Curves Ahead: Auto Industry Faces Connected Car Challenges

Rich Lindow

For three days in the second week of April, thought leaders and engineers from all over the world converged in Cobo Hall in Detroit, Michigan, to shape the future of the automotive world.

Packed with technical sessions, thought leadership panels, and a show floor full of companies displaying their latest technologies, this event brought together the brightest minds to try and solve the biggest challenges in the auto industry.

What are some of the greatest challenges the auto industry is facing in the era of the connected car?


Hidden in plain sight were representatives from forward-thinking companies who are desperate for talent, and who are recruiting in non-traditional ways. As the disruption in the automotive industry continues, automakers are developing new lines of business.

From smart city platforms and bike sharing to vehicle subscriptions and autonomous last mile delivery, the talent needed to lead and develop these lines of business is not something traditionally found inside an automaker. The changing workforce – a disruption of its own – has a responsibility to make these disruptive ideas a reality.

Companies already strapped for talent are faced with significant challenges along the way.

Big data, big problem

As complexity increases in vehicles, especially autonomous vehicles, the amount of data available is mind-blowing. Recently BMW stated that a single vehicle on their autonomous platform creates 16–40 Terabytes of data per day!

For reference, 1 Terabyte of data equates to 250 million pages printed both sides, over 10 miles high! Engineers must now determine how much of that data is critical (needing to be available on board the vehicle) and how much of it can be offloaded to the cloud.

5G: The next generation

Is 5G the answer to the growing data demands of the industry? According to Qualcomm, 5G specific automotive applications will be market ready in 2019. Automakers plan to integrate this technology in 2021–2 years faster than their transition from 3G to 4G.

This is promising, but unique challenges exist. Engineers must develop ways to install broadband modems into the ceiling of a vehicle that could be subjected to -20 degrees in a Michigan winter, or 120 degrees in the desert of Arizona.

5G data may be the answer, but the cost of transmitting this data is significant. This goes against the grain of traditional automotive, built on cost saving. To help overcome these obstacles, the 5G Automotive Associate (5GAA) was created in 2016. 5GAA is global, cross-industry organization of companies from the automotive, technology, and telecommunications industries, all working together to develop end-to-end solutions for future mobility and transportation services.

The Facebook effect

As SAE WCX18 wrapped up, Mark Zuckerburg sat in front of Congress fielding questions on cybersecurity and data privacy. These same challenges are staring the automotive industry in the face.

Large amounts of data are being produced by drivers every day. From dongles installed in a vehicle for insurance purposes to cities monitoring traffic patterns, personal information is being collected at a rate unlike any in history. But who owns this data? How secure is this data? How will the automotive industry use this data in the future?

The connected vehicle challenge

Despite the challenges noted above; one automotive startup has a plan. The first-ever Connected Vehicle Challenge on the Connect2Car Campus debuted in Detroit, bringing together finalists from all over the world to impress judges with their creative ideas around the future of mobility. Hundreds of universities, individuals, and small companies submitted ideas and the top five were given 20 minutes to convince a panel of automotive experts they should take home the $10,000 first prize.

Israeli startup Safemode ( took home first prize with their idea to develop risk scores for every driver using Artificial Intelligence and Big Data. These driver specific profiles would allow autonomous vehicles to make risk-based decisions when interacting with the mixed human and autonomous vehicle ecosystem.

Secure platforms drive the future

With new business models presenting themselves nearly every quarter, automotive companies are creating entire departments reporting to the highest level to monetize these opportunities. These opportunities will only be successful if data quality and security are at the forefront. This challenges the very fabric of how automotive manufactures views their product.

The architecture of an automobile has never been based on security. As the industry changes its mindset to adopt security first, engineers will shape the way you and I interact with the world.

Welcome to disruption.

What do you consider the biggest threat or opportunity in regards to connected vehicles? Let me know by commenting or tweeting: @Rich_Lindow.

This post first appeared on SAP Innovation Spotlight, and is republished here with permission.

Sailing At The Edge: What Ocean Racing Can Teach Us About The Power Of Edge Computing

Elvira Wallis

Every three years, the ultimate race around the world takes place. The 2017-2018 Volvo Ocean Race has a starting line in Spain and a finish line in the Netherlands. At first glance, basic geography might suggest that there isn’t much distance covered between these two locations. However, the journey covers 45,000 miles by way of South Africa, Hong Kong, New Zealand, Brazil, and Sweden, to name just a few of the stops along the way.

The race isn’t for the faint of heart, quite literally. Each sailing team is comprised of 7 to 11 professional crew who don’t have much space to share on these 65-foot yachts. And sailing can be non-stop for three weeks at a time, often with grueling conditions that are unpredictable throughout the course of the 8 months of competition.

This is the backdrop that led one team to try something new. Team AkzoNobel decided to investigate how best to optimize conditions for their crew. Historically, variables such as weather and subsequent route decisions were the main focus in terms of looking for that competitive edge. But what if you could get insight into other conditional variables affecting the crew?

1. Finding answers to difficult questions through precise measurement

It turns out, you can. In fact, there are many more variables and subsequent outcomes that are the result of specific choices that need to be made right on the boat, often in real time. For example, how much sleep is just enough? How long is too long for a single shift? How often should a crewmember eat or rest? How many calories should they take in? How long should breaks be? And the list of questions with the answer “it depends” goes on and on.

Traditionally, most of these questions are answered by a mix of experience and predefined planning that can be adjusted on the fly (even if inexactly). And while experience and planning can serve a crew well, there is a certain amount of precision that’s missing. As the saying goes, you get what you measure. And by extension, the better your measurements, the more you’re likely to get.

2. Facilitating insight even under harsh conditions

But then, how might you facilitate precise measurements when you’re in the middle of nowhere? (That’s not just a saying, in this case: The race passes by Point Nemo, the spot on earth that is farthest from land.) This is where the concept of edge computing comes into play. As the Volvo Ocean Race so acutely illustrates, in the real world, a lot of useful data is generated at “the edge,” meaning not necessarily in the middle of a city with a strong Internet connection.

But now, especially with the prevalence of the Internet of Things (IoT) providing access to an unprecedented amount of data through sensor-enabled devices, it’s often assumed that the cloud is everywhere, with its distributed processing power available on demand to make insightful information out of all this raw data being collected. As that is only partially true; another solution is needed. Enter stage left: edge computing.

If you have the right local processing power, you can still gather and analysis quite a bit of data, all while being disconnected from the cloud. Then, when you’re within range of the cloud, you can sync up your data and analysis for a much more robust set of recommendations for the next leg of your trip.

3. Bringing together the power of the cloud and the edge

Case in point: Team AkzoNobel now has each of their crew members wear biometric sensors (embedded in wristwatches). This IoT data is then captured by a smartphone that acts as a gateway for a local WiFi network within the boat. The smartphone gateway then streams the biometric sensor data to a tiny onboard Raspberry Pi computer, enclosed in a watertight box and connected with USB power, that acts as the local processing power.

The Raspberry Pi has been configured with intelligent edge computing software which handles secure local data storage, synchronizing architecture, analytics models, and algorithms for data gathering and processing to provide real-time insights even from the middle of nowhere. This includes derived insights on each crew member’s fitness, performance, quality of sleep, stress levels, degree of exhaustion, reaction to weather conditions, and more.

The insights are displayed in real time through a custom web application the team can access while at sea. The data for each leg of the race is then synced with the cloud each time the yacht returns to shore and combined with larger historical data sets for predictive analysis for the next leg of the journey.

4. Harvesting gains from deeper insights

This allows for the best of both worlds: insight available in real time based on current conditions, but also deeper analysis and insight after each leg of the journey. Often a larger data set is required to find even small trends lines. But insight into a “small” trend can have huge implications. Even a mere 1 percent gain is significant in the world of ocean racing.

The crew is constantly learning from these insights and can understand the consequences of their choices more precisely and preemptively. For example, a crew member with the best of intentions might push himself until he breaks, but if the data suggests that a break earlier is better for the long run, he can adjust accordingly.

This level of insight also allows for a more tailored approach to food planning and consumption that is specific to each crewmember and their needs. Excessive food weight or less effective types of food, even when adjusted slightly, can secure significant gains. In the end, finding those optimal tradeoffs with more precise intelligence is the goal.

If you think about it, optimizing outcomes while participating in a competition with unpredictable (and often harsh) variables is a fairly accurate description of what it can be like running a business in the digital economy. But with the right combination of hardware, software, and services, you can achieve smooth sailing even while at the edge.

Watch this video to see how SAP Edge Services, as part of SAP Leonardo, can help you gain domain-specific insights in a digital world.

Elvira Wallis

About Elvira Wallis

Elvira Wallis is the Senior Vice President of SAP’s IoT Smart Connected Business organization. Elvira is responsible for ideating, defining, delivering and taking-to-market IoT business solutions to increase revenue, adoption and thought leadership.

Digitalist Flash Briefing: Five Digital And Mobile Trends You Should Know

Bonnie D. Graham

Need more information before you dip your toe in the water or wade deeper in your digital transformation? Here’s a round-up of the latest digital and mobile trends.

  • Amazon Echo or Dot: Enable the “Digitalist” flash briefing skill, and ask Alexa to “play my flash briefings” on every business day.
  • Alexa on a mobile device:
    • Download the Amazon Alexa app: Select Skills, and search “Digitalist”. Then, select Digitalist, and click on the Enable button.
    • Download the Amazon app: Click on the microphone icon and say “Play my flash briefing.”

Find and listen to previous Flash Briefings on

Read more on today’s topic

About Bonnie D. Graham

Bonnie D. Graham is the creator, producer and host/moderator of Game-Changers Radio series presented by SAP, bringing technology and business strategy discussions to a global audience. A broadcast journalist with over 20 years in media production and hosting, Bonnie has held marketing communications management roles in a variety of industries. Listen to the flagship series, Coffee Break with Game-Changers.

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.