It is not your imagination; the world is moving faster.
In 2013, we checked our phones an average of 33 times per day. Today, that number is closer to 46. If you are under 24 years of age, you are likely to check your phone at least 74 times per day. But it’s not just technology. Studies show that in cities, we are even walking 10% faster than we did a decade ago.
When you pair this acceleration in the “speed-of-life” with an increase in connectivity and the amount of information available, interesting things begin to happen. With 3 billion people connected over the Internet, new behaviors emerge at an astounding rate and spread farther and faster than ever before.
All of this — the increase in speed, connectivity, and data availability — results in more complexity. A lot more. And that’s only taking the human factor into consideration.
As the Internet of Things (IoT) begins connecting more and more machines over the web, complexity goes up exponentially. It’s estimated the Internet will connect 50 billion machines by the year 2020. That’s a lot of new information coming online in a very short time.
As data flows begin to make deeper connections with objects, we are going to see disruption and spontaneous restructuring across entire industries, similar to what happened when digital technologies were first applied to music, shopping, and media.
It is at this intersection — the nexus of the virtual and physical worlds — that meaningful transformation begins.
The Transformation Equation: Data + Feedback = New Behavior
With more physical machines sharing data digitally, the first thing to emerge from the noise is insight. But gathering new insight is only part of the story. To engage in meaningful transformation, you must also run these new insights through feedback loops and prepare your industrial organization for the emergence of new, unexpected opportunities.
Take Waze, for example. Its intended purpose was to provide efficient routing recommendations based on user-generated data collected and analyzed in real time. But with the data of 50 million users at its disposal, the app is now helping cities optimize traffic flows and signal cycles. Waze has gone from being a commuter-focused app to a critical infrastructure management service simply by allowing data and feedback to drive behavior.
That’s why data from machines matters so much. When data-driven insights are combined with real-world feedback, the system that emerges is often greater than the sum of its parts. When you take a step back and look at the larger implications of this, it’s plain to see that what emerges from this process can be very disruptive. But it is in this emergence and the resulting disruption that opportunity is found.
The challenge for industrial organizations is to remain open, agile, and adaptive. Even if the new directions that emerge from this process are not fully formed, be careful not to dismiss them as too insignificant. Or worse, too crazy.
Welcome to the Emergent Era
The machines and infrastructure systems that support major industries are capable of so much more than their intended purpose. Today, these machines are becoming engines of innovation poised to deliver increasingly inventive solutions as data loops accelerate and the time between data collection and meaningful action gets shorter.
This paradigm shift signals the approach of an entirely new era: The Emergent Era.
Now we must accept that the old ways are going away and our new path forward may not yet be fully realized. To many, this may seem uncomfortable and chaotic, but it’s happening more often and in nearly every industry.
The concept of emergence explains how complexity can arise from simple rules, and how order can sometimes emerge from chaos. Take ants for example. Each individual ant can’t know what the rest of the colony is doing. But by individually processing their local environment and sharing what they learn — data, essentially — they collectively execute large, complex projects like anthills.
That is the promise of the Emergent Era: when a multitude of individuals pursue simple motives and exchange information in real time, new largescale patterns of organization emerge.
In major markets and in anthills alike, this is an example of what the late economist Thomas Schelling calls “macrobehavior originating from micromotives.”
The key is this: true transformation happens when we collectively and spontaneously reorganize around digital information flows. As more human and machine activity funnels through digital systems, those systems will change according to emergent principles. In essence, the collective micromotives of five 5 connected humans and 50 billion soon-to-be connected machines will grow new macrostructures. In the Emergent Era, every area of activity will be subject to many possibilities in the futures, each represented by a new discovery, a new invention, or new business models that has yet to surface.
But emerge, they will. Maybe all at once. The Emergent Era is coming, and it stands to change everything we know — instantly and spontaneously.
Part two of this blog series will discuss the nature of emergent change and the steps you can take to prepare yourself and your organization for life in this new Emergent Era.