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The Internet Of Things Community Dreams Big For Charity

Jacqueline Prause

What happens when 18,000 people come together to imagine new ways the Internet of Things (IoT) can enhance people’s lives and make the world a better place?

Newborns receive round-the-clock care. Busy crowd areas are effectively monitored and secured. Litter in municipal parks is whisked away before it becomes an eyesore. And hikers on remote trails get the information they need to ensure vital access to water throughout their journey.

Hands-on challenges, crowdsourcing, and expert tools lead to $50,000 in charitable donations

These are just a few of the marvelously innovative ways in which learners in a recent openSAP course applied the principles of IoT to solving problems they noticed in the world around them. Covering fundamental topics sensors, cloud, augmented reality, and wearables, the course culminated in a prototype challenge that engaged learners to design and build their own IoT prototypes that included a story, persona, user experience journey, point of view, and mockup.

The top 10 winners of the challenge decided how SAP should allocate its $50,000 donation among three pre-selected charities: NetHopeInstitute of International Education, and Wikimedia. This unprecedented approach granted each of the 10 winners an opportunity to designate $5,000 to one of the three charities. The charities were chosen based on their support of the “Internet of Good Things” by fostering education and utilizing technology to make the world a better place, as well as their operational effectiveness.

Read more in the SAP Community blogs for further information about the class and the charities.

4 winning prototypes from the “Imagine IoT” challenge

Each of the winning prototypes presents an innovative, targeted solution to a highly specific, real-world problem. Together, they showcase the unique and imaginative ways IoT can be applied to solving a diverse array of challenges in our daily lives.

Visit the gallery (login required) to see the winning prototypes.

1. Hospital newborn baby monitoring system

This prototype aims to provide comprehensive, close monitoring of critical health information for newborn babies during their first precious days in the newborn unit of the hospital. For busy hospital staff, an IoT solution can provide the extra support to ensure each newborn receives proper and timely care – and hospitable staff are quickly alerted to problematic developments.

The chief challenge of this prototype is data consolidation from numerous devices to prevent data gaps and present a single source of truth. Some of the IoT-related technologies used in the prototype include baby wristbands with sensors to measure body temperature and heart rate, and additional sensors to record sleep patterns; room cameras and bed cameras to monitor general conditions in newborn room and follow the babies’ activities; integration interfaces to collect data from other lab systems and to create data pool; and interfaces to show health data, pictures, and videos of babies for nurses and doctors – and for parents too.

For Bahadir Murat Kandemirli, an experienced technology project manager based in Dubai, UAE, the inspiration to create the newborn monitoring system came at 1:12 PM on Friday, May 30, 2014 after his son was born. “When I saw my son for the first time in the newborn room, there were thousands of questions in my mind about his health,” says Kandemirli. “I could not find any answers to my questions. Then I asked myself why they did not have a monitoring system to learn critical data and follow up some important activities about my baby.” When Kandemirli talked to doctors and nurses about his concerns, he saw that the data gap was a pain point for hospital staff. “I understood the fact that they really needed this kind of a tool to help them and increase their work efficiency.”


newborn-monitoring-system-prototype
Figure 1: Newborn monitoring system prototype

See the submission as a PDF or in BUILD  (login required). 

2. Olympic Games safety

Perhaps no show draws more attention and generates more excitement than the Olympic Games. The Games can only be enjoyed, however, in a safe and secure environment. Organizers of the upcoming 2020 Olympic Games in Tokyo, for example, have already begun to engage leading technology firms to develop video intelligence analytics to monitor crowd safety, as well as sophisticated devices that can detect high-risk substances.

The potential of IoT to further expand the number of touchpoints across a system or venue inspired Kevin K. Rad, an SAP solution architect at Coresystems in Switzerland, to create a prototype that focused on ensuring Olympic Games safety, as well as demonstrated how the technology can be made usable for humans in a social context. “IoT can expand the system’s boundaries,” says Rad. “Combined with technologies like cloud computing, Big Data, machine learning, and global WiFi, we can have more things connected, which means more things belong to the whole, as a system. We have more interactions, hence more control.”

A former professional water polo player from Australia, Rad has spent a lot of time around sports venues and knows about the challenges unique to these environments. IoT can make it easier and less expensive to monitor safety on a large scale compared to many of the current security solutions. New technologies used in this prototype include: smart cameras that can detect suspicious behavior or people; sensors that can detect high-risk substances; gas sensors to detect high-risk gas in the area; smart cameras that can predict crowd movement; and smart roads.

olympics-games-safety-prototypeFigure 2: Olympics Games safety prototype

For more information, watch the video.

3. Smart water for long-distance hikers

Water is a precious life resource, so it shouldn’t be left to happenstance as to whether you will have enough or not – certainly not when you’re on a desert trail some 20 miles from the nearest camp or station. Olga Werner, a UX visual designer at SAP, applied the fundamentals of IoT to solving the problem of providing hikers with relevant information about the amount and quality of the water available at various stations on long-distance hiking trails. Werner says, “Lately, I got into hiking and I am inspired by the three long distance hikes in the United States – one in particular: The Pacific Crest Trail. It is over 4,200 km long, and it takes hikers usually from 4 to 6 months to hike. I found it fascinating how hikers handled the water situation, especially in the desert.”

Hikers face the tough choice of having to somewhat blindly rely on the availability of water at the next station – or they can carry their own water, but then they must endure hauling the extra weight. The Pacific Crest Trail report offers crowdsourced information about water along the trail, but unfortunately it may not be current. “I thought that with the help of IoT, this problem could be solved and make this hike even more enjoyable,” says Werner. Sensors at the water stations along the trail can gather valuable data, alerting hikers to dangerous situations like water scarcity or contamination. Hikers are able to access this information in real time with an app to better plan their trip.

prototype-of-smart-water-for-long-distance-hikersFigure 3: Prototype of smart water for long-distance hikers

See the prototype submission as a video or in BUILD (mobile view) (login required). 

4. Municipal solar-powered waste bins

For Mathias Ehret, a senior solution manager at Corporate Business Solutions Unternehmensberatung GmbH in Munich, Germany, the inspiration to create an IoT solution for municipal solar-powered waste bins came during his evening commute when he passed a motorized, solar-powered waste bin that had clearly malfunctioned. “There was a lot of litter around it and the lid was standing open with rubbish,” he recalls. “I got a little angry. You have an expensive device that’s standing around and there’s already more litter than you would have by putting a trash bin there. I thought, well, this poor thing is not able to cry for help. When I got out of my subway train I already had a low-flying prototype.”

This prototype provides a solution for real-time maintenance of the waste bins by alerting municipal workers to problems with specific waste bins – for example, a low battery, a blocked solar panel, or lack of capacity to hold more garbage. This prototype successfully mitigates two common challenges of IoT scenarios. One is the operational management of distributed devices, due to the need to specifically identify which waste bin is malfunctioning or full. The second challenge has to do with the data collection, because of the sheer volume of the data.

Ehret’s company is currently engaged in IoT projects now on behalf of its customers, including smart cities scenarios. It is also developing best practices for various types of IoT scenarios and business processes.

prototype-of-municipal-solar-waste-binsFigure 4: Prototype of municipal solar-powered waste bins

See the prototype submission as a PDF  or in BUILD (login required). 

Learn more about openSAP courses and the challenge

This article originally appeared on SAP News Center.

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About Jacqueline Prause

Jacqueline Prause is the Senior Managing Editor of Media Channels at SAP. She writes, edits, and coordinates journalistic content for SAP.info, SAP's global online news magazine for customers, partners, and business influencers .

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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In An Agile Environment, Revenue Models Are Flexible Too

Todd Wasserman

In 2012, Dollar Shave Club burst on the scene with a cheeky viral video that won praise for its creativity and marketing acumen. Less heralded at the time was the startup’s pricing model, which swapped traditional retail for subscriptions.

For as low as $1 a month (for five two-bladed cartridges), consumers got a package in the mail that saved them a trip to the pharmacy or grocery store. Dollar Shave Club received the ultimate vindication for the idea in 2016 when Unilever purchased the company for $1 billion.

As that example shows, new technology creates the possibility for new pricing models that can disrupt existing industries. The same phenomenon has occurred in software, in which the cloud and Web-based interfaces have ushered in Software as a Service (SaaS), which charges users on a monthly basis, like a utility, instead of the typical purchase-and-later-upgrade model.

Pricing, in other words, is a variable that can be used to disrupt industries. Other options include usage-based pricing and freemium.

Products as services, services as products

There are basically two ways that businesses can use pricing to disrupt the status quo: Turn products into services and turn services into products. Dollar Shave Club and SaaS are two examples of turning products into services.

Others include Amazon’s Dash, a bare-bones Internet of Things device that lets consumers reorder items ranging from Campbell’s Soup to Play-Doh. Another example is Rent the Runway, which rents high-end fashion items for a weekend rather than selling the items. Trunk Club offers a twist on this by sending items picked out by a stylist to users every month. Users pay for what they want and send back the rest.

The other option is productizing a service. Restaurant franchising is based on this model. While the restaurant offers food service to consumers, for entrepreneurs the franchise offers guidance and brand equity that can be condensed into a product format. For instance, a global HR firm called Littler has productized its offerings with Littler CaseSmart-Charges, which is designed for in-house attorneys and features software, project management tools, and access to flextime attorneys.

As that example shows, technology offers opportunities to try new revenue models. Another example is APIs, which have become a large source of revenue for companies. The monetization of APIs is often viewed as a side business that encompasses a wholly different pricing model that’s often engineered to create huge user bases with volume discounts.

Not a new idea

Though technology has opened up new vistas for businesses seeking alternate pricing models, Rajkumar Venkatesan, a marketing professor at University of Virginia’s Darden School of Business, points out that this isn’t necessarily a new idea. For instance, King Gillette made his fortune in the early part of the 20th Century by realizing that a cheap shaving device would pave the way for a recurring revenue stream via replacement razor blades.

“The new variation was the Keurig,” said Venkatesan, referring to the coffee machine that relies on replaceable cartridges. “It has started becoming more prevalent in the last 10 years, but the fundamental model has been there.” For businesses, this can be an attractive model not only for the recurring revenue but also for the ability to cross-sell new goods to existing customers, Venkatesan said.

Another benefit to a subscription model is that it can also supply first-party data that companies can use to better understand and market to their customers. Some believe that Dollar Shave Club’s close relationship with its young male user base was one reason for Unilever’s purchase, for instance. In such a cut-throat market, such relationships can fetch a high price.

To learn more about how you can monetize disruption, watch this video overview of the new SAP Hybris Revenue Cloud.

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