In the move from bits to atoms, people will be the glue.
“Complexity is cheap now,” says Ted Hall, CEO of ShopBot Tools, which designs and manufactures digital fabrication tools priced for individuals and smaller manufacturing shops. “And quality is almost free.”
Indeed, big shifts are happening in how things get made and where value is created. And digital technologies aren’t just impacting production and manufacturing; they’re changing the physical world.
Our physical world is now technology-enabled by the digitization of everything from books to movies to tools—such as the flashlights, cameras, calculators, day planners, music players, and bus schedules that now reside on our smartphones. The Internet and digital technology is most powerful when it is married back into our physical world; when atoms and bytes converge. This intersection also happens to be the source of greatest potential for the Internet of Things (IoT).
For the past several years, we’ve heard and talked a lot about how smart things are getting smarter through Moore’s law and the exponential advances in core digital components. We’ve seen two decades of significant disruption of industries, led by music and publishing. Virtual seemed to be the endpoint. But bits and bytes aren’t the end goal; they are just the means to better discover, use, or manipulate the physical environment.
Embedded within those smart advances is the opportunity to make dumb things, physical things, smarter. Smart technology is being harnessed in technologies such as 3D printing, biosynthetics, and gene sequencing and is enabling a range of new companies and trends, including both Uber and the Maker Movement.
We already see the effects of digital tech on the effective utilization of physical assets—whether they’re owned by individuals or companies. This efficiency may be achieved in a number of ways, like improving “up-time” for a costly machine that has become self-correcting, or by renting out excess capacity to external parties to generate new revenue streams.
Digital technology can locate a car and deliver it to our feet when we need a ride. It matches a spare bed looking for income with an individual in need of a place to stay. It lets us find and modify a design rather than create one and then lets us use a manufacturing-grade tool to execute the design, with limited skill or invested time. The pavement we drive on becomes smarter with sensors that communicate traffic information; heavy earth-moving equipment becomes smarter when sensors monitor tire wear to reduce the risk of down-time. Smart materials can collect and conduct information for the clothing a runner wears or the pipe that water flows through. All of these examples require a degree of human intervention to make them useful, and the next step has seemed to be eliminating the human intervention.
Tech-enabled physical objects are starting to be able to adapt or take action automatically. Think of the anti-skid technology or collision-avoidance features in a car, a set of components communicating with each other and taking action as a result. That type of real-time adjustment and feedback that eliminates or reduces the need for human intervention has begun to extend into larger systems, like wind turbines and complex machinery interacting within a processing plant.
Self-correction and automated load adjustment increases efficiency. That’s good, but we believe there will be far more value unlocked when that information can be fed back to humans for pattern analysis and systemic intervention. Consider exceptions—those one-off shipping requests or customer events that don’t fit into standard processes and consume inordinate amounts of a worker’s time. Over time, information from dumb objects could provide a picture of how and when expensive exceptions occur, revealing patterns that lead to insights. Then, rather than just figuring out a more efficient way to respond to each exception, companies can rethink the process or system to eliminate the causes of exceptions.
The goal is to pull all of the data back into a human sphere where people can add value. We haven’t yet seen good examples of this, but imagine a beverage company that faces fairly frequent stock-outs that cause customer dissatisfaction and lost sales. A year’s worth of data shows that the stock-outs typically occur in conjunction with local and hyper-local events. Now the company has the opportunity not only to track and respond to stock-out situations faster, but to program the inventory-replenishment system to cross-check with event calendars, weather reports, and Twitter feeds to prepare. Companies’ skills in tapping use data will determine the data’s value, but the potential is greater than just cost efficiencies.
This intersection of bits and atoms fed back to humans is of particular interest to anyone trying to create value within the IoT. When we start to integrate bits and atoms, we create an avalanche of data. The challenge and opportunity for those interested in the IoT is going to be finding the best way to analyze that data and create new value and insights from the collision of disparate data.
The movement from atoms to bits and back to atoms creates a paradox. It creates a temptation to throw in with one or the other: It is a world of atoms; It is a world of bits! Resist the temptation to focus on one or the other. Rather it is where bits collide with atoms that real value and opportunity will be found.
John Hagel III, director at Deloitte Consulting LLP, is the co-chairman of the Deloitte Center for the Edge, based in Silicon Valley. John Seely Brown is the independent co-chairman of the Deloitte Center for the Edge.