Will Data Analytics Lead To Breakthrough In Cancer Treatment?

Christine Donato

molecular health 5Early this summer, I had the pleasure of talking with Mark Rodgers, North American director of corporate communications and public relations, and Alexander Picker, EVP product management, both from Molecular Health. Speaking to them only strengthened my (already rooted) passion for healthcare and my belief that advanced technology can fix a struggling industry.

Changing the way doctors approach cancer

In 2000, for the first time, doctors read all 3.4 billion DNA pairs in the human genome. This insight into the complete genetic blueprint for building a human being opened the door to new and more-effective treatments for diseases like cancer. However, back then, this process of genetic sequencing was costly and time-consuming.

In 2014, Molecular Health invented its end-to-end offering TreatmentMAP TM, which runs on the SAP HANA platform. It translates the language of genes into actionable information that doctors and patients can use to make informed decisions about cancer care.

Now, thanks to Molecular Health, information on a person’s complete genomic sequence can be read relatively cost-effectively and in just a few days.

Turning information into action

As Rodgers and Picker explained, the same cancer treatment that saves one person may be toxic to the health of another. Each case of cancer is unique, and it’s very difficult to determine what treatments will have negative side effects on patients and what will work well. There’s no one-size-fits-all treatment.

With precision medicine, or the practice of analyzing existing treatments to see which is best equipped to tackle a particular case of cancer, Molecular Health is on the forefront of a paradigm shift that can radically improve the prevention and treatment of cancer.

How the analysis works

To start the process, a doctor sends a tissue sample from a patient’s tumor to the Molecular Health laboratory. The tissue sample contains both cancerous cell material and healthy cell material from the patient.

At the lab, using TreatmentMAP TM, the sample is genetically analyzed and the cancerous genome sequence is compared to the patient’s healthy genome sequence. Then TreatmentMAPTM compares the patient’s genetic material to the massive amount of available research and clinical information that Molecular Health has been collecting over the past 10 years on biomedical knowledge. This data pool contains information from over 23 million publications, hundreds of cancer indicators, 37,000 drugs, more than 90,000 clinical studies, and more.

After a few hours, the treatment options for the patient are identified, and a specially certified oncologist uses TreatmentMAP  TM to analyze the results and prepare a report for the treating physician. This report contains effective and ineffective treatment methods for this particular instance of cancer, as well as any risks of side effects or toxicity.

It takes about two weeks total from when the physician originally sends out the patient’s sample to when the physician receives the TreatmentMAP TM report. Physicians can then view the best treatments that exist for that particular patient’s instance of cancer, being sure to avoid any treatment that may be harmful to the patient.

COPE-ing with cancer

SAP and Molecular Health have teamed to provide SAP employees with the Corporate Oncology Program for Employees (COPE). Through COPE, Molecular Health partners with corporations to provide employees diagnosed with cancer access to TreatmentMAP TM. The individual tumor analysis and interpretation is part of the company’s benefits package.

SAP was the first company to ever offer COPE to its employees. Through the program, SAP hopes to inspire wider adoption of similar programs among other companies and to make this technology available to as many people as possible.

Future goals

In the future, Molecular Health aims to play a bigger role in drug evaluation and safety for cancer patients. In addition, the organization’s main goal is to expand beyond the treatment of cancer and explore the treatment of other diseases, as well as expand the TreatmentMAP TM approach to cover the complete patient lifestyle.

Molecular Health wants to target healthy patients and work toward early identification and disease prevention. The company wants to make its technology directly available to the consumer.

For more stories, follow me on Twitter and LinkedIn.

To learn how your organization can benefit from real-time analytics, click here.

This post originally appeared on SCN in SAP Business Trends.


About Christine Donato

Christine Donato is a Senior Integrated Marketing Specialist at SAP. She is an accomplished project manager and leader of multiple marketing and sales enablement campaigns and events, that supported a multi million euro business.

How Can Machine Learning Help Eradicate Modern Slavery In Supply Chains?

Shelly Dutton

Hidden in the dark corners of everyday supply chains is a US$51 billion illegal market, comprised of 40.3 million enslaved people – 75% of whom are women. From agriculture and manufacturing to domestic servitude, women are trapped in a supply chain that contains an inescapable cycle of forced labor with little to no pay, daily violence, threats, substandard conditions, and long hours.

Investigative journalists have for years exposed modern slavery in many leading brands’ supply chains. And often the response from reported companies is met with shock, denial, and silence.

But if we look closely at their released statements or lack of acknowledgment, a persisting underlying problem emerges: a lack of transparency across the entire supply chain, including the suppliers of their suppliers.

Unraveling the pervasiveness of forced labor practices in supply chains

The more connected and globalized our world becomes, the riskier supply chains become. Competitive realities are forcing businesses to make decisions that balance cost and quality as well as access and sustainability. But in an environment where cost and access are typically valued more, companies act unknowingly as an accessory to modern-day slavery.

According to Justin Dillion, CEO and founder of Made in a Free World, the best way to eradicate this problem is to help consumers and businesses buy better. During the SAP-sponsored Webcast Monitoring Ethics Deep in the Supply Chain, he said that businesses need to be empowered to “look at these issues more specifically – and do that through the lens of spend data.”

Consider, for example, a global firm with a supply chain consisting of 60,000 vendors and resellers. Such a high volume of suppliers in its network would likely include at least a couple hundred vendors that could expose operations to instances of women in forced labor. And this is not a fictional hypothetical. In fact, Thomson Reuters’ 2016 Global Third-Party Risk Survey revealed that only 36% of surveyed businesses thoroughly monitor their suppliers for risks, while 61% have no knowledge of the outsourcing activities of their third parties.

Overcoming growing complexity to end supply chain exploitation

Businesses can overcome exposure with a platform that gives a clear view of the entire supply chain. Access to real-time intelligence data from online news, media, and government organizations enable buyers, procurement managers, and supply chain leaders to make better-informed sourcing strategies. When drilling down into the data, everyone who touches the supply chain can identify high-risk exposure based on a variety of factors.

With a sense of the risks behind their purchases, they can remediate known sources of modern slavery to improve brand integrity and document it to comply with reporting regulations – but this is just the beginning. Machine learning can further extend insights by uncovering unknown, otherwise invisible, events through the detection of patterns.

Self-learning procurement processes empower businesses to connect the dots quickly between primary, secondary, and tertiary supplier relationships. This application of machine learning not only roots out hidden enslavement practices deep in the supply chain, but it accomplishes it in a way that minimizes supply chain disruption and keeps costs low.

Machine learning turns a noble purpose into a business opportunity

Machine learning gives procurement and supply chain organizations a strategic weapon for freeing millions of women from modern slavery. However, this digital approach is more than just a noble purpose. It’s a strategic investment for identifying effective supply chain practices that meet the demands of customers, investors, and employees that want to see slavery eradicated for good.

It doesn’t matter how far in the supply chain modern slavery resides. Every business along the value chain – from the originating supplier to the final seller – will feel its impact. By “walking the walk” on ethical supply chain operations, businesses are not just doing good – they’re lifting their bottom lines with new sources of growth and innovation.

For more on this topic, see Combating Modern Slavery: It’s More Than Compliance, It’s Ethics!


Unleashing The Power Of Digital: A Technologist’s View Of Data-Driven Innovation In Healthcare

Mala Anand

We see a paradigm shift happening with a new notion of a connected enterprise. A mass transformation is happening in the market with billions of increasingly connected information-gathering devices and business processes. This hyperconnectivity across people, data, process, and things creates a new intersection of business and technology. It’s kept me busy for over 20 years, promoting innovation and championing the impact digital technology can have on our lives.

And just look at what it’s done in those two decades. In education, for example, technology has simplified access to knowledge, and more than 25% of today’s college students are enrolled in an online course. In our relationships, technology helps us stay in touch with childhood friends, it lets us see what our kids are up to, and 90% of single adults have tried online dating. Ninety percent.

When you think of technology, think of what Uber has done to transportation and how videoconferencing has diminished the need for business travel.

The very way we work has been forever changed. Automation, artificial intelligence, and robotics have dramatically altered the labor market, driving a projected 30% increase in productivity over the next 10 years.

The point of all this: digital technology has had an undeniable impact on how we operate. How we live. It has made our everyday lives easier and, for the most part, better.

The City of Karlsruhe, Germany, for example, established a network of smart lampposts across town, collecting and monitoring traffic and emissions data. With this solution, the city can respond in real time to improve traffic flow and air quality.

A major telecommunications company in Japan started to measure drivers’ biomedical data as they move from place to place. The data was combined with GPS location information to provide a comprehensive safety analysis, reducing driver fatigue and detecting safety solutions as they’re needed.

Through such partnerships, combining business and technology, customers are using data to transform everything from pollution control to safety to quality of life.

But as we look at what is real and revolutionary change, let me ask you this: Are we seeing that same, transformational impact in healthcare?

So why can’t healthcare keep up?

Let’s take a look at where healthcare stands. Consider four statistics from the World Health Organization:

  • One in six deaths is caused by cancer
  • 422 million people have diabetes – and 50% are undiagnosed
  • Cardiovascular disease is the leading cause of death globally, accounting for more than 17 million deaths in 2015
  • And chronic diseases like diabetes accounted for seven of the top 10 causes of death in 2014

Naturally, there is some digital innovation in healthcare – take the digitization of patient records through electronic health records, for example – but when you look at stats like those above, you know there’s room for improvement. SAP and Oxford Economics surveyed nearly 400 healthcare executives and found 70% feel that the latest technologies are essential to growth, competitive advantage, and customer experience. But while some healthcare organizations are piloting digital transformation initiatives, few have achieved full digital maturity.

The question is: why?

First, in the healthcare industry the economics rewards treatment, not prevention. As a result, we’ve seen investment and innovation in new therapies, drugs, and medical devices, but we have not seen equal investment in wellness. We’ve been fighting the fire instead of preventing it.

Second, innovation has focused on hardware, not software. So, we have sophisticated devices for diagnostics, but we still have an immature infrastructure to capture and manage the data they generate.

Finally, systems are disconnected and data is siloed. And in the context of a highly regulated industry, this limits collaboration.

Digital transformation in action

To illustrate the impact of these challenges, let’s take a look what’s happening in the field of cancer treatment.

When you have cancer, you hope your doctors are basing their recommendations on the best trial results combined with external data on how other patients like you have been treated. But in most cases, decision-making is far less data-driven. In fact, only five percent of cancer patients enroll in clinical trials. (And is that five percent truly representative of real-world patients?) As a result, doctors have to extrapolate study findings and rely on their own experience.

We can do better. And we are doing better.

Treating cancer with data

The journey to transforming cancer treatment with digital technologies started at the National Center for Tumor Diseases (NCT) in Heidelberg, Germany, which used technology to identify tumor markers from physicians’ notes. Now, while sitting with a patient, physicians can search both local case histories and tumor registries to identify groups of similar patients who have already been treated – helping both doctor and patient understand the outcomes of various therapies.

The American Society for Clinical Oncology developed CancerLinQ – a tool that integrates data from more than 100 clinics and 1 million patients – to help oncologists make better treatment decisions. It will create a network effect through large sets of clinical data.

Gustave Roussy, one of the world’s premier cancer research institutes and treatment centers, is accessing and exploring both clinical and genomic data from more than 300,000 patients. With the reach of this organization plus the others, the industry will keep extending those capabilities to a form broad network in Europe: the Cancer Core Network.

And we’re just getting started. What we’re seeing with this work is organizations rising above their individual institutions to deliver exponential value to patients around the world.

Cancer is just one example. There are many more diseases and patient-centric use cases that will benefit from high-performance technology.

How do we apply this to healthcare holistically?

The first thing we must do as an industry is break the status quo by committing to data-driven decision-making and respecting data as a first-class asset. From there:

  1. Establish a governance framework so that data is formally, consistently, and securely managed across the organization.
  1. Connect to all data, irrespective of source or format. This includes health-related data beyond the clinical environment.
  1. Democratize the data and make it available through the organization to foster a culture of data-driven decision-making.

Now, while data is the “what” that we must focus on, technology is the “how.” And you don’t need to replace your IT infrastructure to make it work. Instead, leverage and extend your current systems through cloud-based solutions. And as you bring new technologies, make sure they’re:

  • Open – systems that can be integrated with your current stack
  • Scalable – to accommodate for ever-increasing data and expanding datasets
  • Real-time – to maximize impact on patients

Finally, and this is the most important thing to remember: Put the patient at the center of your digitization journey.

As you look at developing new solutions, start from the patient and work backwards. Get input from all key constituents (e.g., nurses, physicians, family members) as you develop new solutions. Create positive, immersive patient experiences. And remember: Quality of care is as much a clinical outcome metric as the quality of patient experience.

Steve Jobs once said:

“The biggest innovations of the 21st century will be at the intersection of biology and technology.”

As I mentioned, I work at the intersection of business and technology, and I use this quote by Jobs because of his unique and powerful perspective.

Obviously, Jobs was a technology giant – an innovator regarded as one of the most creative and forward-thinking minds in technology. But he was also a man who battled cancer and who had a liver transplant.

What he’s telling us is that we need each other. The biggest innovations in healthcare will be born from collaboration – within organizations and across organizations, between providers, payers, researchers, and technology companies.

The challenge for us all is to embrace this concept of collaboration. To recognize that our work together is not just about transforming our industry, but about saving lives around the world.

We can do it if we do it if we come together at the intersection.

For another look at how technology is improving healthcare and saving lives, see Mapping A New Strategy To Fight Opioid Addiction.


Mala Anand

About Mala Anand

Mala Anand is President of SAP Leonardo & Analytics at SAP, leading the end-to-end business including go-to-market, product development and strategy. With her primary focus on product development, market acceleration and adoption in one of SAP’s core innovation areas, Mala develops and executes strategy across all markets and ensures operational excellence within the global GTM and product development teams. The core focus of the SAP Analytics business encompasses business intelligence with embedded predictive and machine learning innovations across large data sets. Formerly, Mala led the Data & Analytics | Automation Software Platforms business at Cisco Systems with a focus on innovative solutions to aggregate and analyze today’s hyper-distributed and real-time streaming data. With over 20 years of experience as a senior software executive, Mala places a deep focus on delivering innovative solutions to the market that help customers develop informed, timely insights to establish new modes of engaging their workforce and customers.

The Human Angle

By Jenny Dearborn, David Judge, Tom Raftery, and Neal Ungerleider

In a future teeming with robots and artificial intelligence, humans seem to be on the verge of being crowded out. But in reality the opposite is true.

To be successful, organizations need to become more human than ever.

Organizations that focus only on automation will automate away their competitive edge. The most successful will focus instead on skills that set them apart and that can’t be duplicated by AI or machine learning. Those skills can be summed up in one word: humanness.

You can see it in the numbers. According to David J. Deming of the Harvard Kennedy School, demand for jobs that require social skills has risen nearly 12 percentage points since 1980, while less-social jobs, such as computer coding, have declined by a little over 3 percentage points.

AI is in its infancy, which means that it cannot yet come close to duplicating our most human skills. Stefan van Duin and Naser Bakhshi, consultants at professional services company Deloitte, break down artificial intelligence into two types: narrow and general. Narrow AI is good at specific tasks, such as playing chess or identifying facial expressions. General AI, which can learn and solve complex, multifaceted problems the way a human being does, exists today only in the minds of futurists.

The only thing narrow artificial intelligence can do is automate. It can’t empathize. It can’t collaborate. It can’t innovate. Those abilities, if they ever come, are still a long way off. In the meantime, AI’s biggest value is in augmentation. When human beings work with AI tools, the process results in a sort of augmented intelligence. This augmented intelligence outperforms the work of either human beings or AI software tools on their own.

AI-powered tools will be the partners that free employees and management to tackle higher-level challenges.

Those challenges will, by default, be more human and social in nature because many rote, repetitive tasks will be automated away. Companies will find that developing fundamental human skills, such as critical thinking and problem solving, within the organization will take on a new importance. These skills can’t be automated and they won’t become process steps for algorithms anytime soon.

In a world where technology change is constant and unpredictable, those organizations that make the fullest use of uniquely human skills will win. These skills will be used in collaboration with both other humans and AI-fueled software and hardware tools. The degree of humanness an organization possesses will become a competitive advantage.

This means that today’s companies must think about hiring, training, and leading differently. Most of today’s corporate training programs focus on imparting specific knowledge that will likely become obsolete over time.

Instead of hiring for portfolios of specific subject knowledge, organizations should instead hire—and train—for more foundational skills, whose value can’t erode away as easily.

Recently, educational consulting firm Hanover Research looked at high-growth occupations identified by the U.S. Bureau of Labor Statistics and determined the core skills required in each of them based on a database that it had developed. The most valuable skills were active listening, speaking, and critical thinking—giving lie to the dismissive term soft skills. They’re not soft; they’re human.


This doesn’t mean that STEM skills won’t be important in the future. But organizations will find that their most valuable employees are those with both math and social skills.

That’s because technical skills will become more perishable as AI shifts the pace of technology change from linear to exponential. Employees will require constant retraining over time. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is already outdated by the time students graduate, according to The Future of Jobs, a report from the World Economic Forum (WEF).

The WEF’s report further notes that “65% of children entering primary school today will ultimately end up working in jobs that don’t yet exist.” By contrast, human skills such as interpersonal communication and project management will remain consistent over the years.

For example, organizations already report that they are having difficulty finding people equipped for the Big Data era’s hot job: data scientist. That’s because data scientists need a combination of hard and soft skills. Data scientists can’t just be good programmers and statisticians; they also need to be intuitive and inquisitive and have good communication skills. We don’t expect all these qualities from our engineering graduates, nor from most of our employees.

But we need to start.

From Self-Help to Self-Skills

Even if most schools and employers have yet to see it, employees are starting to understand that their future viability depends on improving their innately human qualities. One of the most popular courses on Coursera, an online learning platform, is called Learning How to Learn. Created by the University of California, San Diego, the course is essentially a master class in human skills: students learn everything from memory techniques to dealing with procrastination and communicating complicated ideas, according to an article in The New York Times.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing.

Although there is a longstanding assumption that social skills are innate, nothing is further from the truth. As the popularity of Learning How to Learn attests, human skills—everything from learning skills to communication skills to empathy—can, and indeed must, be taught.

These human skills are integral for training workers for a workplace where artificial intelligence and automation are part of the daily routine. According to the WEF’s New Vision for Education report, the skills that employees will need in the future fall into three primary categories:

  • Foundational literacies: These core skills needed for the coming age of robotics and AI include understanding the basics of math, science, computing, finance, civics, and culture. While mastery of every topic isn’t required, workers who have a basic comprehension of many different areas will be richly rewarded in the coming economy.
  • Competencies: Developing competencies requires mastering very human skills, such as active listening, critical thinking, problem solving, creativity, communication, and collaboration.
  • Character qualities: Over the next decade, employees will need to master the skills that will help them grasp changing job duties and responsibilities. This means learning the skills that help employees acquire curiosity, initiative, persistence, grit, adaptability, leadership, and social and cultural awareness.


The good news is that learning human skills is not completely divorced from how work is structured today. Yonatan Zunger, a Google engineer with a background working with AI, argues that there is a considerable need for human skills in the workplace already—especially in the tech world. Many employees are simply unaware that when they are working on complicated software or hardware projects, they are using empathy, strategic problem solving, intuition, and interpersonal communication.

The unconscious deployment of human skills takes place even more frequently when employees climb the corporate ladder into management. “This is closely tied to the deeper difference between junior and senior roles: a junior person’s job is to find answers to questions; a senior person’s job is to find the right questions to ask,” says Zunger.

Human skills will be crucial to navigating the AI-infused workplace. There will be no shortage of need for the right questions to ask.

One of the biggest changes narrow AI tools will bring to the workplace is an evolution in how work is performed. AI-based tools will automate repetitive tasks across a wide swath of industries, which means that the day-to-day work for many white-collar workers will become far more focused on tasks requiring problem solving and critical thinking. These tasks will present challenges centered on interpersonal collaboration, clear communication, and autonomous decision-making—all human skills.

Being More Human Is Hard

However, the human skills that are essential for tomorrow’s AI-ified workplace, such as interpersonal communication, project planning, and conflict management, require a different approach from traditional learning. Often, these skills don’t just require people to learn new facts and techniques; they also call for basic changes in the ways individuals behave on—and off—the job.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing. As science gains a better understanding of how the human brain works, many behaviors that affect employees on the job are understood to be universal and natural rather than individual (see “Human Skills 101”).

Human Skills 101

As neuroscience has improved our understanding of the brain, human skills have become increasingly quantifiable—and teachable.

Though the term soft skills has managed to hang on in the popular lexicon, our understanding of these human skills has increased to the point where they aren’t soft at all: they are a clearly definable set of skills that are crucial for organizations in the AI era.

Active listening: Paying close attention when receiving information and drawing out more information than received in normal discourse

Critical thinking: Gathering, analyzing, and evaluating issues and information to come to an unbiased conclusion

Problem solving: Finding solutions to problems and understanding the steps used to solve the problem

Decision-making: Weighing the evidence and options at hand to determine a specific course of action

Monitoring: Paying close attention to an issue, topic, or interaction in order to retain information for the future

Coordination: Working with individuals and other groups to achieve common goals

Social perceptiveness: Inferring what others are thinking by observing them

Time management: Budgeting and allocating time for projects and goals and structuring schedules to minimize conflicts and maximize productivity

Creativity: Generating ideas, concepts, or inferences that can be used to create new things

Curiosity: Desiring to learn and understand new or unfamiliar concepts

Imagination: Conceiving and thinking about new ideas, concepts, or images

Storytelling: Building narratives and concepts out of both new and existing ideas

Experimentation: Trying out new ideas, theories, and activities

Ethics: Practicing rules and standards that guide conduct and guarantee rights and fairness

Empathy: Identifying and understanding the emotional states of others

Collaboration: Working with others, coordinating efforts, and sharing resources to accomplish a common project

Resiliency: Withstanding setbacks, avoiding discouragement, and persisting toward a larger goal

Resistance to change, for example, is now known to result from an involuntary chemical reaction in the brain known as the fight-or-flight response, not from a weakness of character. Scientists and psychologists have developed objective ways of identifying these kinds of behaviors and have come up with universally applicable ways for employees to learn how to deal with them.

Organizations that emphasize such individual behavioral traits as active listening, social perceptiveness, and experimentation will have both an easier transition to a workplace that uses AI tools and more success operating in it.

Framing behavioral training in ways that emphasize its practical application at work and in advancing career goals helps employees feel more comfortable confronting behavioral roadblocks without feeling bad about themselves or stigmatized by others. It also helps organizations see the potential ROI of investing in what has traditionally been dismissed as touchy-feely stuff.

In fact, offering objective means for examining inner behaviors and tools for modifying them is more beneficial than just leaving the job to employees. For example, according to research by psychologist Tasha Eurich, introspection, which is how most of us try to understand our behaviors, can actually be counterproductive.

Human beings are complex creatures. There is generally way too much going on inside our minds to be able to pinpoint the conscious and unconscious behaviors that drive us to act the way we do. We wind up inventing explanations—usually negative—for our behaviors, which can lead to anxiety and depression, according to Eurich’s research.

Structured, objective training can help employees improve their human skills without the negative side effects. At SAP, for example, we offer employees a course on conflict resolution that uses objective research techniques for determining what happens when people get into conflicts. Employees learn about the different conflict styles that researchers have identified and take an assessment to determine their own style of dealing with conflict. Then employees work in teams to discuss their different styles and work together to resolve a specific conflict that one of the group members is currently experiencing.

How Knowing One’s Self Helps the Organization

Courses like this are helpful not just for reducing conflicts between individuals and among teams (and improving organizational productivity); they also contribute to greater self-awareness, which is the basis for enabling people to take fullest advantage of their human skills.

Self-awareness is a powerful tool for improving performance at both the individual and organizational levels. Self-aware people are more confident and creative, make better decisions, build stronger relationships, and communicate more effectively. They are also less likely to lie, cheat, and steal, according to Eurich.

It naturally follows that such people make better employees and are more likely to be promoted. They also make more effective leaders with happier employees, which makes the organization more profitable, according to research by Atuma Okpara and Agwu M. Edwin.

There are two types of self-awareness, writes Eurich. One is having a clear view inside of one’s self: one’s own thoughts, feelings, behaviors, strengths, and weaknesses. The second type is understanding how others view us in terms of these same categories.

Interestingly, while we often assume that those who possess one type of awareness also possess the other, there is no direct correlation between the two. In fact, just 10% to 15% of people have both, according to a survey by Eurich. That means that the vast majority of us must learn one or the other—or both.

Gaining self-awareness is a process that can take many years. But training that gives employees the opportunity to examine their own behaviors against objective standards and gain feedback from expert instructors and peers can help speed up the journey. Just like the conflict management course, there are many ways to do this in a practical context that benefits employees and the organization alike.

For example, SAP also offers courses on building self-confidence, increasing trust with peers, creating connections with others, solving complex problems, and increasing resiliency in the face of difficult situations—all of which increase self-awareness in constructive ways. These human-skills courses are as popular with our employees as the hard-skill courses in new technologies or new programming techniques.

Depending on an organization’s size, budget, and goals, learning programs like these can include small group training, large lectures, online courses, licensing of third-party online content, reimbursement for students to attain certification, and many other models.

Human Skills Are the Constant

Automation and artificial intelligence will change the workplace in unpredictable ways. One thing we can predict, however, is that human skills will be needed more than ever.

The connection between conflict resolution skills, critical thinking courses, and the rise of AI-aided technology might not be immediately obvious. But these new AI tools are leading us down the path to a much more human workplace.

Employees will interact with their computers through voice conversations and image recognition. Machine learning will find unexpected correlations in massive amounts of data but empathy and creativity will be required for data scientists to figure out the right questions to ask. Interpersonal communication will become even more important as teams coordinate between offices, remote workplaces, and AI aides.

While the future might be filled with artificial intelligence, deep learning, and untold amounts of data, uniquely human capabilities will be the ones that matter. Machines can’t write a symphony, design a building, teach a college course, or manage a department. The future belongs to humans working with machines, and for that, you need human skills. D!


About the Authors

Jenny Dearborn is Chief Learning Officer at SAP.

David Judge is Vice President, SAP Leonardo, at SAP.

Tom Raftery is Global Vice President and Internet of Things Evangelist at SAP.

Neal Ungerleider is a Los Angeles-based technology journalist and consultant.

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

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HR In The Age Of Digital Transformation

Neha Makkar Patnaik

HR has come a long way from the days of being called Personnel Management. It’s now known as People & Culture, Employee Experience, or simply People, and the changes in the last few years have been especially far-reaching, to say the least; seismic even.

While focused until recently on topics like efficiency and direct access to HR data and services for individual employees, a new and expanded HR transformation is underway, led by employee experience, cloud capabilities including mobile and continuous upgrades, a renewed focus on talent, as well as the availability of new digital technologies like machine learning and artificial intelligence. These capabilities are enabling HR re-imagine new ways of delivering HR services and strategies throughout the organization. For example:

  • Use advanced prediction and optimization technologies to shift focus from time-consuming candidate-screening processes to innovative HR strategies and business models that support growth
  • Help employees with tailored career paths, push personalized learning recommendations, suggest mentors and mentees based on skills and competencies
  • Predict flight risk of employees and prescribe mitigation strategies for at-risk talent
  • Leverage intelligent management of high-volume, rules-based events with predictions and recommendations

Whereas the traditional view of HR transformation was all about doing existing things better, the next generation of HR transformation is focused on doing completely new things.

These new digital aspects of HR transformation do not replace the existing focus on automation and efficiency. They work hand in hand and, in many cases, digital technologies can further augment automation. Digital approaches are becoming increasingly important, and a digital HR strategy must be a key component of HR’s overall strategy and, therefore, the business strategy.

For years, HR had been working behind a wall, finally got a seat at the table, and now it’s imperative for CHROs to be a strategic partner in the organization’s digital journey. This is what McKinsey calls “Leading with the G-3” in An Agenda for the Talent-First CEO, in which the CEO, CFO, and CHRO (i.e., the “G-3”) ensure HR and finance work in tandem, with the CEO being the linchpin and the person who ensures the talent agenda is threaded into business decisions and not a passive response or afterthought.

However, technology and executive alignment aren’t enough to drive a company’s digital transformation. At the heart of every organization are its people – its most expensive and valuable asset. Keeping them engaged and motivated fosters an innovation culture that is essential for success. This Gallup study reveals that a whopping 85% of employees worldwide are performing below their potential due to engagement issues.

HR experiences that are based on consumer-grade digital experiences along with a focus on the employee’s personal and professional well-being will help engage every worker, inspiring them to do their best and helping them turn every organization’s purpose into performance. Because, we believe, purpose drives people and people drive business results.

Embark on your HR transformation journey

Has your HR organization created a roadmap to support the transformation agenda? Start a discussion with your team about the current and desired state of HR processes using the framework with this white paper.

Also, read SAP’s HR transformation story within the broader context of SAP’s own transformation.


About Neha Makkar Patnaik

Neha Makkar Patnaik is a principal consultant at SAP Labs India. As part of the Digital Transformation Office, Neha is responsible for articulating the value proposition for digitizing the office of the CHRO in alignment with the overall strategic priorities of the organization. She also focuses on thought leadership and value-based selling programs for retail and consumer products industries.