopt a technology to automate the packaging process.
Is it complicated?
Complexity varies by interest, but nobody can be into everything, so intuitive is good. Are you targeting other IT professionals or perhaps, mechanical engineers? How close to plug and play will your offer be? Do you need a computer science degree to understand the installation? Do you need customisation or configuration? Can that be done in house or will customers have to rely on a specialist? Some IoT monitoring solutions can be independent of existing systems, whereas others require installation into the existing control system. Some robots can be easily taught, whereas others have to be programmed.
Can I play with it first?
Trialability in a sense of, can I try before I buy? Lots of consumer software has a demo version to play with, but is that possible in manufacturing? Can your development strategy include an easy to use, cut down version that users can experiment with? Also, trialability in a sense of, can I start small and build my confidence? Additive Manufacturing lends itself to trials. You can get someone else to print your designs, you can start with in-factory parts to build expertise and confidence before you try to make customer parts. You can start out in plastic and graduate to metals once you are satisfied with your results.
Can we see it?
Observability is a big one. You need people to know about your innovation. The first step in the adoption decision process is knowledge. If your innovation can be observed by people before they adopt, they can start to acquire knowledge and be persuaded of its benefit. So, how do you maximise observability? Can your branding be visible on outputs? Could the advantage you deliver be communicated to other customers? What would an ‘intel-inside’ approach add to your visibility? Innovators and Early Adopter often like people to see their early adoption; can they become ambassadors for your innovation? Big tech advertise their role in other company’s success, for example Microsoft uses adverts about Renault F1.
“Addressing these attributes cuts right across the innovation team from idea generation and tech development, to commercial and marketing. This model makes you realise diffusion into manufacturing isn’t easy. Manufacturing happens behind closed doors, with intermingled and optimised processes, interrupting that might make you unpopular! The challenge for the innovator, as set out by Rogers, is to take account of these insights to maximise every possible way in which the innovation can be more easily adopted. The ultimate goal is an innovation that sells itself.”
Kevin Hallas, KTN Manufacturing Team
We are keen to hear your examples of addressing the attributes in your innovations. What are you doing well? What barriers do you still need to work on? Perhaps we can help you to find creative solutions? Share your thoughts with us at firstname.lastname@example.org.
Look out for our Manufacturing Made Smarter event series, starting in April 2021. This will be a chance to hear from manufacturers who have implemented digital and their tech partners, plus other tech innovators, support organisations, etc and you can connect with peers interested in this area.