Why Australians Pay The Highest Power Prices In The World

Gavin Mooney

This is the second in a series of three posts looking at the hot topic of Australian power prices:

  1. Do Australians really pay the highest power prices in the world?
  2. An explanation for the high power prices in Australia (this post)
  3. A look at what can be done about the high power prices in Australia

In Part 1 we established that – while there are a few different ways to compare the data – Australia does have pretty much the most expensive electricity in the world. The price increases in the last decade have been significant, more than doubling according to the Consumer Price Index.

The question now is why prices have risen so much, when Australia is blessed with vast coal and gas reserves and huge renewable energy potential?

First, we need to look at the components of a typical residential electricity bill.

  • Wholesale: Effectively the cost to generate electricity.
  • Network: The charges for delivery of energy via the poles and wires from the point of generation (power stations) to the point of consumption (homes and businesses).
  • Retail: Charges levied by the consumer’s chosen retailer for selling electricity.
  • Federal environment: This includes items such as the large scale renewable energy target and subsidies for feed in tariffs.
  • Metering: These charges only apply in Victoria to fund the state-mandated roll out of smart meters.

These components have all contributed different amounts to the rising energy prices. A September 2017 report by the Australian Competition and Consumer Commission (ACCC) identified and ranked the source components of power bill increases over the last decade by how much they had each contributed:

  1. Network charges (41%)
  2. Retail costs and margins (24%)
  3. Wholesale costs (19%)
  4. Green schemes (16%)

Let’s now look at these one by one in more detail as well as the effects of renewable energy.

1. Network charges

Investment in the electricity network has been the primary driver in power bill increases for some time. 

The way the network companies make their money is by earning a certain rate of return on their asset base. As the size of the asset base increases, so do revenues. A revenue cap is set by the regulator every five years, dictating how much the (natural monopoly) networks can spend on building and maintenance. The end consumers foot the bill for this, even if the spend wasn’t needed. This has turned out to be the case in Australia.

Investment decisions were based on forecasts projecting that demand for electricity would continue to rise. The forecasts were wrong – demand has flatlined and declined since about 2009, mainly due to increased rooftop solar and energy efficiency improvements in household appliances. Consumers may also have reacted to higher energy prices. (As a side note – demand may increase again if there is widespread adoption of electric vehicles in Australia.)

2015 Senate enquiry found that there had been significant overinvestment in networks far beyond what was required, especially in the government-owned companies in NSW and QLD. This has been termed network “gold plating”.

2. Retail costs and margins

Retail costs have also risen. This is the part of a power bill that several investigations have found is the hardest to monitor, and the least transparent to consumers. 

There are a few different reasons for the increases in retail costs.

Finding the best offer
The market is characterised by very wide price dispersion, meaning a consumer can save hundreds of dollars by moving from the worst to the best offer. It is also complex, making it hard to compare rates and find the best offers. Private comparison websites do not include all market offers, while the websites offered by the Australian Energy Regulator and the Victorian government do not provide the tools customers need to differentiate between offers. A Grattan Institute study in March 2017 found the system was so complicated that many consumers did not understand what savings they could make and just gave up.

The Thwaites review in August 2017 found Victorian households are paying on average 21% more for their electricity than the cheapest market offer available. Nearly a quarter of customers could save $500 or more by switching to the best available offer.

Punishing loyal customers
Consumers are often attracted by the deep discounts of a retailer’s initial offer, only to slip unknowingly onto a much smaller discount or a costly standing offer a year or two later. AGL Energy chief executive Andy Vesey admitted last year that big power companies were guilty of punishing their most loyal customers in this way, but said subsequently AGL was abandoning the practice.

Retailer profit margins
Profit margins have also been in the spotlight recently, with a Grattan Institute study finding retailers’ profit margins in Victoria were around 13% – higher than in other retail sectors, and more than double the margin that regulators considered fair when they set retail electricity prices. The study concluded that Victorians would save about $250 million a year if the profit margin of electricity retailers fell to match that of other retail businesses. The companies rejected this, saying they have been forced to spend more on marketing due to increased competition.

Failure of competition
Competition in electricity retailing hasn’t delivered what was promised: lower prices for consumers. The failure appears to be worst in Victoria, the state with the most retailers and the longest experience of deregulation.

The market is highly concentrated. Despite there being 25 energy retailers in Victoria, three players (Origin, AGL and Energy Australia) command a market share of over 70%. The next two largest players, taking the total market share to around 90%, are vertically integrated, making it difficult for others to compete.

3. Wholesale charges

Network charges may have been the primary driver of power bill increases over the last decade, but they have now levelled off. More recently, it is the cost of electricity generation that has been the biggest contributor to rising electricity prices. In the past year or so some states have seen increases of over 100%.

There are two main reasons for the increases in wholesale costs: generator bidding behaviour and the soaring price of gas.

Generator power
With the recent closures of the Northern and Hazelwood coal plants in the last year, the gap between supply and demand at peak times has tightened. The market is therefore now far more susceptible to wholesale price surges if a generator breaks down (not uncommon, given Australia’s ageing fleet of coal generators) or an operator decides to withhold their electrons from the market until demand rises. In each state, the two or three principal generators command a market share of 70% or more, giving them enough clout to swing the market.

Indeed, generator market power was clearly seen in Queensland recently with two generators having two thirds of capacity and prices spiking. When the Queensland Government directed its generators to tone down their bidding, prices immediately reduced significantly.

The rise of gas
The second reason for the sudden increase in wholesale costs is much higher gas prices. As supply has tightened, natural gas fired power plants are increasingly being called upon to meet demand. As illustrated in the diagram below, prices are set in five-minute intervals, determined by the price of the most expensive generator required. At 4:25 this was $38, set by Generator 5. Settlement is done in half hour blocks and the spot price for the half hour is determined as the average of the prices for the six five-minute intervals.

As the most expensive fuel that we rely on to create electricity to meet our needs, gas is increasingly determining the wholesale price that generators are paid. Gas generation now sets the wholesale price around a third of the time in South Australia.

Why is gas going up?
The reason for the rising gas prices is more mysterious. Australia has a lot of gas, so much in fact that it is expected to become the world’s largest exporter by 2020. Yet it is cheaper to buy Australian gas in Japan than it is in Australia and AEMO is already forecasting a shortfall in domestic gas supply.

ACCC chairman Rod Sims noted “International prices are at all-time lows; Australian gas prices are at all-time highs.” High local prices appear to be the result of so-far inexplicable behaviour by exporters, selling gas at lower prices on the export spot market than they could achieve by selling the gas locally. Australians are effectively subsidising loss-making exports. Or it could be down to a cartel controlling Australian gas.

An ACCC inquiry into the east coast gas market identified three causes:

  1. The introduction of the export LNG projects changed gas flows and domestic prices.
  2. Oil prices fell faster and further than some thought possible, curtailing investment in gas exploration and development.
  3. Regulatory uncertainty and exploration moratoria have significantly limited or delayed the potential for new gas supply.

4. Green schemes

Responsible for about one sixth of the electricity price rises in the last decade, green schemes include:

  • The bipartisan renewable energy target
  • Solar feed-in tariffs that pay consumers for power sent into the grid.
  • Some programs designed to boost energy efficiency, mostly through the use of better light bulbs and appliances.

The cost of green schemes is not transparent: it is smeared over all electricity consumers and can appear costless to some. But they do cost consumers, often inequitably as those with solar panels are being subsidised by those who do not have them.

Is renewable energy to blame?

No. Well, maybe partly.

Renewable energy has increased significantly over the last decade and now provides around one fifth of Australia’s energy needs. It is an easy target and often blamed in sweeping statements as the sole reason for power price rises without an appreciation of the finer details explained above.

The Renewable Energy Target has helped reduce power bills and will continue to do so, according to the government’s own modelling as well as analysis by energy market experts ROAM Consulting, who found that Australian households would pay over half a billion dollars more for power in 2020 without the Renewable Energy Target in place (equivalent to more than $50 per household).

The ACT has the lowest bills in the country and is on track to reach its goal of 100% renewable energy. Indeed, a recent report by the Australian National University showed that electricity price increases from 2006-2016 were highest in the states with the least renewable energy.

But on the other hand…

Wind and solar generate intermittently and at zero marginal cost – their operating costs are far lower than coal and gas generators. This means that when wind and solar are generating, prices will be lower.

However, over the medium term, lower wholesale prices could contribute to early retirement decisions for existing coal generators, and push prices higher due to increased reliance on more costly gas plants.

Intermittent generation can also increase spot price volatility and this puts upward pressure on electricity prices as well as making new investment decisions more difficult.

Now we understand the many reasons why Australian power prices have risen so much, we next need to look at what can be done about it. Stay tuned for Part 3!

Read Part 1 of this series here.

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Gavin Mooney

About Gavin Mooney

Gavin Mooney is a utilities industry solution specialist for SAP. From a background in Engineering and IT, Gavin has been working in the utilities industry with SAP products for nearly 15 years. He has had the privilege of working with a number of Electricity, Gas and Water Utilities across the globe to implement SAP’s Industry Solution for Utilities. He now works with utilities to help them identify the best way to run simple and run better with SAP's latest products. Gavin loves to network and build lasting business relationships and is passionate about cleantech and the fundamental transformation currently shaking up the utilities industry.

Fordlandia And The End Of The Vertically Integrated Company

James Marland

At River Rouge, Michigan, Henry Ford set up a company that would produce a million tractors a year. It was to include a blast furnace that would allow him to bring iron ore in on boats and turn the ore into steel, then into the tractors’ component parts, and the tractors would drive out of the other end. The plant also had shipyards, sawmills, concrete plants, and tanneries; this process was called “vertical integration.”

Ford did not want to be dependent on any outside suppliers at all. But there was one raw material that he did not control: rubber, which was controlled in Malaya and Sri Lanka by British agents.

So in 1927, Henry Ford, now the richest man in the world, bought a tract of land twice the size of Delaware in the Brazilian Amazon. His intention was to grow rubber for the wheels for his new Model T cars. In some ways, this was just an extension of his assembly line, one which now started in the fertile soil of the Amazon.

It ended in disaster, and the shells of his houses, chapels, schools, and hospitals can still be seen poking out of the resurgent rainforest. For some, this ended the vision of the vertically integrated company, with raw materials coming in one end and finished goods coming out of the other.

What we see now could not be more different. Companies often own no assets, buy no raw material, and hardly have anyone on the payroll. Apple doesn’t make anything. Facebook’s main assets are the habits and preferences of its customers. Boeing doesn’t make the cockpit on its own aircraft.

But many IT systems are still set up for the age of the vertically integrated company, because they focus only on the processes inside a company. But with most of the value created externally, this approach will always be inferior to a network-based value chain management approach, where the vital assets, intellectual property, and information from customers, suppliers, and stakeholders can be managed as effectively as Henry Ford managed his factories.

You don’t need to wait: Ariba Network is already doing with companies like Coca-Cola, FMC, Microsoft, Emirates, and BASF. Learn how Ariba is powering the world’s global supply chain.

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James Marland

About James Marland

James is responsible for defining and rolling out strategies for the Network with particular focus on Europe. He joined Ariba at the launch of the Ariba Network in 1998 after previously being a Solution Consultant at SAP America. In addition he has held the position of Director of Algorithms at Vendavo, an SAP Partner in the area of Pricing. He has a Bachelor of Science degree in Mathematics from Southampton University. Follow James's twitter feed at @JamesMarland

Can Artificial Intelligence Drive More Ethical Retail?

Judith Magyar

A few years ago Samantha Zirkin and her husband took their two young children and travelled around the world, volunteering at orphanagesschools, and homes for abandoned or abused children.

“I saw many children with the same sad story: dad gone, mother dead or dying after working under appalling conditions in a garment factory, no sanitation, no medical care,” she recounts. “Some children had been so malnourished they could not stand on their own two legs. I decided to delve into the retail world to learn about the supply chain and workers’ rights. And I wanted to know if people would pay $70 instead of $50 for an item they knew had been produced under fair conditions.”

Tackling the big issues in retail

Today Samantha is the CEO and Founder of Point 93, a company that addresses several big problems in retail. Point 93’s software replaces discounting with dynamic pricing and addresses the need to reeducate customers. “Customers have been conditioned to expect deep discounts, which hurt the retailer’s brand and bottom line,” she explains. “Our solution encourages positive buying behavior and allows customers to provide feedback about product, price, and in-store experience.”

Most importantly, the software enables retailers to share their corporate social responsibility (CSR) campaigns with customers and analyze their impact on sales and loyalty.

“Retailers invest a lot in CSR activities, but they do a poor job communicating about them. They often don’t know whether their customers care about the campaigns or if they are willing to pay more for items produced under ethical conditions,” says Samantha.

Retail with a purpose

Research like the SAP/EY market study shows that as digital transformation takes hold across all industries and lines of business, profit alone will not make companies successful. Successful companies must offer their employees a sense of purpose. Take the case of CVS, the American pharmacy chain that stopped selling tobacco products in 2014 because it conflicted with their purpose of helping people on a path to better health.

“CVS has a history of being purpose-led,” said Helena Foulkes, president of CVS Pharmacy and executive vice president of CVS Health, recently at NRF’s Big Show 2018. “We walked away from $2 billion in sales to be a leader in healthcare.”

One year later, the company was able to show a measurable positive effect on public health nationwide. Not only did people purchase fewer cigarettes in states where CVS has stores, they also bought more nicotine patches. This purpose-driven decision did not harm the drugstore giant’s overall sales, which have been up, thanks to new business from in-store medical services and health plans.

For all its advances, modern commerce is a double-edged sword. Some consumer habits can be wasteful or harmful. Is it possible to improve conditions in a garment industry that depends on cutthroat pricing to drive consumption and is notorious for cutting costs at the expense of its employees?

AI to the rescue

Experts believe artificial intelligence (AI) could help make retail more purpose-driven. According to Francesca Rossi, AI ethics global leader at IBM Research, ethical retail should start with the design of algorithms that determine how retailers use data to understand consumers and meet their demands.

“To help human society flourish, we must ask the right questions from the beginning in order to design the human experience differently,” she said at a panel discussion at NRF 2018. Ms. Rossi went on to explain the importance of making AI a multidisciplinary effort. “We shouldn’t leave AI in the hands of developers and designers. AI must become a multi-stakeholder effort involving psychologists, economists, philosophers, the users, and so on.”

Tenzin Priyadarshi, director of the Ethics Initiative at the MIT Media Lab, agreed with Ms Rossi during the discussion. “Normally, you wouldn’t expect to find a monk like me at a retail event,” he quipped. “I believe in moderate consumption. We should ask ourselves: what is a healthy rate of consumption? Retailers now have the right data at their disposal, the right insight into consumer behavior and very powerful tools that can challenge society to be more responsible when it comes to healthy consumption.”

Massive supply chain inefficiencies, environmental damage, and low wages that perpetuate the cycle of human suffering and poverty are all part of the hidden cost and long term damage that can be caused by modern commerce. But it doesn’t have to be like that. Machine learning and AI can help retailers and product managers create dialogues along the customer journey and reward responsible buying behavior. Technology can give the shopper the opportunity to ask about the source of a product or understand what goes on behind the scenes to determine its price. Transparency enables informed decisions.

But we don’t need to wait for machines to guide the way. As consumers, we can all use technology to learn more about the source of our garments, our food, and our medications, and then use common sense to do the right thing!

Check out www.sap.com/nrf and be sure to follow me @magyarj.

This article first appeared on SAP Business Trends.

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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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The “Purpose” Of Data

Timo Elliott

I’ve always been passionate about the ability of data and analytics to transform the world.

It has always seemed to me to be the closest thing we have to modern-day magic, with its ability to conjure up benefits from thin air. Over the last quarter century, I’ve had the honor of working with thousands of “wizards” in organizations around the world, turning information into value in every aspect of our daily lives.

The projects have been as simple as Disney using real-time analytics to move staff from one store to another to keep lines to a minimum: shorter lines led to bigger profits (you’re more likely to buy that Winnie-the-Pooh bear if there’s only one person ahead of you), but also higher customer satisfaction and happier children.

Or they’ve been as complex as the Port of Hamburg: constrained by its urban location, it couldn’t expand to meet the growing volume of traffic. But better use of information meant it was able to dramatically increase throughput – while improving the life of city residents with reduced pollution (less truck idling) and fewer traffic jams (smart lighting that automatically adapts to bridge closures).

I’ve seen analytics used to figure out why cheese was curdling in Wisconsin; count the number of bubbles in Champagne; keep track of excessive fouls in Swiss soccer, track bear sightings in Canada; avoid flooding in Argentina; detect chewing-gum-blocked metro machines in Brussels; uncover networks of tax fraud in Australia; stop trains from being stranded in the middle of the Tuscan countryside; find air travelers exposed to radioactive substances; help abused pets find new homes; find the best people to respond to hurricanes and other disasters; and much, much more.

The reality is that there’s a lot of inefficiency in the world. Most of the time it’s invisible, or we take it for granted. But analytics can help us shine a light on what’s going on, expose the problems, and show us what we can do better – in almost every area of human endeavor.

Data is a powerful weapon. Analytics isn’t just an opportunity to reduce costs and increase profits – it’s an opportunity to make the world a better place.

So to paraphrase a famous world leader, next time you embark on a new project:

“Ask not what you can do with your data, ask what your data can do for the world.”

What are your favorite “magical” examples, where analytics helped create win/win/win situations?

Download our free eBook for more insight on How the Port of Hamburg Doubled Capacity with Digitization.

This article originally appeared on Digital Business & Business Analytics.

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Timo Elliott

About Timo Elliott

Timo Elliott is an Innovation Evangelist for SAP and a passionate advocate of innovation, digital business, analytics, and artificial intelligence. He was the eighth employee of BusinessObjects and for the last 25 years he has worked closely with SAP customers around the world on new technology directions and their impact on real-world organizations. His articles have appeared in publications such as Harvard Business Review, Forbes, ZDNet, The Guardian, and Digitalist Magazine. He has worked in the UK, Hong Kong, New Zealand, and Silicon Valley, and currently lives in Paris, France. He has a degree in Econometrics and a patent in mobile analytics.