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Leveraging The Internet Of Healthcare Things (IoHT)

Bo Dagnall

Imagine having a stroke while on vacation — not while you are out sightseeing, but in a hospital, because technology helped to get you there before the stroke even occurred. Would being in a hospital under the supervision of care providers increase your chances of survival? I believe so, because the amount of time from the onset of a stroke to the administration of thrombolytics is critical1, and faster treatment may limit the extent of brain injury and improve the outcome after a stroke.2

So how can technology help make this a reality? Consider the hypothetical scenario shown below. Sue is a 55-year old ex-smoker with high blood pressure and a family history of cerebrovascular problems.

A Stroke With and Without IoHT Technologies (source: Hewlett Packard Enterprise)

A Stroke With and Without IoHT Technologies (Source: Hewlett Packard Enterprise)

Technology makes a difference in healthcare

Without the Internet of Things (IoT) and mobile technologies, there is nothing in place to determine a baseline dataset for Sue when she awakes. Technology is not in place to detect her potential TIA (an indicator and potential predictor of stroke), notify her GP, identify her location, or collect biometrics while under supervision. The time lost as a result is detrimental to Sue’s chances of full recovery from a stroke.

On the other hand, Sue’s condition is vastly improved when technology is involved. Sue’s wearable devices establish her morning biometrics baseline, her smartwatch detects her slurred speech and notifies her GP of potential TIA or stroke indicators, and her GPS-enabled devices allow emergency services to quickly locate and transfer her to the nearest care facility. Once she is admitted, in-hospital sensors collect her biometrics and care providers are immediately notified when she actually has the stroke. All of these things matter because research shows that intravenous administration of thrombolytics is effective only if administered within three hours from the onset of symptoms1.

Real-time health systems (RTHS)

The intelligent convergence and integration of sensor-based data collected via IoT devices and mobile technologies is collectively referred to as the Internet of Healthcare Things (IoHT).

This data can be combined with existing electronic health record (EHR) systems3, to create something called a Real-Time Health System (RTHS)4.

One of the things a modern EHR does not necessarily address is patient-based situational awareness. A modern EHR collects and uses clinical data about a patient’s health and the care provided to that patient in a care facility. An episode of care typically starts by documenting the chief complaint and any additional relevant historical information previously captured or provided by the patient; often missing critical information about what else happened when the medical event took place. This is where the RTHS comes in.

What does an RHTS do?

An RTHS collects IoHT data, analyzes it to identify clinically relevant indicators and trends, integrates findings and alerts into EHR systems, and leverages native capabilities of mobile devices to provide an immediate feedback loop to both providers and patients.

The business benefit is better situational awareness of the patient’s health condition during a medical event occurring in the gaps between EHR-recorded episodes of care. To do this, the RTHS is not inventing something new, but instead leveraging and converging emerging technologies that currently are not effectively connected, including IoT and sensor-based technologies, mobile devices, Big Data analytics, and EHR systems.

Learn more about emerging technology in the Internet of Healthcare Things (IoHT)

For an in-depth look at the Internet of Things and other factors driving digital disruption in healthcare and other sectors, download the SAP eBook, Digital Disruption: How Digital Technology is Transforming Our World.

To learn more about business innovation in the digital era, download the SAP eBook, The Digital Economy: Reinventing the Business World.

References

1.  Madden K, “Optimal timing of thrombolytic therapy in acute aschaemic stroke”, CNS Drugs. 2002;16(4):213-8

2. Adams, H et al., “Guidelines for Thrombolytic Therapy for Acute Stroke: A Supplement to the Guidelines for the Management of Patients With Acute Ischemic Stroke. A Statement for Healthcare Professionals From a Special Writing Group of the Stroke Council, American Heart Association”, Stroke. 1994;25:1901-1914

3. http://dashboard.healthit.gov/quickstats/quickstats.php, accessed September 2015

4. Hewlett Packard Enterprise (HPE)

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Bo Dagnall

About Bo Dagnall

Bo Dagnall is the account chief technologist for Hewlett-Packard Enterprise (HPE) focused on the Department of Veterans Affairs (VA) within the Military Health and Veterans Affairs (MHVA) account. In this role, Bo oversees and delivers technology strategy for HPE’s VA opportunities. At any point in time, HPE has 15-20 active projects with the VA almost exclusively around applications support and modernization.

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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Daniel Newman

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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Live Businesses Deliver a Personal Customer Experience Without Losing Trust

Lori Mitchell-Keller, Brian Walker, Johann Wrede, Polly Traylor, and Stephanie Overby

Trust is the foundation of customer relationships. People who don’t trust your business are not likely to become or remain customers.

The trust relationship has taken some big hits lately. Beloved brands like Chipotle and Toyota have seen customer trust ebb due to public perception of their roles in safety issues. Consumers continue to experience occasional data breaches from large brands.

Yet these traditional threats have short half-lives. The latest threat could last forever.

Most customers claim they want personalization across all the channels in which they interact with companies. Such personalization should create long-term loyalty by creating a new level of intimacy in the relationship.

sap_Q216_digital_double_feature3_images2But that intimacy comes at a high price. For personalization to work, brands need to gather unprecedented amounts of personal information about customers and continue to do so over the course of the relationship. Customers are already wary: 80% of consumers have updated their privacy settings recently, according to an article in VentureBeat.

Companies must get personalization right. If they do, customers are more likely to purchase again and less likely to switch to a competitor. Personalization is also an important step toward the holy grail of digital transformation: becoming a Live Business, capable of meeting customers with relevant and customized offers, products, and services in real time or in the moments of customers’ choosing.

When done wrong, personalization can cause customers to feel that they’ve been deceived and that their privacy has been violated. It can also turn into an uncomfortable headline. When Target used its database of customer purchases to send coupons for diapers to the home of an expectant teen before her father knew about the pregnancy, its action backfired. The incident became the centerpiece of a New York Times story on Target’s consumer intelligence gathering practices and privacy.

Straddling the Line of Trust

Customers can’t define the line between helpful and creepy, but they know it when they see it.

Research conducted by RichRelevance in 2015 made something abundantly clear: what marketers think is cool may be seen as creepy by consumers. For example, facial-recognition technology that identifies age and gender to target advertisements on digital screens is considered creepy by 73% of people surveyed. Yet consumers were happy about scanning a product on their mobile device to see product reviews and recommendations for other items they might like, the survey revealed. Here’s what else resonates as creepy or cool when it comes to digital engagement with consumers, courtesy of RichRelevance and Edelman Berland (now called Edelman).

Creepy

  • Shoppers are put off when salespeople greet them by name because of mobile phone signals or know their spending habits because of facial-recognition software.
  • Dynamic pricing, such as a digital display showing a lower price “just for you,” also puts shoppers off.
  • When brands collect data on consumers without their knowledge, 83% of people consider it an invasion of privacy, according to RichRelevance’s research, and 65% feel the same way about ads that follow them from Web site to Web site (retargeting).

Cool

  • Shoppers like mobile apps with interactive maps that efficiently guide them to products in the store.
  • They also like when their in-store location triggers a coupon or other promotion for a product nearby.
  • When a Web site reminds the consumer of past purchases, a majority of shoppers like it.

There are no hard-and-fast rules about which personalization tactics are creepy and which are cool, but trust is particularly threatened in face-to-face interactions. Nobody minds much if Amazon sends product recommendations through a computer, but when salespeople approach customers like a long-lost friend based on information collected without the customer’s knowledge or permission, the violation of trust feels much more personal and emotional. The stage is set for an angry, embarrassed customer to walk out  the door, forever.

sap_Q216_digital_double_feature3_images3It doesn’t help that the limits of trust shift constantly as social media tempts us to reveal more and more about ourselves and as companies’ data collection techniques continue to improve. It’s easy to cross the line from helpful to creepy or annoying (see Straddling the Line of Trust).

Online, customers are similarly choosy about personalization. For example, when online shoppers are simply looking at a product category, ads that matched their prior Web-browsing interests are ineffective, an MIT study reports. Yet after consumers have visited a review site to seek out information and are closer to a purchase, personalized content is more effective than generic ads.

Personalization Requires a Live Business

Yet the limits of trust are definitely shifting toward more personalization, not less. Customers already enjoy frictionless personalized experiences with digital-native companies like Uber, and they are applying those heightened expectations to all companies. For example, 91% of customers want to pick up where they left off when they switch between channels, according to Aspect research. And personalization is helpful when you receive recommendations for products that you would like based on previous in-store or online purchases.

sap_Q216_digital_double_feature3_images-0004Customers also want their interactions to be live—or in the moment they choose. Fulfilling that need means that companies must become Live Businesses, capable of creating a technological infrastructure that allows real-time interactions and that allows the entire organization—its structure, people, and processes—to respond to customers in all the moments that matter.

Coordinating across channels and meeting customers in the right moments with personalized interactions will become critical as the digital economy matures and customer expectations rise. For instance, when customers air complaints about a brand on social media, 72% expect a response within an hour, according to consulting firm Bain & Company. Meanwhile, an Accenture survey found that nearly 60% of consumers want real-time promotions; 48% like online reminders to order items that they might have run out of; and 51% like the idea of a one-click checkout, where they can skip payment method or shipping forms because the retailer has saved their preferences. Those types of services build trust, showing that companies care enough to understand their customers and send offers or information that save them time, money, or both.

So while trust is difficult to earn, once you’ve earned it and figured out how to maintain it, you can have customers for life—as long as you respect the shifting boundaries.

“Do customers think the company is truly acting with their best interests at heart, or is it just trying to feed the quarterly earnings beast?” asks Donna Peeples, a customer experience expert and the former chief customer experience officer at AIG. “Customer data should be accurate and timely, the company should be transparent about how the data is being used, and it should give customers control over data collection.”

sap_Q216_digital_double_feature3_images-0005How to Earn Trust for a Live Business

Despite spending US$600 billion on online purchases, U.S. consumers are concerned with transaction privacy, the 2015 Consumer Trust Survey from CA Security Council reveals. These concerns will become acute as Live Businesses make personalization across channels a reality.

Here are some ways to improve trust while moving forward with omnichannel personalization.

  • Determine the value of trust. Customers want to know what value they are getting in exchange for their data. An Accenture study found that the majority of consumers in the United States and the United Kingdom are willing to have trusted retailers use some of their personal data in order to present personalized and targeted products, services, recommendations, and offers.
    “If customers get substantial discounts or offers that are appealing to them, they are often more than willing to make that trade-off,” says Tom Davenport, author of Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. “But a lot of companies are cheap. They use the information but don’t give anything back. They make offers that aren’t particularly relevant or useful. They don’t give discounts for loyalty. They’re just trying to sell more.”
  • Let customers make the first move. Customers who voluntarily give up data are more likely to trust personalization across the channels where they do business. Mobile apps are a great way to invite customers to share more data in a more intimate relationship that they control. By entering the data they choose into the app, customers won’t be annoyed by personalization that’s built around it.
    For example, a leading luxury retailer’s sales associates may offer customers their favorite beverages based on information they entered into the app about their interests and preferences.
  • Simplify data collection and usage policies. Slapping a dense data- use policy written in legalese on the corporate website does little to earn customers’ trust. Instead, companies should think about the customer data transaction, such as what information the customer is giving them, how they’re using it, and what the result will be, and describe it as simply as possible.
    “Try to describe it in words so simple that your grandmother can understand it. And then ask your grandmother if it’s reasonable,” suggests Elea McDonnell Feit, assistant professor of marketing at Drexel University’s LeBow College of Business. “If your grandmother can’t understand what’s happening, you’ve got a problem.”
    The use of data should be totally transparent in the interaction itself, adds Feit. “When a company uses data to customize a service or offering to a customer, the customer should be able to figure out where the company got the data and immediately see how the company is providing added value to the customers by using the data,” Feit says.
  • Create trust through education. Yes, bombarding customers with generic offers and pushing those offers across the different Web sites they visit may boost profits over the short term, but customers will eventually become weary and mistrustful. To create trust that lasts and that supports personalization, educate the customers.

Procter & Gamble’s (P&G’s) Mean Stinks campaign for Secret deodorant encourages girl-to-girl anti-bullying posts on Twitter, Facebook, and Instagram. The pages let participants send apologies to those they have bullied; view videos; and share tips, tools, and challenges with their peers.

P&G has said that participation in Mean Stinks has helped drive market share increases for the core Secret brand as well as the specific line of deodorant promoted by the effort. Offering education without pushing products or services creates a sense that companies are putting customers’ interests before their own, which is one of the bedrock elements of trust. Opting in to personalization seems less risky to customers if they perceive that companies have built up a reserve of value and trust.

“Companies that do personalization well demonstrate that they care, respect customers’ time, know and understand their customers and their needs and interests,” says Peeples. “It also reinforces that interactions are not merely transactions but opportunities to build a long-term relationship with that customer.”

Laying the Foundation for Live, Personalized Omnichannel Processes

sap_Q216_digital_double_feature3_images-0006Creating a personalized omnichannel strategy that balances trust and business goals starts with knowing the customer. This can happen only when multiple aspects of your business are coordinated in a live fashion. But marketers today struggle to collect the kind of data that could drive more meaningful connections with customers. In an Infogroup survey of more than 500 marketers, only 21% said they are “very confident in the accuracy and completeness of their customer profiles.” A little over half of respondents said they aren’t collecting enough data overall.

Collecting enough of the right types of data requires more holistic data-collection techniques:

  • Take advantage of the lower costs for processing and storing terabytes of data, and develop a data strategy that combines and crunches all the customer data points needed to drive relevant interactions. This includes transactional, mobile, sensor, and  Web data.
  • Social media analytics is also a central tactic. Social profiles and activity are rich sources of data about behavior and character, merging what people buy or look for with their interests, for instance. Such data can feed predictive analytics and personalization campaigns.
  • Experiment with commercial tools that can filter and mine the data of customers and prospects in real time. This is a significant step beyond basic demographic data collections of the past.

sap_Q216_digital_double_feature3_images-0007Once the necessary data is available, companies need the technology, processes, and people to make sensible use of it in an omnichannel personalization strategy. Only when a company is organized as a Live Business can that happen. Here’s how your company can move toward being a Live Business:
Be live across channels. Having a consistent customer journey map across channels is core to omnichannel personalization. It requires integration across multiple systems and organizational silos to enable core capabilities, such as inventory visibility and purchase/pickup/return across channels. This integration also constitutes a major chunk of the transition to becoming a company that can act in the moments that matter most to customers. If all channels can sync in real time, customers can get what they want in the moment they want it.

Free the data scientists. Marketing rarely has full control over the omnichannel experience, but it is the undisputed leader in understanding customer behavior. While data science is part of that understanding, it has traditionally played a background role. Marketers need to bring the data scientists into efforts to sort through the different options for digitizing the omnichannel experience. The right data scientists understand not only how to use the tools but also how to apply the data to make accurate decisions and follow customers from channel to channel with personalized offers.

Walgreens’ Technology Approach to Personalization

Walgreens is a leader in building the kind of technology base that can enable real-time, omnichannel personalization. Its digital transformation is 16 years in the making, according to Jason Fei, senior director of architecture for digital engineering at Walgreens. At the heart of its infrastructure is a Big Data engine that feeds many customer interaction and omnichannel processes, including customer segmentation. The company adds third-party systems in areas such as predictive analytics and marketing software. Walgreens has a cloud-first strategy for all new applications, such as its image-processing and print-ordering applications. Other elements of the drugstore chain’s technology platform include:

  • Application programming interface (API)-driven architecture. Walgreens’ APIs enable more than 50 partners to connect with its apps and systems to drive customer-facing processes, including integrations with consumer wearables to drive reward points for healthy habits, as well as content partnerships with companies such as WebMD. “With APIs we can be an extensible business, allowing other companies to connect to us easily and help in the digital enablement of our physical stores,” Fei says.
  • Responsive Web sites. The company’s Web site is built using responsive and adaptive design practices so that the site automatically adapts to the consumer’s device, whether that is a mobile phone, tablet, or desktop computer. “We have a single code base that runs anywhere and delivers a consistent, optimized experience to all of our customers,” Fei says.

Making the Most of the Technology Base

This technology foundation has allowed Walgreens to push forward in personalization. For example, according to Fei the company uses sophisticated segmentation and personalization engines to drive outbound e-mail and text campaigns to customers based on their purchase history and profile. “We don’t blast out messages to customers; we use our personalization recommendations to be relevant,” says Fei.

The next phase of this strategy is to develop live inbound personalization tactics, such as recognizing customers when they come back to the Web site and tailoring their experience accordingly. These highly automated, self-learning systems improve over time, becoming more relevant at the moment a customer logs back in.

“When you search for a product, the Web site will take a good guess of what you might actually want. If you always print greeting cards at the same time of year, for example, the system would automatically deliver content around that,” Fei explains. “Everyone comes to Walgreens with a mission, so we can be very targeted with our communications.”

Walgreens’ mobile app combines real-time personalization with convenience. You can scan a pill bottle to refill a prescription, access coupons, send photos from your phone to print in the store, track rewards, and find the exact location of a product on the shelf.

Walgreens also recently deployed a new integrated interactive voice-response system that includes a personalization engine that recognizes the individual, says Troy Mills, vice president of customer care at Walgreens. The system can then predict the most probable reason for the customer’s call and quickly get them to the right individual for further help.

How to Get Started with Live Customer Experiences

sap_Q216_digital_double_feature3_images-0008As Fei can attest, getting Walgreens’ omnichannel and personalization infrastructure to this point has involved a lot of work, with much more to come. For companies just now embarking on this journey, especially midsize and large companies, getting started will mean overhauling an outdated and ineffective technology infrastructure where duplicate systems and processes for managing customer data, marketing programs, and transactions are common.

A bad internal user experience often transcends into a bad customer-facing experience, says Peeples. “We can’t afford the distractions of the latest app or social ‘shiny penny’ without addressing the root causes of our systems’ issues.”

Live Business Requires Striking the Right Balance

The boundaries of trust are a moving target. Sales tactics that used to be acceptable decades ago, such as the door-to-door salesperson, are unwelcome today to most homeowners. And consumers’ expectations are unpredictable. At the dawn of social media, many people were anxious about their photos unexpectedly showing up online. Now our identities are tagged and our posts and photos distributed and commented on regularly.

But while consumers are getting more comfortable with online technology and its trade-offs, they won’t put up with personalization efforts that make use of their data without their knowledge or permission. That data has value, and customers want to decide for themselves when it’s worth giving it away. Marketers need to strike the right balance between personalization and a healthy respect for the unique needs and concerns of individuals. D!

 

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Lori Mitchell-Keller

About Lori Mitchell-Keller

Lori Mitchell-Keller is the Executive Vice President and Global General Manager Consumer Industries at SAP. She leads the Retail, Wholesale Distribution, Consumer Products, and Life Sciences Industries with a strong focus on helping our customers transform their business and derive value while getting closer to their customers.

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The Future Of Medicine: Mass Customization

Sarah Harvey

A century ago, Henry Ford transformed the world with the Model T, the first mass-produced automobile. As other retail giants quickly realized the benefits of mass production, more goods became affordable, accessible, and standardized. Individualization took a back seat.

But by the 1990’s the individual was back in focus, under mass customization—a method that combines custom-made flexibility with the low unit costs of mass production. For example, Nike allows customers to choose colors for every element of a standard shoe. Japanese eyeglass retailer Paris Miki uses data, images, and preferences to recommend best-fit glasses. Automakers like Ford – whose founder once said that customers could have the Model T in any color, as long as it’s black – now offer millions of variations in style and functionality to cater to consumer needs. The customer is empowered to have a collaborative dialogue with the provider for a more personalized product.

But what about when the customer is a patient – and the product is a potentially lifesaving treatment?

Mass production has long been the norm in healthcare, too. As in manufacturing, economies of scale in healthcare have supported the development of mass-produced drugs to treat and cure disease.

But today a new approach is revolutionizing the industry. Called personalized or precision medicine, it uses genomics and Big Data to move beyond the one-size-fits-all model into more individualized care. It promises cost savings, better patient outcomes, and progress against diseases like cancer, diabetes, and even aging.

Mass-market medicine is not going away, but according to a new study conducted by Oxford Economics, more than two-thirds of healthcare professionals say that personalized medicine is already having a measurable effect on patient outcomes. Roughly the same number expect it to in the next two years.

Looking ahead

But to reach the full potential of personalized medicine, the healthcare industry and its stakeholders must accept a new landscape. Organizations need to adopt advanced technology and talent. The industry must adjust to new governance models. And we all must accept significant cultural shifts around data sharing.

Personalized medicine allows researchers and providers to segment large populations into smaller groups. Patients are then slotted into the appropriate group based on their own characteristics, including genetic information, age, and personal habits. Providers then can make decisions based on analysis of past successes, tailoring treatment for the smaller group – or even the individual.

But although healthcare organizations are investing heavily in tools like analytics, they still need to fully build out IT capabilities and find workers with the right digital skills. Advanced fields like genomics are not fulfilling their potential – though when tapped, the outcomes are impressive, as researchers at institutions like Stanford University have discovered.

Perhaps most significantly, however, personalized medicine requires adjustments to industry culture in key areas like privacy, data sharing, and governance. The patient is empowered in new ways, with an unprecedented level of involvement in all phases of care. Yet we’re still trying to balance patient privacy with data sharing, as institutions also address issues of collaboration. Finding meaningful trends using personalized medicine requires a huge amount of data, more than any single institution can access. Solutions such as CancerLinQ from ASCO attempt to tackle this problem by aggregating data from member institutions, but more must accept the reality that sharing data and research outcomes is the key to finding cures.

And while economic case for personalized medicine strengthening, it comes down to much more than cost savings. Customization of care will impact the lives of patients around the world. As mass customization of medicine is mastered, we’ll see even more individual courses of care. We’ll see treatment tailored to each and every single patient. We’ll see more lives saved. Personalized medicine puts patients first – and empowers them to be at the center of their treatment process.

To learn more about how SAP is making the world run better and improving people’s lives, visit the SAP Connected Health Center, or continue the discussion on Twitter @SAP_Healthcare.

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Sarah Harvey

About Sarah Harvey

Sarah Harvey is the Deputy Head of Strategy & Operations, Global Corporate Affairs at SAP. She focuses on engaging highly relevant influencers, cultivating skills, and ensuring operational excellence to drive overall success. She also drives integrated strategy, messaging, and content for communications campaigns on the topics of healthcare, sports, and youth.