The United Nations predicts that the world population will approach 10 billion by the middle of the century. To feed everyone, we must double the amount of food we currently produce. But the challenge of feeding everyone is not just a production issue. It’s also a distribution and need issue. Even a modest demand increase for protein, for example, can strain land resources, reports the United Nations News Centre, underscoring the need for increased efficiency to meet global needs. Digitization in the agribusiness sector increases the ability to feed the rapidly growing world. Companies including Land O’Lakes, Nestle, and Monsanto are leading the way by reimagining agribusiness models and proactively evolving to meet the world’s changing demands.
Land O’Lakes and GEOSYS: How satellite-gathered crop data is changing agriculture
The complexity of agricultural production is one of its greatest challenges. Every decision affects the next. As an added challenge, by the time an issue is actually visible in the field, it’s often too late to change course: the damage is done. Agriculture is the world’s greatest balancing act. While a traditional prescription may give growers a solid start, the ability to continuously monitor fields via technology solutions empowers growers to make decisions that optimize productivity. Growers can stay one step ahead by “seeing” what the human eye cannot detect.
To better address this challenge, Land O’Lakes acquired GEOSYS, an innovative company that uses satellite-based remote sensing to provide current, actionable data. GEOSYS also draws on historical records throughout the growing season and this data combines with real-time observations. Rather than a “one and done” evaluation of a field, GEOSYS empowers growers through continuous monitoring to optimize productivity along the entire agriculture value chain.
Cargill develops software to guide crop production from farm to fork
Severe weather patterns – from floods to heat waves – are wreaking havoc on crop production, costing farmers millions – and a simple Farmer’s Almanac is insufficient for predicting these changing patterns. What if technology could predict these changes and help farmers avoid crop catastrophe?
Like the Land O’Lakes/GEOSYS partnership, Cargill is also developing its own software service to help guide farmers on crop production and putting its own spin on “prescriptive planting.” The software service offers guidance to farmers on the best timing to plant crops, maximizing farm output. The tool, called NextField DataR, crunches a number of different data pieces, such as soil content, seed type, and temperature fluctuations, to help farmers determine the optimal time for crop planting. The result: farmers have more detailed data about optimal planting times, reducing the risk for crop loss in smallholder farming.
Monsanto, Precision Planting, and Climate Corporation: Empowering agriculture through Big Data
While Monsanto has a reputation for being a business built on chemicals, seeds, and genetic traits, the company is rapidly expanding its data science services, reports Reuters. Monsanto acquired Precision Planting, a manufacturer of precision equipment, and Climate Corporation, a provider of super-local weather information. Monsanto’s expansion shows it is serious about precision farming and has now transformed from a seed business to a data science organization, providing the “glue that holds the pieces together.”
Nestle builds lean upstream supply chains from farm to factory via Farmer Connect
Nearly half of all Nestle factories (46%) are located in emerging countries, and 74% of those factories are located in rural areas. Nestle faces a unique challenge: how to locally source raw materials (like milk, grains, and cocoa) while ensuring responsible farming, production, and consumption practices. Nestle’s solution: the Farmer Connect program.
Nestle is not only buying from rural farmers, but is also investing in farmer training to secure a sustainable and high-quality supply of commodities, such as specialty coffee, and improve food traceability. Nestle’s Farmer Connect program is designed to ensure long-term supply of safe, quality-assured, and regulatory-compliant agricultural materials to consumers that also comply with responsible farming practices. In Western Africa, for example, Nestle partnered with the International Institute for Tropical Agriculture to train 10,000 farmers on good agriculture and storage practices. Farmers now meet Nestle quality production standards and achieve a price premium on their goods. The farmers benefit from expanded market access for locally produced grains in Western Africa, and Nestle benefits from replicable and consistent quality and food safety via sustainable production.
John Deere: Fleet telemetrics empower remote equipment management
Still think of John Deere as just a tractor company? Think again: John Deere has 2,600 employees that come to work every morning just to develop software solutions to optimize John Deere fleet performance. John Deere is providing fleet telematics solutions that make it easier for farmers to remotely manage their equipment and analyze sensor data in real-time.
JDLinks is John Deere’s telemetrics system that remotely connects all make/model machines in the field with mobile devices. Farmers can keep track of their fleet, monitor work progress, analyze performance, and perform remote operator support and automated data exchange. John Deere also offers a new FarmSite service package that increases machine uptime by utilizing remote dealer service capabilities including CAN-data tracking, diagnostics, software updates, and operator support. John Deere is also a leader in predictive maintenance, integrating sensor data, business data, and environmental data to proactively manage equipment-servicing needs and reduce downtime.
What’s next for digital farming
For farmers and food manufacturers alike, the road map to relevance requires reimagining agribusiness models and proactively evolving. Increased hyperconnectivity is allowing farmers from Western Africa to the United States to improve crop productivity, food safety, and sustainability practices. Improving vertical integration along the agricultural value chain means that industry boundaries are blurring. As agribusinesses reimagine their business models, business processes, and work, they must engage with new partners as technology continues to drive collaborative value.
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About Bill Hamilton
Bill Hamilton is a director in the Industry Cloud Solution group for agribusiness with a focus on commodities at SAP. His C-level experience surrounding the comprehensive transaction cycles bring deep and valuable expertise to SAP and its customers, which is essential to address the growing needs of the agribusiness industry.
Millions of people around the world still lack consistent access to the basics of modern life. They also lack resources to build conventional infrastructure in order to obtain essentials such as water and a consistent supply of electricity. Enter frugal innovation—a process for simplifying complex technologies so they are less expensive to produce and operate. Two startups have devised affordable systems that give people access to essential utilities.
Waterpoint Data Transmitter
About 780 million people, mainly in rural locations, don’t have indoor plumbing. Instead, they rely on hand pumps to access groundwater. Sooner or later, these hand pumps break and often aren’t fixed due to lack of parts and know-how. By some estimates, one-third of pumps aren’t functioning at any given time.
OxWater, a startup launched from Oxford University, has a solution that incorporates basic cell phone technology. The Waterpoint Data Transmitter is a monitoring device that communities deploy to track pump usage. If a pump stops working, a local, trained repair team receives a notification to fix it. The device also provides predictions of which pumps are likely to break and reports low water levels. A pilot project in Kenya showed a dramatic reduction in repair times, from an average of 37 days down to just two.
Solar power has become an important technology for people living in off-the-grid rural environments. But once the sun goes down, or during spells of cloudy days, the solar panels may not generate enough electricity. That often means a return to inefficient and unsafe solutions, such as kerosene lamps for lighting.
Azuri Technologies has developed a simple, independent system that enables solar users to adapt the amount of power they use according to the amount of energy they generate. The Quad is a small wall-mounted unit that’s wired to a solar panel that comes with a USB port for mobile phone charging. The system uses the company’s HomeSmart technology to monitor local weather patterns and learn consumers’ energy usage. Then, based on available energy, it automatically regulates the amount of power used for lighting (by, for example, adjusting brightness) and battery charging.
A 5-watt system costs about US$156, which users can pay off weekly using a mobile money account. Once they own the unit, they can generate power at no cost. Since its launch in Kenya in 2011, 90,000 Quads have been purchased in 12 African countries.
Preventing disasters and delivering aid when they do hit are difficult in isolated locations, where there aren’t enough services that enable quick reaction. Complexity and cost can also keep aid from reaching its targets. These startups are using frugal technology in imaginative ways to issue alerts of impending problems and deliver help to people in need.
Disaster relief is an uphill race against the clock. Whether responding to a natural disaster, war, or famine, aid workers must assemble and deliver supplies, navigate around natural obstacles, avoid thieves, and stay safe. Windhorse Aerospace has developed POUNCER, a disposable drone, to address these problems.
Designed for takeoff from a C-130 Hercules military transport plane and guided using a built-in GPS, POUNCER can be launched from up to 40 kilometers from its destination, with a landing accuracy of within 7 meters. The drone can carry enough food and water rations for 50 people. What’s more, every part is reusable and disposable. For example, the frame, which has a 3-meter wingspan, can be used for shelter or burned for fuel (Windhorse is meanwhile looking to develop an edible frame). Because the entire unit is designed for on-site use, there’s also no cost or peril involved in recovering it from the disaster area.
Many of the world’s poor live in shacks that are built very close together, and they lack electricity. As a result, they rely heavily on open flames for light, heat, and cooking, creating a high risk of fire. But conventional smoke detectors can’t be relied on in places that are already smoky. One devastating fire in Cape Town, South Africa, prompted a group of local university students to design a fire detection device specifically for these environments.
The Lumkani detector is a small wall-mounted unit that runs on batteries and, instead of being triggered by smoke, detects fires by monitoring temperature increases. The detectors use basic radio frequency technology to link all units within a 60-meter radius to a mesh network, which enables early warning alerts for the surrounding inhabitants. The $7 device also stores GPS coordinates, sends warning texts to residents, and can self-monitor the operating health of the whole linked system. Lumkani is working on a way to send real-time data to local emergency response units.
Data at the Digital Frontier
Do you own the land you’re farming? When will the next rainstorm hit? These are basic questions, but for some people living in emerging economies, they’re not so easy to answer. Startups are using clever designs and simple interfaces to provide the information that rural communities need to thrive.
For millions of small landowners around the world, verifying a legal claim to their land is a complex, expensive, and practically insurmountable process. And without documentation that proves that they own their land, protecting their property rights is nearly impossible, as is getting loans to expand their land holdings and businesses.
Landmapp, based in Amsterdam and operating in Ghana, has developed a mobile platform to make mapping and filing claims accessible to small landowners. The company educates farmers about property rights and then, for a small fee, uses its own platform to record and legally validate land ownership. Landmapp uses geospatial technology and cloud data on a tablet, meaning they don’t need fancy and expensive surveying equipment. FarmSeal, Landmapp’s first product, serves farmers; the company is also launching HomeSeal, for homeowners, and CropSeal, for sharecroppers and landowners. The startup’s platform incorporates local government, legal, and traditional community agreements, and is customizable for different locales.
3D-Printed Weather Stations
Weather data drives numerous economic and public safety decisions. But in many countries, a scarcity of weather stations means no data about vast geographic areas. Unfortunately, conventional weather stations are expensive, costing upwards of $20,000 per unit. In emerging economies, governments and rural communities don’t have the resources or training to buy and maintain them.
At the nonprofit university consortium University Corporation for Academic Research, researchers are leveraging 3D printing to fill the weather gap. They’ve devised a weather station that local government agencies can install in rural communities. The units use off-the-shelf, basic sensors, store data on a small computer, and run on energy generated by a single solar panel. The local agencies have 3D printers to create other parts, including the frame and wind gauges, which can be easily customized or replaced.
The cost? About $300. And beyond letting communities know when, for example, rain is on the horizon, the unit can also be a first alert for natural disasters, like floods.
Back in early December, The Guardian ran an article asking whether the Internet of Things will save or sacrifice the environment. As you’d expect, the answer is far from clear. Some environmentalists worry about the effects of producing, installing, and powering those billions of extra devices; others urge the use of IoT sensor networks to help us monitor and curb resource consumption and emissions.
On the surface, the thought of creating huge wireless sensor networks for the benefit of the environment seems paradoxical. However, there is a much bigger picture lurking underneath. The Global e-Sustainability Initiative’s (GeSI) recent #SMARTer2030 report suggests that IoT-related technologies could save “almost 10 times the carbon dioxide emissions that it generates by 2030 through reduced travel, smart buildings, and greater efficiencies in manufacturing and agriculture.”
Even if we achieve a situation in which physical IoT devices have a net positive effect on humanity’s carbon footprint, there is still the massive data transmission and storage growth to consider. Speaking as an executive of a company providing the cloud-based data platform for IoT networks, I can say that it’s in our best interests to keep energy consumption as low as possible, because it costs less. That’s why data centers are built with energy efficiency top of mind.
Ultimately, whether or not the IoT turns out to be an environmentalist’s dream will depend on how we apply its concepts. If it’s primarily used to stream endless high-quality video feeds 24 hours a day or for power-hungry gimmicks and trivialities, the footprint will be far worse than if it’s used directly to get resource and energy management under control. It seems unlikely that the private sector and consumers alone will summon the collective motivation to veer in the direction of the latter, so policy will need to keep up and be sound and assertive.
The attitude of disposability in Western society today is another issue altogether. Perfectly functional year-old smartphones and computers are piling up in landfills across the globe as consumers struggle to resist the lure of the latest model. Can the IoT buck this trend by being founded on sensor networks built to last? With the world trending away from centralized hardware and toward cloud-based software, it could be that upgrades to the virtual aspects of IoT will be enough to satisfy our lust for innovation, while the sensors hum away out of sight and out of mind.
Time will tell.
Register here to listen to an SAP Live webcast in which IBM’s IoT guru Michael Martin discusses the possibilities and challenges of our connected future.
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About John Graham
John Graham is president of SAP Canada. Driving growth across SAP’s industry-leading cloud, mobile, and database solutions, he is helping more than 9,500 Canadian customers in 25 industries become best-run businesses.
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.
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!
Despite the progress made in some countries, I am also aware of others that are still resistant to digitizing their economy and automating operations. What’s the difference between firms that are digital leaders and those that are slow to mature? From my perspective in working with a variety of businesses throughout Europe, it’s a combination of diversity and technology availability.
European companies are hardly homogenous. Comprising 47 countries across the continent, they serve communities that speak any of 225 spoken languages. Each one is experiencing various stages of digital development, economic stability, and workforce needs.
Nevertheless, as a whole, European firms do prioritize customer acquisition as well as improving efficiency and reducing costs. Over one-third of small and midsize companies are investing in collaboration software, customer relationship management solutions, e-commerce platforms, analytics, and talent management applications. Steadily, business leaders are finding better ways to go beyond data collection by applying predictive analytics to gain real-time insight from predictive analytics and machine learning to automate processes where possible.
Small and midsize businesses have a distinct advantage in this area over their larger rivals because they can, by nature, adopt new technology and practices quickly and act on decisions with greater agility. Nearly two-thirds (64%) of European firms are embracing the early stages of digitalization and planning to mature over time. Yet, the level of adoption depends solely on the leadership team’s commitment.
For many small and midsize companies across this region, the path to digital maturity resides in the cloud, more so than on-premise software deployment. For example, the flexibility associated with cloud deployment is viewed as a top attribute, especially among U.K. firms. This brings us back to the diversity of our region. Some countries prioritize personal data security while others may be more concerned with the ability to access the information they need in even the most remote of areas.
Technology alone does not deliver digital transformation
Digital transformation is certainly worth the effort for European firms. Between 60%–90% of small and midsize European businesses say their technology investments have met or exceeded their expectations – indicative of the steady, powerhouse transitions enabled by cloud computing. Companies are now getting the same access to the latest technology, data storage, and IT resources.
However, it is also important to note that a cloud platform is only as effective as the long-term digital strategy that it enables. To invigorate transformative changes, leadership needs to go beyond technology and adopt a mindset that embraces new ideas, tests the fitness of business models and processes continuously, and allows the flexibility to evolve the company as quickly as market dynamics change. By taking a step back and integrating digital objectives throughout the business strategy, leadership can pull together the elements needed to turn technology investments into differentiating, sustainable change. For example, the best talent with the right skills is hired. Plus, partners and suppliers with a complementary or shared digital vision and capability are onboarded.
The IDC Infobrief confirms what I have known all along: Small and midsize businesses are beginning to digitally mature and maintain a strategy that is relevant to their end-to-end processes. And furthering their digital transformation go hand in hand with the firms’ ability to ignite a transformational force that will likely progress Europe’s culture, social structure, and economy.