Theo Priestley tackled the excessive hype around the “things” part of the Internet of Things (IoT) today with his piece, “Everything is Connected in the Internet of Things.” Priestley very accurately says that the emphasis of what’s coming shouldn’t be on the “Things” or the “Internet” but instead on the data that will be generated (and, I would argue, consumed).
It’s The Decisions
Taking the argument one step further, even the data that gets generated and consumed by an Internet that has an enormous number of connected devices (“things”) is of limited value by itself. The real power of the Internet of Things is the analytics that can be performed on a much broader and more immediate set of information, the more meaningful patterns that are then anticipated and identified as they occur, and the complex set of actions (and actions upon actions) that are taken because so many things are connected and talking to each other in the moment.
Our past method for making decisions and taking action was a recipe that called for one part human experience and one part math. Getting to a great decision was based on how much you could expect to know, what you could “crunch” and how much you could infer from relevant experiences (with a few assumptions thrown in). In the IoT world, how much you can know is exponentially higher, the assumptions much lower, and experience something found not only in humans but in systems with perfect memories.
Where To Invest
If the outcome of the IoT is far more data, we can solve the world’s problems with far more storage. But that isn’t the challenge and data storage, while a component of the solution, isn’t even close to the crux. Investment needs to be made in the logical apparatus that watches the information flowing from everywhere and to anywhere. While that information is in flight, it has remarkable value to highlight problems and opportunities that exist only for a very short period of time. Humans aren’t biologically equipped to see, understand, decide and act upon the data volumes that the IoT brings, making logical systems crucial.
These logical systems exist today in the form of machine-to-machine interfaces, complex event processing and business rules. They’ve been active in some industries but not all, and have been highly efficient in solving some of our pressing problems but not all. Organizations that have these systems in place stand to disrupt their manpower-intensive competitors for one simple reason — the Internet is becoming a network dominated by things talking to each other with far lower tolerance for human bottlenecks.
What holds us back
This is a big change and as such, there’s plenty of friction holding the IoT back. For starters, the timing of the World’s recent economic crisis was terrible for investment. Just when the technologies came together, many sectors of the economy canceled plans to modernize. Some are still in that place. Secondly, the panic over the challenge of big data took focus away from the real challenge, making real-time decisions, and put it on Hadoop and other technologies that have value for some, but not for all. Automation took a back seat to batch-processed information. We gained “amazing insights” but lost valuable time in plenty of other ways. Lastly, we live in societies that puts intentional breaks on change that affects workers and industries. There are emotional and very tangible financial reasons to take it easy and survive this latest change intact. We need to be thoughtful about disruption and avoid the potential negative unintended consequences.
With that said, the financial crisis is passing in most places and there’s an opportunity to reset priorities going forward. If we see the Internet of Things as a way to better feed Hadoop or simply as data, we’re missing the point. The real opportunity is in real-time decision making, both automated and not, and a level of efficiency that we’ve never known before. Efficiency in how we distribute water, power, food and how we design, produce, sell and service consumer goods. There are weighty implications for security and, potentially, repression and there are certainly privacy questions. All of these issues revolve around a central challenge of how well we can feed and control the decision-making processes that all of this new data and connectivity affords.