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As organizations take early steps to implement the Internet of Things, they run the risk of being overwhelmed by data and possibilities. But there are clearheaded ways to gain momentum and achieve measurable results now.

Like a wildfire racing across a dry prairie, the Internet of Things (IoT) is expanding rapidly and relentlessly. Vehicles, machine tools, streetlights, wearables, wind turbines, and a seemingly infinite number of other devices are being embedded with software, sensors, and connectivity at breakneck speed. Gartner forecasts that 6.4 billion connected things will be in use worldwide in 2016, up 30 percent from 2015, and that the number will reach 20.8 billion by 2020. In 2016, 5.5 million new things will be connected to network infrastructure each day.

As IoT grows, so do the volumes of data it generates. Globally, the data created by IoT devices in 2019 will be 269 times greater than the data being transmitted to data centers from end-user devices and 49 times higher than total data center traffic.¹

Even as businesses, government agencies, and other pioneering organizations take initial steps to implement IoT’s component parts—sensors, devices, software, connectivity—they run the risk of being overwhelmed by the sheer magnitude of the digital data generated by connected devices. Many will focus narrowly on passive monitoring of operational areas that have been historically “off the grid” or visible only through aggregated, batch-driven glimpses.

But to fully explore IoT’s potential, companies should think big, start small, and then scale fast.

Most enterprises already have islands of existing data from their manufacturing machinery, control systems, and IT software. We call these dormant components “brownfields,” places where new development is designed and implemented considering systems already in place: sensors, structures, and services. Connecting brownfield components helps companies leapfrog some implementation steps and gives their IoT initiatives a boost. In contrast, undeveloped “greenfields”—i.e., enterprise environments with no pre-existing IoT infrastructure—require “clean sheet of paper” thinking, installing new sensors, systems, and services, as well as incorporating new data.

The value that IoT brings lies in the information it creates. It has powerful potential for boosting analytics efforts. Strategically deployed, analytics can help organizations translate IoT’s digital data into meaningful insights that can be used to develop new products, offerings, and business models. IoT can provide a line of sight into the world outside company walls, and help strategists and decision-makers understand their customers, products, and markets more clearly. And IoT can drive so much more—including opportunities to integrate and automate business processes in ways never before possible.

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Sensing and sensibility

With so few detailed use cases, the sheer number of IoT possibilities makes it difficult to scope initiatives properly and achieve momentum. Many are finding that IoT cannot be the Internet of everything. As such, organizations are increasingly approaching IoT as the Internet of some things, purposefully bounded for deliberate intent and outcomes, and focused on specific, actionable business processes, functions, and domains.

Where do you start?

Think Big

Ideate. Analyze the big ideas and use cases in your industry. Move beyond sensing to doing. Also, explore opportunities for achieving greater consumer and human impact with IoT.

Start Small

Take stock. Before investing in new equipment, conduct an inventory of all the sensors and connected devices already on your balance sheet. Find your brownfields. How many sit dormant—either deactivated or pumping out potentially valuable information into the existential equivalent of /dev/null?

Get to know the data you already have. Many organizations have troves of raw data they’ve never leveraged. By working with data scientists to analyze these assets before embarking on IoT initiatives, companies can better understand their data’s current value, and selectively install sensors to plug data gaps.

Pilot your ecosystem. Pick proven IoT partners to quickly pilot ideas, try new things, and learn from failures. Many aspects of IoT cannot be tested or proven in laboratories but only with real enterprise users and outside customers.

Get into the weeds. At some point, IoT initiatives require low-level expertise around the underlying sensors, connectivity, embedded components, and ambient services required to drive orchestration, signal detection, and distributed rules. The difference between a provocative “proof of concept” and a fully baked offering lies in a host of nuanced details: understanding the precision and variability of underlying sensing capabilities; MEMS sourcing, pricing, and installation; and wireless or cellular characteristics, among others. To fill knowledge gaps in the short term, some organizations leverage talent and skill sets from other parts of the IT ecosystem.

Scale Fast

Adapt an Agile approach. Go to market and iterate often. One benefit of all the investment being made in and around IoT is that the underlying technology is continually improving as existing products evolve and new categories emerge. As you explore possible IoT strategies and use cases, consider using lightweight prototypes and rapid experimentation. This way, you can factor in feasibility concerns, but you won’t be saddled—at least for the time being—with the burden of enterprise constraints. As compelling ideas gain momentum, you can then shape your solution, refine the business case, and explore it at scale.

Enhance your talent model. Just as aircraft manufacturers hire aeronautical engineers to design products and software vendors employ legions of coders with specific skills, so too must companies pursuing IoT strategies hire the right people for the job. Does your IT organization currently include talent with the hardware expertise needed to operate and maintain thousands of connected devices? Most don’t. Before pursuing an IoT strategy, consider enhancing your talent model not only to bring in new skills from the outside, but also to retrain current employees.

Bring it home. Remotely deployed assets and equipment often have starring roles in IoT use cases. But call centers, manufacturing floors, and corporate offices also offer considerable IoT potential. Consider how creating an “intranet of things” might lead to improved workplace conditions and enhanced comfort and safety at individual work stations. Moreover, how might reimagining employee experiences in this way help your company attract new employees and retain existing ones?

The sheer scope of IoT carries countless implications for business, both finite and abstract. To sidestep such distractions, focus on solving real business problems by creating bounded business scenarios with deliberate, measurable value. Look for hidden value in your brownfields. Move from strategy to prototyping as quickly as possible. Only real data, actual users, and sensors that respond with actions can demonstrate the remarkable value proposition of IoT.

—by Andy Daecher, principal, Technology Strategy & Architecture, and Robert Schmid, Chief IoT Technologist, Deloitte Consulting LLP