Looking At IoT And Connected Products Across Three Dimensions

Rakesh Gandhi

The Internet of Things (IoT) involves connected products, assets, fleets, infrastructures, markets, and people. In this, the first in a series of blogs, we’ll look at connected products; future posts will address each aspect in turn.

From hairbrushes to trash cans, more products are being designed with built-in IoT sensors and Internet connections. But connected products are about more than just consumer packaged goods, and their benefits extend to more than just consumers.

Smart, connected products include everything from consumer-grade dishwashers to commercial-use vending machines to industrial-level drills. They enable manufacturers to offer new functionality or track performance and usage by end users. They allow retailers and service providers to monitor inventory levels or manage maintenance and repair. In all cases, the goal of connected products is to create an end-to-end solution that delivers new business value.

To achieve that goal, companies should look at connected products across three dimensions:

Goods and equipment

Connected products enable manufacturers and service providers to collect and analyze data on how products are being used. You can perform track-and-trace to identify the physical location of products. You can measure environmental factors such as temperature and humidity to ensure operating efficiency or predict failures. You can monitor actual usage for compliance with warranty terms or contractual agreements. And you can effectively replenish inventory to avoid stock-outs.

You can even leverage connected products for new business models. One SAP customer has envisioned transforming its business from manufacturing industrial drills to providing drilling services. So instead of merely selling drills, it would also lease drills and charge based on the number of holes drilled.

The company can already closely track usage of expensive industrial drill bits. One thing it discovered is that bits were being used on weekends, when customer factories were closed – revealing unauthorized usage. It anticipates saving millions of dollars in drill-bit misplacements and leakage.

Product insights

IoT solves the disconnect between product engineering and actual usage in the field. Rather than guessing and waiting – guessing how end users are using products, waiting for feedback to filter in from the marketplace – engineering now gains instant insights.

By creating digital twins of your products, you can continuously and rapidly improve them, rolling out better designs or new functionality far faster than the competition. Digital twins also allow for better collaboration among teams, reuse of product and project data throughout the company, and even rapid and cost-effective mass customization. Some product enhancements can even be delivered in real time through over-the-air software upgrades.

Supply networks

Finally, connected products enable you to transform your supply networks. You can leverage a digital supply control tower and feed it with IoT data to control and respond to changing conditions such as inventory levels. You can also improve service quality by extending the supply chain into the business network.

Let’s say you manage vending machines with products from 10 vendors. In the past, planning for replenishment would be handled with Microsoft Excel files and separate procurement processes for each vendor. With IoT, you can automate replenishment by integrating procurement with the connected vending machines. You can achieve real-time visibility from the vending machines all the way back through your suppliers’ supply chains to avoid stock-outs and spoilages and deliver better customer service.

The key with all these dimensions is to start now. Identify high-value use cases, start small, and grow. IoT deployment is a journey, and as with any journey, there will be surprises along the way. It helps to identify a specific desired outcome of high value – reducing shrinkage, increasing uptime – and start there for faster return on investment. You can build on early successes toward achieving live engineering or new business models, leveraging connected products to transform your position in the marketplace.

Effective IoT connectedness requires a unifying foundation. SAP has addressed this need by introducing SAP Leonardo Internet of Things portfolio, innovative solutions designed to help organizations digitally transform existing processes and evolve to new digital models. Learn more by reading about real-world use cases, visiting sap.com/iot, attending our flagship event Leonardo Live this July 11–12 in Frankfurt, and following us on Twitter at @SAPLeonardo.

Rakesh Gandhi

About Rakesh Gandhi

Rakesh Gandhi is Vice President of the Internet of Things (IoT) Go-to-Market business unit at SAP. As an avid innovation enthusiast and IOT evangelist, he supports the go-to-market strategy and solution management of the SAP Leonardo IoT portfolio. Rakesh is a 12-year veteran of SAP and, besides the IoT, has experience in incubating new innovations around mobile; cloud solutions for the customer experience and commerce, and more.

Will There Be A Digital Twin For Everything And Everyone?

Markus Steer

Digital twins will evolve from concept to reality for nearly everything—everyone, every service, and every network.

The digital twin, as the virtual representation of the physical product, service or person, acts as a mirror of the real world to provides a means to simulate, predict, forecast, service, and self-heal. As such, it presents huge opportunities for businesses and to improve people’s lives.

A digital twin is not really new. For decades, weather forecasts have captured real-time conditions measured by numerous sensors and devices, simulating and visually representing them in digital form to make long-term climate predictions and short-term forecasts.

Now, with the massive technology push in the Internet of Things (IoT), sensors, and cloud solutions, the potential of digital twins is no longer just a concept, but a disruptive driver of innovation, and it is more affordable than ever.

With sensor prices dropping more than 50% between 2010 and 2020 and new technology like IoT and cloud solution now much more affordable, this technology can be applied to even low-value goods and consumer products. The digital twin, in combination with IoT sensors and emerging technologies, is now entering a new phase in market acceptance. After several years of evaluating, it becomes more and more an indispensable component of life. According the Gartner Hype Cycle, IoT will reach the plateau of productivity between 2019 and 2022, followed by digital twins from 2022 onwards.

Digital twins will touch every area of our lives: things, services, people, and networks.

The value of a digital twin

Digital twins offer a huge business potential moving away from analyzing the past towards predicting the future.1 The live representation of reality via digital twins allows us to evolve from ex-post data gathering and analytics towards real-time and ex-ante business practices. Based on the digital twin, formerly impossible practices can now be performed. Examples include real-time simulation, self-healing processes, and increased predictability. Imagine how customer satisfaction and customer loyalty will increase when products will let people know there’s a problem before they break down.

Things (products/assets)

The digital twin has huge potential spanning across the entire product lifecycle, from R&D engineering, manufacturing, service and maintenance, to operations. Here are some examples:

The digital twin helps manage the manufacturing of the “segment of one” more efficiently. Each physical product has a live representation in the digital world that can be tailored, designed, and created to individual needs. The individualized demand will be channeled into the digital supply chain. Hence a drastic change will happen: Production will evolve towards mass customization and individualization.

The maintenance business of products and assets will benefit from reduced downtime and time for inspection. The effort for physical inspection could be significantly reduced. Usage and performance data will provide insight into the physical state of a product or asset. Based on usage patterns combined with machine learning, the optimized, cost-effective maintenance plan will be derived for industrial assets and as well as in your home. The digital twin allows establishing predictive maintenance strategies: Fix it before it breaks!

In manufacturing operations, the digital twin innovation is a tremendous opportunity to simulate production and plant operations. Leveraging simulation of real scenarios using digital twins will help to optimize plant layout and accelerate production line design.


Another area where digital twins offer huge opportunities is the representation of people. They can improve lives in three main areas: Medical health, sports, and employee training and education.

The representation of an individual person, including personal data like weight, health data, activity tracking data, and medical treatment data can help to establish predictive alerts and guide people to healthier lifestyles. It will give better insights and transparency on the individual’s health situation by offering more data points. Data shared with doctors will help define better preventive strategies and recovery plans and shrink health care costs.

Athletes can benefit from digital twins by designing training programs for their specific needs based on physical fitness level. In addition, the technology can have a dramatic impact on individual performance in conjunction with IoT such as smart tennis racquets and other sports equipment.

In the business world, employee training plays an important role in time to market. Workers can be trained in the digital world first, leading to tremendous resource optimization for on-site training.


Using a digital twin offers new opportunities for value-added services, some that are brand-new services and others that are attached to products and assets. For example, you can add value by analyzing a product’s current state and providing the perfect service in time to prevent downtime. Improve service by delivering the right information at the right time on product state, diagnostics, spare parts, and technical information.

In addition, new service models, such as remote service, are now becoming reality. With the digital twin,  equipment acts as a service delivery unit and can self-heal, adding new services or features via software updates.


The network of digital twins is a game-changer. By connecting things, people, and services, every aspect of business can be virtually represented. Connecting distributed digital twins within companies, across companies, and across the ecosystem will allow companies to build virtual connected supply chain networks. Leveraging Big Data capabilities, this strategy provides unprecedented visibility into operating performance conditions and states of health, and creates the possibility of predicting future needs in a network of digital twins. Finally, it will add tremendous value by:

  • Offering new choices
  • Enhancing decision-making capabilities
  • Performing corrective actions before a system breaks

Imagine having the opportunity to manage air quality in big cities. By connecting data on traffic, weather conditions, air pollution, and health impact, measures can be taken to improve people’s lives significantly.


Digital twins will be a disrupter for many industries and will radically change business models. Ultimately, capitalizing the power of IoT and data regarding things, services, people, and networks, digital twins will change how businesses create, simulate, perform, predict, and self-heal.

Don’t wait—stay ahead of the curve by moving now. Start with a proof of concept, to better understand the technology’s value for your business. Be the disruptor of your industry rather than being disrupted.

This blog is the first one of a series to share insight into digital twins.

IDC expects that ”by 2020, 30% of G2000 companies will using data from Digital Twins of IoT-connected products and assets to improve product innovation success rates and organization productivity, achieving gains up to 25%.”

Markus Steer

About Markus Steer

Markus Steer is an advisor with SAP & experienced leader for Digital Transformation to connect people, things and businesses to run the world better. He helps CEOs and Biz leaders to define their vision and leverage digital trends to transform their company. He provides guidance to CTOs and Enterprise Architects on end-to-end architecture design. Connect with Markus on LinkedIn.

Improving Workplace Safety With IoT

Rosina Geiger

From factories, plant facilities, and construction sites to warehouses, airports, and oil rigs (and a lot more), there is hardly a shortage of worksite environments that pose potential danger to workers. But by using emerging technologies such as the Internet of Things (IoT) and pervasive cloud connectivity, organizations can now pull in work environment data, analyze it, and respond in ways to help keep workers safe and healthy.

What kind of data should be tracked? Common points of concern are temperature, humidity, noise levels, air quality, and more. One startup focused on tracking such metrics is Heads Up – a U.S.-based device manufacturer providing a wearable communication system that workers can attach to an eyepiece.

On its own, the Heads Up technology can detect out-of-tolerance conditions for heat, humidity, and noise levels – flashing different colored lights that alert workers to take action accordingly. But when you connect Heads Up – or similar technology – to critical business applications, enterprise data, and analysis engines on the backend, you can achieve even more. Here are some examples:

  • Ensure long-term safety – By analyzing data over weeks and months, you can calculate long-term exposure to potentially hazardous conditions. With integration into HR and scheduling solutions, you could then trigger re-rostering processes to keep exposure levels below acceptable limits
  • Improve compliance – With integration into business data regarding local, regional, or national worker safety regulations, you can monitor compliance and demonstrate your adherence to the rules as needed
  • Predict issues and take proactive action – Using machine learning algorithms, you can analyze data across worksites to detect patterns that can predict potential issues before they impact workers
  • Track workers with context awareness – With geolocation capabilities and schematics on particular worksite environments stored in business applications, you can track workers’ locations and alert them, for example, to not enter secured areas for which they may lack authorization
  • Speed and improve rescue operations – In a disaster situation, you can collect critical data in real time, enabling rescue crews to understand the situation quickly and plan rescue operations that have a higher chance of success

Learn more

To learn more about how Heads Up and other startups are integrating with SAP technology to improve worker safety, get in touch with the SAP IoT Startup Accelerator.

Twitter: IoT_Accelerator
SAP IoT Startup Accelerator

Heads UP website: www.headsupsafe.com

Rosina Geiger

About Rosina Geiger

Rosina Geiger is the Director of Startup Engagement at SAP. She has worked at the Hasso Plattner Institute in Potsdam before joining SAP in 2016 to establish the SAP IoT Startup Accelerator in Berlin and Palo Alto.

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.

Neha Makkar Patnaik

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.