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Driving unconventional growth through the industrial Internet of Things
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Driving unconventional growth through the industrial Internet of Things

Posted by Paul DaughertyOctober 6, 2014

The Industrial Internet of Things (IIoT) is a major trend with significant implications for the global economy. It spans industries representing 62 percent of gross domestic product (GDP) among G20 nations, according to Oxford Economics, including manufacturing, mining, agriculture, oil and gas, and utilities.

Not surprisingly, the IIoT’s potential payoff is enormous. The most conservative independent estimates place spending on the IIoT worldwide at $20 billion in 2012, with spending expected to reach $500 billion by 2020. More optimistic predictions of the value created by the IIoT range as high as $15 trillion of global GDP by 2030.

Paul-Daugherty----Accenture

Paul Daugherty

So how can executives at industrial companies exploit the revenue-generating opportunities of the IIoT? Accenture’s research suggests that executives must meet three imperatives: boost revenues by increasing production and hybrid business models, fuel innovation with intelligent technologies, and transform the workforce for the IIoT. In addition, we outline how innovation is critical to developing and delivering differentiated new product-service hybrids that drive growth.

Boost revenues and production and create hybrid business models

Companies are already spending heavily on digital services to help increase production and efficiency. These product-service hybrids, by connecting intelligent physical assets capable of producing data for use in digital services, have the ability to combine product sales and leasing with recurring income streams from digital services. These services also enable firms in industries such as resource-extraction (such as mining or oil companies) and process industries (such as food or chemical manufacturers) to make better decisions, enjoy better visibility along the value chain and improve productivity.

Fuel innovation through intelligent technologies

Manufacturers soon will be building intelligence into every machine they produce and the innovative applications that accompany these smart machines will be vehicles for driving new revenue streams out of product-service hybrids. To reap the full benefits of the Industrial Internet of Things, companies must exploit sensor-driven computing, industrial analytics and intelligent machine applications and weave together enterprise and machine-generated data to create new monetisation opportunities.

Transform the workforce to cultivate new skills and talent

The Industrial Internet of Things will open up new workforce needs as it simultaneously creates redundancy in others. It will digitise certain tasks and workflow, especially repetitive jobs that, up until now, have resisted automation. We forecast that to efficiently capture these burgeoning opportunities, companies will need to look for skills in data science, software development, hardware engineering, testing, operations, marketing and sales. And they will need to expand their talent base to handle the creation of new service sectors that support these diverse users of industrial products and services while mastering new ways of working.

Driving innovation

Innovation is critical to developing and delivering differentiated new product-service hybrids that drive growth. To reap the full benefits of the IIoT, companies will need to excel at exploiting three technology capabilities: intelligent machine applications, sensor-driven computing and industrial analytics.

Intelligent machine applications

Soon, manufacturers will no longer build machines that have only mechanical functions—they will now include intelligence. For example, product and application lifecycle management tools, by addressing integration issues and ensuring cross-domain collaboration, help developers build innovative applications.

Take connected products like the Nest thermostat, which ships with a user-friendly interface that lets consumers set their preferences and understand and manage their energy consumption. If these intelligent thermostats are integrated with electric utilities through demand-response applications by the likes of C3 Energy or Opower, utilities can create incentives for consumers to reduce consumption during peak hours. This will help maintain the stability of the electric grid while encouraging consumption at times of low demand.

Also, consider SAP’s pilot with BMW’s connected vehicles. SAP sees cars as conduits for information services. Cars can receive offers from merchants as they drive nearby or receive information about available parking spots. Taking the connected vehicles concept further, we envision a scenario where drivers will no longer pay at the gas pumps and gasoline retailers will no longer have to pay credit card fees. The gas pump would recognise the car and know how many litres or gallons of gas were put in the tank. At the end of the month, the consumer would get a bill from the gasoline retailer.

Furthermore, scenarios like these need not be limited to equipment; anything can be made into an intelligent machine. Roads can be embedded with sensors that gather data on traffic and with materials that recharge electric vehicles while being driven. Recognising the latter opportunity, Qualcomm has begun licensing an electric vehicle recharging product to automakers for testing.

Sensor-driven computing

Sensors give objects the power of perception—into conditions such as temperature, pressure, voltage, motion, chemistry and usage. Sensor-driven computing converts perception into insights (using the industrial analytics described below) that operators and systems can act on. As with most technology advancements, sensors are swiftly becoming smaller, cheaper and more sophisticated.

For example, in 2007 the average cost of an accelerometer sensor was $3; in 2014, the average is 54 cents. By 2020, component costs will have come down to the point that connectivity will become a standard feature, even for processors costing less than $1.23.

Industrial analytics

Industrial analytics turns data from sensors and other sources into actionable insights. For example, GE’s latest locomotive has 250 sensors that measure 150,000 data points per minute. The end user—whether it is a machine enmeshed in a process or an individual—can use these analytics to interpret the massive streams of incoming data from the locomotive’s sensors, along with information and operational systems, to drive real-time decision making and to anticipate events.

In another example, Caterpillar has started using industrial analytics to help its dealers succeed. The company harnesses and analyses data from its machines, engines and services and transmits the resulting insights to dealers, enabling them to anticipate problems, proactively schedule maintenance and help customers manage their fleets more efficiently.

Healthcare companies are also finding opportunities to offer analytic services. Take Virtual Radiologic Corp. (vRad), a tele-radiology services company. vRad has collected data from more than 22 million X-ray, MRI and tomography readings and patient studies. Now it has launched an analytics service that benchmarks radiology equipment utilisation and results.

Getting Ready for the IIoT

The IIoT is coming on fast and its potential for disruption is enormous. Organisations should start planning now for how they will adapt to take advantage of emerging growth opportunities. They should strategise on the development of their IIoT platforms and identify new ways to create value for customers.  They can define new digital services that will be possible through product-service hybrids and prepare their sales and marketing functions to focus on promoting those new services.  While there are still some technology challenges and other hurdles to overcome, the IIoT will undoubtedly usher in a new era of industrial products and services that will be delivered by those businesses who are already looking ahead at the changing digital landscape of tomorrow.

Read more about Paul Daugherty : http://www.accenture.com/us-en/company/people/Pages/paul-daugherty.aspx

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