Thursday, May 09, 2019

Digital Innovation meets As a service

For a while now I've been considering the impact of all the emerging digital transformation tools on innovation.  Artificial intelligence, machine learning, IoT, blockchain and a host of other technologies will have a bit impact on how corporations conduct work and create new insights and new products and services.  However, I'm increasingly of the opinion that we are guilty of focusing on the technology and ignoring the real benefit of these technologies and other IT-influenced changes, and what customers really want.  As these technologies are implemented, the real benefit will be the data they generate and companies will have to confront the question - how do we gather, use and most importantly, monetize all of the data?  And this, I think, is where the real impact on innovation will be felt.

Two converging themes

There are two really interesting and potentially impactful converging themes in innovation, both of them led ultimately by the increasing power of information technology and ubiquitous connectivity.  The first is digital transformation - the ability to both generate vast amounts of data from sensors and IoT devices, as well as to manage the data and make sense of it using other technologies like Artificial Intelligence, Machine learning or predictive analytics.  The second is the increasing demand for solutions, not products.  I think increasingly people will want to acquire solutions "as a service" or will be happy to share data about device usage in order to receive a less expensive product. 

Companies can provide products "as a service" by changing value propositions and business models, and can further lower the cost of the service by collecting and monetizing the data generated by usage or by pushing other offers to the user of the device.  An entire generation is entering the workforce that grew up with Facebook and Google, so these data exchange models are well understood and already accepted.  The big challenge is for "as a service" solutions to move from the purely digital world (search, social networks) to physical products.  In some senses the shift has occurred for larger capital goods like aircraft engines.  GE doesn't sell the engines, they sell flight hours of operation.  Michelin has a "tires as a service" offering, which is where this really becomes interesting, because tires are a consumable commodity.  If we reach the point where consumables can be offered "as a service" then almost any physical product can be offered as a service, which will have to be supported by new business models.  Further, many of the "as a service" models will be funded to some extent by data, either harvested from the device or information pushed to the device.

Why a new "whole solution" emerges

If these ideas above are true, they have significant impact on innovation and how it is conducted today.  In the past, Geoffrey Moore created the idea of the "whole product" to cross the adoption chasm.  If the arguments above are true, we need to consider a new "whole solution" model to compete in the digital innovation economy, where the value proposition of the physical product shrinks but is augmented by value from the data that surrounds it, the customer experience that empowers it, new business models that sustain it and ecosystem partners who fulfill the promise.

Yes, companies that make physical products will continue to make physical products, but increasingly they'll find that customers expect a more holistic "whole solution" which will incorporate data (from the digital transformation application).  That data may originate from sensors on the product, from a bluetooth connection between the product and the smart phone or device the owner possesses, or eventually from ubiquitous 5G, which just creates a virtual network between any internet enabled device anywhere.

Customer experience
Beyond the physical product and the data that enables, surrounds or funds it, the customer experience will need to change.  In the Michelin example, tires as a service indicates that my experience expectations are actually higher than if I manage the tires myself, because my expectation is that Michelin has experts on staff ready to identify any issue, and who can guarantee that I get the most value and longest life from my tires.  In this example my expected experience is that I do nothing and simultaneously get more, which means my experience expectations are vastly increased.

Business Models
Finally, those products, data and experiences will come wrapped in a different business model - or, more likely two or three different business models.  Again, Michelin is a great example.  Michelin still sells tires to consumers without any support or "as a service" offering, as well as providing an "as a service" offer.  The revenue models, service models, pricing, support and warranty options for these two delivery models are significantly different, and any company that embarks on an "as a service" offer will encounter those who prefer to acquire and own a device or product, and those who are happy to use it as a service, so multiple business models will be required.

The challenge for innovators

I'll submit that the converging factors - increased data generation and management, and increasing expectations of products as service - are here and will continue to converge.  This means that innovators must decide how and when to include data as a component of the offering, and how to shape and ensure customer experience and be prepared to offer multiple, concurrent business models based on the same product.  In other words, are innovators ready to vastly accelerate innovation thinking and options, and work well beyond the innovation requirements of the physical product to include data, customer experience, business models and other factors?

If not, what will it take to develop the innovation teams and skills in order to compete in this market?  The impact to innovation is real and cannot be denied.  Can you and your team rethink and revise how you innovate?  If you need help, we can help think through not only the core product, but how and where data is important, the customer experiences expected by consumers and the requisite business models, as well as critical ecosystem partners.

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posted by Jeffrey Phillips at 6:39 AM


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