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2016 Brings Three Opportunities To Rethink Resource Optimization

Shelly Dutton

Digital. Disruptive. Deep in data. 2015 certainly kept many executives awake at night. In one short year, we witnessed the arrival of new businesses that own nothing and earn millions. Another crop of iconic brands disappeared, succumbing to the effects of mergers and acquisitions or the competitive muscle and creativity of digital darlings. And as the need for natural resources escalates, climate change and drought conditions continue to widen the gap between supply and demand.

No business can afford to continue down this path. In fact, a study from the John M. Olin School of Business at Washington University estimates that 40% of today’s FORTUNE 500 companies on the S&P 500 will no longer exist in less than 10 years.

What’s needed is a meaningful focus on resource optimization – and 2016 may be the year to do just that.

New trends that will change your resource optimization strategies 

According to the recent report IDC FutureScape: Worldwide Digital Transformation 2016 Predictions, IDC foresees three trends that may change how businesses look at their resource optimization strategies:

  1. 22 billion Internet of Things (IoT) devices installed by 2018, driving the development of over 200,000 new IoT apps and services.
  1. More than 50% of developer teams will embed cognitive services in their apps (vs. one percent today), saving U.S. enterprises over $60 billion annually by 2020.
  1. Over 50% of enterprises will create and/or partner with industry cloud platforms to distribute their innovations and source others’.

When I read these predictions, three things came to mind: continuous intelligence, continuous innovation, and continuous optimization. By linking digital technology to analytics-driven decision making in every area of the business, companies have an opportunity to evolve and better understand and serve their customers.

Why wait and see whether IDC’s predictions hold true? Take a look at five areas that you can impact now with digital technology.

  1. Asset management: Fixed assets can take up as much as one-third of all operating costs. As the use of IoT sensors and devices continues to grow, continuous monitoring will become the norm. As a result, companies can adjust the routing of its fleet and logistics process, drive down production downtime, and forecast production and operational demand more accurately. Once the data generated from these devices is shared across the entire business network, companies can help their external partners, suppliers, and other third-parties create a relationship that value continuous performance improvement and innovation.
  1. Teamwork and collaboration: Through digital intelligence, machine automation, and robotics, workers can expand their ability to increase efficiency and make real-time decisions that can directly impact business outcomes.
  1. Customer experience: There’s no debate that the proliferation of the digital channel is radically changing how companies engage with customers. Brands can directly impact the entire customer experience; from the first Google search to product and service delivery, businesses can transform passive customers into loyal advocates.
  1. User adoption: The beauty of Big Data is that there is no longer an excuse for creating goods and services that customers do not want. The rise of social media and lowering inhibitions in providing personal information are empowering businesses to improve offerings and innovate in step with customer needs and wants. By using this digital intelligence, brands can proactively impact the mass-market appeal adoption of their products and services.
  1. Environmental impact: Customers are more conscious about the environmental effects of the goods and services they use. More important, brand perception is directly tied to this criteria. In his blog “The Meaning – And Opportunity – Behind the Internet of Things,” Kai Goerlich states, “As decision makers receive information from direct and indirect environments, they can scan for precise navigation, logistics, weather prediction, agricultural planning, and pollution management, for example. By combining this streaming information with existing data, companies can create new insights and develop new products and services.”

As the next chapter of the digital economy unfolds this year, the business world finds itself at an inflection point. Some will rapidly scale their digital transformation to thrive in this new world. Others will operate “business as usual” and hope for the best. Which way will your business go?

For more thoughts on the impact of digital transformation, check out Kai Goerlich’s blog “The Meaning – And Opportunity – Behind the Internet of Things.”

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IoT And The New COO Scorecard

Tom Raftery

“Real knowledge is to know the extent of one’s ignorance,” said Kong Qui, better known as Confucius. I doubt he had chief operating officers (COOs) in mind when he said it, but 2,000 years later, he still makes a good a point. The Internet of Things (IoT) is taking us into unprecedented disruption, opportunity, and innovation. Business models are fluid, existing processes are becoming less relevant, and for many, we don’t know what we don’t know yet. IoT is not only changing how we do things, but also the definitions of our roles and our measurements of success – particularly for COOs. If ever there was a time for a bit of professional navel gazing, it’s now.

In the same way that CEOs and founders need entrepreneurial skills to devise new business ideas and create a culture of innovation, COOs must also be somewhat “intrapreneurial.” But that remit is changing from operational to transformational. And not everyone knows how to get there.

In my last blog, I touched on the transformational effect of IoT on almost every division and line of business head in the organization. Here I’ll talk specifically about COOs, because they’re at the digital coalface leading this transformation.

Of course, business transformation is hardly a new concept for a COO, but the seismic impact of IoT has permanently raised the bar. A new playing field with unparalleled processes, potential, and performance metrics is redefining what success looks like.  So much so that IDC has created a scorecard for the new COO remit, giving actionable evaluation measures and advice on how to think and execute differently in the brave new world of digital transformation. (If you’ve not yet seen it, it’s worth a read for the success of your future career, not just your current role.)

As organizations digitally mature, the KPIs for COOs are becoming more closely aligned to the broader organizational objectives with subtle, yet critical, interdependencies. IDC’s COO Scorecard identifies five key dimensions for these KPIs:

  1. Operational vision. The ability to gain active responsibility for technology governance while maintaining fidelity to corporate IT standards and guidelines.
  1. Connected assets and processes. The ability to connect corporate assets to improve effectiveness (inclusive of efficiency, reliability, and availability) and to digitally connect processes, both intracompany and intercompany, to create a more responsive operating capability.
  1. Connected experiences. The ability to support corporate’s transformation initiative based on digitally connected products and services to enable higher levels of customer satisfaction and to unlock information-based revenue opportunities.
  1. Intelligent decision making. The ability to connect corporate strategy with operational decision making, down to tactical plans, on an organizational scale.
  1. Talent and culture. The ability to create an environment where people are committed and enabled to change, where employees at any level move in the same direction promoting the same shared values.

What we are talking about here is essentially changing the COO’s remit from a utility to a transformer – and mastering that change in the process. The real issue is not if a company’s business model will transform (competition and disruption will typically take care of that), but rather whether COOs understand how best to steer the ship while this is happening. I don’t just wish you success in your company’s transformation, but also the digital acumen for you to make it happen.

Check out The COO Scorecard for Digital Transformation to see how you’re doing in advancing your organization’s digital maturity.

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About Tom Raftery

Tom Raftery is VP and Global Internet of Things Evangelist for SAP. Previously Tom worked as an independent analyst focussing on the Internet of Things, Energy and CleanTech. Tom has a very strong background in social media, is the former co-founder of a software firm and is co-founder and director of hyper energy-efficient data center Cork Internet eXchange. More recently, Tom worked as an Industry Analyst for RedMonk, leading their GreenMonk practice for 7 years.

How The Internet Of Things Is Fueling The F-35 Of The Farm Fields

John Ward

Eric Froebel is a man who truly appreciates the sophistication of modern farm equipment.

“With all its onboard software and hardware technology, a state-of-the-art tractor or combine is more like a fighter jet than the family car,” he observes.

Froebel, who is director of global engineering processes and IT architecture at AGCO Corporation, is not exaggerating. Loaded with sensor-driven telematics, GPS positioning, automatic guidance systems, and wireless data transfer technology, it’s easy to imagine a top-of-the-line tractor as the F-35 of the farm field.

This is exactly the kind of farm equipment that AGCO is known for manufacturing. And Froebel sees such high-tech machines as a present-day necessity.

“World population is growing, while the planet’s arable land is decreasing,” Froebel says matter-of-factly. “That means the yield from smaller amounts of land has to feed more people.”

There’s little doubt that sophisticated farm equipment and the larger world of the Internet of Things (IoT) will play an important role in boosting future harvests.

The IoT of farming

In fact, IoT could be biggest thing in agriculture since the domestication of farm animals.

“Smart agriculture and precision farming are taking off, but they could just be the precursors to even greater use of technology in the farming world,” notes a recent article in Business Insider. “The IoT is set to push the future of farming to the next level.”

The article points out that advancements such as agricultural drones, farm-field sensors, and self-driving tractors promise to be powerful tools in improving the efficiency of day-to-day work out on the farm.

Furthermore, this technology will be churning out enormous amounts of data.

Business Insider predicts IoT device installations in the agriculture world will increase from 30 million in 2015 to 75 million in 2020, and that the average farm will generate an average of 4.1 million data points per day in 2050.

Maximizing the yield from this data will be key.

AGCO’s vision of the connected farm

Part of AGCO’s vision is a next-generation approach to precision agriculture that it calls Fuse. Fuse is designed to provide mixed-fleet farming operations with improved access to their farm data to make more informed business decisions – resulting in enhanced productivity and profitability. It connects the entire crop cycle from enterprise planning and planting to crop care, harvesting, and grain storage.

“Of course, we want our equipment to talk to each other and to our management systems,” says Froebel, “but our strategy reflects a more open architecture. If a farmer already has a farm management solution, we want to be able to feed that system information too.”

Wheels firmly on the ground

But agricultural sophistication comes with its challenges as well. For farmers, these include issues such as data privacy and equipment maintenance that is, in itself, high-tech.

Again, better quality data is likely part of the solution.

“We want to gather live maintenance data from our machines,” says Christian Klingler, AGCO’s manager of global costing tools and process. “Not only so the farmer can manage their own equipment, but also for us as a manufacturer to use a means to improve our products.”

With global brands that include Massey Ferguson, Challenger, GSI, Valtra, and Fendt, AGCO is committed to promoting sustainable farm mechanization around the world.

Wherever it operates, one thing is certain. The piece of equipment tilling today’s farm fields is not your grandfather’s tractor.

Fueled by still-evolving IoT technologies, these modern miracle machines seem to do everything but fly.

Learn more about SAP Leonardo – SAP’s system of breakthrough technologies and services that let you take full advantage of embedded IoT capabilities and other innovation technologies through the cloud. Join us at Leonardo Live in Frankfurt July 11-12. #LeonardoLive. Learn more here.

Please follow me on Twitter @JohnGWard3.

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About John Ward

John Ward is an Integrated Marketing Expert at SAP. He has over 30 years of professional writing experience that includes marketing material, sales support, technical documentation, video scripting, and magazine articles.

Heroes in the Race to Save Antibiotics

Dr. David Delaney, Joseph Miles, Walt Ellenberger, Saravana Chandran, and Stephanie Overby

Last August, a woman arrived at a Reno, Nevada, hospital and told the attending doctors that she had recently returned from an extended trip to India, where she had broken her right thighbone two years ago. The woman, who was in her 70s, had subsequently developed an infection in her thigh and hip for which she was hospitalized in India several times. The Reno doctors recognized that the infection was serious—and the visit to India, where antibiotic-resistant bacteria runs rampant, raised red flags.

When none of the 14 antibiotics the physicians used to treat the woman worked, they sent a sample of the bacterium to the U.S. Centers for Disease Control (CDC) for testing. The CDC confirmed the doctors’ worst fears: the woman had a class of microbe called carbapenem-resistant Enterobacteriaceae (CRE). Carbapenems are a powerful class of antibiotics used as last-resort treatment for multidrug-resistant infections. The CDC further found that, in this patient’s case, the pathogen was impervious to all 26 antibiotics approved by the U.S. Food and Drug Administration (FDA).

In other words, there was no cure.

This is just the latest alarming development signaling the end of the road for antibiotics as we know them. In September, the woman died from septic shock, in which an infection takes over and shuts down the body’s systems, according to the CDC’s Morbidity and Mortality Weekly Report.

Other antibiotic options, had they been available, might have saved the Nevada woman. But the solution to the larger problem won’t be a new drug. It will have to be an entirely new approach to the diagnosis of infectious disease, to the use of antibiotics, and to the monitoring of antimicrobial resistance (AMR)—all enabled by new technology.

But that new technology is not being implemented fast enough to prevent what former CDC director Tom Frieden has nicknamed nightmare bacteria. And the nightmare is becoming scarier by the year. A 2014 British study calculated that 700,000 people die globally each year because of AMR. By 2050, the global cost of antibiotic resistance could grow to 10 million deaths and US$100 trillion a year, according to a 2014 estimate. And the rate of AMR is growing exponentially, thanks to the speed with which humans serving as hosts for these nasty bugs can move among healthcare facilities—or countries. In the United States, for example, CRE had been seen only in North Carolina in 2000; today it’s nationwide.

Abuse and overuse of antibiotics in healthcare and livestock production have enabled bacteria to both mutate and acquire resistant genes from other organisms, resulting in truly pan-drug resistant organisms. As ever-more powerful superbugs continue to proliferate, we are potentially facing the deadliest and most costly human-made catastrophe in modern times.

“Without urgent, coordinated action by many stakeholders, the world is headed for a post-antibiotic era, in which common infections and minor injuries which have been treatable for decades can once again kill,” said Dr. Keiji Fukuda, assistant director-general for health security for the World Health Organization (WHO).

Even if new antibiotics could solve the problem, there are obstacles to their development. For one thing, antibiotics have complex molecular structures, which slows the discovery process. Further, they aren’t terribly lucrative for pharmaceutical manufacturers: public health concerns call for new antimicrobials to be financially accessible to patients and used conservatively precisely because of the AMR issue, which reduces the financial incentives to create new compounds. The last entirely new class of antibiotic was introduced 30 year ago. Finally, bacteria will develop resistance to new antibiotics as well if we don’t adopt new approaches to using them.

Technology can play the lead role in heading off this disaster. Vast amounts of data from multiple sources are required for better decision making at all points in the process, from tracking or predicting antibiotic-resistant disease outbreaks to speeding the potential discovery of new antibiotic compounds. However, microbes will quickly adapt and resist new medications, too, if we don’t also employ systems that help doctors diagnose and treat infection in a more targeted and judicious way.

Indeed, digital tools can help in all four actions that the CDC recommends for combating AMR: preventing infections and their spread, tracking resistance patterns, improving antibiotic use, and developing new diagnostics and treatment.

Meanwhile, individuals who understand both the complexities of AMR and the value of technologies like machine learning, human-computer interaction (HCI), and mobile applications are working to develop and advocate for solutions that could save millions of lives.

Keeping an Eye Out for Outbreaks

Like others who are leading the fight against AMR, Dr. Steven Solomon has no illusions about the difficulty of the challenge. “It is the single most complex problem in all of medicine and public health—far outpacing the complexity and the difficulty of any other problem that we face,” says Solomon, who is a global health consultant and former director of the CDC’s Office of Antimicrobial Resistance.

Solomon wants to take the battle against AMR beyond the laboratory. In his view, surveillance—tracking and analyzing various data on AMR—is critical, particularly given how quickly and widely it spreads. But surveillance efforts are currently fraught with shortcomings. The available data is fragmented and often not comparable. Hospitals fail to collect the representative samples necessary for surveillance analytics, collecting data only on those patients who experience resistance and not on those who get better. Laboratories use a wide variety of testing methods, and reporting is not always consistent or complete.

Surveillance can serve as an early warning system. But weaknesses in these systems have caused public health officials to consistently underestimate the impact of AMR in loss of lives and financial costs. That’s why improving surveillance must be a top priority, says Solomon, who previously served as chair of the U.S. Federal Interagency Task Force on AMR and has been tracking the advance of AMR since he joined the U.S. Public Health Service in 1981.

A Collaborative Diagnosis

Ineffective surveillance has also contributed to huge growth in the use of antibiotics when they aren’t warranted. Strong patient demand and financial incentives for prescribing physicians are blamed for antibiotics abuse in China. India has become the largest consumer of antibiotics on the planet, in part because they are prescribed or sold for diarrheal diseases and upper respiratory infections for which they have limited value. And many countries allow individuals to purchase antibiotics over the counter, exacerbating misuse and overuse.

In the United States, antibiotics are improperly prescribed 50% of the time, according to CDC estimates. One study of adult patients visiting U.S. doctors to treat respiratory problems found that more than two-thirds of antibiotics were prescribed for conditions that were not infections at all or for infections caused by viruses—for which an antibiotic would do nothing. That’s 27 million courses of antibiotics wasted a year—just for respiratory problems—in the United States alone.

And even in countries where there are national guidelines for prescribing antibiotics, those guidelines aren’t always followed. A study published in medical journal Family Practice showed that Swedish doctors, both those trained in Sweden and those trained abroad, inconsistently followed rules for prescribing antibiotics.

Solomon strongly believes that, worldwide, doctors need to expand their use of technology in their offices or at the bedside to guide them through a more rational approach to antibiotic use. Doctors have traditionally been reluctant to adopt digital technologies, but Solomon thinks that the AMR crisis could change that. New digital tools could help doctors and hospitals integrate guidelines for optimal antibiotic prescribing into their everyday treatment routines.

“Human-computer interactions are critical, as the amount of information available on antibiotic resistance far exceeds the ability of humans to process it,” says Solomon. “It offers the possibility of greatly enhancing the utility of computer-assisted physician order entry (CPOE), combined with clinical decision support.” Healthcare facilities could embed relevant information and protocols at the point of care, guiding the physician through diagnosis and prescription and, as a byproduct, facilitating the collection and reporting of antibiotic use.

Cincinnati Children’s Hospital’s antibiotic stewardship division has deployed a software program that gathers information from electronic medical records, order entries, computerized laboratory and pathology reports, and more. The system measures baseline antimicrobial use, dosing, duration, costs, and use patterns. It also analyzes bacteria and trends in their susceptibilities and helps with clinical decision making and prescription choices. The goal, says Dr. David Haslam, who heads the program, is to decrease the use of “big gun” super antibiotics in favor of more targeted treatment.

While this approach is not yet widespread, there is consensus that incorporating such clinical-decision support into electronic health records will help improve quality of care, contain costs, and reduce overtreatment in healthcare overall—not just in AMR. A 2013 randomized clinical trial finds that doctors who used decision-support tools were significantly less likely to order antibiotics than those in the control group and prescribed 50% fewer broad-spectrum antibiotics.

Putting mobile devices into doctors’ hands could also help them accept decision support, believes Solomon. Last summer, Scotland’s National Health Service developed an antimicrobial companion app to give practitioners nationwide mobile access to clinical guidance, as well as an audit tool to support boards in gathering data for local and national use.

“The immediacy and the consistency of the input to physicians at the time of ordering antibiotics may significantly help address the problem of overprescribing in ways that less-immediate interventions have failed to do,” Solomon says. In addition, handheld devices with so-called lab-on-a-chip  technology could be used to test clinical specimens at the bedside and transmit the data across cellular or satellite networks in areas where infrastructure is more limited.

Artificial intelligence (AI) and machine learning can also become invaluable technology collaborators to help doctors more precisely diagnose and treat infection. In such a system, “the physician and the AI program are really ‘co-prescribing,’” says Solomon. “The AI can handle so much more information than the physician and make recommendations that can incorporate more input on the type of infection, the patient’s physiologic status and history, and resistance patterns of recent isolates in that ward, in that hospital, and in the community.”

Speed Is Everything

Growing bacteria in a dish has never appealed to Dr. James Davis, a computational biologist with joint appointments at Argonne National Laboratory and the University of Chicago Computation Institute. The first of a growing breed of computational biologists, Davis chose a PhD advisor in 2004 who was steeped in bioinformatics technology “because you could see that things were starting to change,” he says. He was one of the first in his microbiology department to submit a completely “dry” dissertation—that is, one that was all digital with nothing grown in a lab.

Upon graduation, Davis wanted to see if it was possible to predict whether an organism would be susceptible or resistant to a given antibiotic, leading him to explore the potential of machine learning to predict AMR.

As the availability of cheap computing power has gone up and the cost of genome sequencing has gone down, it has become possible to sequence a pathogen sample in order to detect its AMR resistance mechanisms. This could allow doctors to identify the nature of an infection in minutes instead of hours or days, says Davis.

Davis is part of a team creating a giant database of bacterial genomes with AMR metadata for the Pathosystems Resource Integration Center (PATRIC), funded by the U.S. National Institute of Allergy and Infectious Diseases to collect data on priority pathogens, such as tuberculosis and gonorrhea.

Because the current inability to identify microbes quickly is one of the biggest roadblocks to making an accurate diagnosis, the team’s work is critically important. The standard method for identifying drug resistance is to take a sample from a wound, blood, or urine and expose the resident bacteria to various antibiotics. If the bacterial colony continues to divide and thrive despite the presence of a normally effective drug, it indicates resistance. The process typically takes between 16 and 20 hours, itself an inordinate amount of time in matters of life and death. For certain strains of antibiotic-resistant tuberculosis, though, such testing can take a week. While physicians are waiting for test results, they often prescribe broad-spectrum antibiotics or make a best guess about what drug will work based on their knowledge of what’s happening in their hospital, “and in the meantime, you either get better,” says Davis, “or you don’t.”

At PATRIC, researchers are using machine-learning classifiers to identify regions of the genome involved in antibiotic resistance that could form the foundation for a “laboratory free” process for predicting resistance. Being able to identify the genetic mechanisms of AMR and predict the behavior of bacterial pathogens without petri dishes could inform clinical decision making and improve reaction time. Thus far, the researchers have developed machine-learning classifiers for identifying antibiotic resistance in Acinetobacter baumannii (a big player in hospital-acquired infection), methicillin-resistant Staphylococcus aureus (a.k.a. MRSA, a worldwide problem), and Streptococcus pneumoniae (a leading cause of bacterial meningitis), with accuracies ranging from 88% to 99%.

Houston Methodist Hospital, which uses the PATRIC database, is researching multidrug-resistant bacteria, specifically MRSA. Not only does resistance increase the cost of care, but people with MRSA are 64% more likely to die than people with a nonresistant form of the infection, according to WHO. Houston Methodist is investigating the molecular genetic causes of drug resistance in MRSA in order to identify new treatment approaches and help develop novel antimicrobial agents.

The Hunt for a New Class of Antibiotics

There are antibiotic-resistant bacteria, and then there’s Clostridium difficile—a.k.a. C. difficile—a bacterium that attacks the intestines even in young and healthy patients in hospitals after the use of antibiotics.

It is because of C. difficile that Dr. L. Clifford McDonald jumped into the AMR fight. The epidemiologist was finishing his work analyzing the spread of SARS in Toronto hospitals in 2004 when he turned his attention to C. difficile, convinced that the bacteria would become more common and more deadly. He was right, and today he’s at the forefront of treating the infection and preventing the spread of AMR as senior advisor for science and integrity in the CDC’s Division of Healthcare Quality Promotion. “[AMR] is an area that we’re funding heavily…insofar as the CDC budget can fund anything heavily,” says McDonald, whose group has awarded $14 million in contracts for innovative anti-AMR approaches.

Developing new antibiotics is a major part of the AMR battle. The majority of new antibiotics developed in recent years have been variations of existing drug classes. It’s been three decades since the last new class of antibiotics was introduced. Less than 5% of venture capital in pharmaceutical R&D is focused on antimicrobial development. A 2008 study found that less than 10% of the 167 antibiotics in development at the time had a new “mechanism of action” to deal with multidrug resistance. “The low-hanging fruit [of antibiotic development] has been picked,” noted a WHO report.

Researchers will have to dig much deeper to develop novel medicines. Machine learning could help drug developers sort through much larger data sets and go about the capital-intensive drug development process in a more prescriptive fashion, synthesizing those molecules most likely to have an impact.

McDonald believes that it will become easier to find new antibiotics if we gain a better understanding of the communities of bacteria living in each of us—as many as 1,000 different types of microbes live in our intestines, for example. Disruption to those microbial communities—our “microbiome”—can herald AMR. McDonald says that Big Data and machine learning will be needed to unlock our microbiomes, and that’s where much of the medical community’s investment is going.

He predicts that within five years, hospitals will take fecal samples or skin swabs and sequence the microorganisms in them as a kind of pulse check on antibiotic resistance. “Just doing the bioinformatics to sort out what’s there and the types of antibiotic resistance that might be in that microbiome is a Big Data challenge,” McDonald says. “The only way to make sense of it, going forward, will be advanced analytic techniques, which will no doubt include machine learning.”

Reducing Resistance on the Farm

Bringing information closer to where it’s needed could also help reduce agriculture’s contribution to the antibiotic resistance problem. Antibiotics are widely given to livestock to promote growth or prevent disease. In the United States, more kilograms of antibiotics are administered to animals than to people, according to data from the FDA.

One company has developed a rapid, on-farm diagnostics tool to provide livestock producers with more accurate disease detection to make more informed management and treatment decisions, which it says has demonstrated a 47% to 59% reduction in antibiotic usage. Such systems, combined with pressure or regulations to reduce antibiotic use in meat production, could also help turn the AMR tide.

Breaking Down Data Silos Is the First Step

Adding to the complexity of the fight against AMR is the structure and culture of the global healthcare system itself. Historically, healthcare has been a siloed industry, notorious for its scattered approach focused on transactions rather than healthy outcomes or the true value of treatment. There’s no definitive data on the impact of AMR worldwide; the best we can do is infer estimates from the information that does exist.

The biggest issue is the availability of good data to share through mobile solutions, to drive HCI clinical-decision support tools, and to feed supercomputers and machine-learning platforms. “We have a fragmented healthcare delivery system and therefore we have fragmented information. Getting these sources of data all into one place and then enabling them all to talk to each other has been problematic,” McDonald says.

Collecting, integrating, and sharing AMR-related data on a national and ultimately global scale will be necessary to better understand the issue. HCI and mobile tools can help doctors, hospitals, and public health authorities collect more information while advanced analytics, machine learning, and in-memory computing can enable them to analyze that data in close to real time. As a result, we’ll better understand patterns of resistance from the bedside to the community and up to national and international levels, says Solomon. The good news is that new technology capabilities like AI and new potential streams of data are coming online as an era of data sharing in healthcare is beginning to dawn, adds McDonald.

The ideal goal is a digitally enabled virtuous cycle of information and treatment that could save millions of dollars, lives, and perhaps even civilization if we can get there. D!

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


About the Authors:

Dr. David Delaney is Chief Medical Officer for SAP.

Joseph Miles is Global Vice President, Life Sciences, for SAP.

Walt Ellenberger is Senior Director Business Development, Healthcare Transformation and Innovation, for SAP.

Saravana Chandran is Senior Director, Advanced Analytics, for SAP.

Stephanie Overby is an independent writer and editor focused on the intersection of business and technology.

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4 Traits Set Digital Leaders Apart From 97% Of The Competition

Vivek Bapat

Like the classic parable of the blind man and the elephant, it seems everyone has a unique take on digital transformation. Some equate digital transformation with emerging technologies, placing their bets on as the Internet of Things, machine learning, and artificial intelligence. Others see it as a way to increase efficiencies and change business processes to accelerate product to market. Some others think of it is a means of strategic differentiation, innovating new business models for serving and engaging their customers. Despite the range of viewpoints, many businesses are still challenged with pragmatically evolving digital in ways that are meaningful, industry-disruptive, and market-leading.

According to a recent study of more than 3,000 senior executives across 17 countries and regions, only a paltry three percent of businesses worldwide have successfully completed enterprise-wide digital transformation initiatives, even though 84% of C-level executives ranks such efforts as “critically important” to the fundamental sustenance of their business.

The most comprehensive global study of its kind, the SAP Center for Business Insight report “SAP Digital Transformation Executive Study: 4 Ways Leaders Set Themselves Apart,” in collaboration with Oxford Economics, identified the challenges, opportunities, value, and key technologies driving digital transformation. The findings specifically analyzed the performance of “digital leaders” – those who are connecting people, things, and businesses more intelligently, more effectively, and creating punctuated change faster than their less advanced rivals.

After analyzing the data, it was eye-opening to see that only three percent of companies (top 100) are successfully realizing their full potential through digital transformation. However, even more remarkable was that these leaders have four fundamental traits in common, regardless of their region of operation, their size, their organizational structure, or their industry.

We distilled these traits in the hope that others in the early stages of transformation or that are still struggling to find their bearings can embrace these principles in order to succeed. Ultimately I see these leaders as true ambidextrous organizations, managing evolutionary and revolutionary change simultaneously, willing to embrace innovation – not just on the edges of their business, but firmly into their core.

Here are the four traits that set these leaders apart from the rest:

Trait #1: They see digital transformation as truly transformational

An overwhelming majority (96%) of digital leaders view digital transformation as a core business goal that requires a unified digital mindset across the entire enterprise. But instead of allowing individual functions to change at their own pace, digital leaders prefer to evolve the organization to help ensure the success of their digital strategies.

The study found that 56% of these businesses regularly shift their organizational structure, which includes processes, partners, suppliers, and customers, compared to 10% of remaining companies. Plus, 70% actively bring lines of business together through cross-functional processes and technologies.

By creating a firm foundation for transformation, digital leaders are further widening the gap between themselves and their less advanced competitors as they innovate business models that can mitigate emerging risks and seize new opportunities quickly.

Trait #2: They focus on transforming customer-facing functions first

Although most companies believe technology, the pace of change, and growing global competition are the key global trends that will affect everything for years to come, digital leaders are expanding their frame of mind to consider the influence of customer empowerment. Executives who build a momentum of breakthrough innovation and industry transformation are the ones that are moving beyond the high stakes of the market to the activation of complete, end-to-end customer experiences.

In fact, 92% of digital leaders have established sophisticated digital transformation strategies and processes to drive transformational change in customer satisfaction and engagement, compared to 22% of their less mature counterparts. As a result, 70% have realized significant or transformational value from these efforts.

Trait #3: They create a virtuous cycle of digital talent

There’s little doubt that the competition for qualified talent is fierce. But for nearly three-quarters of companies that demonstrate digital-transformation leadership, it is easier to attract and retain talent because they are five times more likely to leverage digitization to change their talent management efforts.

The impact of their efforts goes beyond empowering recruiters to identify best-fit candidates, highlight risk factors and hiring errors, and predict long-term talent needs. Nearly half (48%) of digital leaders understand that they must invest heavily in the development of digital skills and technology to drive revenue, retain productive employees, and create new roles to keep up with their digital maturity over the next two years, compared to 30% of all surveyed executives.

Trait #4: They invest in next-generation technology using a bimodal architecture

A couple years ago, Peter Sondergaard, senior vice president at Gartner and global head of research, observed that “CIOs can’t transform their old IT organization into a digital startup, but they can turn it into a bi-modal IT organization. Forty-five percent of CIOs state they currently have a fast mode of operation, and we predict that 75% of IT organizations will be bimodal in some way by 2017.”

Based on the results of the SAP Center for Business Insight study, Sondergaard’s prediction was spot on. As digital leaders dive into advanced technologies, 72% are using a digital twin of the conventional IT organization to operate efficiently without disruption while refining innovative scenarios to resolve business challenges and integrate them to stay ahead of the competition. Unfortunately, only 30% of less advanced businesses embrace this view.

Working within this bimodal architecture is emboldening digital leaders to take on incredibly progressive technology. For example, the study found that 50% of these firms are using artificial intelligence and machine learning, compared to seven percent of all respondents. They are also leading the adoption curve of Big Data solutions and analytics (94% vs. 60%) and the Internet of Things (76% vs. 52%).

Digital leadership is a practice of balance, not pure digitization

Most executives understand that digital transformation is a critical driver of revenue growth, profitability, and business expansion. However, as digital leaders are proving, digital strategies must deliver a balance of organizational flexibility, forward-looking technology adoption, and bold change. And clearly, this approach is paying dividends for them. They are growing market share, increasing customer satisfaction, improving employee engagement, and, perhaps more important, achieving more profitability than ever before.

For any company looking to catch up to digital leaders, the conversation around digital transformation needs to change immediately to combat three deadly sins: Stop investing in one-off, isolated projects hidden in a single organization. Stop viewing IT as an enabler instead of a strategic partner. Stop walling off the rest of the business from siloed digital successes.

As our study shows, companies that treat their digital transformation as an all-encompassing, all-sharing, and all-knowing business imperative will be the ones that disrupt the competitive landscape and stay ahead of a constantly evolving economy.

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For more insight on digital leaders, check out the SAP Center for Business Insight report, conducted in collaboration with Oxford Economics,SAP Digital Transformation Executive Study: 4 Ways Leaders Set Themselves Apart.”

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About Vivek Bapat

Vivek Bapat is the Senior Vice President, Global Head of Marketing Strategy and Thought Leadership, at SAP. He leads SAP's Global Marketing Strategy, Messaging, Positioning and related Thought Leadership initiatives.