Sections

Are You Social Selling Or Social Spamming?

Mark Babbitt

The Social Age has ushered in a new way of connecting, contributing, and collaborating like we’ve never seen before.

We can now communicate with anyone at any time, anywhere in the world over a variety of platforms. We can now begin to build mutually beneficial relationships with a single Tweet, post, or upload. We can share our stories, build awareness, and right some wrongs from our kitchen table, the subway, and during work.

Social media, when used for good, is beyond powerful – it is unifying.

And then there’s the dark side: the trolls, drama queens, divas, fakers, takers, ask-holes – and especially the spammers – who pollute social media with their own brand of selfishness.

Lately, it’s the spammers that have caught my attention most. That’s probably because I can shut down the other malcontents easily enough, but those spammers… they won’t go away. The worst part? They don’t see themselves as spammers! They call what they do “social selling.”

I prefer to call it what it is: social spamming.

How do you tell the difference between social selling and social spamming? Well, you are a social spammer if you:

Send auto DMs and emails

Use of auto-DMs on Twitter, for any reason, is unacceptable. Yes, this includes those ridiculous “Thanks for following me, {Twitter_Handle}! Let’s also connect on Facebook {Facebook URL} and LinkedIn {LinkedIn URL}!” messages. It also includes ANY request to download a FREE ANYTHING by visiting your site.

Auto DMs suck. Period. And everyone knows that by now. Which means you’re either blissfully unaware… or you don’t care.

Abuse LinkedIn inmail

You connect with people on LinkedIn using “InMaul” (Steve Levy’s clever term) not to build a mutually beneficial relationship, but to sell them something on your very next communication. And then there are the below-average recruiters, sourcers, and HR types who target people, then send an InMail to promote their job posting or an open requisition… but that job doesn’t actually exist. And you knew that, but decided that increasing your network for future commission-based sales was more important than getting job seekers’ hopes up – and then dash them – for your personal gain.

This isn’t just the Social Age equivalent of telemarketing… it’s a violation of trust.

Treat LinkedIn like Facebook

When you contribute to the rapid downfall of LinkedIn by posting a Donald Trump meme, a math game, or a pretty picture of a sunset – or anything else that doesn’t involve professional networking or career development, you are a spammer.

Social media is NOT all about you and your personal agendas – that is especially true, some of us still believe, of LinkedIn.

Add the unwilling and unknowing to Facebook groups

When you add people to your Facebook group without their permission, you’re a spammer. I mostly blame Facebook for this one; why would they allow ANYONE else be able to add you to their Facebook groups without asking you first?!

And yet I can only be added by a “friend” so many times to the “Fans of Days of Our Lives” Facebook Group before I start to take it personally.

Exploit Facebook tags

You tag people on your Facebook posts not because they are already involved in the discussion, or even because the discussion is relevant to them, but because you want them to read and share your latest post or join in your latest outrage. You know those tags mean YOUR stuff shows up in MY Facebook timeline, right? That your drama becomes my drama?

Why would you do that?

Seek Facebook friends from low places

So, we have 138 friends in common on Facebook… but I’ve never heard of you. And yet you still send a “friend” request? We have a different definition of “friend.” As Jon Ferrara says, “How about following me on Twitter first, adding value to my conversation, then reach out on LinkedIn with a tailored invite demonstrating that you’ve taken time to understand who I am and why your connecting. Finally after you’ve earned some trust and intimacy, now let’s be friends on Facebook.”

Leverage fake Twitter followers

If you create, sell, or buy fake Twitter followers, you are deliberately contributing to the noise and everything that can be wrong with social media. You are a cheater. And a liar. Besides, you know that we all know how to discover how “real” your Twitter followers are, right?

Maybe not, because you are probably that unaware character who also sends all of those auto-friggin-DMs.

Scrape email addresses

You scrape websites, including LinkedIn, for email addresses. You then work around every aspect of the CAN-SPAM law to send an email you had no business sending. And now, even though it might tell you the email address really is me so you can sell it to some other spammer, we all have to hit that ‘Unsubscribe’ button you put in the bottom of each email as required by CAN-SPAM.

Which proves you knew better.

Scrape cell numbers

You read in a blog somewhere that people always respond to a text, even if they don’t respond to email or social. So you went to the ‘Contact Info’ section of LinkedIn, or perhaps our website, and scraped a phone number. And now you text and text and text and text. Even when I don’t answer your feeble attempts to sell me your crap via text, you text. This, my spammy unfriend, is why we have ‘Block’ buttons on our phones. (Thanks to Nicole Virant for her contribution to this post… she brought this one home.)

Fail to follow up

You make it through all the filters in place. Based on implied trust, you convince me you are interested in building a relationship. And then I never hear from you again. Or, perhaps even worse, we set up a time to talk and you either don’t show up or are ill-prepared?

From my perspective (and Jon Ferrara’s): This is one of the worst kinds of spam, because you got past the gatekeepers only to become a total time-suck.

Any attempt to sell lead-generation services

As Janet Fouts says, “You endorse me for several things on Linkedin over a series of days to get my attention, then ask to connect only to send an automated spam message asking me if I want to buy leads.”

I get this all the time, and my immediate thought is, “You got to me by spamming. If I use your system or service, is that how you want me to be thought of too?” Yeah, I’ll pass.

Expose cleavage on KinkedIn – the UNprofessional network

The newest trend on LinkedIn is also one of the most concerning – a likely carryover from the Twitter wannabe-Kardashians who seem to show up in every trending topic on that platform. I’m talking about the profile pictures from young women who seem to attract a lot of attention from frat brothers, single young men, and lonely old men.

Cover the girls up, ladies… your cleavage shots, duck lips, and Vogue-poses are just contributing to the noise in social media. (Credit to Julie Albright for the term “KinkedIn” – made coffee come out my nose when I first read it.)

So there you have it… 12 ways we know you’re using “social selling” as an excuse to use social and digital media as a personal spamming platform.

If you are doing any of these, either to promote your business or inject others into your personal life, drama, or ambitions without their consent… you’re a social spammer.

Do us all a favor: Stop.

Help us get social media back to what it was intended to be…  social.

For more insight on social media strategies, see Should You Outsource Your Company’s Social Media Initiative?

The post Are You Social Selling or Social Spamming? appeared first on Switch & Shift.

Comments

Why $4.6 Trillion Was Left In Abandoned Online Shopping Carts In 2016

Aaron Solomon

Nearly 70% of online shopping carts are abandoned without the customer ever completing the purchase. According to Business Insider, that added up to over $4.6 trillion in the global economy in 2016. So, what can online retailers do to fix this problem? Keep reading to learn why cart abandonment is so prevalent, and the steps you can take to recapture potential sales in your business.

Top 3 (preventable) reasons for cart abandonment

Customers abandon online carts for a variety of reasons, ranging from issues with your online store to simply getting distracted and leaving their computer. Studies show three common, and often preventable, reasons customers do not complete the checkout process.

1. Shipping cost sticker shock

For a whopping 61% of U.S. shoppers, the number one reason they don’t complete the checkout process is unexpectedly high shipping costs. Customers may have found your product prices acceptable, but high shipping costs can change their view completely. Not every company can subsidize shipping, and even fewer can on all orders, but here are a few things you can do to try to reduce your customers’ shipping cost shock:

  • Price fairly: Review what you are charging your customers for shipping against what your actual costs are. It’s no sin to turn shipping into a revenue stream, but if these costs are excessive, it may be costing you more in sales than it’s worth.
  • Offer options: Depending on your carriers, consider offering customers slower, but more cost-effective options, such as UPS 3 Day Select instead of Next Day or Second Day Air.
  • In-store pickup: If you also have physical stores, consider offering in-store pickup as an option.

2. Lack of trust in your site

Whenever a first-time customer makes a purchase, they are demonstrating trust in your ability to fulfill their order, charge them accurately, and most importantly, protect their data. There are several website attributes that could cause customers to consider shopping elsewhere:

  • Site maintenance: If your site has blurry images or broken links, customers may doubt your ability to meet their needs.
  • Online security: Include a “Trusted Site” logo from your certificate authority on your site to tell customers that you have properly secured your site.
  • Return policy: Having a complete and accessible return policy on your online store can provide customers with the reassurance that if the product does not meet their expectations, there will be a way for them to address this issue.
  • Shipping clarity: A shipping information page provides customers information they will want to know before committing to a purchase, such as how long after an order is placed it will be shipped or what shipping carriers and delivery options are available.

3. Frustration during the checkout process

The main perk of online shopping is convenience. If your checkout process is slow or tedious, customers get frustrated quickly. Take the following three points into consideration to mitigate this concern:

  • Guest checkout: In 2016, 33% of U.S. shoppers abandoned their carts when forced to create an account. Having a customer create an account can be beneficial for your business, but, if customers are forced to create an account to make a purchase, is it worth it? Consider leaving the option for them to check out as a guest to simplify their shopping experience.
  • Coupon codes: If you offer promotions with coupon codes, make sure that all your marketing information has the correct coupon codes and expiration dates for these codes.
  • Make it easy for customers to reach you: As a best practice, online stores should always have a “Contact Us” page to allow customers to easily reach out. If customers are experiencing frustration, being able to reach you can be the deciding factor on whether they give up or not.

Successful online retailers manage these issues to ensure that when customers abandon carts, it is not due to failures of the business. Taking these steps can reduce the amount of lost revenue, as well as increase your business’ reputation with both current and prospective customers.

For more insight on selling through digital channels, see Primed: Prompting Customers to Buy.

This blog was originally posted on the SAP Anywhere Customer Success Portal, and has been reposted with permission.

Comments

About Aaron Solomon

Aaron Solomon is the head of Training and Content Development for SAP Anywhere. With a dedicated history in knowledge management and consulting, he is driven to provide quality information to customers and help them understand how best to grow their businesses. His areas of expertise include e-commerce management, data analysis, and leveraging technology to improve efficiency.

Using Philosophy To Find Happiness In A Hyperconnected World

Adam Winfield

Zen and the Art of Motorcycle Maintenance, published in 1974 by Robert M. Pirsig, has been called the biggest-selling and most widely read philosophy book ever. A fictionalized autobiography of a motorcycle road trip the author took with his son Chris across America, the book became influential thanks to its transcendent philosophical digressions. Despite the title, it’s not really about Zen Buddhism – or motorcycles – but living a good and meaningful life.

Pirsig, who died earlier this year, showed us “it might actually be possible to unify the cold, rational, numbingly systematized world of science and technology with the warm, intuitive realm of art and the spirit,” according to writer Tim Wilson, who interviewed him the year the book was released.

“If you run from technology, it will chase you,” Pirsig told Wilson, a caution that carries increased significance in a time when GPS tracks the location of our smartphones and high-bandwidth wireless Internet coverage smothers much of the populated land on Earth.

Pirsig’s point wasn’t that we should run from technology, or hate it. He called out the self-defeating hypocrisy of loathing and resisting technology but lapping up the standard of living it provides. Instead, technology should be considered part of nature, and part of humanity. “The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital computer or the gears of a cycle transmission as he does at the top of a mountain or in the petals of a flower,” he wrote.

Zen and the Art of Motorcycle Maintenance, 2017 edition

Had Pirsig taken his road trip in 2017 he’d be faced with a very different world to the one of 1974, more than 25 years before the Internet went mainstream. Given his willingness to embrace technology, we can assume he’d have taken a 4G-enabled smartphone along for the ride. The technology – the satellites, the data, the sensors – wouldn’t be chasing him; it’d be right there in his pocket.

Unlike those who retreat into nature for “digital detoxes,” not realizing their addiction to technology rather than technology itself is the problem, Pirsig would have seen the beauty in a connected device that made his journey through the American wilderness more enjoyable, safer, and easier.

He’d have been with nature in all its glory, but also connected to the rest of humanity, dipping into the benefits that offers whenever he deemed it necessary or worthwhile. It’s unlikely he’d have felt the urge to check the latest gossip on Twitter or Facebook, but Google Maps, TripAdvisor, and Airbnb sure would have come in handy.

Those more suspicious of today’s hyperconnected technology might say this fails to consider the dark side of sharing your browsing habits, your whereabouts, and other aspects of your existence through your smartphone. To take advantage of the best your device can offer, you must in turn give up so much of your privacy to companies looking to make a buck off the data you’re generating.

Take location-based marketing, for example, which sends location-specific advertisements to consumer’s mobile devices. Sounds pesky and a little… dystopian, doesn’t it? It evokes the scene from the 2002 science fiction movie “Minority Report,” in which Tom Cruise’s character is hit with a personalized ad that tells him he could “use a Guinness right about now.” Pirsig would have felt location-based marketing’s full brunt as he made his way across 2017 America, seeking food, shelter, and supplies.

How would Pirsig have felt about location-based marketing?

Again, though, he likely would have taken a more pragmatic view than the dystopian Luddites. You cannot, surely, buy a 4G smartphone, blindly connect it to servers around the world, and then fly into a rage when you discover your data and location is being sold off to the highest bidder. Unless human microchip implants are written into law, we’ll always have the option to avoid that inevitability.

For those naturally more open to the idea of location-based marketing and the serendipitous moments of magic it can help create – as well as those who stand to profit from it – 2017 looks like being a good year for the technology.

Nearly a third of the world’s population will own a smartphone this year, according to Statista, and 80% of social media activity now happens on mobile devices. This gives companies a much fuller picture of what people are doing and where they’re doing it. People aren’t afraid to use their phones to buy things, either; global mobile e-commerce revenues are projected to reach $549 billion in 2017.

These trends are converging with breakthroughs in technology that are taking location-based marketing to new levels of complexity. Sensors enabling near-field communications (NFC) are not new, but they’re coming down in price. This technology was included in the last two generations of Samsung and Apple phones. Elsewhere, geo-fences use GPS, Wi-Fi, electromagnetic fields, or RFID technologies that capture data from consumers situated in specified areas – a concept Google and Apple are invested in.

Pokémon Go showed that people are ready for augmented reality; again “Minority Report”’s Guinness holograms offer us a vision of how that technology could translate into the world of advertising. And then there’s context, the plumbing of location-based marketing. Context, which feeds on Big Data, is only getting richer, giving brands a deeper understanding of where consumers are, where they’re headed, and what they might want to buy. Done well, all this technological advancement is undeniably useful for consumers too.

So, next time you get out on the open road looking for a clean break from your neurosis-inducing technology habits, consider taking your smartphone with you. It will almost certainly come in handy. As Pirsig might have said (albeit more eloquently), nature and technology are friends, not enemies. Embracing both, warts and all – and embracing them wisely – is the key to living a full and happy life.

For more insight on technology and the well-balanced life, see Give Me Technology, But Help Me Deal With It.

Comments

About Adam Winfield

Adam Winfield writes about technology, how it's affecting industries, how it's affecting businesses, and how it's affecting people.

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.

Comments

Tags:

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.”

Comments

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.