How London Achieved, And Maintained, Its Leadership In International Finance

Tom Groenfeldt

As a guide to the issues facing the City of London during Brexit, who could be better than Tony Norfield, a university Marxist-turned-City-trader now sporting a Ph.D. in economics from the University of London?

With 20 years of experience in dealing rooms at money center banks in London, he explains how finance concentrates power and profits in just a few financial centers, and London leads as an international center. As England and Europe prepare to set the terms of Brexit, Norfield’s historical perspective on how England has promoted finance is fascinating.

For fintech firms wondering if they should stay in London, follow the siren calls from Berlin, apply to the French Tech Ticket program, or look at Lisbon. Norfield has some history to offer: The City, with backing from both Labor and Conservative governments and the Bank of England, has adapted remarkably well to change. It shifted from lending to acting as an intermediary. It used the Big Bang to bring in foreign competition and capital. It shifted from sterling to doing business in the U.S. dollar and dozens of other currencies. And it has welcomed Arab capital with 22 Islamic banks, more than all other western countries combined.

Writing before the Brexit referendum, Norfield predicted that Europe might act against the financial domination of the UK and U.S., and that does appear, sporadically, to be happening. French President François Hollande recently called for a hard Brexit to discourage other countries from following the UK’s example, but the erratic nature of French politics confirms Norfield’s emphasis on the value arising from the security and centuries-long stability of the British state. Unlike Paris, London did not erupt in 1968 and it hasn’t experienced a leadership assassination attempt like the one on DeGaulle. (Norfield kindly omits comparisons with the U.S. on this topic.)

London,which holds a substantial lead over New York as an international financial center, has a geographical advantage, sitting in a time zone between Asia and the U.S., so it can trade with both during regular working hours. It also enjoys a regulatory climate that has long favored finance by allowing its banks, for example, to work with communist countries during the Cold War.

The author occasionally mentions his personal experience at some key points in finance. He was working at a Japanese bank when that country’s surging economy imploded, and he was at ABN AMRO when it moved its securities business to London, but left FX in Amsterdam. A stint in Sydney showed him Australia’s time-zone disadvantage, and he was in regular chats with a Bundesbank officer in London when Britain pulled out of the Exchange Rate Mechanism (ERM).

Norfield uses the term imperialism to describe the role of financial power centers.

The concentration of financial power is a little startling. In 2013, Norfield writes, 75% of the top 100 international corporations were in just six countries — the U.S., UK, France, Germany, Japan, and Switzerland.

“All forms of international finance, and even commerce, can also be seen as parasitic on the value created elsewhere,” he wrote. Countries with advanced finance find customers in countries, rich or poor, with less sophisticated finance. In 2013, the U.S. had a net gain of $209 billion from its  foreign investments, equivalent to receiving the entire economic output of the Czech Republic.

Finance is intertwined with politics, with corporations and with competition between the U.S. and UK for primacy. American banking laws have sometimes handicapped the U.S. financial services industry. Even as the U.S. was trying to gain access to the British Empire and trade with Commonwealth countries, American restrictions on foreign banking clashed with its large corporations which were seeking international expansion.

One result was the euromarket, which grew from $1 billion in 1960 to $1,050 billion by 1983, drawing European finance houses to expand their London operations. German banks, Norfield notes, do most of their securities business in London. U.S. banks also expanded London offices because they could serve international corporate clients with funding that was not so readily, or cheaply, available in the U.S. By 1971 the eurodollar market was equal to the money supply of France, and London had attracted 160 banks from 48 countries.

Staying outside the euro has also been a key to London’s position. British political leaders saw in 1976 and 1992 that inside Europe’s monetary system, it would be constrained by other states, particularly Germany.

Norfield believes global developments, often first visible in the financial sphere, can destabilize relationships between major powers.

It is likely that finance will continue to have the support of the British government to help it adjust.

“Above all, there was more consistent promotion of international financial business by the British authorities, which included an implicit promise not to distract financial interests with any changes in legislation,” he wrote.

Fintech firms and banks based in London might find Britain’s consistency encouraging. For updates, check Norfield’s blogs about Brexit and other finance topics. And for regular reports on the status of international finance centers, see Z/YEN’s Global Financial Centres Index.


About Tom Groenfeldt

Tom Groenfeldt is a freelance reporter who focuses largely on finance and technology including trading, risk, back-office systems, big data, analytics, retail banking, international banking, and e-commerce. His work appears in several publications, including in the U.S. and Banking Technology in London. In 2015, he was named to the "FinServ 25," the top 25 top global influencers in banking, by The Financial Brand.

Becoming An Exceptional Accountant

Zach Deming

Part 9 in the continuous accounting blog series. Read Part 1, Part 2, Part 3, Part 4, Part 5,  Part 6,  Part 7, and Part 8.

As an accounting and finance professional, you do so much more than just handle money matters; you’re also critical for creating strategy and driving process improvements across the entire organization.

But if you spend most of your time manually reconciling accounts and matching transactions, little is left for these bigger-picture activities.

What if you could be more productive with fewer resources and less overtime, and also easily improve the quality of your work? Not only would you be pleased with this improvement, but it would set you apart in the industry.

The modern approach

Continuous accounting is a modern approach that enables this improvement and creates competitive advantage. It transforms the way accounting and finance are done by embedding automation, control, and period-end tasks within day-to-day activities, smoothing out the end-of-period spikes and allowing the rigid accounting calendar to more closely mirror the broader business.

Effectively implementing continuous accounting requires a holistic approach, combining a mix of technology, process, and people to realize continued improvements across the accounting organization.

Using technology to automate procedures enhances the benefits of process optimization while increasing the overall productivity of accounting team members. Optimized processes will streamline automation, reduce risk, improve accuracy, and increase efficiency, benefiting the entire accounting and finance function.

Optimizing your people

Your accounting and finance professionals are at the heart of your organization’s innovation, and crucial to driving strategy and future business growth. But according to a recent BlackLine survey conducted by Censuswide, many midsize and large company decision-makers are not fully leveraging this talent.

Manual processes and tedious tasks take up too much time and result in this invaluable skillset being widely underutilized. To unlock this value, companies need to automate the tedious and manual accounting work that consumes so much of accountants’ time and effort.

When manual processes are automated, accounting and finance teams spend fewer hours on transactional activities. The focus shifts to analyzing the data and reports, and addressing only the exceptions.

Thus, by embedding continuous accounting practices, every accountant can become an exceptional accountant, providing high-value services in areas like fraud detection, compliance, data analytics, technology, and business advice.

What is an exceptional accountant?

By researching only the anomalies, accounting and finance staff can also refocus on providing strategic guidance to the business, such as improving internal processes or finding cost-saving opportunities. In other words, the added time allows accountants to apply not just their knowledge and expertise, but also their nuanced creativity and intelligence.

According to Helen Brand, chief executive of the Association of Chartered Certified Accountants (ACCA), “To succeed as a professional accountant…a vastly different set of skills is required than was necessary just 10 short years ago. And in the next decade, things are likely to change even faster and more dramatically as the global economy continues to evolve at an ever-quickening pace.”

So, what does the exceptional accountant of tomorrow need to cultivate today? Think mastering communication, not macros. Strategic aptitude, instead of being spreadsheet savvy. In short, capabilities that enable any accountant to deliver predictive insights to leadership, drive data-based decisions, and provide expert counsel. Analytical skills, communication skills, relationship skills, creativity, business acumen, and tech savviness: these six skills work in unison to serve as building blocks to Exceptional Accountant status.

My next blog on Wednesday, August 2 will explore in more detail.

To learn more about continuous accounting, read the Ventana Research Paper.

Follow SAP Finance online: @SAPFinance (Twitter)  | LinkedIn | FacebookYouTube


Zach Deming

About Zach Deming

Zach Deming is the director of Product Marketing at BlackLine. Zach partners with accounting and finance leaders to help them realize how their spreadsheet-driven processes hiding in the shadows simply can’t cope with the demands of always-on modern business, and the expectation of real-time analysis. After a decade in the industry, he thinks the benefits of cloud software can free accountants from the chains of transactions, liberating them to focus on strategy and analysis. Zach is skeptical of the robot uprising, and as a champion of Continuous Accounting, he believes the future of accounting does not lie in new technology alone, but also with the nuanced intelligence of skilled accountants. Connect with Zach on LinkedIn and Twitter (@ZachDeming).

How CFOs Can Make A Real Impact: A Q&A With SAP's Neil Krefsky

Olivia Berkman

FEI Daily spoke with Neil Krefsky, senior director, Solution Marketing at SAP, on the ways CFOs can stay ahead of the pack.

FEI Daily: SAP recently released the results of a survey with Oxford Economics of 1,500 finance executives to evaluate how finance roles are evolving in the face of the digital economy. What were some of the standout statistics you saw?

Neil Krefsky: The number-one statistic to me that stands out was [that people in] the “leader” class were twice as likely to report an increase in their company’s market share in the last year. When finance is involved and being highly effective, beyond just the traditional, there is a direct correlation with performance and market share. That’s one of the biggest competitive performance indicators that are out there.

The other thing that I thought was interesting was that in the traditional responsibilities, across core accounting and closing, across core GRC, and across core financial planning and analysis, the leaders said they were highly effective. There’s no surprise there. What did stand out to me is that everyone else did not rate themselves very effective in those areas. That is a very candid response. Nobody likes to say, “I’m not doing that well in my core responsibility.”

For example, the overall population of survey respondents basically rated themselves as highly effective only 33% of the time in FP&A. In GRC the whole population only rated themselves as highly effective 40% of the time. Even in the most mature area, core accounting and closing, they only rated themselves highly effective 54% of the time. The leaders were the ones that were on top of their core functions, which really enables them to do some more ambitious things like driving strategy throughout the organization.

FEI Daily: The biggest obstacle to making their company more efficient was the difficulty of updating technology without disrupting daily activities. How can that be improved?

Krefsky: There are a few aspects to it. Some is addressed with technology, some with change management, and some with people. The ones that do it effectively address all three of those. From a technology standpoint, it has to be part of an evaluation, so not just what might be the best technology or the hottest thing out there, but what will accomplish what they’re trying to accomplish where there’s some flexibility, and how to deploy it where it won’t be that disruptive. Leaders make part of their evaluation criteria not just what a certain technology or solution can do, but also how they can get this live within their company. That’s the first thing. Ignoring that in an evaluation already sets you back.

Then there’s certainly a change management aspect that’s nothing new. There have been good deployments and bad deployments for decades now. Companies put a plan in place and look at how effective they are in terms of allocating resources, how they’re going to go through a migration process, and if they have the executive support so that if they reallocate a resource here or there, there won’t be a negative point of view on that reallocation.

I think the newest trend from the people aspect is certainly training and bringing in a fresh level of talent. Having familiarity with millennial-type technology and work styles can really help move the needle faster to get away from “the way we’ve always done things.” I think Excel is the perfect example of that. I’ve seen in a lot of companies what I call “PhDs in Excel” who have almost built a new software and done some amazing things in Excel. However, if that person leaves or gets promoted or moves to a new job, that expertise is gone and it’s not re-trainable.

FEI Daily: How can finance executives use this study to improve their own performance?

Krefsky: 11% of them, a very small population, were clearly leading the pack in terms of how their companies performed, and those 11% all had stated themselves to be highly effective in six areas:

  • Drive strategic growth initiatives
  • Are well equipped to handle regulatory change
  • Improve efficiency with automation
  • Have strong influence beyond the finance function
  • Are very effective at core finance processes
  • Collaborate regularly with other business units

To help boost their own company’s performance, they can see [what leaders are consistently] doing very effectively from their own rankings. They can benchmark themselves to see, “Do I have a gap here in our company? Is this more of an ambition in our company? Are we lagging behind? Are we doing well in these things?” If there are some gaps, then they can put a plan in place to best get there.

FEI Daily: How can executives find the pain points in the business and then prioritize them?

Krefsky: There’s a lot of information out there, a lot of technologies to adopt, and a lot of areas that every finance organization can improve on. It’s not a one-size-fits-all for every company, every industry, every region. The leaders are very effective in identifying where the low-hanging fruit is: Where are the areas that will have the biggest impact if we move forward with this? Where I think a lot of the others could be adopting technology for technology’s sake. It could be the latest buzzword, whether cloud or machine learning or whatever. For some companies, that could be the biggest area of impact. Where are other companies? They may be ignoring certain things like, “Should I be addressing cybersecurity before I go to a cloud strategy?”

What we’ve found is leaders were very good at identifying which areas of improvement would have the biggest impact, and prioritizing and taking those on first, because there are opportunities everywhere with technology and efficiency at companies.

FEI Daily: What is the connection between effective GRC processes and performance?

Krefsky: A few things. One was the effective collaboration between a risk and compliance team with the core finance team. Many companies are already very effective at that. Especially with more and more [need for] compliance, more of a global business landscape where regulations come into play [with determining] how you do business effectively, GRC and the CFO need to be tightly aligned. In fact, we found a high portion of them present to the board together. Certainly that makes a company more effective, and they grow globally. Their ability to navigate the regulatory and compliance aspect: GRC can’t do it without finance, and finance can’t do it without GRC.

The other thing is that, in terms of confidence in a company from the outside looking in, and whether you would invest in that company—not just from the standpoint of its performance potential—depends on its ability to address cybersecurity risks. We found that there may be an underestimation of cybersecurity risk and data breaches over what the real impact could be, especially in certain regions. So leaders definitely have that much higher on their agenda.

For more on the evolving role of the CFO, see New Global Survey: CFOs Feel Growing Impact Of Digital Economy.

This article originally appeared in FEI Daily and is republished by permission.


Olivia Berkman

About Olivia Berkman

Olivia Berkman is the managing editor of FEI Daily, Financial Executives International’s daily newsletter delivering financial, business, and management news, trends, and strategies.

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.



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.

Follow me on twitter @vivek_bapat 

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.”


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.