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How Quickly Are Industries Adopting the Internet of Things?

Kai Goerlich

Science fiction writer William Gibson is credited with saying, ”The future is already here—it’s just not evenly distributed.” Such is the case with the Internet of Things (IoT).

Digital business requires both data and the equipment to capture, store, manage, and analyze that data before enterprises can better inform their decisions, automate actions, and improve operations. IoT technology provides a way.

According to IDC, companies are ramping up their IoT investments rapidly, which can be seen in seven major industries with high levels of physical products or assets. Overall, the market research firm forecasts that IoT spending will increase 19% on average through 2018. Some industries, such as discrete manufacturing, have already invested significantly; others, such as healthcare, have spent less to date but are expected to expand quickly in the future.

Opportunities for Connection

The IoT is poised for rapid growth across a wide variety of industries that are connecting physical assets 2016_Q1_charted_09
Download the infographic here.

The IoT Creates New Revenue Models

The Internet of Things represents a new course for automation and data-enabled decision making. Companies can use data collected from sensors on machines to create new business processes and revenue models.

It’s no wonder the numbers that researchers at Gartner cite—6.4 billion connected things in use in 2016, an increase of 30% over 2015—sound both large (billions, up 30%) and small at the same time (we’re just getting started). The future is being distributed unevenly, but it will reach just about everywhere, eventually.

2016_Q1_charted_02Utilities

Utilities are still in the early stages of connecting their physical assets, a McKinsey Global Institute analysis finds. Deregulation and new market entrants are expected to prompt greater investments in the future. For example, smart metering systems and renewable energy sources, both growing activities in this industry, require IoT connections.

And to compete, utilities will need to invest in systems that monitor and analyze data from smart devices at homes and businesses, Tata Consultancy Services notes. IDC predicts that eventually this industry will see a high impact from its IoT investments because both utility companies and consumers have a stake in making energy production and use more efficient.

2016_Q1_charted_03Healthcare

The industry as a whole has been slowed by regulatory and privacy concerns, Tata Consultancy Services research finds. But as healthcare providers install more equipment to connect medical devices to networks, they, too, will adopt more data-driven devices. Ultimately, IDC suggests that the IoT will have a high impact through monitoring applications and sensors that enable patients to manage their health and fitness.

2016_Q1_charted_04Wholesale

The IoT promises to bring new capabilities to distributors, including new opportunities to sell goods through industrial vending machines and automated transportation systems. However, the industry as a whole has been what McKinsey Global Institute calls a medium-level player on
the road to digitization.

 

2016_Q1_charted_05Discrete Manufacturing

Companies ranging from consumer goods makers to industrial manufacturers are applying IoT investments to monitor production and the flow of goods. Sensors enable predictive applications to schedule maintenance for jet engines, for example. And consumer goods makers are starting to experiment with marketing applications enabled by machine sensors and smartphones, Tata Consultancy Services notes.

2016_Q1_charted_06Retail

As VDC Research Group points out, the drive to digitize business has been going on since well before 2013. Prices for RFID transponders have dipped over the past decade, which has enabled retailers to affix tags to goods, speeding up inventory tracking and shipments processing and reducing shrinkage, RFID Journal reports.

 

2016_Q1_charted_07Logistics

Logistics firm DHL and networking vendor Cisco predict that there will be 50 billion connected devices by 2020, while making the point that this “represents only a tiny fraction of what could be connected—something on the order of 3% of all connectable things.” The resulting connectivity will reshape how decisions are made about the way goods are stored, monitored, serviced, and delivered. According to IDC, the IoT will have a high impact on the logistics industry because the benefits are clear and easy to measure.

2016_Q1_charted_08Process Manufacturing

Companies in process industries have been heavy investors in technologies that make their assets more productive, including enterprise resource planning and supply chain management software. Leading players see the IoT as a way to extend the value of these investments. For example, Deloitte researchers note that oil and gas companies can wring more efficiency from resource processing and distribution by collecting and analyzing data from sensors and by monitoring equipment to reduce unplanned equipment outages.

By Michael S. Goldberg and Kai Goerlich

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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

IoT Can Keep You Healthy — Even When You Sleep [VIDEO]

Christine Donato

Today the Internet of Things is revamping technology. IoT image from American Geniuses.jpg

Smart devices speak to each other and work together to provide the end user with a better product experience.

Coinciding with this change in technology is a change in people. We’ve transitioned from a world of people who love processed foods and french fries to people who eat kale chips and Greek yogurt…and actually like it.

People are taking ownership of their well-being, and preventative care is at the forefront of focus for both physicians and patients. Fitness trackers alert wearers of the exact number of calories burned from walking a certain number of steps. Mobile apps calculate our perfect nutritional balance. And even while we sleep, people are realizing that it’s important to monitor vitals.

According to research conducted at Harvard University, proper sleep patterns bolster healthy side effects such as improved immune function, a faster metabolism, preserved memory, and reduced stress and depression.

Conversely, the Harvard study determined that lack of sleep can negatively affect judgement, mood, and the ability retain information, as well as increase the risk of obesity, diabetes, cardiovascular disease, and even premature death.

Through the Internet of Things, researchers can now explore sleep patterns without the usual sleep labs and movement-restricting electrode wires. And with connected devices, individuals can now easily monitor and positively influence their own health.

EarlySense, a startup credited with the creation of continuous patient monitoring solutions focused on early detection of patient deterioration, mid-sleep falls, and pressure ulcers, began with a mission to prevent premature and preventable deaths.

Without constant monitoring, patients with unexpected clinical deterioration may be accidentally neglected, and their conditions can easily escalate into emergency situations.

Motivated by many instances of patients who died from preventable post-elective surgery complications, EarlySense founders created a product that constantly monitors patients when hospital nurses can’t, alerting the main nurse station when a patient leaves his or her bed and could potentially fall, or when a patient’s vital signs drop or rise unexpectedly.

Now EarlySense technology has expanded outside of the hospital realm. The EarlySense wellness sensor, a device connected via the Internet of Things, mobile solutions, and supported by SAP HANA Cloud Platform, monitors all vital signs while a person sleeps. The device is completely wireless and lies subtly underneath one’s mattress. The sensor collects all mechanical vibrations that the patient’s body emits while sleeping, continuously monitoring heart and respiratory rates.

Watch this short video to learn more about how the EarlySense wellness sensor works:

The result is faster diagnoses with better treatments and outcomes. Sleep issues can be identified and addressed; individuals can use the data collected to make adjustments in diet or exercise habits; and those on heavy pain medications can monitor the way their bodies react to the medication. In addition, physicians can use the data collected from the sensor to identify patient health problems before they escalate into an emergency situation.

Connected care is opening the door for a new way to practice health. Through connected care apps that link people with their doctors, fitness trackers that measure daily activity, and sensors like the EarlySense wellness sensor, today’s technology enables people and physicians to work together to prevent sickness and accidents before they occur. Technology is forever changing the way we live, and in turn we are living longer, healthier lives.

To learn how SAP HANA Cloud Platform can affect your business, visit It&Me.

For more stories, join me on Twitter.

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Christine Donato

About Christine Donato

Christine Donato is a Senior Integrated Marketing Specialist at SAP. She is an accomplished project manager and leader of multiple marketing and sales enablement campaigns and events, that supported a multi million euro business.

Size Doesn't Matter For Businesses In The Digital Economy

Christine Donato

SAP_Talks_Banner_2When I first entered the job market, I interviewed at a few different companies, one of which was a small insurance firm outside Philadelphia. My interviewer was a C-level executive, and he gave me a piece of advice I’ll never forget. He said, “You know, at a large corporation, you’re going to learn a lot about a little. Here with us, at a small business, you will learn a lot about a lot.”

He meant, of course, that employees of small to mid-sized companies wear many hats.  And usually, their organizational leaders are accessible resources and serve as CEO, CMO, CIO, CFO, and more all at one time.

Size doesn’t matter

Today, small businesses can be just as successful as, if not more successful than, their larger competitors. Why? Because with the right technology, small businesses can easily cause positive disruption in the market.

Within the boom of the digital economy, small businesses now have the power to reshape their markets and industries. A couple popular examples of this are Uber disrupting the transportation industry and Airbnb disrupting the hospitality industry.

Both have significantly shaken their larger competitors because they are successfully leveraging the Internet of Things to provide customers with a simple and easy way to purchase a service. And according to a recent blog by Vivek Bapat, 70% of consumers will recommend brands that offer a simpler experience.  And 38% of consumers will pay a premium for it (The Digitalist).

Learn more… Listen to #SAPTalks

According to a recent Economist Intelligence Unit study, 59% of executives agree that in order for their businesses to survive with today’s customers, their businesses must embrace and adapt to hyperconnectivity.

To learn more about numerous small and mid-sized businesses that are ditching legacy processes and inside-the box thinking to become disruptive forces in their markets, check out the new podcast series, #SAPTalks…Small to Midsized Business, hosted by David Trites.

In about 20 minutes per episode, guest speakers from small and mid-sized companies share their unscripted and in-depth digital transformation experiences. They explain their industries, challenges, current technology projects, best practices, and lessons learned along the journey.

The first episode will air on the Voice America Channel on Tuesday October 13th and will feature Paula Muesse, CIO and CFO of Zhena’s Gypsy Tea. On the show, Paula will explain how Zhena’s adopted new technology to best sell organic, fair-trade, and competitive teas.

You can follow the conversation on Twitter by hash tagging #SAPTalks and by following @SAPSmallBiz.

Follow the blog series

Read about more companies that have broken the myth that SAP is only for big business:

How to be a World-Leading Publisher in a Digital World

Franklin Valve Shows How Small Business Tackles Rapid Growth

Who is Feeding China’s Half Billion Pigs?

How Prime Meats Cuts Through Business Complexity

High-Tech ERP Helps EvoShield Protect Athletes and Grow Business

Stick to Basics in Family Recipes and the Sausage Business

For more on how you can successfully sell into the small and mid-sized market, please click here.

For more stories, follow me on Twitter and LinkedIn.

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Christine Donato

About Christine Donato

Christine Donato is a Senior Integrated Marketing Specialist at SAP. She is an accomplished project manager and leader of multiple marketing and sales enablement campaigns and events, that supported a multi million euro business.

Running Future Cities on Blockchain

Dan Wellers , Raimund Gross and Ulrich Scholl

Building on the Blockchain Framework

Some experts say these seemingly far-future speculations about the possibilities of combining technologies using blockchain are actually both inevitable and imminent:


Democratizing design and manufacturing by enabling individuals and small businesses to buy, sell, share, and digitally remix products affordably while protecting intellectual property rights.
Decentralizing warehousing and logistics by combining autonomous vehicles, 3D printers, and smart contracts to optimize delivery of products and materials, and even to create them on site as needed.
Distributing commerce by mixing virtual reality, 3D scanning and printing, self-driving vehicles, and artificial intelligence into immersive, personalized, on-demand shopping experiences that still protect buyers’ personal and proprietary data.

The City of the Future

Imagine that every agency, building, office, residence, and piece of infrastructure has an entry on a blockchain used as a city’s digital ledger. This “digital twin” could transform the delivery of city services.

For example:

  • Property owners could easily monetize assets by renting rooms, selling solar power back to the grid, and more.
  • Utilities could use customer data and AIs to make energy-saving recommendations, and smart contracts to automatically adjust power usage for greater efficiency.
  • Embedded sensors could sense problems (like a water main break) and alert an AI to send a technician with the right parts, tools, and training.
  • Autonomous vehicles could route themselves to open parking spaces or charging stations, and pay for services safely and automatically.
  • Cities could improve traffic monitoring and routing, saving commuters’ time and fuel while increasing productivity.

Every interaction would be transparent and verifiable, providing more data to analyze for future improvements.


Welcome to the Next Industrial Revolution

When exponential technologies intersect and combine, transformation happens on a massive scale. It’s time to start thinking through outcomes in a disciplined, proactive way to prepare for a future we’re only just beginning to imagine.

Download the executive brief Running Future Cities on Blockchain.


Read the full article Pulling Cities Into The Future With Blockchain

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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.

Raimund Gross

About Raimund Gross

Raimund Gross is a solution architect and futurist at SAP Innovation Center Network, where he evaluates emerging technologies and trends to address the challenges of businesses arising from digitization. He is currently evaluating the impact of blockchain for SAP and our enterprise customers.

Ulrich Scholl

About Ulrich Scholl

Ulrich Scholl is Vice President of Industry Cloud and Custom Development at SAP. In this role, Ulrich discovers and implements best practices to help further the understanding and adoption of the SAP portfolio of industry cloud innovations.

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Are AI And Machine Learning Killing Analytics As We Know It?

Joerg Koesters

According to IDC, artificial intelligence (AI) is expected to become pervasive across customer journeys, supply networks, merchandizing, and marketing and commerce because it provides better insights to optimize retail execution. For example, in the next two years:

  • 40% of digital transformation initiatives will be supported by cognitive computing and AI capabilities to provide critical, on-time insights for new operating and monetization models.
  • 30% of major retailers will adopt a retail omnichannel commerce platform that integrates a data analytics layer that centrally orchestrates omnichannel capabilities.

One thing is clear: new analytic technologies are expected to radically change analytics – and retail – as we know them.

AI and machine learning defined in the context of retail

AI is defined broadly as the ability of computers to mimic human thinking and logic. Machine learning is a subset of AI that focuses on how computers can learn from data without being programmed through the use of algorithms that adapt to change; in other words, they can “learn” continuously in response to new data. We’re seeing these breakthroughs now because of massive improvements in hardware (for example, GPUs and multicore processing) that can handle Big Data volumes and run deep learning algorithms needed to analyze and learn from the data.

Ivano Ortis, vice president at IDC, recently shared with me how he believes, “Artificial intelligence will take analytics to the next level and will be the foundation for retail innovation, as reported by one out of every two retailers globally. AI enables scale, automation, and unprecedented precision and will drive customer experience innovation when applied to both hyper micro customer segmentation and contextual interaction.”

Given the capabilities of AI and machine learning, it’s easy to see how they can be powerful tools for retailers. Now computers can read and listen to data, understand and learn from it, and instantly and accurately recommend the next best action without having to be explicitly programmed. This is a boon for retailers seeking to accurately predict demand, anticipate customer behavior, and optimize and personalize customer experiences.

For example, it can be used to automate:

  • Personalized product recommendations based on data about each customer’s unique interests and buying propensity
  • The selection of additional upsell and cross-sell options that drive greater customer value
  • Chat bots that can drive intelligent and meaningful engagement with customers
  • Recommendations on additional services and offerings based on past and current buying data and customer data
  • Planogram analyses, which support in-store merchandizing by telling people what’s missing, comparing sales to shelf space, and accelerating shelf replenishment by automating reorders
  • Pricing engines used to make tailored, situational pricing decisions

Particularly in the United States, retailers are already able to collect large volumes of transaction-based and behavioral data from their customers. And as data volumes grow and processing power improves, machine learning becomes increasingly applicable in a wider range of retail areas to further optimize business processes and drive more impactful personalized and contextual consumer experiences and products.

The transformation of retail has already begun

The impacts of AI and machine learning are already being felt. For example:

  • Retailers are predicting demand with machine learning in combination with IoT technologies to optimize store businesses and relieve workforces
  • Advertisements are being personalized based on in-store camera detections and taking over semi-manual clienteling tasks of store employees
  • Retailers can monitor wait times in checkout lines to understand store traffic and merchandising effectiveness at the individual store level – and then tailor assortments and store layouts to maximize basket size, satisfaction, and sell through
  • Systems can now recognize and predict customer behavior and improve employee productivity by turning scheduled tasks into on-demand activities
  • Camera systems can detect the “fresh” status of perishable products before onsite employees can
  • Brick-and-mortar stores are automating operational tasks, such as setting shelf pricing, determining product assortments and mixes, and optimizing trade promotions
  • In-store apps can tell how long a customer has been in a certain aisle and deliver targeted offers and recommendations (via his or her mobile device) based on data about data about personal consumption histories and preferences

A recent McKinsey study provided examples that quantify the potential value of these technologies in transforming how retailers operate and compete. For example:

  • U.S. retailer supply chain operations that have adopted data and analytics have seen up to a 19% increase in operating margin over the last five years. Using data and analytics to improve merchandising, including pricing, assortment, and placement optimization, is leading to an additional 16% in operating margin improvement.
  • Personalizing advertising is one of the strongest use cases for machine learning today. Additional retail use cases with high potential include optimizing pricing, routing, and scheduling based on real-time data in travel and logistics, as well as optimizing merchandising strategies.

Exploiting the full value of data

Thin margins (especially in the grocery sector) and pressure from industry-leading early adopters such as Amazon and Walmart have created strong incentives to put customer data to work to improve everything from cross-selling additional products to reducing costs throughout the entire value chain. But McKinsey has assessed that the U.S. retail sector has realized only 30-40% of the potential margin improvements and productivity growth its analysts envisioned in 2011 – and a large share of the value of this growth has gone to consumers through lower prices. So thus far, only a fraction of the potential value from AI and machine learning has been realized.

According to Forbes, U.S. retailers have the potential to see a 60%+ increase in net margin and 0.5–1.0% annual productivity growth. But there are major barriers to realizing this value, including lack of analytical talent and siloed data within companies.

This is where machine learning and analytics kick in. AI and machine learning can help scale the repetitive analytics tasks required to drive leverage of the available data. When deployed on a companywide, real-time analytics platform, they can become the single source of truth that all enterprise functions rely on to make better decisions.

How will this change analytics?

So how will AI and machine learning change retail analytics? We expect that AI and machine learning will not kill analytics as we know it, but rather give it a new and even more impactful role in driving the future of retail. For example, we anticipate that:

  • Retailers will include machine learning algorithms as an additional factor in analyzing and  monitoring business outcomes in relation to machine learning algorithms
  • They will use AI and machine learning to sharpen analytic algorithms, detect more early warning signals, anticipate trends, and have accurate answers before competitors do
  • Analytics will happen in real time and act as the glue between all areas of the business
  • Analytics will increasingly focus on analyzing manufacturing machine behavior, not just business and consumer behavior

Ivano Ortis at IDC authored a recent report, “Why Retail Analytics are a Foundation for Retail Profits,” in which he provides further insights on this topic. He notes how retail leaders will use new kinds of analytics to drive greater profitability, further differentiate the customer experience, and compete more effectively, “In conclusion, commerce and technology will converge, enabling retailers to achieve short-term ROI objectives while discovering untapped demand. But implementing analytics will require coordination across key management roles and business processes up and down each retail organization. Early adopters are realizing demonstrably significant value from their initiatives – double-digit improvements in margins, same-store and e-commerce revenue, inventory positions and sell-through, and core marketing metrics. A huge opportunity awaits.”

So how do you see your retail business adopting advanced analytics like AI and machine learning? I encourage you to read IDC’s report in detail, as it provides valuable insights to help you invest in – and apply – new kinds of analytics that will be essential to profitable growth.

For more information, download IDC’s “Why Retail Analytics are a Foundation for Retail Profits.

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Joerg Koesters

About Joerg Koesters

Joerg Koesters is the Head of Retail Marketing and Communication at SAP. He is a Technology Marketing executive with 20 years of experience in Marketing, Sales and Consulting, Joerg has deep knowledge in retail and consumer products having worked both in the industry and in the technology sector.