Shopping In A Galaxy Not So Far Away: AI And Robots In E-Commerce

Erica Vialardi

Unconscious imprinting from growing up a Gen-Xer during the original Star Wars years tells my generation that robots are futuristic. Except that is no longer so, and hasn’t been for a while now.

One of the features that made robots from Star Wars so awe-inspiring when we were children was their ability to understand and express human sentiments and behavior. Think about little R2-D2 rolling away offended, or C-3PO’s exaggerated politeness building bonds and empathy with viewers.

AI and robots are “invading” our daily lives, especially for shopping and e-commerce. Here are three robots and related technologies that are starting to integrate meta-communication aspects that go beyond purely utilitarian language to make the communication more human in consumers’ daily lives.

Meta-communication: When chatbots speak from another dimension

If you’ve ever been stuck with a customer support chatbot commanding you to “simplify your question,” you probably wondered why they even exist, since they appear to comprehend only questions that are listed in the company’s FAQ.

Instead, what if bots were able to pick up on the emotional state of a customer support request, such as if a customer is angry? Of interest is the conceptual idea of Charly the Chatbot being taught to understand emotional communication and react accordingly. This intuitive ability will help to lighten the mood between customers and brands with entertaining, small-talk conversations. Understanding secondary, unspoken meanings would make chatbot communication and problem-solving with customers much more efficient.

Body language: An army of clones could help

You may have already encountered an in-store robot assistant in some larger retailers’ stores. However, interacting with a robot in a public space still holds a dose of awkwardness.

Speaking live with another person means using words, tone of voice, facial mimicry, and gestures. But what “face” is one supposed to display when talking to a robot in front of other people? One quality that makes the humanoid robot Pepper so well-received is its capacity to use and mimic some body language.

Pepper can move its arms, turn its head toward you, and even use its eyes (not a weird built-in scanner) to scan your coupons. These user-friendly features are certain to delight any customer, and can even serve up some nostalgic vibes to Gen-Xers and older who dreamed of communicating with C-3PO.

Cultural awareness: The whole galaxy matters

When Siri was first released a few years ago, it seemed that her main function was to have people shout unspeakable sentences to her to test her array of smarty, generic retorts.

Now that voice and conversational commerce are getting a foothold in our everyday lives, the time has come to move on from mono-cultural voice assistants that express all-purpose phrases. The way we relate to shopkeepers and salespeople may greatly vary based on geography and culture.

This is something to consider carefully when programming voice devices, especially when attempting to make the robots more “human” through casual chit-chat. For example, some cultures may prefer different modes of communication based on gender or age, or an AI may need to expressly announce that a statement is intended as humor.

The current excitement around robotics and artificial intelligence is starting to provide answers on the optimal ways to have robots interact with customers, and where to draw the line between a frustrating or awkward shopping experience versus a satisfactory, mutually beneficial one.

After all, as C-3PO said: “He’s quite clever, you know… for a human being.”

Martin Stocker is the co-author of this post. 

AI increasingly means automating ethical choices that can alter human lives. Learn more about Teaching Machines Right from Wrong.

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

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Underfit Vs. Overfit: Why Your Machine Learning Model May Be Wrong

Paul Kurchina

Just shy of 60 years old, machine learning has never looked so good. Exponential data growth, advanced algorithms, and powerful computer processing are enabling the technology to fulfill its ultimate destiny: identifying profitable opportunities and avoiding unknown risks by evaluating massive volumes of complex data and delivering accurate results in real time.

However, during the Americas’ SAP Users’ Group (ASUG) Webcast “Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes,” Darwin Deano, principal and chief SAP Leonardo officer, and Denise McGuigan, senior manager and Deloitte reimagine platform leader (both from Deloitte Consulting LLP), forewarned that machine learning is only as good as the algorithm. And the algorithm is only as good as the data.

Deano advised, “Data evolves over time. Even though ERP systems provide a strong foundation for identifying opportunities and delivering on the promise of machine learning, it does not factor in information outside the core structure, nor does it move with information as it changes.”

Adding to Deano’s observation, McGuigan noted the importance of understanding data well. “Businesses must know all of the variables and data sets that drive certain decisions. Doing so will reduce the risk of bringing information into the analysis that will only cause noise or false positives within machine learning results,” she said.

Machine learning success depends on finding the right data “fit”

Although it’s tempting to jump into machine learning by automating heavily used transactions, McGuigan warned that this view misses the cognitive advantages of machine learning. “Companies have a considerable opportunity to operate with tremendous efficiency and speed,” she said. “They should also consider enabling processes and tasks that free up resources, time, and talent for entering new markets; offering breakthrough products and services; and innovating industry-disruptive business models.”

To successfully execute such an advanced form of machine learning, organizations must ensure that the right data is being applied to the machine learning model. Understanding how each data category impacts the training data helps businesses fine-tune the model to increase prediction accuracy and efficient automation. However, as McGuigan suggested, one of the most common causes of underperforming or inaccurate models can be attributed to an imbalance of data used, commonly referred as biased invariance.

One form of disparity is experienced when the model underfits the training data when assumptions are oversimplified to the point where either the wrong information or too little insight is applied. This condition leads to the inability to capture the relationship between the programmed input examples and the targeted outcomes.

On the flip side, a model can overfit training data when too much information is used and there is too much complexity. Even though it performs well with training data, the model cannot accurately evaluate data to deliver the expected outcome. The model only memorizes data, instead of learning from it to generalize how unseen examples should be treated.

It’s also important to remember that this exercise is an iterative process of trial and error. The model may be calibrated well enough at one moment to deliver expected outcomes consistently and predictively; however, as Deano suggested, “what may be overfitting today may not be the same situation six months from now as data evolves.”

For more insights into putting machine intelligence to work for your organization, watch the replay of the Americas’ SAP Users’ Group (ASUG) Webcast “Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes,” featuring Darwin Deano, principal and chief SAP Leonardo officer for Deloitte Consulting LLP, and Denise McGuigan, senior manager and Deloitte reimagine platform leader for Lights Out Finance at Deloitte Consulting LLP

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Paul Kurchina

About Paul Kurchina

Paul Kurchina is a community builder and evangelist with the Americas’ SAP Users Group (ASUG), responsible for developing a change management program for ASUG members.

How To Cope With Decision Fatigue

Lauren Pytel

Decision fatigue refers to the deteriorating quality of decisions as one is forced to engage in more and more decision-making. If you’ve ever planned an event, redesigned a home or purchased a new car, you probably remember the exhaustion and indifference that eventually resulted from being faced with so many choices.

Many companies put managers at risk of decision fatigue by creating performance management, compensation, staffing and development processes that require evaluating multiple people on multiple factors in a short period of time. For example, annual talent or compensation reviews where managers are required to make significant and critical decisions about multiple employees in less than four weeks, while also performing their full-time job.

Decision fatigue can lead to impulsive and irrational decision-making that can impact the accuracy of critical decisions related to employee promotion, staffing and compensation. Research shows that when our brains are tired, we tend to use mental short-cuts or heuristics to make decisions, rather than engage in effortful thought about a choice’s pros and cons. While heuristics can save decision-makers time and energy, they can also prove highly problematic for talent management decisions for several reasons.

Overly simplified decision-making

Fatigued managers may choose to pay everyone the same amount because it’s quick and easy, rather than critically evaluate whether some employees warrant greater levels of investment given their past contributions and future potential. Heuristics can result in biased decision-making. For example, people exhibit the ‘familiarity heuristic’ or ‘similarity heuristic’ when their decision-making reflects a bias for familiarity over novelty. This suggests that employees who were promoted by a manager in the past could be favored over employees who were not, or that employees who are demographically similar to a manager might be favored over employees who are not. This bias could have disastrous consequences for underrepresented demographic groups.

It would be difficult to completely eliminate decision fatigue as a risk, but there are things your organization can do to mitigate its negative effects:

Conduct calibration talent reviews

Calibration sessions can reduce individual manager decision fatigue, but only if they are conducted the right way. One of the most compelling reasons to hold calibration sessions is that the conversations they promote provide managers with a deeper understanding of the unique skills and capabilities their employees have to offer. But this only works if you provide adequate time to discuss employees. Including too many employees or failing to dedicate enough time to talk about the employees in a session defeats their purpose. In fact, when designed ineffectively, calibration reviews can actually make decision fatigue more likely as people may rush through evaluating employees so they can end the meeting on time.

Two additional calibration session best practices can also help mitigate the effects of decision fatigue. First, include a diverse group of raters with a variety of viewpoints and perspectives. Research suggests that group members can act as a ‘check & balance’ system against individuals’ biases, but only if all group members do not exhibit the same bias. Intentionally including raters who are not like other members of the rater group can help ensure that biases are detected and resolved before they affect decision-making. Second, randomize the order of evaluation.

Having to evaluate a large number of employees in a small period of time may, in some cases, be unavoidable. In such cases, it is useful to randomize the order in which employees are evaluated. Research has shown that the order in which individuals are assessed can influence how they are assessed. Rather than using some arbitrary criteria like an employee’s last name or their manager to order assessment, create a standardized process for defining assessment order that can be used across the organization.

Encourage managers to engage in continuous feedback

Managers can simplify the number of critical decisions during annual reviews by engaging in continuous dialogue with employees about their performance, progress and expectations throughout the year. Addressing these topics in small chunks can help reduce the burden of decision-making in terms of both the number of decisions that must be made as well as their level of criticality.

Managers are faced with an enormous number of decisions each day. While some of these may be insignificant, others, such as deciding who is up for promotion or a bonus, have critical long-term consequences. It is amazing how often managers suffering from decision fatigue make these critical decisions in a way that emphasizes efficiency over quality. Ensuring that your organization’s talent review process and philosophy protects managers against experiencing decision fatigue is important, not only for your managers’ senses of well-being but for the fairness and accuracy of your talent management decisions.

For more insight on decision-making in HR, see Succession Management: Why Do We Still Fail To Get It Right?

This article originally appeared on Forbes SAPVoice.

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Lauren Pytel

About Lauren Pytel

Lauren Pytel is a human capital management researcher at SAP SuccessFactors (SAP).

Why Strategic Plans Need Multiple Futures

By Dan Wellers, Kai Goerlich, and Stephanie Overby , Kai Goerlich and Stephanie Overby

When members of Lowe’s Innovation Labs first began talking with the home improvement retailer’s senior executives about how disruptive technologies would affect the future, the presentations were well received but nothing stuck.

“We’d give a really great presentation and everyone would say, ‘Great job,’ but nothing would really happen,” says Amanda Manna, head of narratives and partnerships for the lab.

The team realized that it needed to ditch the PowerPoints and try something radical. The team’s leader, Kyle Nel, is a behavioral scientist by training. He knows people are wired to receive new information best through stories. Sharing far-future concepts through narrative, he surmised, could unlock hidden potential to drive meaningful change.

So Nel hired science fiction writers to pen the future in comic book format, with characters and a narrative arc revealed pane by pane.

The first storyline, written several years before Oculus Rift became a household name, told the tale of a couple envisioning their kitchen renovation using virtual reality headsets. The comic might have been fun and fanciful, but its intent was deadly serious. It was a vision of a future in which Lowe’s might solve one of its long-standing struggles: the approximately US$70 billion left on the table when people are unable to start a home improvement project because they can’t envision what it will look like.

When the lab presented leaders with the first comic, “it was like a light bulb went on,” says Manna. “Not only did they immediately understand the value of the concept, they were convinced that if we didn’t build it, someone else would.”

Today, Lowe’s customers in select stores can use the HoloRoom How To virtual reality tool to learn basic DIY skills in an interactive and immersive environment.

Other comics followed and were greeted with similar enthusiasm—and investment, where possible. One tells the story of robots that help customers navigate stores. That comic spawned the LoweBot, which roamed the aisles of several Lowe’s stores during a pilot program in California and is being evaluated to determine next steps.

And the comic about tools that can be 3D-printed in space? Last year, Lowe’s partnered with Made in Space, which specializes in making 3D printers that can operate in zero gravity, to install the first commercial 3D printer in the International Space Station, where it was used to make tools and parts for astronauts.

The comics are the result of sending writers out on an open-ended assignment, armed with trends, market research, and other input, to envision what home improvement planning might look like in the future or what the experience of shopping will be in 10 years. The writers come back with several potential story ideas in a given area and work collaboratively with lab team members to refine it over time.

The process of working with writers and business partners to develop the comics helps the future strategy team at Lowe’s, working under chief development officer Richard D. Maltsbarger, to inhabit that future. They can imagine how it might play out, what obstacles might surface, and what steps the company would need to take to bring that future to life.

Once the final vision hits the page, the lab team can clearly envision how to work backward to enable the innovation. Importantly, the narrative is shared not only within the company but also out in the world. It serves as a kind of “bat signal” to potential technology partners with capabilities that might be required to make it happen, says Manna. “It’s all part of our strategy for staking a claim in the future.”

Planning must become completely oriented toward—and sourced from—the future.

Companies like Lowe’s are realizing that standard ways of planning for the future won’t get them where they need to go. The problem with traditional strategic planning is that the approach, which dates back to the 1950s and has remained largely unchanged since then, is based on the company’s existing mission, resources, core competencies, and competitors.

Yet the future rarely looks like the past. What’s more, digital technology is now driving change at exponential rates. Companies must be able to analyze and assess the potential impacts of the many variables at play, determine the possible futures they want to pursue, and develop the agility to pivot as conditions change along the way.

This is why planning must become completely oriented toward—and sourced from—the future, rather than from the past or the present. “Every winning strategy is based on a compelling insight, but most strategic planning originates in today’s marketplace, which means the resulting plans are constrained to incremental innovation,” says Bob Johansen, distinguished fellow at the Institute for the Future. “Most corporate strategists and CEOs are just inching their way to the future.” (Read more from Bob Johansen in the Thinkers story, “Fear Factor.”)

Inching forward won’t cut it anymore. Half of the S&P 500 organizations will be replaced over the next decade, according to research company Innosight. The reason? They can’t see the portfolio of possible futures, they can’t act on them, or both. Indeed, when SAP conducts future planning workshops with clients, we find that they usually struggle to look beyond current models and assumptions and lack clear ideas about how to work toward radically different futures.

Companies that want to increase their chances of long-term survival are incorporating three steps: envisioning, planning for, and executing on possible futures. And doing so all while the actual future is unfolding in expected and unexpected ways.

Those that pull it off are rewarded. A 2017 benchmarking report from the Strategic Foresight Research Network (SFRN) revealed that vigilant companies (those with the most mature processes for identifying, interpreting, and responding to factors that induce change) achieved 200% greater market capitalization growth and 33% higher profitability than the average, while the least mature companies experienced negative market-cap growth and had 44% lower profitability.

Looking Outside the Margins

“Most organizations lack sufficient capacity to detect, interpret, and act on the critically important but weak and ambiguous signals of fresh threats or new opportunities that emerge on the periphery of their usual business environment,” write George S. Day and Paul J. H. Schoemaker in their book Peripheral Vision.

But that’s exactly where effective future planning begins: examining what is happening outside the margins of day-to-day business as usual in order to peer into the future.

Business leaders who take this approach understand that despite the uncertainties of the future there are drivers of change that can be identified and studied and actions that can be taken to better prepare for—and influence—how events unfold.

That starts with developing foresight, typically a decade out. Ten years, most future planners agree, is the sweet spot. “It is far enough out that it gives you a bit more latitude to come up with a broader way to the future, allowing for disruption and innovation,” says Brian David Johnson, former chief futurist for Intel and current futurist in residence at Arizona State University’s Center for Science and the Imagination. “But you can still see the light from it.”

The process involves gathering information about the factors and forces—technological, business, sociological, and industry or ecosystem trends—that are effecting change to envision a range of potential impacts.

Seeing New Worlds

Intel, for example, looks beyond its own industry boundaries to envision possible future developments in adjacent businesses in the larger ecosystem it operates in. In 2008, the Intel Labs team, led by anthropologist Genevieve Bell, determined that the introduction of flexible glass displays would open up a whole new category of foldable consumer electronic devices.

To take advantage of that advance, Intel would need to be able to make silicon small enough to fit into some imagined device of the future. By the time glass manufacturer Corning unveiled its ultra-slim, flexible glass surface for mobile devices, laptops, televisions, and other displays of the future in 2012, Intel had already created design prototypes and kicked its development into higher gear. “Because we had done the future casting, we were already imagining how people might use flexible glass to create consumer devices,” says Johnson.

Because future planning relies so heavily on the quality of the input it receives, bringing in experts can elevate the practice. They can come from inside an organization, but the most influential insight may come from the outside and span a wide range of disciplines, says Steve Brown, a futurist, consultant, and CEO of BaldFuturist.com who worked for Intel Labs from 2007 to 2016.

Companies may look to sociologists or behaviorists who have insight into the needs and wants of people and how that influences their actions. Some organizations bring in an applied futurist, skilled at scanning many different forces and factors likely to coalesce in important ways (see Do You Need a Futurist?).

Do You Need a Futurist?

Most organizations need an outsider to help envision their future. Futurists are good at looking beyond the big picture to the biggest picture.

Business leaders who want to be better prepared for an uncertain and disruptive future will build future planning as a strategic capability into their organizations and create an organizational culture that embraces the approach. But working with credible futurists, at least in the beginning, can jump-start the process.

“The present can be so noisy and business leaders are so close to it that it’s helpful to provide a fresh outside-in point of view,” says veteran futurist Bob Johansen.

To put it simply, futurists like Johansen are good at connecting dots—lots of them. They look beyond the boundaries of a single company or even an industry, incorporating into their work social science, technical research, cultural movements, economic data, trends, and the input of other experts.

They can also factor in the cultural history of the specific company with whom they’re working, says Brian David Johnson, futurist in residence at Arizona State University’s Center for Science and the Imagination. “These large corporations have processes and procedures in place—typically for good reasons,” Johnson explains. “But all of those reasons have everything to do with the past and nothing to do with the future. Looking at that is important so you can understand the inertia that you need to overcome.”

One thing the best futurists will say they can’t do: predict the future. That’s not the point. “The future punishes certainty,” Johansen says, “but it rewards clarity.” The methods futurists employ are designed to trigger discussions and considerations of possibilities corporate leaders might not otherwise consider.

You don’t even necessarily have to buy into all the foresight that results, says Johansen. Many leaders don’t. “Every forecast is debatable,” Johansen says. “Foresight is a way to provoke insight, even if you don’t believe it. The value is in letting yourself be provoked.”

External expert input serves several purposes. It brings everyone up to a common level of knowledge. It can stimulate and shift the thinking of participants by introducing them to new information or ideas. And it can challenge the status quo by illustrating how people and organizations in different sectors are harnessing emerging trends.

The goal is not to come up with one definitive future but multiple possibilities—positive and negative—along with a list of the likely obstacles or accelerants that could surface on the road ahead. The result: increased clarity—rather than certainty—in the face of the unknown that enables business decision makers to execute and refine business plans and strategy over time.

Plotting the Steps Along the Way

Coming up with potential trends is an important first step in futuring, but even more critical is figuring out what steps need to be taken along the way: eight years from now, four years from now, two years from now, and now. Considerations include technologies to develop, infrastructure to deploy, talent to hire, partnerships to forge, and acquisitions to make. Without this vital step, says Brown, everybody goes back to their day jobs and the new thinking generated by future planning is wasted. To work, the future steps must be tangible, concrete, and actionable.

Organizations must build a roadmap for the desired future state that anticipates both developments and detours, complete with signals that will let them know if they’re headed in the right direction. Brown works with corporate leaders to set indicator flags to look out for on the way to the anticipated future. “If we see these flagged events occurring in the ecosystem, they help to confirm the strength of our hypothesis that a particular imagined future is likely to occur,” he explains.

For example, one of Brown’s clients envisioned two potential futures: one in which gestural interfaces took hold and another in which voice control dominated. The team set a flag to look out for early examples of the interfaces that emerged in areas such as home appliances and automobiles. “Once you saw not just Amazon Echo but also Google Home and other copycat speakers, it would increase your confidence that you were moving more towards a voice-first era rather than a gesture-first era,” Brown says. “It doesn’t mean that gesture won’t happen, but it’s less likely to be the predominant modality for communication.”

How to Keep Experiments from Being Stifled

Once organizations have a vision for the future, making it a reality requires testing ideas in the marketplace and then scaling them across the enterprise. “There’s a huge change piece involved,”
says Frank Diana, futurist and global consultant with Tata Consultancy Services, “and that’s the place where most
businesses will fall down.”

Many large firms have forgotten what it’s like to experiment in several new markets on a small scale to determine what will stick and what won’t, says René Rohrbeck, professor of strategy at the Aarhus School of Business and Social Sciences. Companies must be able to fail quickly, bring the lessons learned back in, adapt, and try again.

Lowe’s increases its chances of success by creating master narratives across a number of different areas at once, such as robotics, mixed-reality tools, on-demand manufacturing, sustainability, and startup acceleration. The lab maps components of each by expected timelines: short, medium, and long term. “From there, we’ll try to build as many of them as quickly as we can,” says Manna. “And we’re always looking for that next suite of things that we should be working on.” Along the way certain innovations, like the HoloRoom How-To, become developed enough to integrate into the larger business as part of the core strategy.

One way Lowe’s accelerates the process of deciding what is ready to scale is by being open about its nascent plans with the world. “In the past, Lowe’s would never talk about projects that weren’t at scale,” says Manna. Now the company is sharing its future plans with the media and, as a result, attracting partners that can jump-start their realization.

Seeing a Lowe’s comic about employee exoskeletons, for example, led Virginia Tech engineering professor Alan Asbeck to the retailer. He helped develop a prototype for a three-month pilot with stock employees at a Christiansburg, Virginia, store.

The high-tech suit makes it easier to move heavy objects. Employees trying out the suits are also fitted with an EEG headset that the lab incorporates into all its pilots to gauge unstated, subconscious reactions. That direct feedback on the user experience helps the company refine its innovations over time.

Make the Future Part of the Culture

Regardless of whether all the elements of its master narratives come to pass, Lowe’s has already accomplished something important: It has embedded future thinking into the culture of the company.

Companies like Lowe’s constantly scan the environment for meaningful economic, technology, and cultural changes that could impact its future assessments and plans. “They can regularly draw on future planning to answer challenges,” says Rohrbeck. “This intensive, ongoing, agile strategizing is only possible because they’ve done their homework up front and they keep it updated.”

It’s impossible to predict what’s going to happen in the future, but companies can help to shape it, says Manna of Lowe’s. “It’s really about painting a picture of a preferred future state that we can try to achieve while being flexible and capable of change as we learn things along the way.” D!


About the Authors

Dan Wellers is Global Lead, Digital Futures, at SAP.

Kai Goerlich is Chief Futurist at SAP’s Innovation Center Network.

Stephanie Overby is a Boston-based business and technology journalist.


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

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About Dan Wellers

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

Kai Goerlich

About Kai Goerlich

Kai Goerlich is the Chief Futurist at SAP Innovation Center network His specialties include Competitive Intelligence, Market Intelligence, Corporate Foresight, Trends, Futuring and ideation.

Share your thoughts with Kai on Twitter @KaiGoe.heif Futu

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Future Of Work 2018: 10 Predictions You Can’t Ignore

Steven Hunt

The start of winter is often referred to as the “holiday season.” But it might also be called the “prediction season.” When it comes to human capital management (HCM), most predictions tend to be variations of the same things.

A colleague and I even created a scale to rate HCM predictions based on whether they are new or just “old wine in new bottles.”  The reason HCM predictions do not change much over time is because the “H” in HCM is about people. People do not evolve as fast as technology. Consequently, the basic challenges of HCM are constant: getting the right people in the right roles and providing them with the right work environments while complying with employment laws.

The following are my “top ten” predictions about how these will change in 2018.

Workforce agility will become the most critical concept in HCM. It is often said that the only constant is change. It is now more accurate to say the only constant is an ever-accelerating rate of change. The only way companies can survive in the modern economy is to excel at adapting to changing markets, technologies, and business landscapes. This requires tapping into people’s innate capacity for learning, growth, and innovation.

Staffing will reach new levels of complexity. For over 100 years, most people interpreted “staffing” to mean hiring employees to work onsite in full-time or part-time roles.  This concept is changing due to shifting skill shortages, global labor pools, and a massive rise in virtual work and contract employment.  Staffing no longer means hiring employees.  It means finding the right mix of skills and matching them to business demands by tapping into an increasingly global, virtual, and contingent labor force. Companies will be forced to redefine workforce planning, recruiting, staffing, and management to work in this much more complex labor market.

The experience of work will greatly improve.  Technology has made a lot of things about our lives much easier and more enjoyable. Finding our way around a city, buying products, staying in touch with our friends, watching movies, and hundreds of other life experiences have been transformed by social and mobile technologies leveraging artificially intelligent interfaces and machine learning algorithms. We will see exponential growth in the use of artificial intelligence, chatbots, intelligent services, machine learning, mobile solutions, and social platforms to make work more enjoyable, simple, and engaging.

Performance management will become a solution, not a problem. People have hated performance management for decades.  This is changing thanks to companies rethinking performance management to focus on ongoing coaching and team based decision making.  We will soon reach a tipping point where the dreaded annual review will be nothing more than a painful memory, having been replaced by mobile technology enabled continuous performance management solutions that employees and managers both appreciate and like.

Re-conceptualizing compensation. Companies spend billions of dollars each year on merit increases, bonuses, and other form of compensation.  Yet few of them can confidently answer this question: “What is the return on investment you get from the money spent on compensation in terms of increased employee engagement, productivity, and retention?” Companies can tell down to the last penny how much is spent on compensation, but they cannot tell if that money is being spent wisely. The future of compensation will involve more continuous processes where employees receive different types of rewards throughout the year from different sources.  And analytics will be used to link investments in compensation to returns in workforce productivity.

Intolerance of inequity. For too long, companies have viewed inequity as a problem, but not a problem worth solving. With the workforce becoming increasingly diverse, particularly the rise of women who now represent 50 percent or more of the employees in many fields, society is reaching a long-awaited tipping point where inequitable treatment based on non-job relevant factors such as gender, ethnicity, and age is being openly acknowledged and addressed. Smart companies will proactively redesign their talent management practices to ensure bias is identified and addressed before it happens.

The rise of well-being tech. People are not meant to live in an “always on” 24-7 world.  The pace of work is literally burning people out.  Companies need employees to be highly engaged, creative, and service oriented.  But this is impossible to do if employees are tired, stressed, and distracted.  In the coming year, companies will continue to make more well-being tools available to their employees. With the explosion of well-being technology at the consumer level, such as smartwatches and fitness technology, many employers will be looking to bring these tools into the workplace.  However, successful organizations will be those who make such technologies accessible, enjoyable, and cultural for their employees.

Org charts will begin to phase out. There is a lot of talk about updating businesses for the digital age, and yet companies continue to manage work forces using a tool that has changed little since the Roman Empire: the hierarchical organization chart (“org chart”). Relying on org charts to guide workforce management decisions is both foolish and dangerous in a digitalized world. And while 2018 will not be “the year the org chart died,” some progressive organizations will begin to phase out traditional org charts for more modern, digital approaches.

Companies will ditch all-or-nothing retirement. 2018 will bring about a major shift in workplace dynamics with regards to older generations. Today, individuals are living longer, and thus working longer – past 60, 70, and even 80.  Forward-thinking organizations realize the need to keep this skilled talent in their organization, particularly as many industries face increasing skills shortages. However, this transition will also force companies to rethink jobs; for example, many positions that used to be full time will become part time.  In the coming year, organizations will begin to move away from the traditional, all-or-nothing view of retirement.

Growth in HR cybersecurity threats. Ransom ware made its main stage debut in 2017 with the WannaCry and NotPetya attacks.  In 2018, ransom ware threats will continue to proliferate.  HR systems have not historically been a major target of cyber criminals.  Unfortunately, this will change.  There will be a growing number of attacks against human resources departments, with cyber-criminals posing as potential applicants in the hopes of infecting the larger organization.

We should feel confident these trends will continue to evolve over the coming years. If there is one thing psychologists have proven over the years about predictions, it is that the best predictor of future behavior is past behavior.

For more on technology and HR, see Why (And How) Technology Is Bringing HR And The CFO Together.

This article originally appeared on Forbes SAPVoice.

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Steven Hunt

About Steven Hunt

Steven Hunt is the Senior Vice President of Customer Value at SAP. He is responsible for guiding the strategy and deployment of knowledge, tools and process improvements that increase the value customers receive from SuccessFactors & SAP Cloud software as a service solutions.