Amp The Supply Chain

Hans Thalbauer and Michael S. Goldberg

Earlier this decade, manufacturing executives were skeptical about the benefits of digitizing their operations. According to various studies, only 37% believed digital business could drive revenue growth; 25% thought the sector would be highly impacted by digital transformation within the following five years; and fewer than 10% were implementing digital technologies to transform their businesses end to end.

That was then. The future is arriving fast.

Now every manufacturing C-suite in the world is on the path to digital transformation, with the supply chain at its heart. A transformed supply chain is the enabler for companies to deploy technology for personalizing products, accelerating delivery, and meeting rising customer expectations—all while constantly probing the boundaries of their existing business models.

Researchers at IDC have identified a clear turning point ahead: they predict that half of manufacturers will be benefiting from digital transformation in their supply chains by 2019.

Charging Ahead with
Supply Chain Transformation

When successfully implemented, digital supply chain technologies will lead to revenue gains, boost service quality, help cut innovation costs, and speed product-to-market times. The evidence is already apparent.

 2018

90% of supply chains will use B2B commerce networks to collaborate. By enabling decentralized collaboration among members of networks, blockchain technology is beginning to demonstrate its potential to automatically speed up supply chain network transactions. CoinDesk reports that BHP Billiton, one of the world’s largest mining companies, has started using blockchain technology to automatically share data with vendors (including geologists and shipping firms) that collect and analyze mining samples instead of relying on spreadsheets.

Manufacturing centers and microfactories with 3D printers will receive 500% more funding. Ford is testing 3D printing to make parts, starting with plastic molding for auto interiors and spoilers that go on racing models. The technology has potential to speed delivery of parts and save money in assembly and service processes.

Data: IDC

2019

Supply chain productivity and efficiency using Internet of Things (IoT) sensors will improve 30%. IoT-based sensors that enable the collection and analysis of data—and the analytics tools that make good on the variety and speed of that data—make productivity and efficiency improvements possible. Following a model with jet engines made famous by General Electric, Kaeser Compressors has fitted its air compressors with internet-connected sensors and is selling metered air compressor services rather than the equipment itself. Not only does this represent a new business model for Kaeser, it also improves uptime and service quality for customers, because the manufacturer, not the user, is responsible for maintenance.

50% of supply chains will benefit from digital transformation, while others will lag due to outdated business models and systems. The creation of local factories and mini-warehouses will put subsets of products closer to where they are needed and will locate production processes and products closer to customers. Adidas is building a “Speedfactory” in Atlanta, slated to open in 2017, that will bring customized products to American retail customers faster than could be done when manufacturing is executed primarily in Asia. The Atlanta facility, modeled after a factory in Germany, will use robots to automate production processes that can, for example,  customize shoe styles and fit to match customer specifications.

Data: IDC

2020

50% of mature supply chains will use artificial intelligence and advanced analytics for planning and forecasting. Intelligent systems can make faster and better predictions than people can. The healthcare unit at Merck KGaA is working on an initiative to bring sensors and intelligent software algorithms to bear on its supply chain, according to The Wall Street Journal. The goals: better data about how products do in the market and an accelerated planning process.

50% of manufacturers will deliver directly to consumers. The McDonald’s supply chain once stopped at the restaurant door. But after offering delivery services in Asia and the Middle East, the company has begun pilots to bring burgers to customers—even partnering with ride-sharing digital natives at Uber in Florida to deliver meals.

Data: IDC

Digital Power Source

The opportunities for supply chain transformation are real, although the path forward is challenging. An SAP-sponsored study by research and advisory firm Longitude notes that while many enterprises appear to be digitized, the foundations of their operations—supply chain, procurement, and logistics—are still analog. Market forces are placing these companies under great strain, making them susceptible to disruption by digital startups.

Transformation means converting analog processes into digital supply networks—now. While every company’s digitization strategy will be different, enabling these processes requires the following:

  • Ask the right questions. To avoid being overtaken by a lean startup, you need to continually evaluate your operations against competitors. Some questions to ask, according to Peter Weill and Stephanie L. Woerner in the MIT Sloan Management Review: Are the products you make ordered and delivered digitally? Can you equip them with data to make them more valuable? Are there other firms serving your customers that could become competitors? Can a digital offering replace your products now or in the future?
  • Have the right data systems in place. You need information from everything in your production ecosystem—including sensors, machines, factory and warehouse equipment, trucks, and even products—in forms that you can analyze to improve production processes.
  • Commit to automation. Machine-learning technologies make your systems more intelligent, so you can pursue the right opportunities and produce the right outcomes. For example, blockchain technology applied to supply chain systems can configure order processes so they happen immediately.
  • Include every process. The digitization effort should cover manufacturing processes from product design and configuration to supply chain planning, manufacturing, shipping, and after-sales service.

These points are where the discussion starts. Every C-suite will have its own approach to how these elements come together for their firm to succeed. Many companies are executing their strategies now. The rest need to head that way. D!

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Hans Thalbauer

About Hans Thalbauer

Hans Thalbauer is globally responsible for solution management and the go-to-market functions for SAP digital supply chain solutions and the SAP Leonardo portfolio of Internet of Things solutions. In this role, he is engaged in creative dialogues with businesses and operations worldwide, addressing customer needs and introducing innovative business processes, including the vision of creating a live business environment for everyone working in operations. Hans has more than 17 years with SAP and is based out of Palo Alto, CA, USA. He has held positions in development, product and solution management, and the go-to-market organization. Hans holds a degree in Business Information Systems from the University Vienna, Austria.

Michael S. Goldberg

About Michael S. Goldberg

Michael S. Goldberg is an independent writer and editor focusing on management and technology issues.

Digitalist Flash Briefing: Transformation In The Forest Products Industry

Bonnie D. Graham

Today’s briefing looks at how, contrary to popular opinion, the paper mill industry is impacted by digital transformation as much as other industries.

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Bonnie D. Graham

About Bonnie D. Graham

Bonnie D. Graham is the creator, producer and host/moderator of 29 Game-Changers Radio series presented by SAP, bringing technology and business strategy thought leadership panel discussions to a global audience via the Business Channel on World Talk Radio. A broadcast journalist with nearly 20 years in media production and hosting, Bonnie has held marketing communications management roles in the business software, financial services, and real estate industries. She calls SAP Radio her “dream job”. Listen to Coffee Break with Game-Changers.

Beyond Spare Parts: 3D Printing And Machine Learning

Stefan Krauss

The concept of 3D printing isn’t a new one. In fact, it’s been around for more than 30 years – long before it became popular in consumer settings. In industries like automotive and aerospace, we call it additive manufacturing – the process of creating something new by layering materials, like plastic, metal, or concrete, using computer-modeled designs.

This approach is extremely versatile, allowing manufacturing teams to visualize large design projects through miniature scale models, design and create small runs of custom parts and equipment for customers, and prototype new products. As 3D printing speeds increase, Gartner predicts the 3D printing industry will be a $4.6 billion market by 2019.

Until now, the primary application for 3D printing in discrete industries has been prototyping new parts and equipment. But there’s significant room for expansion, especially in the efficient fabrication of spare parts.

Most discrete manufacturers are already producing spare parts, but few have adopted tactical 3D printing as an update to their process. The lead time currently required to create many spare parts can be both long and expensive, so the only way to ensure these parts are available to the customer in a timely fashion is to create and store them in advance. This process is inefficient and cost-prohibitive for the manufacturer – resulting in higher costs and longer wait times for customers. 3D printing provides a turnkey solution to this problem, and gives manufacturers the opportunity to supply their customers with high-quality parts, on-demand, when they are needed most.

Even more exciting, with innovations in other emerging technologies concurrently maturing, 3D printing is just the start of what manufacturers can do to enhance their production process for spare parts. While 3D printing certainly expedites creation, storage and delivery, it’s still a reactionary operation at its core. Instead of relying on customers to tell them when to print these parts, discrete manufacturers must transform their operations to think proactively – leveraging machine learning (ML) to solve maintenance issues before they occur.

As 3D printing capabilities grow, maintenance teams face a variety of challenges, including the number of parts that can be printed and increasing demand from customers for faster delivery. Regardless of these challenges, their goals remain the same: to ensure that parts are available and shipped to a customer in a timely fashion. As such, it’s critical that manufacturers evolve to meet this demand by incorporating machine learning into their process.

Machine learning technology identifies, analyzes, and monitors nearly infinite amounts of data, allowing it to provide a real-time status of processes and machinery. When implemented in a discrete manufacturing setting, teams can use ML to analyze the life remaining on a specific part or piece of equipment, and flag system failures before they happen. Similarly, when synchronized with a predetermined replacement schedule, ML can help proactively identify when it’s time for a customer to replace their parts – thereby avoiding unplanned downtime for machinery that would otherwise need to be taken out of service.

Manufacturers could combine this predictive maintenance with their ability to 3D print spare parts efficiently to become full-service vendors for their customers. Those who do so will not only serve as true leaders in spare parts manufacturing, but also in customer service.

With technology disrupting nearly every type of enterprise business model, customers are demanding more, and have higher expectations than ever before. They expect materials on time and on-hand when they need them, and they expect their suppliers to adjust accordingly. Discrete manufacturers producing spare parts must meet this demand by incorporating 3D printing, in conjunction with ML, to help quickly deliver high-quality spare parts to customers ahead of demand.

Manufacturers who can take advantage of ML to predict when equipment and parts will fail, then subsequently employ 3D printing to proactively print and ship replacement parts ahead of these failures, will enjoy significantly reduced spare parts costs and delivery times, and higher customer satisfaction.

For more on implementing advanced technology to your business processes, see Managing Digital Disruption Requires The Right Strategy And Mindset.

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Stefan Krauss

About Stefan Krauss

Stefan Krauss is the general manager for Discrete Industries at SAP. Together with his team, he is responsible for the integrated management of the industries Aerospace & Defense, Automotive, High Tech and Industrial Machinery & Components – spanning development, solution management, sales and marketing, value engineering, partner management, services and support. The mission of this unit is to deliver industry cloud solutions that help SAP customers sustainably innovate and grow their business, operate safely, and develop their people.

More Than Noise: Digital Trends That Are Bigger Than You Think

By Maurizio Cattaneo, David Delaney, Volker Hildebrand, and Neal Ungerleider

In the tech world in 2017, several trends emerged as signals amid the noise, signifying much larger changes to come.

As we noted in last year’s More Than Noise list, things are changing—and the changes are occurring in ways that don’t necessarily fit into the prevailing narrative.

While many of 2017’s signals have a dark tint to them, perhaps reflecting the times we live in, we have sought out some rays of light to illuminate the way forward. The following signals differ considerably, but understanding them can help guide businesses in the right direction for 2018 and beyond.

When a team of psychologists, linguists, and software engineers created Woebot, an AI chatbot that helps people learn cognitive behavioral therapy techniques for managing mental health issues like anxiety and depression, they did something unusual, at least when it comes to chatbots: they submitted it for peer review.

Stanford University researchers recruited a sample group of 70 college-age participants on social media to take part in a randomized control study of Woebot. The researchers found that their creation was useful for improving anxiety and depression symptoms. A study of the user interaction with the bot was submitted for peer review and published in the Journal of Medical Internet Research Mental Health in June 2017.

While Woebot may not revolutionize the field of psychology, it could change the way we view AI development. Well-known figures such as Elon Musk and Bill Gates have expressed concerns that artificial intelligence is essentially ungovernable. Peer review, such as with the Stanford study, is one way to approach this challenge and figure out how to properly evaluate and find a place for these software programs.

The healthcare community could be onto something. We’ve already seen instances where AI chatbots have spun out of control, such as when internet trolls trained Microsoft’s Tay to become a hate-spewing misanthrope. Bots are only as good as their design; making sure they stay on message and don’t act in unexpected ways is crucial.

This is especially true in healthcare. When chatbots are offering therapeutic services, they must be properly designed, vetted, and tested to maintain patient safety.

It may be prudent to apply the same level of caution to a business setting. By treating chatbots as if they’re akin to medicine or drugs, we have a model for thorough vetting that, while not perfect, is generally effective and time tested.

It may seem like overkill to think of chatbots that manage pizza orders or help resolve parking tickets as potential health threats. But it’s already clear that AI can have unintended side effects that could extend far beyond Tay’s loathsome behavior.

For example, in July, Facebook shut down an experiment where it challenged two AIs to negotiate with each other over a trade. When the experiment began, the two chatbots quickly went rogue, developing linguistic shortcuts to reduce negotiating time and leaving their creators unable to understand what they were saying.

Do we want AIs interacting in a secret language because designers didn’t fully understand what they were designing?

The implications are chilling. Do we want AIs interacting in a secret language because designers didn’t fully understand what they were designing?

In this context, the healthcare community’s conservative approach doesn’t seem so farfetched. Woebot could ultimately become an example of the kind of oversight that’s needed for all AIs.

Meanwhile, it’s clear that chatbots have great potential in healthcare—not just for treating mental health issues but for helping patients understand symptoms, build treatment regimens, and more. They could also help unclog barriers to healthcare, which is plagued worldwide by high prices, long wait times, and other challenges. While they are not a substitute for actual humans, chatbots can be used by anyone with a computer or smartphone, 24 hours a day, seven days a week, regardless of financial status.

Finding the right governance for AI development won’t happen overnight. But peer review, extensive internal quality analysis, and other processes will go a long way to ensuring bots function as expected. Otherwise, companies and their customers could pay a big price.

Elon Musk is an expert at dominating the news cycle with his sci-fi premonitions about space travel and high-speed hyperloops. However, he captured media attention in Australia in April 2017 for something much more down to earth: how to deal with blackouts and power outages.

In 2016, a massive blackout hit the state of South Australia following a storm. Although power was restored quickly in Adelaide, the capital, people in the wide stretches of arid desert that surround it spent days waiting for the power to return. That hit South Australia’s wine and livestock industries especially hard.

South Australia’s electrical grid currently gets more than half of its energy from wind and solar, with coal and gas plants acting as backups for when the sun hides or the wind doesn’t blow, according to ABC News Australia. But this network is vulnerable to sudden loss of generation—which is exactly what happened in the storm that caused the 2016 blackout, when tornadoes ripped through some key transmission lines. Getting the system back on stable footing has been an issue ever since.

Displaying his usual talent for showmanship, Musk stepped in and promised to build the world’s largest battery to store backup energy for the network—and he pledged to complete it within 100 days of signing the contract or the battery would be free. Pen met paper with South Australia and French utility Neoen in September. As of press time in November, construction was underway.

For South Australia, the Tesla deal offers an easy and secure way to store renewable energy. Tesla’s 129 MWh battery will be the most powerful battery system in the world by 60% once completed, according to Gizmodo. The battery, which is stationed at a wind farm, will cover temporary drops in wind power and kick in to help conventional gas and coal plants balance generation with demand across the network. South Australian citizens and politicians largely support the project, which Tesla claims will be able to power 30,000 homes.

Until Musk made his bold promise, batteries did not figure much in renewable energy networks, mostly because they just aren’t that good. They have limited charges, are difficult to build, and are difficult to manage. Utilities also worry about relying on the same lithium-ion battery technology as cellphone makers like Samsung, whose Galaxy Note 7 had to be recalled in 2016 after some defective batteries burst into flames, according to CNET.

However, when made right, the batteries are safe. It’s just that they’ve traditionally been too expensive for large-scale uses such as renewable power storage. But battery innovations such as Tesla’s could radically change how we power the economy. According to a study that appeared this year in Nature, the continued drop in the cost of battery storage has made renewable energy price-competitive with traditional fossil fuels.

This is a massive shift. Or, as David Roberts of news site Vox puts it, “Batteries are soon going to disrupt power markets at all scales.” Furthermore, if the cost of batteries continues to drop, supply chains could experience radical energy cost savings. This could disrupt energy utilities, manufacturing, transportation, and construction, to name just a few, and create many opportunities while changing established business models. (For more on how renewable energy will affect business, read the feature “Tick Tock” in this issue.)

Battery research and development has become big business. Thanks to electric cars and powerful smartphones, there has been incredible pressure to make more powerful batteries that last longer between charges.

The proof of this is in the R&D funding pudding. A Brookings Institution report notes that both the Chinese and U.S. governments offer generous subsidies for lithium-ion battery advancement. Automakers such as Daimler and BMW have established divisions marketing residential and commercial energy storage products. Boeing, Airbus, Rolls-Royce, and General Electric are all experimenting with various electric propulsion systems for aircraft—which means that hybrid airplanes are also a possibility.

Meanwhile, governments around the world are accelerating battery research investment by banning internal combustion vehicles. Britain, France, India, and Norway are seeking to go all electric as early as 2025 and by 2040 at the latest.

In the meantime, expect huge investment and new battery innovation from interested parties across industries that all share a stake in the outcome. This past September, for example, Volkswagen announced a €50 billion research investment in batteries to help bring 300 electric vehicle models to market by 2030.

At first, it sounds like a narrative device from a science fiction novel or a particularly bad urban legend.

Powerful cameras in several Chinese cities capture photographs of jaywalkers as they cross the street and, several minutes later, display their photograph, name, and home address on a large screen posted at the intersection. Several days later, a summons appears in the offender’s mailbox demanding payment of a fine or fulfillment of community service.

As Orwellian as it seems, this technology is very real for residents of Jinan and several other Chinese cities. According to a Xinhua interview with Li Yong of the Jinan traffic police, “Since the new technology has been adopted, the cases of jaywalking have been reduced from 200 to 20 each day at the major intersection of Jingshi and Shungeng roads.”

The sophisticated cameras and facial recognition systems already used in China—and their near–real-time public shaming—are an example of how machine learning, mobile phone surveillance, and internet activity tracking are being used to censor and control populations. Most worryingly, the prospect of real-time surveillance makes running surveillance states such as the former East Germany and current North Korea much more financially efficient.

According to a 2015 discussion paper by the Institute for the Study of Labor, a German research center, by the 1980s almost 0.5% of the East German population was directly employed by the Stasi, the country’s state security service and secret police—1 for every 166 citizens. An additional 1.1% of the population (1 for every 66 citizens) were working as unofficial informers, which represented a massive economic drain. Automated, real-time, algorithm-driven monitoring could potentially drive the cost of controlling the population down substantially in police states—and elsewhere.

We could see a radical new era of censorship that is much more manipulative than anything that has come before. Previously, dissidents were identified when investigators manually combed through photos, read writings, or listened in on phone calls. Real-time algorithmic monitoring means that acts of perceived defiance can be identified and deleted in the moment and their perpetrators marked for swift judgment before they can make an impression on others.

Businesses need to be aware of the wider trend toward real-time, automated censorship and how it might be used in both commercial and governmental settings. These tools can easily be used in countries with unstable political dynamics and could become a real concern for businesses that operate across borders. Businesses must learn to educate and protect employees when technology can censor and punish in real time.

Indeed, the technologies used for this kind of repression could be easily adapted from those that have already been developed for businesses. For instance, both Facebook and Google use near–real-time facial identification algorithms that automatically identify people in images uploaded by users—which helps the companies build out their social graphs and target users with profitable advertisements. Automated algorithms also flag Facebook posts that potentially violate the company’s terms of service.

China is already using these technologies to control its own people in ways that are largely hidden to outsiders.

According to a report by the University of Toronto’s Citizen Lab, the popular Chinese social network WeChat operates under a policy its authors call “One App, Two Systems.” Users with Chinese phone numbers are subjected to dynamic keyword censorship that changes depending on current events and whether a user is in a private chat or in a group. Depending on the political winds, users are blocked from accessing a range of websites that report critically on China through WeChat’s internal browser. Non-Chinese users, however, are not subject to any of these restrictions.

The censorship is also designed to be invisible. Messages are blocked without any user notification, and China has intermittently blocked WhatsApp and other foreign social networks. As a result, Chinese users are steered toward national social networks, which are more compliant with government pressure.

China’s policies play into a larger global trend: the nationalization of the internet. China, Russia, the European Union, and the United States have all adopted different approaches to censorship, user privacy, and surveillance. Although there are social networks such as WeChat or Russia’s VKontakte that are popular in primarily one country, nationalizing the internet challenges users of multinational services such as Facebook and YouTube. These different approaches, which impact everything from data safe harbor laws to legal consequences for posting inflammatory material, have implications for businesses working in multiple countries, as well.

For instance, Twitter is legally obligated to hide Nazi and neo-fascist imagery and some tweets in Germany and France—but not elsewhere. YouTube was officially banned in Turkey for two years because of videos a Turkish court deemed “insulting to the memory of Mustafa Kemal Atatürk,” father of modern Turkey. In Russia, Google must keep Russian users’ personal data on servers located inside Russia to comply with government policy.

While China is a pioneer in the field of instant censorship, tech companies in the United States are matching China’s progress, which could potentially have a chilling effect on democracy. In 2016, Apple applied for a patent on technology that censors audio streams in real time—automating the previously manual process of censoring curse words in streaming audio.

In March, after U.S. President Donald Trump told Fox News, “I think maybe I wouldn’t be [president] if it wasn’t for Twitter,” Twitter founder Evan “Ev” Williams did something highly unusual for the creator of a massive social network.

He apologized.

Speaking with David Streitfeld of The New York Times, Williams said, “It’s a very bad thing, Twitter’s role in that. If it’s true that he wouldn’t be president if it weren’t for Twitter, then yeah, I’m sorry.”

Entrepreneurs tend to be very proud of their innovations. Williams, however, offers a far more ambivalent response to his creation’s success. Much of the 2016 presidential election’s rancor was fueled by Twitter, and the instant gratification of Twitter attracts trolls, bullies, and bigots just as easily as it attracts politicians, celebrities, comedians, and sports fans.

Services such as Twitter, Facebook, YouTube, and Instagram are designed through a mix of look and feel, algorithmic wizardry, and psychological techniques to hang on to users for as long as possible—which helps the services sell more advertisements and make more money. Toxic political discourse and online harassment are unintended side effects of the economic-driven urge to keep users engaged no matter what.

Keeping users’ eyeballs on their screens requires endless hours of multivariate testing, user research, and algorithm refinement. For instance, Casey Newton of tech publication The Verge notes that Google Brain, Google’s AI division, plays a key part in generating YouTube’s video recommendations.

According to Jim McFadden, the technical lead for YouTube recommendations, “Before, if I watch this video from a comedian, our recommendations were pretty good at saying, here’s another one just like it,” he told Newton. “But the Google Brain model figures out other comedians who are similar but not exactly the same—even more adjacent relationships. It’s able to see patterns that are less obvious.”

A never-ending flow of content that is interesting without being repetitive is harder to resist. With users glued to online services, addiction and other behavioral problems occur to an unhealthy degree. According to a 2016 poll by nonprofit research company Common Sense Media, 50% of American teenagers believe they are addicted to their smartphones.

This pattern is extending into the workplace. Seventy-five percent of companies told research company Harris Poll in 2016 that two or more hours a day are lost in productivity because employees are distracted. The number one reason? Cellphones and texting, according to 55% of those companies surveyed. Another 41% pointed to the internet.

Tristan Harris, a former design ethicist at Google, argues that many product designers for online services try to exploit psychological vulnerabilities in a bid to keep users engaged for longer periods. Harris refers to an iPhone as “a slot machine in my pocket” and argues that user interface (UI) and user experience (UX) designers need to adopt something akin to a Hippocratic Oath to stop exploiting users’ psychological vulnerabilities.

In fact, there is an entire school of study devoted to “dark UX”—small design tweaks to increase profits. These can be as innocuous as a “Buy Now” button in a visually pleasing color or as controversial as when Facebook tweaked its algorithm in 2012 to show a randomly selected group of almost 700,000 users (who had not given their permission) newsfeeds that skewed more positive to some users and more negative to others to gauge the impact on their respective emotional states, according to an article in Wired.

As computers, smartphones, and televisions come ever closer to convergence, these issues matter increasingly to businesses. Some of the universal side effects of addiction are lost productivity at work and poor health. Businesses should offer training and help for employees who can’t stop checking their smartphones.

Mindfulness-centered mobile apps such as Headspace, Calm, and Forest offer one way to break the habit. Users can also choose to break internet addiction by going for a walk, turning their computers off, or using tools like StayFocusd or Freedom to block addictive websites or apps.

Most importantly, companies in the business of creating tech products need to design software and hardware that discourages addictive behavior. This means avoiding bad designs that emphasize engagement metrics over human health. A world of advertising preroll showing up on smart refrigerator touchscreens at 2 a.m. benefits no one.

According to a 2014 study in Cyberpsychology, Behavior and Social Networking, approximately 6% of the world’s population suffers from internet addiction to one degree or another. As more users in emerging economies gain access to cheap data, smartphones, and laptops, that percentage will only increase. For businesses, getting a head start on stopping internet addiction will make employees happier and more productive. D!


About the Authors

Maurizio Cattaneo is Director, Delivery Execution, Energy, and Natural Resources, at SAP.

David Delaney is Global Vice President and Chief Medical Officer, SAP Health.

Volker Hildebrand is Global Vice President for SAP Hybris solutions.

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.

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No Longer Soft Skills: Five Crucial Workplace Skills Everyone Should Learn

Carmen O'Shea

My child’s elementary school focuses on skills they believe support children in becoming changemakers. Through use of an integrated, project-based curriculum, they explicitly teach and assess “learner values” such as iteration, risk, failure, collaboration, and perspective. Their philosophy is that these attributes long considered “soft skills” have become the crucial educational priorities for this generation.

Why do they believe this? Much knowledge is now easily accessed and readily queried, such that the acquisition of specific content or know-how is far less important than how to apply that content in different situations and how to interact with others in the pursuit of goals. This holds true in the workplace as well as the academic environment. When I think about how I operate in my job at a large technology company, it’s not really what I know but what I do with what I know, and whom I engage to get things accomplished.

Watching the school teach these skills just as they do math or language has made me stop and consider what they look like for an employee. I wanted to share my thoughts on five qualities beyond relevant academic skills or professional experience that are just as important (if not more so) in predicting top work performance. These are more qualitative skills that managers should hire for, employees should develop, and organizations should optimize for.

  • Empathythe ability to see and integrate multiple perspectives and to understand the impact of how others think. Empathy can also mean advocating and showing empathy for oneself and for others. Empathy is assuming a good intention even when someone has said or done something we dislike – to stop and pause, attempt to understand, and respond compassionately in a difficult workplace situation. Empathy also extends to intuiting beyond just the professional environment to more of a personal level to truly understand what drives a colleague or employee.
  • Resiliencethe ability to take risks even when you know you may fail and then to bounce back, sometimes repeatedly, from failure. Inherent in resilience is the idea of iteration – that it is often essential to try things multiple times, in multiple ways, from multiple angles, before achieving a desired outcome. Resilience is receiving difficult yet constructive feedback from a manager or peer and resolving to act positively on it instead of wallowing or harboring a grudge. Resilience is maintaining a sense of optimism even in a down quarter at work.
  • Creativitythe ability to think differently or expansively and to approach a problem from multiple angles. Sometimes it’s called “thinking outside the box.” Creativity often includes inquiry, the act of questioning and satisfying one’s curiosity about particular topics. Torrance defined it along several parameters – number of ideas generated, number of categories of ideas, originality of ideas, and how detailed each idea is elaborated. We see it in action during brainstorming phases of projects, but it’s also possible to apply creativity on a continual basis, by pushing colleagues to expand on their thoughts, by not being satisfied with a less than stellar answer, by taking time to understand how multiple approaches to an issue could be combined, or by simply trying something new in a familiar situation.
  • Collaborationthe ability to interact and work productively with others, in all size groups. Effective collaboration requires empathy, especially when collaborators have different backgrounds, styles, or thought processes. Collaboration also requires exemplary communication skills, both oral and written, as well as reflective listening. So much of our tasks on the job require collaboration with others, whether to inform, persuade, learn, or engage, and these interactions form the bedrock for innovation. It’s tough to innovate without collaborating.
  • Flexibilitythe ability to adapt or change course if that is what the situation demands. Flexibility includes letting go of one’s idea in the interest of attaining a goal more quickly. It can also include development a comfort level with uncertainty or ambiguity, especially in times of change. Flexibility is a willingness to absorb feedback objectively and course correct as needed without personalizing the information or demonizing the provider of it. Expounding on another’s idea (not our own) in a brainstorming session demonstrates flexibility, as does remaining calm while an org change takes effect and roles are temporarily unclear.

When employees exhibit these qualities, they are better able to understand their purpose at work and to unleash their passions in the pursuit of that purpose. When teams exhibit these qualities, achievement and employee engagement are higher.  I wager that retention and innovation will improve as well. It’s heartening that as a society we’re beginning to consider how to best prepare our children educationally for the kind of work environments they will encounter after they finish their academic journey.

Do you also see these qualities as valuable in assessing employee fit? How can managers and organizations better identify, train and reward employees for living these qualities?

For more on this topic, see Your Business Needs People With Skills, Not Just Qualifications.

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Carmen O'Shea

About Carmen O'Shea

Carmen O’Shea is the Senior Vice President of HR Change & Engagement at SAP. She leads a global team supporting major transformation initiatives across the company, focused on change management, employee engagement, and creative marketing and interaction. You can follow Carmen on Twitter.