Why Dynamic Planning And Analysis Optimizes Decisions

Birgit Starmanns

Gone are the days of a single annual planning cycle. Or at least – those days should be gone.

Planning processes have certainly evolved. Previously, many companies started their planning process in September (assuming a December fiscal year-end), and spent a large part of the fourth quarter on planning iterations. Once the plan was approved, there were few adjustments; however, a significant amount of time was spent on explaining plan/actual differences throughout the year.

As changes in the business environment began to accelerate, companies evolved to a rolling forecast. Instead of waiting until the end of the fiscal year to begin a new planning cycle, companies began to plan and adjust their budgets based on actual data that came in during a financial period, giving them a rolling 12-month forecast.

Today we need real-time planning to account for disruptive business models and sudden changes in demand. This requires organizations to act quickly to make changes to the plan, potentially moving funds due to changes in a business model, customer demand, or other factors.

Levels of planning

Every part of the organization, not just finance, must engage in planning:

  • Finance: There are many ways to plan financial information. Of course, there are balance sheets and P&L financial planning, but also management accounting planning for cost centers, internal orders, profit centers, projects, and dimensions of profitability, including logistics information such as customers, products, and regions.
  • Operations: HR plans for headcount, salary, benefits, and training costs. Sales and marketing departments estimate customer demand, plan for expenses to ensure closed deals, and evaluate product pricing. Meanwhile, manufacturing plans capacity and product mix, as well as any materials they need to procure. In the best case, sales and manufacturing planning complement each other.
  • Organizational hierarchies: Especially in large organizations, business units and subsidiaries also plan, and these plans need to roll up to the corporate level. Similar to intercompany reconciliation of actuals, cross-business adjustments may need to be made.

Integrated planning

A key challenge has always been the siloed nature of planning, both for financial planning as well as the influence of operational planning on finance. In many companies, the different types of planning are performed in a different system or spreadsheet, requiring manual consolidation. And each time there is a change, the reconciliation starts from scratch.

Enter modern finance solutions.

Instead of relying on different systems and manual processes, these solutions enable a single, consolidated view of all planning and forecasting information across all financial, operational, and organizational levels. This includes a rollup of planning information from subsidiaries into corporate planning, as well as automatically including operational plans in financial plans to measure their impact on both the financial and management controlling plans.

And since the same information is used for transactional processing – analytics as well as planning – there is no lag time, ensuring that the most up-to-date information is available at any time. Simulations, what-if analyses, and predictive capabilities allow for the modeling of all planning options.

Before and after

To see how this works, let’s take a look at the planning processes in two organizations. One company – let’s call it Mary’s Manufacturing – has many disparate planning systems, as discussed above. The other, Stephanie’s Software, has implemented a state-of-the-art finance solution. This team is not only capable of consolidating and updating planning information in real time, but can also use sophisticated dynamic planning tools to evaluate the financial impact of all strategic options available.

Consider a merger and acquisition (M&A) scenario. The finance team at Mary’s Manufacturing spends so much time in manual consolidations that they cannot possibly evaluate each M&A scenario. Instead, they must pre-select only a few options, meaning they’re not considering every scenario. On the other hand, Stephanie’s Software, using dynamic planning and predictive tools, can evaluate each and every option, even tweaking individual parameters in the model to determine the most profitable and sustainable scenario for the organization.

At Mary’s Manufacturing, the finance team spends most of their time doing manual consolidation and reconciliation of planning data. This task repeats every time a source plan changes to ensure that financial planning reflects any changes in sales, operational, and HR planning. However, with dynamic planning and forecasting capabilities, the finance team at Stephanie’s Software can add value to the organization by spending the majority of their time in analysis of all potential scenarios. The finance team thus becomes a valuable member of the executive team that can provide answers to “what if” questions immediately, even in an executive boardroom situation.

For more information about solutions that support planning processes, please visit:

Follow SAP Finance online: @SAPFinance (Twitter)  | LinkedIn | FacebookYouTube


Birgit Starmanns

About Birgit Starmanns

Birgit Starmanns is a senior director in the Global Center of Excellence for Finance and Risk at SAP. She is focused on the go-to-market for new solutions, and the business benefits they can bring to organizations, such as cloud solutions for finance and applications based on SAP Leonardo technologies such as machine learning. Birgit has over 27 years of experience across solution marketing, solution management, and strategic customer communities. Prior to SAP, she was a principal in management consulting organizations, including Price Waterhouse and several boutique firms. Birgit holds a BA and MBA from the College of William and Mary. She is the author of many articles for the Financials Expert, the coauthor of the SAP Press book Accelerated Financial Closing with SAP, and the SAP Labs guidebook Product Costing Scenarios Made Easy. In addition, she is a regular presenter at various SAP events.

Blockchain In Finance Sales Support: Smart Contracting

Vaag Durgaryan

Blockchain and bitcoin have been in news headlines since the end of last year. However, few people know about their potential implication on finance sales support, and more specifically, on contracts.

Run smarter, not harder

According to blockgeeks.com, smart contract technology can be compared to a vending machine. Typically, you would visit a lawyer or a notary, pay them, and wait for your document. With smart contracts, you simply drop a cryptocurrency into the vending machine, along with your driver’s license or other documents. Here’s how it works:

  • A contract between two parties is coded into blockchain. The coded contract includes information on terms, conditions, and triggering event.
  • As soon as the event happens, the contract automatically executes according to the coded terms and conditions.

Application in finance sales support

Contracting is one of the main activities in finance sales support. Suppose a seller sells a product to a buyer. This can be done through the blockchain by paying in cryptocurrency. The buyer would get a proof of purchase, which is held in the coded contract in blockchain; the seller would deliver the product by a specified date. If the product doesn’t come on time, the blockchain releases a refund. If product comes before that specific date, the function holds it, releasing both the fee and product respectively when the date arrives, and the terms and conditions are met.

The blockchain could not only provide a single ledger as a source of trust, but it also smoothes possible issues in communication and approval workflow. For instance, before making a transaction to sell products, a company currently needs to wait for a department to complete all approvals and meet internal or external conditions. In smart contracting, once the contract is coded, it will wait until all conditions of the contract are met and will execute it automatically.

Even more digital

From the perspective of the buyer, the smart contracting process can be supported by chatbots, which are available 24×7 and can consult on the process, terms, and conditions. Total digitalization and automation of non-complex contracting processes enables finance salespeople on the seller’s side to reinvest in “white-glove” support of very large contracts and deals.

Problems

Blockchain and smart contracting are not perfect. In traditional contracting, a court would review and provide a ruling in case of disagreement. In blockchain, the contract performs, no matter what. Additional concerns include security and technical bugs. While such factors may discourage smart contracting in the short term, we may see those problems fixed in the future as technology adoption increases.

Further reading

For more on this topic, read “Smart Contracts with Blockchain: New Foundation for Binding Legal Agreements” by Peter David, SAP regional CFO.

Also, read 3 Reasons CFOs & Finance Professionals Should Attend SAPPHIRE NOW to learn about what’s happening at this year’s SAPPHIRE NOW and ASUG Conference – panels, keynotes, discussions, presentations, and endless ways to connect to people and gain new ideas for streamlining processes. Join SAP’s finance team and partners June 5–7, in Orlando, Florida.

Follow SAP Finance online: @SAPFinance (Twitter) | LinkedIn | Facebook | YouTube


Vaag Durgaryan

About Vaag Durgaryan

Vaag Durgaryan is the commercial finance director for SAP in the Middle East and North Africa, which comprises of over 20 countries. Starting in 2017, he oversees a multinational team that provides finance expertise, knowledge, and strategy outlook for finance sales support in the region. Prior to that, Vaag was chief of staff for the CFO for SAP Global Field Finance and co-drove global transformation initiatives with focus on process simplification and people enablement. He holds an Executive MBA degree from ESSEC Business School and Mannheim Business School. Vaag has a passion in digitalization and learning culture.

Artificial Intelligence: From Novelty To Practical Workplace Application

Sven Denecken

Over the past few years, businesses have pondered what an intelligent workplace powered by artificial intelligence (AI) might look like. Well, the day is finally here, and it’s not as daunting or as intimidating as many might have anticipated.

While some organizations were apprehensive that the arrival of AI would result in worker displacement or business process confusion, most now agree that AI will ultimately benefit their businesses. In fact, Gartner predicts that AI augmentation will recover 6.2 billion hours of worker productivity by 2021.

Still, many companies are left wondering how these technologies will work to actually boost productivity and positively impact the bottom line. The good news is that there are a number of ways to implement AI based on your business objectives and goals.

How to foster an intelligent workplace

Businesses can start implementing useful AI technologies such as digital assistants into everyday operations to not only increase employee productivity, but also streamline business processes. The beauty of AI is that it can be rolled out to various departments on a case-by-case basis. If the sales team is struggling to streamline certain functions, then it might make sense to make the AI investment with sales first and go from there.

  • Accounting: In accounting, employees can use machine learning and predictive analytics technologies to match incoming payments to the applicable invoices, reducing time spent manually matching payments, and reducing the risk of human error.
  • Sales: Sales teams can use machine learning to identify probable orders and predict sales volume for more precise forecasting. They can also use predictive analytics to get a glimpse into the probability that a deal will close — helping them adjust revenue goals as needed.
  • Human resources: AI technology can streamline routine tasks in the hiring process, such as answering basic questions and checking off a candidate’s qualifications. This allows HR professionals to spend more time getting to know candidates on a human level by gauging body language, tone of voice, etc.
  • Sourcing and procurement: Machine learning tools can review purchase order confirmations and proactively alert users to potential shipping and logistics problems and automatically contact customers when deliveries are at risk of not arriving on time.

Incorporating AI on a personal level

Given that the B2B sector is largely influenced by trends taking place in the B2C world, it’s no surprise that Amazon announced Alexa for Business last quarter in response to business needs. You can use a “personal assistant” that combines machine learning, natural language processing, and predictive analytics to do more than simply turn on the lights or dial into conference calls. However, in order to break into the next level of productivity, enterprises need to understand how to train such technologies to adapt to specific business settings, and to employees’ daily tasks.

One way employees can train their digital assistants is by integrating them with their work calendars. A digital assistant that is fully integrated with your work schedule could, for example, inform you that, after your last in-person meeting at 3:00 p.m., you should have time, based on current traffic conditions, to drive home and take your last call of the day from your house. That information helps you avoid rush hour traffic and still finish everything you needed to do for the day. A true win-win situation.

The importance of education and training

As previously mentioned, having AI technology at the fingertips of your enterprise is great, but only if your employees know how to work with it. A Pew Research survey found that 87 percent of workers believe that it will be essential for them to receive ongoing training and develop new skills throughout their work lives in order to keep up with the changes in the workplace, especially those changes brought about by AI.

An investment in AI systems such as digital assistants and predictive analytics tools also requires an investment in employee education and training so you can be sure that the technology is used correctly. Whether the C-level executive team or the IT department takes the lead in education efforts, any training you offer will pay off down the road as AI becomes more integrated in the enterprise.

Organizations will have to embrace digital transformation if they want to truly become intelligent businesses. It’s an exciting time to get started with the phenomenon that will only continue to gain ground in the enterprise environment. Start by envisioning how AI can be successfully implemented within your company, then begin planning how to make it happen.

Gone are the days of implementing AI just for the sake of staying relevant. It’s critical that businesses deploy AI applications that serve practical, functional purposes in the workplace to garner the best results.

This article originally appeared on CMS Wire.

For more on this topic, see How Artificial Intelligence Can Increase Your Business Productivity.


Sven Denecken

About Sven Denecken

Sven Denecken is Senior Vice President, Product Management and Co-Innovation of SAP S/4HANA, at SAP. His experience working with customers and partners for decades and networking with the SAP field organization and industry analysts allows him to bring client issues and challenges directly into the solution development process, ensuring that next-generation software solutions address customer requirements to focus on business outcome and help customers gain competitive advantage. Connect with Sven on Twitter @SDenecken or e-mail at sven.denecken@sap.com.

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.

Tags:

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.