The “Ayurvedic” Approach To GDPR

Neil Patrick

At around 11 months before the General Data Protection Regulation (GDPR) or Regulation (EU) 2016/679 becomes effective, how are things looking in the marketplace?

GDPR is a topic I’ve been working on for some nine months as part of my role. This entails a lot of reading and research; talking to many, many customers and peers on the topic; learning what they are doing; and assisting customers with an approach to an end-to-end compliance capability. (Read our other GDPR articles.)

Beware of misleading comments

I’ve seen a number of misunderstandings and misrepresentations for GDPR that worry me. For example, I’ve seen it stated by others that GDPR requires data to be encrypted, or that data centres have to relocate from the United States to the European Union to be GDPR-compliant. Both are untrue, but contain just enough similar wording to GDPR to make it sound plausible. This reminds me of the story about someone suffering with up to 17 headaches a day and how that was resolved (but more on that a bit later).

Part of the problem is that vendors and agencies are bending the meaning of GDPR to suit their niche functional capabilities. I have also noticed a laziness when they don’t actually read the GDPR, but instead use someone else’s interpretation and/or summary points to develop a feature map and collateral. So, for example, software being positioned (and possibly purchased?) is a few levels of separation and interpretation away from the real GDPR requirement.

In addition to being wrong and confusing, this can also lead to a plethora of disconnected niche pieces of software cluttering up the enterprise, while not really addressing the needs of the actual regulation.

Give it a go—read the GDPR

The GDPR is not the most riveting read, true, but it’s actually quite well structured. And if one takes the perspective of its intent—to protect people’s personal data from accidental or institutionalized misuse or loss—it makes a whole lot of sense. You don’t have to be a lawyer to understand that intent.

I was at a seminar recently and a representative from the supervising authority for that member state reflected that their GDPR experts were being poached by industry. They also pointed out that GDPR was an operational exercise, not a legal one, so lawyers alone wouldn’t be enough to determine a corporate response.

Pressure to sell drives confusion

Software companies want to sell licenses, and they want to get into the market quickly, so they need to enable their sales teams to articulate why their GDPR story is better than their competitors’. There is pressure to sell and to simplify the message.

But GDPR in its full extent is not that simple, and it touches a very broad range of roles in an organization as well as different levels. Legal, finance, compliance, audit, IT, security, training, as well as the board of directors, all own a slice of the GDPR pie. Combinations of technical tools, plus ongoing sustainable process governance and cultural change, are required

Because of the breadth of GDPR, the majority of vendors in this space can only offer niche solutions. This sometimes makes it difficult for them to add any real substantive contribution to GDPR compliance. But they still try to find some storyline to hook into.

Diagram courtesy of Neil Patrick

The diagram above is a way of interpreting and delivering a core set of GDPR requirements that can be operationalized via a single solution, as part of a centralized corporate response to GDPR. It has been crafted around the regulation itself as the source of truth. The solution can be integrated with other new tools and legacy systems to deliver a coordinated and centralized view on GDPR compliance.

I believe software vendors have a duty to go back to the regulation and read it, then determine how their software meets the requirements, and clean up their messaging. We’re less likely to get misleading statements, less likely to induce customer GDPR fatigue, and more likely to aggregate around approaches that benefit our customers.

GDPR requires a holistic approach to be effective, and to be a value-add

Now back to the person with the 17 headaches a day. Significant testing was done of the head, blood, hormones, enzymes, and so forth, focusing on solving the problem of headaches. After quite some time, a holistic doctor was engaged who approached the problem from a whole-body perspective, not just focusing on the head. The doctor discovered a misalignment of vertebra in the spine, plus a way of life that led to constrictions in the spine, resulting in the headaches. This is much like the Ayurvedic approach to medicine, which has the belief that health and wellness depend on a delicate balance between body, mind, and spirit.

GDPR needs to be addressed with the same contextualized—the whole-body approach. Organizations shouldn’t be acquiring and implementing niche tools to tick off stated problems as presented by third parties, but should be taking a holistic approach to rolling out the business change that is required by GDPR. Yes, this includes software, but also a permanent cultural shift in how the organization thinks about and handles personal data.

Ayurvedic GDPR

So what is required? Good software focusing on technical GDPR requirements (which does include encryption, but also pseudonymization and other appropriate technical measures); governance of the GDPR compliance processes; and ensuring that the necessary cultural change is pushed out into the business. In other words: better corporate body, mind, and spirit.

If done well and thoroughly, these are the same activities that will deliver benefits like:

  • Reduced cost of compliance (not just GDPR) and likelihood of a fine
  • Reduced organizational and individual risk, linked to business planning and mission
  • Good data governance
  • Reduce cybersecurity risk and reputational risk
  • Smaller, better-organized IT toolset
  • Cleaner user privilege administration
  • Greater organizational agility

Learn more

  • Read our other blogs about GDPR.
  • Read our other GRC Tuesday series blogs.

This article, GRC Tuesdays: “Ayurvedic” GDPR, originally appeared on the SAP BusinessObjects Analytics blog and has been republished with permission.

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Neil Patrick

About Neil Patrick

Dr. Neil Patrick is a Director of SAP Centre of Excellence for GRC & Security covering EMEA. He has over 12 years’ experience in Governance, Risk Management and Compliance (GRC) & Security fields. During this time he has been a managing consultant, run professional services delivery teams in the UK and USA, conducted customer business requirements sessions around the world, and sales and business development initiatives. Neil has presented core GRC and Security thought leadership sessions in strategic customer-facing engagements, conferences and briefing sessions.

Steering Model Redesign: The “Plan, Do, Check, Act” Principle

Reinhold Exner and Kerstin Heining

Part 2 of the “Steering Model” series.

In Part 1 of this series, we looked at how mapping out a transformation strategy must involve redesigning a steering model that aligns directly with that strategy. Here, we’ll cover how to conduct that redesign.

Setting targets

Steering means setting targets. In other words, without touching the current and new requirements towards a target-setting or budgeting process, a discussion of a steering model will by no means be complete.

While starting a steering model discussion, we will enter the area of closed-loop thinking and acting. Commonly we see a “Plan – Do – Check – Act”[1] closed loop established as steering model principle. In this model, we typically understand the components as follows:

  • Plan: Planning starts with understanding the relevant context and the needs of the parties involved, and ends up in setting clear targets.
  • Do: Planning is useless unless the plan is carried out. “Doing” encompasses putting all activities in place to operationalize the plan.
  • Check: Monitoring ensures that targets are likely to be achieved as planned.
  • Act: In case any issues are found in the “Check” step, corrective actions are needed to eliminate the causes of actual or potential nonconformities

Granularity or an aggregated view?

Would it make sense to have on the “Do” side a granular view, along with an aggregated view on the “Plan” side?

Certainly not. It needs to be sufficiently balanced. This balancing is by no means a zero-one decision. It’s a result of a management discussion and future-oriented decision, which should consider the whole steering model. Otherwise we potentially end up by confirming the utmost granularity “down to line-item level” on the “Do” side while neglecting a balanced granularity on the planning side.

Does this mean that in consequence, we generally should aim for the highest planning granularity? “Certainly not” might be the first answer to this question. In practice, the question is not that easy to answer. If we are aiming for more detailed reporting granularity, we should rebalance this requirement with a potentially revised planning philosophy.

Furthermore, we need to understand the implications for follow-up decision-making (“Check”) and resulting actions (“Act”). Again, if we aim for the highest granularity, we accept that the checking might lead us to many detailed questions and decisions and by nature, follow-up actions. A situation where the organization needs 5 days to check, perform, and monitor corrective actions on a detailed level while getting the latest reporting update on a real-time basis contradicts itself. If on the other side, we accept “Plan – Do – Check” without ambition to act, steering will become a theoretical exercise.

Angles for a New Steering Model Discussion

In many large global companies, people complain about growing organizational complexity with lots of silos, scattered accountabilities, and hence, inadequate decision-making and steering capabilities. Additionally, driven by simplified communication technology at lower cost like email and community platforms, more and more people are involved in decision-making processes, often without sufficient clarification of prerequisites, rules, and expected contribution. The result is often too many meetings and email threads with too little outcome, which paralyzes the organization rather than enabling effective and efficient steering.

In his 1982 book Megatrends, author John Naisbitt wrote, “We are drowning in information but starved for knowledge.” This quote is particularly relevant to redesign of a steering model. Data comes at us faster than we can make sense of it. In consequence, it’s not sufficient to describe a future-state steering model just by “Plan – Do – Check – Act.” We need to dig deeper into other improvement areas.

But what are the improvement areas to be considered? The next blogs in this series will explore further.

[1] Source: Plan-Do-Check-Act (also called “PDCA”) originated by Walter Shewhart and made popular by Edward Deming.

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Reinhold Exner

About Reinhold Exner

Reinhold Exner is a principal business transformation consultant with SAP. He has 14 years of management experience in various controlling functions and has worked with SAP for 8 years. He supports international operating companies in optimizing their finance organization and processes leveraging SAP solutions. Reinhold holds a degree in Industrial Engineering (Dipl. Wirtschaftsingenieur) from Technical University of Karlsruhe, Germany.

Kerstin Heining

About Kerstin Heining

Kerstin Heining is a business enterprise principal consultant, working with SAP for 8 years. She supports companies in optimizing their finance organization and processes leveraging SAP solutions. Kerstin holds a degree in Industrial Engineering (Dipl. Wirtschaftsingenieur) from Karlsruhe Technical University, Germany.

It’s Time For Corporate Spending To Manage Itself

Shivani Govil

The past few months have shown that natural disasters such as fires and hurricanes can wreak havoc on our lives, devastating regions and destroying homes. For our businesses, they can also disrupt supply chains and impact operations. But what if you could predict the occurrence of a disaster, anticipate its impact, and act preemptively to avoid any disruption to a production line or your business operations?

What the world considers magic, SAP Ariba considers intelligent procurement – and it’s right around the corner.

For many global organizations, managing hundreds of millions of dollars of spend each year remains a daunting task due to strenuous manual effort. Every day, procurement professionals need to navigate a complex environment with imperfect information. Their goal is to answer questions such as:

  • How do I maximize my spend under management?
  • How do I get insight into my categories of spend, and plan my sourcing strategies?
  • How do I optimize my contracts so that they meet my key goals?
  • How do I minimize supply chain risks while supporting sustainability goals?
  • How can I be sure that orders and invoices comply with preferred suppliers and negotiated prices?
  • How do I process incoming invoices accurately and efficiently?

In fact, there are answers – and solutions. Artificial intelligence (AI) technologies have tremendous value to create better connections between people, processes, systems, data, and context. With AI, the systems you rely on can be more intelligent, instantly and reliably identifying the right information and providing the right insights to help you deliver better business outcomes.

AI technologies can be used to combine relevant data on spend, demand, suppliers, contracts, company policies, and so on, as well as contextual information such as commodity prices, news, and financial data sentiment. Using these technologies, you can discover hidden patterns and relationships in your data, gain valuable new insights, and make better decisions about sourcing strategies, supplier risk assessments, contract negotiations, purchasing decisions, and related procurement activities.

Monitoring and predicting risk events

Consider the potential to improve supplier risk assessments. Imagine if an intelligent system could do the work of a team of analysts, compiling information across reputational, financial, operational, and compliance risks in a fraction of the time. Going further, it could continuously monitor new data and reevaluate risk scores across all key commodity categories. This intelligent system, running 24 hours a day, 7 days a week, could even predict risk events and mitigation measures before the event happens.

AI’s potential to impact the purchasing process can be equally transformational. Imagine being able to use simple voice commands to buy a product through your requisitioning system while being compliant with the existing policy. Or simply taking a picture of a broken part and having your procurement system automatically identify the part and order it for you. Going further, what if your procurement system already anticipates when you need to order something, sends you an alert, and helps place the order – making things easy for you so you don’t have to do the work.

With a new generation of self-learning systems, the procurement process can constantly deliver increased value for the organization – improving effectiveness and accuracy, automating tasks, and detecting opportunities for cost savings. User experiences can be improved through conversational interactions, voice commands, and enabling interactions through messaging platforms.

Are you ready to join the discussion? Listen to SAP Ariba’s Webinar on Intelligent Procurement to learn more.

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Shivani Govil

About Shivani Govil

Shivani Govil is the VP and Global Lead, Mobile Innovation Program, at SAP. Her specialties include mobile, Big Data, IoT, cloud, analytics, product management, sales/go-to-market, strategy, and business development.

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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Death Of An IT Salesman

Jesper Schleimann

As software shifts from supporting the strategy to becoming the strategy of most companies, the relationship and even the sales process between the vendor side and the customer side in the IT industry is subsequently also undergoing some remarkable changes. The traditional IT salesman is an endangered species.

I recently had the pleasure of participating in a workshop with one of Scandinavia’s largest companies to create new business models in the company’s operations business area. As an IT vendor, we worked with the customer in an open process using the design thinking methodology—a creative process in which we jointly visualized, defined, and solidified how new flows of data can change business processes and their business models.

By working with “personas” relevant to their business, we could better understand how technology can help different roles in the involved departments deliver their contributions faster and more efficiently. The scope was completely open. We put our knowledge and experience with technological opportunities in parallel with the company’s own knowledge of the market, processes, and business.

The results may trigger a sale of software from our side at a point, but we do not know exactly which solution—or even if it will happen. What we did do was innovate together and better understand our customer’s future and viable routes to success. Such is the reality of the strategic work of digitizing here on the verge of year 2018.

Solution selling is not enough

In my view, the transgressive nature of technology is radically changing the way businesses and the sales process works. The IT industry—at least parts of it—must focus on completely different types of collaboration with the customer.

Historically, the sales process has already realized major changes. In the past, you’d find a product-fixated “used-car-sales” approach, which identified the characteristics of the box or solution and left it to the customer to find the hole in the cheese. Since then, a generation of IT key account managers learned “solution selling,” with a sharp focus on finding and defining a “pain point” at the customer and then position the solution against this. But today, even that approach falls short.

Endangered species

The challenge is that software solutions now support the formation of new, yet unknown business models. They transverse processes and do not respect silo borders within organizations. Consequently, businesses struggle to define a clear operational road. Top management faces a much broader search of potential for innovation. The creation of a compelling vision itself requires a continuous and comprehensive study of what digitization can do for the value chain and for the company’s ecosystem.

Vendors abandon their customers if they are too busy selling different tools and platforms without entering into a committed partnership to create the new business model. Therefore, the traditional IT salesperson, preoccupied with their own goals, is becoming an endangered species. The customer-driven process requires even key account managers to dig deep and endeavor to understand the customer’s business. The best in the IT industry will move closer to the role of trusted adviser, mastering the required capabilities and accepting the risks and rewards that follow.

Leaving the comfort zone

This obviously has major consequences for the sales culture in the IT industry. Reward mechanisms and incentive structures need to be reconsidered toward a more behavioral incentive. And the individual IT salesperson is going on a personal journey, as the end goal is no longer to close an order, but to create visions and deliver value in partnership with the customer and to do so in an ever-changing context, where the future is volatile and unpredictable.

A key account manager is the customer’s traveling companion. Do not expect to be able to reduce complexity and stay in your comfort zone and not be affected by this change. Vendors should think bigger, and as an IT salesperson, you need to show your ability for transformational thinking. Everyone must be prepared to take the first baby steps, but there will definitely also be some who cannot handle the change. Disruption is not just something you, as a vendor, deliver to a customer. The noble art of being a digital vendor is facing some serious earthquakes.

For more on how tech innovation is disrupting traditional business models, see Why You Should Consider Disrupting Your Own Business.

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Jesper Schleimann

About Jesper Schleimann

Chief Technology Officer, Nordic & Baltic region In his role as Nordic CTO, Jesper's mission is to help customers unlock their business potential by simplifying their digital transformation. Jesper has a Cand.polit. from the University of Copenhagen as well as an Executive MBA from Copenhagen Business School.