Digital Transformation: Quo vadis, corporate innovation management? (Part 1)

True’ Digital Transformation, i.e. Digital Transformation for growth, provides a huge opportunity for corporate innovation – but also a large number of challenges. We are exploring how corporate innovation management (Note: In this post we understand ‘corporate innovation management’ to be a corporate function and/or the management process) should move ahead.

This first part deals with new opportunities that corporate innovation management needs to seize. The next post will focus on new challenges and how corporate innovation management should engage in the transformation process.

As you may have noticed HERE we have started a peer group process ‘Digital Transformation for growth in Process Industries’. Our first step was to cut through the buzz that is surrounding ‘Digital Transformation’ (DT). We saw that there are two sides.

Digital Transformation for optimizing

There is one side, in which Digital tools such as

  • Big Data / Smart Data analytics,
  • Cloud,
  • Internet Of Things including Additive Manufacturing,
  • Mobile including Augmented Reality,
  • Artificial Intelligence incl. Machine Learning,
  • etc.

are deployed for ‘improving what is there’, i.e. optimizing existing business models and functions. In this side of DT, lighthouse projects can be put under headlines such as

  • operational excellence (e.g. smart plants / Industry 4.0 which use predictive maintenance and remote controlling, smart supply chains. etc.),
  • increasing management capabilities via real-time insights into KPIs,
  • improving customer insights from CRM and other data (customer segmentation, journeys, etc.) and
  • improving the predictability of future business

There is a tremendous business value in these areas. However, from a ‘transformation’ point of view, this is the easier part. In many instances, deploying state-of-the art tools is a straight-forward approach and does not imply a transformation, neither in the rigorous customer-orientation, nor in business model, the in the operating model, the corporate structures and in culture / mindset.

Digital Transformation for growth

The other side of ‘Digital Transformation’, the growth side, is much more challenging. One needs a clear view how Digital can be used to change the game and to generate innovations in customer experience, value proposition, products, processes, services and business models.

Our project experience and the discussions in our Peer Group show that success in this area is a fairly complex issue. Among others, the success factors include

  • radical re-orientation of the company towards customer experience and customer value
  • breaking down functional silos
  • re-orchestration of the interplay between ‘business’ and ‘IT’
  • establishing a ‘digital mindset’ within the company
  • make/partner/buy-decisions in the Digital journey
  • setting up structures (e.g. ‘Digital labs’) that allow for an agile work style and aligning with external ecosystem partners
  • devise and implement to attract and retain talent (e.g. Data Scientists)
  • provide new methodology (e.g. Design Thinking in ecosystem environments and how to identify and occupy pivotal points in these ecosystems)

In other words, ‘true’ Digital Transformation (as described above) changes the corporate fabric. Which implies that corporate innovation management needs to change as well.

New innovation horizons

A first deep dive shows, that ‘true’ Digital Transformation provides new innovation horizons and new opportunities that need to be addressed.
As pointed out in a recent post HERE, we have found that there are 8 pathways in ‘Digital Transformation for growth’, opening up new innovation horizons for corporate innovation management.

Extended products

In the future, physical products will be ‘extended products’ surrounded by ‘data wraps’, ‘digital halos’, ‘digital trails’ or whatever you’d like to call these digital twins. We already see this massively in Discrete Manufacturing B2B environments (with Big Data analytics and Internet Of Things (IOT), in particular in ‘Remote Monitoring’ / ‘Predictive Maintenance’ as key technologies). We see this emerging in Process Industries B2B environments as well, in which ‘product plus data trail’ will be a key driver for ‘making the company’s customers more successful‘. In both industry sectors, virtual integration via Cloud technologies will enable cross-value-chain / cross-industry scenarios.

Process Industries also see that “extended products’ will become more common in B2C environments. For instance, some Food & Beverage manufacturers are currently designing personalized, ‘transparent products’. Via individualized QR codes, consumers can check the origins of the ingredients contained and be connected with online offerings such as e.g. Facebook communities. Next generation RFIDs made from printed organic electronics enable the consumer (and also grocery retailers) to check the compliance with the cold chain.

Digital service and business model innovation

As a consequence, future ‘product innovation’ will be designed in a way that it opens up doors for service innovation and business model innovation. The Internet Of Things, for example, allows chemicals companies to add intelligence to their existing products and deliver better customer service. In addition, chemicals companies could complement their traditional pay-by-the-ton revenue model by offering value-added data services.

Many Chemical companies are in a good position. They can use years of collaboration with their customers to integrate within their customers’ operations. In the traditional approach, manufacturers advised their customers based on site visits and their understanding of materials and assets. With Digital (Cloud and Big data analytics), these companies can have direct visibility into their customers’ operations, and can provide real-time recommendations to optimize their operations.

This approach may even lead to new business models: ‘Dear customer, we promise to increase your production yield by x% – Let’s run a joint project and we share the savings.’

Smart products

In the Discrete Manufacturing sector It is almost a no-brainer to think about up-smarting products (both B2B as well as B2C). It is not quite so easy to imagine in the Process Industry, but it is emerging. Three examples may underline this statement:

  • Functional surfaces that change e.g. color depending on environmental conditions
  • 4D-Printing: The MIT has already developed materials which are 3D-printed and additionally are programmable. Programmable materials can self-assemble and change shape and form with time. External stimuli such as light, heat or water trigger expansion and contraction at different places in the material.
  • Smart clothing: A leading manufacturer of Specialty Chemicals recently developed stretchable and screen-printable electronic inks to be used for smart clothing. Textile manufacturers can use the printable ink to embed sensors on conventional fabrics. These sensor data may then be transferred to a smartphone app.

Cross-value-chain / cross-industry innovation

Last but not least, Digital will also blur established industry boundaries and allow for cross-industry plays.

In the Discrete Manufacturing space for instance, Caterpillar is a prime example. In order to ensure customer’s success, Caterpillar remotely monitors remotely the 350,000 machines its customers are using. Using Big Data analytics, Caterpillar anticipates upcoming breakdown events and advises its customers how to avoid unscheduled downtime. Going one step further, Caterpillar also shares valuable asset performance information with its customers, hence providing clients with information how to make the most out of their assets. But Caterpillar is aiming even higher. It plans to open up its ‘Analytics hub’ to third party vendors (an asset base which is 10 times larger as Caterpillar’s).

This kind of cross-x platform innovation plays are also emerging in the Process Industries:

  • Agrochemicals companies for example are teaming up with companies producing harvesters and other agricultural machinery to create a ‘agricultural cloud’ which would allow for ‘precision farming’ – Predicting exactly when to sow, when to fertilize and when to reap.
  • Another example is currently underway in the functional food space, in which health insurers, online retailers and food ingredient manufacturers are planning a cross-industry business model innovation aiming at providing discounts for health insurance customers who consume specifically prescribed nutritional supplements.

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