Mastering the “upstream” process to exploit IoT data as a natural resource

When we discuss data as a natural resource, we usually focus on what the classical natural resource industries call the downstream processes: how to extract value from the data. Discussions with device manufacturers looking to use data from connected devices to drive revenue growth and a transition to service business models show that pervasive problems in the upstream processes must be solved first: how to obtain the data in an economical way. The functional diversity of a manufacturer’s product lines adds even more complexity.

A close look at the problems shows that adding connectivity to consumer devices deeply affects every business process at a manufacturer:

·   The manufacturers must define a common architecture for a range of device types with diverse functions and cost points. And they need to define a common connectivity and back-end architecture. 

·   Connectivity implies new regulatory requirements for device design and consumer communication.

·   For each device type, connectivity creates new functions beyond standard hardware features. This requires new testing and quality assurance processes. The new, still uncertain usage patterns must be integrated into a common user interface.   

·   The manufacturers must align the roll-out across multiple product lines and organizations with potentially different hardware and software architectures, often acquired through acquisition. They have to coordinated timelines for design, manufacture, and go to market. 

·   The new electronic parts needed may require establishing new supplier relationships.

·   The correct software – version, language, target market - must be flashed onto devices without slowing logistics, and the appropriate back-ends must be enabled in a timely manner.

·   Aftermarket software updates might be needed. How can they be handled technically and with consumer communication?

·   The best way to communicate the benefits to the channels and to consumers must be determined.

·   Marketing must allocate scarce budgets and real estate to the new features for which consumer interest still has to be generated.

·   Retailers and installers must be motivated to promote, implement, and support the connectivity.  

·   Consumers must be motivated to connect their appliances, and continually use new functions to generate a data flow.

·   The costs and benefits, both of which are still uncertain, must be allocated across diverse organizations and business processes.

·   And with all this, the manufacturers have to find ways to make money!  

As we can see, connectivity for consumer devices creates a totally new meaning of digital transformation! At first sight, these problems appear to be daunting. However, there are proven practices to conquer them. A holistic, detailed analysis of the entire device life cycle, from design to manufacture, market, sell and service will surface the obstacles, costs, and opportunities.

The IBM Garage methodology provides a unique framework that facilitates a clear understanding of the desired business capabilities, and ability to derive the IT, product and service capabilities required to reach the business goals. Joint cross-disciplinary teams find the starting points with the greatest leverage. Starting small, they implement early function points, using rapid feedback cycles to learn, and expand towards full scale enterprise solutions. IBM labs around the world, from Munich to Dallas, Singapore and Tokyo, combine the technical and business capabilities to lead enterprises on their digital transformation to explore the natural resource of IoT data.