IoT is a cultural shift, not a technical one
The current state of IoT is as diverse as it can get – and at the same time, this makes one thing clearer than ever: people must be at the center of its development. They must be empowered to “use” IoT in order to achieve their respective goals.
Attending this year’s (massive!) manufacturing hackathon at Bosch ConnectedExperience (#BCX17) gave me a very clear insight into where we stand in terms of the promises made by IoT leaders. These include “zero distance to user,” disruptive business models, transparency, and new sales channels.
But more importantly, it gave me a chance to test a top-to-bottom approach on modeling a sales strategy I had in mind. Being a 33/33/33 tech/business/design chameleon myself, this was an exciting journey!
The sales idea was to establish a sticker on product packaging – the “QualityDot” – that lets consumers see how their individual product scores on production metrics. OEMs would get new tools for sales by customer segmentation. For example, they could sell “B class” quality at a discount to customers who don’t care about, let’s say, a little scratch on the back of their new tablet (with the inner parts being intact). This would result in less waste, prevent grey markets, and strengthen customer confidence.
This could be the kind of idea a marketing strategist might have. They have no idea about production lanes, apps, cloud, sensors, code, but their idea might be a real winner on the market.
In an “IoT-ized” company, they are closer to a functioning prototype than one would think.
Let’s pretend for a moment that, compared to traditional technology, IoT is “just”
- the multiplication of real-world events made visible to us and
- our reactions to these events (in either the physical or virtual world)
The current IoT platforms – in the case of this hack, the Bosch IoT Suite and the GE “Predix” – support these 2 mechanisms strikingly well.
Under these edge conditions, new business opportunities are composed entirely of “soft,” non-technical components , for example:
- customer needs (known and unknown to the customer!) = market, pain points
- value proposition
- aesthetics, emotions, and others…
Of course, this kind of knowledge and competence is present in any successful, traditional company. However, the way skills and access levels are distributed across the multiple value-generating fields is very hierarchical and isolated. In other words: The innovation pools are very much segmented by categories such as technology, marketing, business models, customer service, and so on. They are not very well connected.
For our sales idea, this means that our marketing guy needs a quicker, more direct way to bring his idea to life and try it out with real customers.
This seems to be the true opportunity offered by IoT: connecting the separate pools of skills and access levels to create greater company-wide innovation potential and build something of more value:
This is where technology takes effect. IoT products from Bosch, General Electric, AWS – to name but a few – do the heavy lifting for us. With IoT gateways, application platforms, new sensors and actors, and micro-computers, they provide us with the tools to operate innovation seeding to an unprecedented extent .
People usually located far away from “the tech” get the chance to try their business ideas in small teams by implementing real prototypes (yes, without PowerPoint!). It’s kind of like a shortcut to the physical world. Conversely, people working on the hardware at the very end of the technology stack might have business ideas they want to try.
This means startup mentality at your fingertips: build fast, fail early, learn, or ship!
Great! Yeah! Woohoo! But wait, that sounds too easy…
This brings us to the actual challenge: not every business pro is a developer or has a technical background. Likewise, not every engineer has skills in marketing, user empathy, design thinking, or sales. And talented workers with interface competence are rare.
However, building interdisciplinary teams will grow the needed skills if the culture is set up right. In addition, coaching can greatly boost a person’s potential. Third, recruiting can be aligned along this shift. And fourth, I believe the platforms will become more and more accessible to untrained users over time, resulting in a shorter time to market.
Companies will also have to look for people who are not only willing to change, but are also able to drive that change. That’s because most of the time, there is huge innovation potential, but fear or an unsupportive environment is holding good ideas back.
Combine open innovation culture with accelerating, goal-supporting IoT tools, and you are on your way to creating an agile, value-generating network instead of a monolithic, slow corporate dinosaur.
My guess is that treating innovation in smaller pools will also produce more disruptive ideas . A recent article by etventure’s Philipp Depiereux, for example, shows that German companies innovate in a way that is far too conservative.
Altogether, the industry mood and direction we’re heading in sound a lot like “The golden age of management” to me.
So, now you ask yourself: Weren’t we talking about a prototype built during the BCX17? A marketing idea brought to life in only a couple of days? How did that turn out?
First off: Yes, the prototype was built – and it worked!
We had a Bosch XDK sensor connected to the PPM (Production Performance Manager). It simulated a scratch on the back cover of a tablet being recognized during production (in real life, this would be some kind of optical recognition sensor). This information was coupled with the individual data record of the product’s serial number and stored in our back-end, which was hosted on the Predix cloud. We received events from the PPM if a scratch was detected.
For the consumer side of the solution, we built an iPhone app connected to the customer back-end. When they scanned the “QualityDot” logo (it includes a QR code), users could see the production metrics of the very device they were holding in their hands:
Sure, to achieve some kind of real functionality, you have to simulate a few things, especially when you’re not connected to the actual production machines your use case’s product is being produced on. But considering how little time we had to think up a business model AND build it, the results were above and beyond what we had expected. In a real economic scenario, the time to build such a solution might take weeks instead of days – but hey, what’s that compared to months or years, or not building at all!