IoT And Connected Assets

Ken Pierce

The Internet of Things (IoT) involves connected products, assets, fleets, infrastructures, markets, and people. In this series of blogs, we’ll address each of these connected aspects in turn.

IoT promises to revolutionize the operation and maintenance of high-value, long-life equipment such as industrial machinery. The operators of these assets can use IoT data to optimize performance, uptime, costs, and business processes. The manufacturers and providers of service for these assets can use IoT data to optimize design, functionality, customer service, and business models.

But IoT data has remained separated from the context of business information and processes. For example, sensor data might tell you that an asset is operating outside its specifications. So you watch the asset for a period of time. If it seems like there has been an impact on production output, you send out a technician to inspect the asset. The technician estimates that the asset should be fixed and manually submits a request to maintenance. Maintenance creates a work order and procures a spare part. When the part comes in, the asset is scheduled for repair.

In the meantime, the asset fails, and production grinds to a halt.

But there’s a better way. In the past we worked to integrate the shop floor with the top floor. Now we need to integrate operational technology (OT) with information technology (IT). By capturing sensor data and combining it with other business data in real time, asset operators can achieve predictive maintenance and automated procurement of parts and dispatch of service. At the same time, manufacturers and service providers can continuously improve asset quality and even create new, more effective assets.

Three dimensions of IoT data

To achieve these outcomes, OT-IT integration needs to occur across three dimensions:

Fixed-asset insights: Companies must move from a reactive to a proactive approach to maintenance. They can achieve this through an integrated asset network that enables collaboration among manufacturers, service providers, and end customers. Fixed-asset insights let you achieve predictive maintenance and service, from identifying emerging problems early to automating parts procurement and maintenance scheduling. These capabilities can serve assets that are owned and operated by a company, as well as those that are installed at a customer site and covered by a service contract.

Manufacturing execution: Manufacturers need to gain real-time visibility across plants, suppliers, and machines. They can do this by connecting manufacturing IoT data within the business context of orders, quality, and performance. They can further connect IoT data with supply chain networks. The result is more flexible, scalable, cost-efficient, and tightly controlled manufacturing.

Manufacturing networks: Manufacturers need to identify and resolve problems across the supply chain to manage product introductions and changes, share process improvements, and improve on-time delivery. They can achieve this by combining IoT data with a collaborative B2B network. Among other advantages, they’ll be able to identify hidden production capacity and rapidly and cost-effectively scale production to respond to market demand.

IoT data, the new oil

Data in the 21st century has been compared to oil in the 19th century: a vast, valuable, and still largely untapped resource.

Some energy companies are taking that metaphor literally and realizing transformational results from integrating OT and IT. In one case, an energy company that operates numerous large gas turbines across several plants noted that 13 of those turbines needed constant maintenance. By linking data across plants, the company realized that the 13 turbines were all made by the same vendor. The new visibility can help it reduce costs for service and increase uptime. It also gives the company new options – for example, replacing the assets with turbines from another vendor or working with the original vendor to make design improvements.

Another energy company that has more than 70 plants worldwide discovered that the operational costs for its Malaysia plant are four times as much as expected compared to other plants. Integration of real-time IoT data with business data is helping the company home in on potential causes such as faulty equipment, over-maintenance, or culturally influenced approaches to plant operation.

IoT provided the data. Integration with business context delivered the insights. The good news is that the technologies and capabilities now exist to achieve this integration.

Effective IoT connectedness requires a unifying foundation. SAP has addressed this need by introducing SAP Leonardo Internet of Things portfolio, innovative solutions designed to help organizations digitally transform existing processes and evolve to new digital models. Learn more by reading about real-world use cases, visiting sap.com/iot, attending our flagship event Leonardo Live this July 11–12 in Frankfurt, and following us on Twitter at @SAPLeonardo.

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Ken Pierce

About Ken Pierce

Ken Pierce is the global leader of the Internet of Things (IoT) for the Energy and Natural Resources Sector (which includes oil and gas, chemicals, utilities, mill products, and mining) at SAP. He helps customers define their IoT and digital transformation strategy, bringing to the table over 25 years of experience serving as a trusted advisor to business and IT executives. Ken focuses on understanding their challenges, establishing a solution vision, and building compelling value propositions that produce business results.

Why The IoT Means You'll Never Run Out Of Paper

Alfred Becker

In business, efficiency is critical. Any improvement to a standing process – even if relatively small – can have a profound impact when scaled up. Consider, for example, software that allows a train to travel more efficiently. While cutting a minute or two from a trip may not seem that significant, when those fuel savings are scaled up over thousands of trips, it becomes a serious cost savings.

The Internet of Things (IoT) has had a transformational effect on industries seeking to make their processes easier and more efficient. By leveraging the power of connected devices and data analysis, companies and governments are figuring out new ways to modernize established processes. Cities use IoT technology to reduce traffic congestion and pollution. Farmers use connected devices to improve crop yields. Railways use IoT technology to enhance safety and timeliness.

And companies can use it to ensure they never run out of paper supply.

How the IoT can keep paper supplies fully stocked

The applications of IoT technology are so varied as to seem almost unlimited. Companies are discovering ways, large and small, to increase productivity and efficiency through the use of data-based sensors and other devices.

Consider the case of paper companies and printer producers. The two have what should be a naturally synergistic relationship. Each produces half the equipment in a common office device. Yet, historically, paper companies and printer producers haven’t necessarily worked together. A business purchases its printers and paper from separate suppliers. Paper is restocked either through an ordering process initiated once paper stock runs low, or though a planning process that automatically orders paper through electronic data interchange (EDI). Both approaches are based on planned paper consumption, not real-world use, which often is different. In addition, there is always a time lag, even using the planning approach, between paper order and receipt.

It’s easy to see the inefficiency in this process. Waiting for the printer’s “load more paper” light to start flashing is a reactive move. It’s also inefficient, as it all but ensures printers regularly run out of paper, forcing workers to wait while paper is resupplied or go to another location.

Now consider an even larger problem for companies that require a variety of specific paper types in order to operate. If an error during the inventory process results in one paper type running out, the company’s productivity slows and costs rise while it waits for delivery.

Fortunately, this is a scenario that no longer needs to occur, thanks to IoT-driven process improvements. Paper companies and printer producers can collaborate to ensure paper supplies remain constant. Sensors can transmit data from printers to paper companies, showing the precise type of paper being used and predicting when it will need to be replenished. This real-time data can be integrated into the planning process – ideally using the print shop’s production planning software – and order paper automatically via EDI based on actual consumption.

This ensures there are no gaps in supply, no halt to productivity. The predictive power of IoT technology helps printer and paper companies collaborate in an efficient manner that benefits all parties: Businesses are guaranteed the timely replenishment of paper inventory. Printer and paper companies benefit from the synergies facilitated by the IoT. Print shops can offer customers the option to automatically stock paper as a value-added service, requiring no action from the customer.

The end result? Greater productivity, higher efficiency, enhanced collaboration, and new business opportunities.

The awesome growth potential of connected devices

Ensuring continuous access to paper is just one small example of the transformational power of IoT technology. Opportunities such as these can be found in virtually every industry. The way we work, live, travel, and take care of our health and our homes can all be improved through the use of smart, connected devices.

The most exciting thing? We’re only seeing the tip of the iceberg. Because IoT technology is relatively young, even more revolutionary opportunities are likely to develop. According to Gartner, roughly 8.4 billion connected devices will be in use in 2017. This represents a 31% jump over 2016. Business spending represents slightly less than 60% of the overall market.

By 2020, overall IoT spending is expected to reach nearly $1.3 billion. This rapid growth will be driven in part by increasing adoption in the manufacturing, retail, healthcare, and transportation sectors. Cross-industry IoT spending, featuring use cases relevant to all industries (think smart buildings), will also be a significant growth driver.

The takeaway

Ultimately, IoT technology holds not only the promise of sustained innovation and business transformation, but profound changes to the way we live and work. Having printers that never run out of paper is but one example of the almost countless number of opportunities that will arise as IoT technology matures.

Learn how to bring new technologies and services together to power digital transformation by downloading The IoT Imperative for Energy and Natural Resource Companies. Explore how to bring Industry 4.0 insights into your business today by reading Industry 4.0: What’s Next?

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Alfred Becker

About Alfred Becker

Alfred Becker is the global lead for Paper & Packaging Industry
and Manufacturing within Mill Products Industries at SAP.

Building An IoT Foundation For The Future

Tanja Rueckert

Part 3 of the “Manufacturing Value from IoT” series

In my last blog, I talked about characteristics of manufacturing IoT innovators that help them outperform others in the industry. Here, I will talk about the short-term and long-term investments your company needs to bring your IoT transformation to fruition.

Interest in the Internet of Things (IoT) among manufacturers has reached a fever pitch. Executives in every sector recognize opportunities to improve quality, speed, security, and costs by applying smart devices to operations and plant processes.

Unfortunately, hoping for IoT benefits isn’t enough to achieve IoT success – especially when a company doesn’t have the network infrastructure and information technology (IT) to deploy IoT solutions. Yet many executives simply don’t realize how complicated and far-reaching an IoT transformation will be.

  • Vision, strategy, and leadership: An IoT deployment will link many functions and fiefdoms within an organization; to make sure that connection leads to collaboration, senior executives must offer strategic guidance and commitment. That’s a problem at most companies, because only 11% of manufacturers have implemented an IoT strategy for operations. Even worse, 10% of manufacturing executives “don’t know” who leads their company’s IoT strategy. It’s no wonder that the biggest IoT challenge in operations is “identifying opportunities/benefits of IoT” (44% of manufacturers).
  • Skills and experience: Industries as diverse as consumer goods, chemical processing, and textile milling can leverage the IoT – if they have the smarts to do so. The IoT requires new skillsets within plants and among suppliers. The ability to incorporate high-tech electronics into products – including commodities such as concrete, fabrics, rubber, etc. – will be new to most manufacturers. More than a third of manufacturers report that skills/talent to leverage data/intelligence is an IoT operations challenge.
  • Network capabilities and capacities: Antiquated technology is the biggest IoT headache that manufacturers encounter in capturing, communicating, and leveraging data from operations. Only 10% have network infrastructures capable of machine-to-machine communications, and just 13% have networks capable of machine-to-enterprise communications. A quarter of manufacturers report that network capacity is a problem, too. And even when technology and bandwidth are available, cooperation among operations technology (OT) staff in the plant and IT staff in the business is often limited, hindering transfer and optimization of IoT data.

Manufacturers can achieve game-changing competitive advantage with the IoT – but few are ready. Most still need to develop networks, systems, and applications that transform data into insights. That will require short-term upgrades (e.g., update antiquated equipment, sensors, and controls; apply IoT intelligence to pressing problems, such as safety and data security) and longer-term investments and change (e.g., connect enterprise and supply-chain data streams; combine IoT intelligence with business analytics for improved forecasting, planning, and decisions).

Can your IoT infrastructure deliver on the promise of the IoT?

Stay tuned for more on how your company can increase productivity and profitability with IoT, analytics, machine learning, and artificial intelligence. In the meantime, download the report “The IoT is Delivering the Future – Now” to learn more about the complexity of an IoT transformation.

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Tanja Rueckert

About Tanja Rueckert

Tanja Rueckert is President of the Internet of Things and Digital Supply Chain Business Unit at SAP.

Human Skills for the Digital Future

Dan Wellers and Kai Goerlich

Technology Evolves.
So Must We.


Technology replacing human effort is as old as the first stone axe, and so is the disruption it creates.
Thanks to deep learning and other advances in AI, machine learning is catching up to the human mind faster than expected.
How do we maintain our value in a world in which AI can perform many high-value tasks?


Uniquely Human Abilities

AI is excellent at automating routine knowledge work and generating new insights from existing data — but humans know what they don’t know.

We’re driven to explore, try new and risky things, and make a difference.
 
 
 
We deduce the existence of information we don’t yet know about.
 
 
 
We imagine radical new business models, products, and opportunities.
 
 
 
We have creativity, imagination, humor, ethics, persistence, and critical thinking.


There’s Nothing Soft About “Soft Skills”

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level. There’s nothing soft about these skills, and we can’t afford to leave them to chance.

We must revamp how and what we teach to nurture the critical skills of passion, curiosity, imagination, creativity, critical thinking, and persistence. In the era of AI, no one will be able to thrive without these abilities, and most people will need help acquiring and improving them.

Anything artificial intelligence does has to fit into a human-centered value system that takes our unique abilities into account. While we help AI get more powerful, we need to get better at being human.


Download the executive brief Human Skills for the Digital Future.


Read the full article The Human Factor in an AI Future.


Comments

Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.

Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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The Human Factor In An AI Future

Dan Wellers and Kai Goerlich

As artificial intelligence becomes more sophisticated and its ability to perform human tasks accelerates exponentially, we’re finally seeing some attempts to wrestle with what that means, not just for business, but for humanity as a whole.

From the first stone ax to the printing press to the latest ERP solution, technology that reduces or even eliminates physical and mental effort is as old as the human race itself. However, that doesn’t make each step forward any less uncomfortable for the people whose work is directly affected – and the rise of AI is qualitatively different from past developments.

Until now, we developed technology to handle specific routine tasks. A human needed to break down complex processes into their component tasks, determine how to automate each of those tasks, and finally create and refine the automation process. AI is different. Because AI can evaluate, select, act, and learn from its actions, it can be independent and self-sustaining.

Some people, like investor/inventor Elon Musk and Alibaba founder and chairman Jack Ma, are focusing intently on how AI will impact the labor market. It’s going to do far more than eliminate repetitive manual jobs like warehouse picking. Any job that involves routine problem-solving within existing structures, processes, and knowledge is ripe for handing over to a machine. Indeed, jobs like customer service, travel planning, medical diagnostics, stock trading, real estate, and even clothing design are already increasingly automated.

As for more complex problem-solving, we used to think it would take computers decades or even centuries to catch up to the nimble human mind, but we underestimated the exponential explosion of deep learning. IBM’s Watson trounced past Jeopardy champions in 2011 – and just last year, Google’s DeepMind AI beat the reigning European champion at Go, a game once thought too complex for even the most sophisticated computer.

Where does AI leave human?

This raises an urgent question for the future: How do human beings maintain our economic value in a world in which AI will keep getting better than us at more and more things?

The concept of the technological singularity – the point at which machines attain superhuman intelligence and permanently outpace the human mind – is based on the idea that human thinking can’t evolve fast enough to keep up with technology. However, the limits of human performance have yet to be found. It’s possible that people are only at risk of lagging behind machines because nothing has forced us to test ourselves at scale.

Other than a handful of notable individual thinkers, scientists, and artists, most of humanity has met survival-level needs through mostly repetitive tasks. Most people don’t have the time or energy for higher-level activities. But as the human race faces the unique challenge of imminent obsolescence, we need to think of those activities not as luxuries, but as necessities. As technology replaces our traditional economic value, the economic system may stop attaching value to us entirely unless we determine the unique value humanity offers – and what we can and must do to cultivate the uniquely human skills that deliver that value.

Honing the human advantage

As a species, humans are driven to push past boundaries, to try new things, to build something worthwhile, and to make a difference. We have strong instincts to explore and enjoy novelty and risk – but according to psychologist Mihaly Csikszentmihalyi, these instincts crumble if we don’t cultivate them.

AI is brilliant at automating routine knowledge work and generating new insights from existing data. What it can’t do is deduce the existence, or even the possibility, of information it isn’t already aware of. It can’t imagine radical new products and business models. Or ask previously unconceptualized questions. Or envision unimagined opportunities and achievements. AI doesn’t even have common sense! As theoretical physicist Michio Kaku says, a robot doesn’t know that water is wet or that strings can pull but not push. Nor can robots engage in what Kaku calls “intellectual capitalism” – activities that involve creativity, imagination, leadership, analysis, humor, and original thought.

At the moment, though, we don’t generally value these so-called “soft skills” enough to prioritize them. We expect people to develop their competency in emotional intelligence, cross-cultural awareness, curiosity, critical thinking, and persistence organically, as if these skills simply emerge on their own given enough time. But there’s nothing soft about these skills, and we can’t afford to leave them to chance.

Lessons in being human

To stay ahead of AI in an increasingly automated world, we need to start cultivating our most human abilities on a societal level – and to do so not just as soon as possible, but as early as possible.

Singularity University chairman Peter Diamandis, for example, advocates revamping the elementary school curriculum to nurture the critical skills of passion, curiosity, imagination, critical thinking, and persistence. He envisions a curriculum that, among other things, teaches kids to communicate, ask questions, solve problems with creativity, empathy, and ethics, and accept failure as an opportunity to try again. These concepts aren’t necessarily new – Waldorf and Montessori schools have been encouraging similar approaches for decades – but increasing automation and digitization make them newly relevant and urgent.

The Mastery Transcript Consortium is approaching the same problem from the opposite side, by starting with outcomes. This organization is pushing to redesign the secondary school transcript to better reflect whether and how high school students are acquiring the necessary combination of creative, critical, and analytical abilities. By measuring student achievement in a more nuanced way than through letter grades and test scores, the consortium’s approach would inherently require schools to reverse-engineer their curricula to emphasize those abilities.

Most critically, this isn’t simply a concern of high-tuition private schools and “good school districts” intended to create tomorrow’s executives and high-level knowledge workers. One critical aspect of the challenge we face is the assumption that the vast majority of people are inevitably destined for lives that don’t require creativity or critical thinking – that either they will somehow be able to thrive anyway or their inability to thrive isn’t a cause for concern. In the era of AI, no one will be able to thrive without these abilities, which means that everyone will need help acquiring them. For humanitarian, political, and economic reasons, we cannot just write off a large percentage of the population as disposable.

In the end, anything an AI does has to fit into a human-centered value system that takes our unique human abilities into account. Why would we want to give up our humanity in favor of letting machines determine whether or not an action or idea is valuable? Instead, while we let artificial intelligence get better at being what it is, we need to get better at being human. That’s how we’ll keep coming up with groundbreaking new ideas like jazz music, graphic novels, self-driving cars, blockchain, machine learning – and AI itself.

Read the executive brief Human Skills for the Digital Future.

Build an intelligent enterprise with AI and machine learning to unite human expertise and computer insights. Run live with SAP Leonardo.


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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.

Share your thoughts with Kai on Twitter @KaiGoe.heif Futu