The Tiny Engines Driving The Digital Revolution

Christopher Koch and Dan Wellers

In computing, bigger is never better. The smaller computers get, the more useful they become—like that computer you carry around in your pocket or purse, otherwise known as a smartphone.

The same holds true for digital sensors. Today we think of them as discrete devices that we attach to our fitness wristbands or factory machinery.

But sensors are on the verge of becoming so small that they will be ubiquitous. They will be completely integrated into the world around us (and inside us).

These tiny sensors will create a world where everything can be measured and manipulated. And that will make sensors a powerful force in the future of business and society.

Sensors have already shifted the healthcare model for treatment of some diseases from reactive—waiting until someone gets sick before treatment begins—to a proactive plan of real-time monitoring to sense and respond to symptoms before they become acute and potentially life-threatening.

Businesses will need to adopt the same strategy to survive in a sensor-filled world. It will become unacceptable for your product or service to break down. Customers will gravitate to providers that monitor and detect problems with everything from smartphones to turbines before they become catastrophic and expensive. Businesses of all kinds need to think about how the future of sensors will play out.

And that future is playing out right now.

Look Ma, no batteries

One of the biggest potential uses for sensors is to monitor things in inhospitable or remote places where it’s expensive, dangerous, or soul-crushing for humans to go, such as checking on the structural integrity of oil pipelines in the middle of nowhere. But sensors have always needed a dedicated power source to keep them running, which has limited their use.

That will change soon. As sensors become smaller, they need less energy to run, which begets new possibilities for untethering them from batteries.

University of Washington researchers have created a tiny sensor that grabs energy from radio waves that flow invisibly around us from sources like TV and radio broadcasts, cellphones, and wi-fi, and converts it to a viable power source. It’s a way to make sensors self-sustaining, which means they can be used just about anywhere.

Radio waves are just one source of ambient energy that will enable sensors to generate their own power. Companies have developed prototypes of sensors that can harvest energy from virtually all types of electromagnetic radiation or vibration (even oscillations as minor as from putting your fingers on your desk)—technology that will enable sensors one day soon to go where none have gone before.

No more fly on the wall

Until recently, sensors couldn’t be anything but a fly on the wall, limited by their relatively large size and power consumption to being highly sophisticated monitors of the world around them—able to measure everything from motion, acceleration, and pressure to light, heat, chemicals, and radioactivity.

However, despite their increasingly diminutive size, sensors have become more assertive, not less. Beyond merely sensing their surroundings, they are actively affecting them.

For example, researchers recently created an experimental sensor small enough to be swallowed but so powerful that it not only monitors fat levels in obese patients but also automatically releases medication that gives them a sense of fullness and dissuades them from eating. Another group of researchers is working on a sensor-equipped pill the size of a baby aspirin that will monitor medication intake and send a text message to doctors if patients skip a dose or don’t take enough.

But that’s just the beginning of sensors’ emboldened miniaturization. Researchers at the University of California, Berkeley have created sensors small enough (roughly the size of a grain of sand) to be attached to individual muscle and nerve fibers of rats. These sensors could monitor our health long term or perhaps even let us work out while we sleep. Researchers have also created biodegradable sensors that can be implanted within the body to monitor traumatic injuries and simply melt away when the injuries have healed.

The Berkeley researchers are confident they will one day be able to shrink sensors to 50 microns—half the width of a human hair. This smart dust could be integrated into the cells of the body, such as inside brain cells, allowing paraplegics to control a robotic arm the same way as their original limb. Smart dust could create a new category of treatment, known as electroceuticals, to fight chronic diseases such as epilepsy, stimulate the immune system to fight infections, or reduce inflammation.

Smart dust also has tremendous potential for business. Engineers at General Electric and 3D-printing company Optomec have already started down this path by creating a compound that can be painted on almost any surface. It hardens into a sensor that can function in the dirtiest, hottest places. GE is using the compound to print sensors directly on the blades of an industrial gas turbine.

A new sense of reality

Sensors this versatile could help us experience a reality well beyond that defined by evolution. Sensors could, for example, enable us to hear the low-pitched sounds that elephants hear, or the high-pitched sounds heard by dolphins. Already, amateur hackers have created a handheld device that mimics bats’ echolocation abilities by using ultrasound to detect the distance of objects.

Sensors could also give us entirely new abilities that are not in nature, such as extra sensory perception. We could also improvise different combinations of senses as required, such as swapping in ultraviolet, infrared, and night vision to meet our individual needs at any given time.

Data to the max

The catch in creating this new world of perception will come in managing the data needed to make it come alive. Researchers recently ran an experiment in which they needed 82,944 processors and 40 minutes on a supercomputer to simulate just one second of human brain processing capability. The simulation used about one petabyte of system memory to model 1.73 billion nerve cells, which is just a tiny fraction of the 80-100 billion nerve cells believed to be in the brain.

In other words, a fully sensor-enabled world is not going to run on today’s internet. Computing power will move to the edge, where the sensors are—as we’re already seeing in today’s experimental autonomous vehicles, which cart around their own little data centers and cloud computing environments (known as cloudlets or fog computing) to process all the information (roughly 1 GB per second, according to one estimate) coming from all the vehicles’ sensors and cameras. These cloudlets perform analytics at the sensor site while sending only the most basic descriptive information, or metadata, back over the internet so as not to overwhelm limited cell network bandwidth.

Suffice it to say that when our bodies, our cars, even the paint on our walls are all generating data, we will need extraordinary amounts of computing power to process it all. We will also need much better methods of securing data if we are to avoid potentially lethal manipulation and misuse of that data.

Redefining market success

In a world that senses everyone and everything all the time, businesses will have real-time insight into customers’ every whim, offering unprecedented opportunities for service and innovation. But competitors will have the same degree of insight. And they will be able to sense and respond to your moves in the market much more quickly.

When technology allows us to move this fast, we will need new ways of thinking about how to succeed in the market. The opportunities for differentiation will become increasingly fine-grained. The way we think of competitive advantage will change. It will be a new era of real-time business.

Read the executive brief How Sensors Will Redefine Business and Our World.

About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing.

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Intelligent Sales Lead To Cash

Swati Sinha

Digital disruption is mandating that organizations revisit their business processes and consider an end-to-end approach for upgrading and managing their functions with the help of technology.

Silos, disconnected applications, and scattered information across business processes obstruct an organization’s ability to respond to ever-changing customer and market needs. Today’s buyers are sophisticated and in control, and they want a combination of products and services customized to meet their individual needs, available on their preferred channel, and on perceived price point.

Lead to cash: Transform the buyer journey

To deliver an exceptional customer experience in this new landscape, all customer-focused business units – from marketing to sales to fulfillment to billing – must join forces. To achieve this, a solution is needed that fully integrates internal and external data and processes, and the solution must be the one source of truth across the organization.

Lead to cash is arguably the most important customer-centric process in an organization, starting with the customer’s intention to buy, and ending with revenue recognition. Utilizing artificial intelligence and in-depth integration of data, you can make your processes inherently intelligent, thus guiding sales to be proactive, rather than reactive, to changing customer needs.

Lead : AI and integration transform sales leads

When marketing and sales are aligned and harness the power of AI to focus on high propensity leads, an effective understanding of customer needs and interests – as well as insights into how to close the deal – are created.

With an integrated solution, marketing can effectively hand off lead information to sales. Research by the Aberdeen Group suggests that companies that optimize the sales and marketing relationship see 32% faster growth in revenue, 90% higher growth in brand awareness, and a huge increase in average deal size, sales acceptance of marketing-generated leads, attainment of team quota, and percent of sales-forecasted pipeline generated by marketing.

Opportunity knocks: Is it what your customer wants?

Deals and opportunities are the foundation of your sales cycle. To pursue an opportunity, salespeople spend extensive time searching for customer information that is typically spread throughout a disparate system and then go with their “gut feel” or personal network to pursue it. This can result in fragmented conversations and even loss of deal.

With the help of artificial intelligence and real-time access to holistic internal and external customer information, sales professionals can engage effectively, focusing their time on the best deals, and taking recommended actions to convert prospects to customers.

This intelligent approach eliminates clutter from the pipeline and increases forecast accuracy.

Trusted advisor

A report by Forrester suggests that 79% of B2B buyers say it’s critical for them to interact with a sale rep who can be a trusted advisor – which means not only meeting expressed needs but the ability to foresee and support the future customer goals. For this sales reps need to listen and surface customer pain, identify needs, and proactively recommend an ideal solution.

Products are constantly changing to match customer expectation of customization and options, generating thousands of SKUs. As catalogs grow, sales reps are placed in a difficult spot: they have to be trusted advisors with in-depth knowledge about their products, but with the complexity of products, they don’t have a grasp on the entire product line and possible customizations.

In absence of an intelligent solution, the rep sells based on limited knowledge – which may or may not be the best choice for the customer, or most profitable for the organization. Guided selling simplifies this process by recommending products based on various attributes, like the type of sales, past customer behavior of similar customers, etc.

Intelligent pricing generates revenue

Correct pricing is critical in determining the revenue of an organization. Pricing not only influences customer behavior, but also the sales rep’s behavior.

Sales reps want to price a solution that is lucrative to customers, and might end-up applying discounts that cut into the overall margin, especially in complex, bundled sales. Intelligent pricing helps sales rep price the solution that is competitive and optimizes their commission without impacting the deal profitability.

It allows them to build in rules to prevent discounts that dip below a certain level of margin, contingent on the products included in the deal. It also helps in identifying up/cross-sell of add-ons, options, and special promotions to increase deal size.

Putting it together: Effective quotes are crucial to sales

Effective quoting requires both speed and accuracy and is an integral part of the sales cycle. While an accurate quote can help close a deal fast, a delayed and error-filled quote can frustrate the customer, and may even cause the loss of deal.

Automated and streamlined approval processes help in protecting margin throughout any negotiations, introducing quality control, but not bottleneck. Triggers can be set for an approval of special quotes, such as exceeding discount or gross margin thresholds, or non-standard terms.

Since sales reps have real-time visibility into margins, delays in non-standard discounts and negotiations are minimized. Quotes with no special terms are automatically approved to speed up quote delivery.

Deliver on your promises

After the contract is signed, the fulfillment center ensures that right product, including add-on items, etc., are delivered to the customer, on time.

An integrated and streamlined process provides the visibility needed to stay attuned should any ‘change in order’ arise, thus avoiding any surprises upon deal closure. Sales solutions should also be able to move order details from the quote to the contract to ERP, and on the other hand, have the ability to add details to the CRM to enable fast and intelligent renewals.

Integrated billing solutions: Flexible and insightful

Monetization strategies continue to evolve as companies look for new ways to sell their products. Billing solutions should be flexible enough to customize subscription models for various levels of services, allowing for upgrades or one-time charges.

Integrated billing solutions should be able to consolidate even complicated B2B products and service packages into a single bill, and personalize it before sending to the customer. With integrated billing solutions, sales has visibility into purchase and transaction history and can create personalized offers for existing customer bases, thereby increasing revenue by lowering the cost of customer acquisition.

So, with integrated and intelligent Lead to Cash solution organizations can accelerate sales velocity and time to revenue, have margin-protecting guardrails and price optimization, increase cross and upsell opportunities, avoid revenue leakage at various points and help an organization transform their customer buying journey.

Ready to transform sales with intelligent lead to cash solutions? Join us here.

This article originally appeared on The Future of Customer Engagement and Commerce.

Swati Sinha

About Swati Sinha

Swati is part of the Analytic Applications for Line of Business team at SAP. She is passionate about marketing and is a technologist with a masters in business administration and masters in computer applications. Her experience spans development and product management with various technology companies.

Vive La CX Revolution! Customer-For-Life Mindset Enhances Customer Experience

Saj Hoffman-Hussain

We live in a world of non-stop branding, with companies begging for our attention on a minute-to-minute basis. Yet, often, the message doesn’t live up to its promise, and customers are left disappointed. With hopes dashed, you can expect them to jump ship.

When contrasting organizations that get the customer experience right against those that don’t, a clear marker is the lack of or attention paid to researching the individual customer. Much like a first date, first impressions count, and your brand is a digital swipe away from being discarded on the scrapheap of broken marketers’ dreams if you don’t do one vital thing – pay attention.

“Major disruptors in the customer relations industry are driven by an intense need to secure personal connections with customers – both current and potential – as a means to enhance the customer experience at all touchpoints through a customer-for-life mindset,” said Eugenio Cassiano, chief innovation officer at SAP Hybris.

The impact of Big Data and analytics on the customer experience: A bridge over troubled water

According to Cassiano, the CX revolution of the future will rely heavily on employees becoming more customer-focused and working creatively to resolve problems, offering a highly focused, responsive, and personalized service.

“Machine learning is something that is going to impact how employees interact with the customer, and it will also become a tool that supports the customer as they progress through different touchpoints within an organization. It’s important for us, being in the business of customer relations, to get to the next level of intelligent enterprise, and we do this by focusing less on the outcome and more on doing the right thing at the time.”

It’s vital for any brand to have the foresight to get ahead of upcoming technology trends. Examples include the increasing sophistication of virtual assistants to facilitate everyday customer interactions and augmented machine learning software for immersive customer experiences.

The cutting edge of omnichannel marketing and AI

Omnichannel marketing is changing. Though it works across many touchpoints, there is a gradual evolution towards what is known as customer success management. This shifts the traditional role of a CMO into a customer success manager position.

The message is clear from the top – we want to develop customers for life, i.e. continuing beyond a touchpoint. In the customer experience revolution, it will be this approach that gives leaders of commerce the edge in customer relations management.

Customer success: What sales orgs must know

If there were only two or three key factors for sales organizations to be aware of for customer success, what would these be?

Efficiency: Organizations need to optimize costs where possible, and make more intelligent sales decisions, which will lead to less waste.

Customer-for-life mindset: As customer expectations change, so should we – we need new and responsive models for developing and maintaining customer satisfaction. This will lead to increased revenues and stability.

Keep it simple: Get back to basics, but with more empathy. In the future, employees will have an intimate understanding of the customer developed through Big Data and will be working towards a longer-term relationship, past the point of sale.

Gain more intelligence on marketing to today’s buyers in Influencing Customers Through Infinite Personalization.

This article originally appeared on The Future of Customer Engagement and Commerce.

Saj Hoffman-Hussain

About Saj Hoffman-Hussain

Saj is a former BBC News journalist who decided to hop over the pond to the USA in 2014 and since then has worked as a freelance media professional for CBS/NPR and local TV affiliates before transitioning to marketing content development. He has specialist expertise in digital technologies, politics, and commerce. His philosophy is to never underestimate the power of a well-brewed cup of tea, and don’t be afraid to take calculated risks after said cup of tea. Also, be nice to people who bring you tea.

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.


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.