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The Future of Smart Connected Systems and Information Automation

…And The Decline and Fall (Hopefully) of Existing IT Empires

The convergence of networked computing and large scale data management with real-time machine intelligence is driving the integration of the physical and virtual worlds. The intersection of these trends – the Internet of Things, Data and People – should create unimagined new values. But will it?

The term “convergence” implies unification, but you wouldn’t know it from today’s rapidly evolving “Internet of Things” market—a fragmented landscape full of incomplete platforms, narrow point-solutions, and software incompatibility seemingly all based on the premise of some outsized dependency on big data and the cloud.





One company, innovation limited, who has kindly provided us with an exclusive “insider’s” view of their developments over the last three years, is anticipating a very different future. Over the many years we have known Doug Standley and his team, we have shared a common view of the potential of connected digital systems; a view focused on the need to consider “design” as much [or more] as the “technology.”

Companies need to move beyond a conventional orientation to IT technology skills, culture and behaviors. Organizations need a disciplined process focused on applying new digital enabling technologies to optimize all tangible and intangible skills and assets including people and competencies, brands and positioning, technical capabilities and intellectual property, alliances, relationships and business and operational processes.

Too many people today take it on faith that the best possible designs for the future of connected things, people, systems and information will emerge from large corporations and established authorities.   Yet, in the course of the last two decades, the world has become so dependent upon the existing ways computing is organized that most people, inside IT and out, cannot bring themselves to think about it with any critical detachment. Even in sophisticated discussions, today’s key enabling information technologies are usually viewed as utterly inevitable and unquestionable.

Artificial intelligence, machine learning and the Internet of Things are all in some way trying to break from today’s computing paradigms to enable real-world physical systems – particularly as they become more and more intelligent, get fully integrated onto networks, and the data they contain becomes an integral part of all information systems.

But even if we can make a computer capable of beating the reigning genius of chess, we can’t make a robot capable of walking across the street as well as any normal two-year-old child.  The real world is not a strictly regulated, closed system like a chess game.  Sensing a player’s moves on a wired chessboard and responding quickly and intelligently is one thing.  Sensing—and physically responding to reality – it turns out is still completely different.

IT professionals talk these days about the need for ever-evolving information services that can be made available anywhere, anytime, for any kind of information.  But would you or I recommend an IT person as the architect or integrator of real world physical systems with computing systems?  I think not.

With each additional layer of engineering and administration, computing systems come closer and closer to resembling a fantastically jury-rigged Rube Goldberg contraption. The reason is simple. Today’s computing systems were not really designed for a “real” world driven by pervasive diverse information flow.

Some things that look easy turn out to be hard. That’s part of the strange saga of the Internet of Things and its perpetual attempts to get itself off the ground. But some things that should be kept simple are allowed to get unnecessarily complex, and that’s the other part of the story.

This is where the new values of’s platform really come into focus.

The platform anticipates [IoT] developers’ and users’ toughest challenges—from interoperability and latency to database dependency and user complexity—as a group of problems that can be addressed by a single, unified, scalable software solution. In taking this approach, we believe is defining a new market meta-category that underscores the need to empower users and developers to exploit the vast potential of complex systems intelligence and information automation.’s strategy reflects a clever combination of architectural attributes and the increasing importance of three critical elements:

  • a fully configurable software platform architecture that enables peer-to-peer and client-server distribution of services;
  • a platform that can simultaneously and asynchronously act on any type of information from any device, storage or streaming source; and,
  • a platform that enables intelligent and real-time temporal, spatial and state-based contextual processing.

Demand for these types of capabilities is hardly new, but as they converge, radical new modes of value creation are emerging.  These technologies need to be interwoven and mutually supportive; success will only go to players who effectively leverage their combined potential.

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