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.


Gavin Mooney

About Gavin Mooney

Gavin Mooney is a utilities industry solution advisor for SAP. From a background in Engineering and IT, Gavin has been working in the utilities industry with SAP products for 16 years. After working as a consultant with a number of Electricity, Gas and Water Utilities across the globe to implement SAP’s Industry Solution for Utilities, Gavin joined SAP in 2014. He now works with utilities across Australia and New Zealand to help them simplify, innovate 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.

The Realities Of Innovation In Manufacturing

Kevin Jinks

Many leaders in manufacturing say, “There are things on our shop floor we wouldn’t want anyone to see.” When they say this, they mean the sheer amount of manual effort needed to keep things running. They mean paperwork, Post-it notes, and a lack of automation at the operational, tactical level. Throughout the industry, my customers are talking about operational efficiencies. I’ve learned that no matter the size or location of your business, there are plenty of people who share your problems.

Operational efficiency: goodbye Post-it notes and paperwork

If you’re like most of my customers, you’re taking a hard look at how well your shop or plant functions. Demand forecasting, for example, is a tough call when data about markets is not tightly aligned to production.

A single-system approach can be part of the answer to these problems. New technologies give you solutions that are end-to-end, capable of automating your shop floor and then delivering cognitive technology to help you figure out failures in advance. This gives you fresh insight into demand.

Realistically, the best way to help improve your businesses is with pre-built solutions; these become the core to your success because the commodity work that you normally do on your nickel has already been done. And when you can remove risk, it’s a good thing.

To predict demand, you don’t need 40 systems; you need one

Even the best-run shops struggle with how to predict demand. Let’s say your forecasting is way off – you completely underestimated demand and market. This missed forecast becomes a missed profit opportunity. And your competitors will be quick to step in.

That’s why a digital approach works so well for manufacturers. Technology is a powerful tool here, because it can deliver input into the demand side. If you can do this well, you won’t undermake or overmake. You’ll optimize profits.

The latest “digital core” solutions for manufacturing are robust. They’re provable. And when you have the building blocks into which you can add robotics, prepare to be surprised. The best solutions use AI to mine data that you’re not thinking of, including strong social media mining. This is the kind of information that lets you refine your products – or launch new ones.

You don’t need 40 ERP systems to improve your business; you need one. Imagine a plant that uses the IoT and real-time sensors to read equipment and perform predictive maintenance; you’ll keep the lines running. Plus you’ll keep track of how many products you’ve created and can sell. You’ll be able to tell which products consumed lots of raw materials, which means that plant managers are armed with the information they need to proactively understand what’s going on. Again, it’s not about the number of systems you have in place, but the effectiveness and reliability of just one.

The realities of change

You can’t gain a lot of insight if you have 40 different systems. So when you’re investigating a single-system approach, make sure that you’re adopting best practices, rather than designing best practices. Your projects should involve adopting processes, not creating them.

Today, digital transformation is not a design/build project. After all, there are already solutions available that determine how you take an order, process that order, store your inventory, pick it and ship it. So don’t spend your time on an accounts-receivable aging report. Instead, seek out technology that lets you take advantage of AI, cloud, security and deep, predictive analytics. You’ll surround great code with advanced tech to get you light years ahead of the competition.

Learn more

To take advantage of all the benefits described in this post, request your HANA Impact assessment today. IBM will be at SAPPHIRE NOW and ASUG Annual SAP Conference this June 5-7 in Orlando. Visit IBM at booth #612 and talk to IBM-SAP experts – check out our event website to see what we’re doing at the event.


Kevin Jinks

About Kevin Jinks

Kevin Jinks is Vice President & Partner / Industrial Sector SAP Leader for IBM Global Business Services. With more than 22 years of IT consulting and client management experience, he has extensive knowledge in ERP systems, architectural design, system development and implementation management for major clients globally.

Three Ways Digital Transformation Is Disrupting The Metals Industry

Jennifer Scholze

The metals industry is at a crossroads. It faces decreasing global demand, trade flow disruptions, widening workforce skill gaps, and declining resource quality. These challenges have hurt profits and reduced capital investments. The metals industry is ripe for change – and digital transformation is leading the way.

Stefan Koch, global lead for metals in the mill products industry business unit at SAP, recently spoke about the future of the metals industry on the S.M.A.C. Talk Technology Podcast. Koch addressed the three major ways digitization will change the industry. Machine learning will simplify production processes and streamline operations. Virtual reality (VR) will enable virtual plant operations, creating new business models. Blockchain will enable verified material tracking for purchases like green (recycled) steel. Together, these technologies can disrupt everything from extraction to production to sales.

1. Machine learning simplifies production processes, predicts quality outcomes

“Smart machines” are not a new addition to the metals industry. The industry already relies on sensor data to monitor machine performance and maximize uptime. For most companies, however, that’s the current extent of this data utility.

“It’s still very often that you see this island of information,” says Stefan Koch on the S.M.A.C. Talk Technology Podcast. “Somebody thinks of production. Another one thinks of, “Oh yeah, that’s my customers, that’s my sales.” In the future, everything will need to go together and work together in an integrated way.”

Machine learning will allow companies to do more with their data, optimizing everything from materials sourcing to process adjustments. For example, a company could link systems across multiple operations and operators. This company could then use machine learning to either eliminate or automate redundant processes like invoicing.

Koch predicts that machine learning will also enable more advanced metal production capabilities that are cost-effective and high-value for the end customer. Presently, identical production processes may still yield slightly different finished products. These differences are due to naturally occurring material variances. Machine learning will allow companies to “look into the future” and predict quality outcomes down to the slightest variation. Producers could then pre-assign products to specific customers, delivering greater value and increasing customer satisfaction.

2. Virtual reality enables remote plant operations and value chain control

Will metal companies of the future still own physical deposits? Perhaps not, says Koch. On the S.M.A.C. Talk Technology Podcast, Koch notes that some metal companies are already moving away from asset ownership. These companies are “contracting production, resources, logistics, and materials” in a bid to control the value chain.

Consider, for example, a company that shares tasks with suppliers in other countries. This company could use virtual reality contacts to enable repair and control. The company could also use virtual reality to exchange or integrate data, boosting collaboration across the value chain.

Koch predicts that virtual reality will play an important role in streamlining remote plant operation. “These are concepts we see already picking up.”

3. Blockchain guarantees supply chain validity and authenticity

A blockchain is a tamper-proof distributed ledger that maintains a historical record of all data. Since this record is independent of a central authority, it is inherently resilient. Algorithms enable continuous verification and validity calibration. Data can be signed, timestamped, and immutably recorded in the blockchain. Blockchain can then provide essential transaction validation and purity verification, guaranteeing authenticity.

Koch predicts the metal industry will use blockchain to “provide faster and more rapid ways to authenticate materials.” In the recycling industry, for example, not all parties involved communicate with one another every day. The lack of a closed loop supply chain creates authentication challenges. In fact, Koch characterizes the current metal recycling supply chain as “a pretty random list of partners who interact on a long timeframe.” Blockchain solves this challenge by providing an immutable authenticity guarantee at each step.

Why the future of metals depends on digital transformation

Digitization is more than using predictive maintenance to maximize machine uptime. It’s about disrupting outdated processes and creating new business models.

The World Economic Forum predicts that, by 2025, digital transformation will create more than $425 billion of value for the mining and metals industry. Companies that embrace digital transformation will be best positioned to capitalize on this value creation.

To learn more about how digital transformation is disrupting the metals industry, listen to the S.M.A.C. Talk Technology Podcast with Stefan Koch. Learn how to bring new technologies and services together to power digital transformation by downloading The IoT Imperative for Energy and Natural Resource Companies.


Jennifer Scholze

About Jennifer Scholze

Jennifer Scholze is the Global Lead for Industry Marketing for the Mill Products and Mining Industries at SAP. She has over 20 years of technology marketing, communications and venture capital experience and lives in the Boston area with her husband and two children.

The Human Angle

By Jenny Dearborn, David Judge, Tom Raftery, and Neal Ungerleider

In a future teeming with robots and artificial intelligence, humans seem to be on the verge of being crowded out. But in reality the opposite is true.

To be successful, organizations need to become more human than ever.

Organizations that focus only on automation will automate away their competitive edge. The most successful will focus instead on skills that set them apart and that can’t be duplicated by AI or machine learning. Those skills can be summed up in one word: humanness.

You can see it in the numbers. According to David J. Deming of the Harvard Kennedy School, demand for jobs that require social skills has risen nearly 12 percentage points since 1980, while less-social jobs, such as computer coding, have declined by a little over 3 percentage points.

AI is in its infancy, which means that it cannot yet come close to duplicating our most human skills. Stefan van Duin and Naser Bakhshi, consultants at professional services company Deloitte, break down artificial intelligence into two types: narrow and general. Narrow AI is good at specific tasks, such as playing chess or identifying facial expressions. General AI, which can learn and solve complex, multifaceted problems the way a human being does, exists today only in the minds of futurists.

The only thing narrow artificial intelligence can do is automate. It can’t empathize. It can’t collaborate. It can’t innovate. Those abilities, if they ever come, are still a long way off. In the meantime, AI’s biggest value is in augmentation. When human beings work with AI tools, the process results in a sort of augmented intelligence. This augmented intelligence outperforms the work of either human beings or AI software tools on their own.

AI-powered tools will be the partners that free employees and management to tackle higher-level challenges.

Those challenges will, by default, be more human and social in nature because many rote, repetitive tasks will be automated away. Companies will find that developing fundamental human skills, such as critical thinking and problem solving, within the organization will take on a new importance. These skills can’t be automated and they won’t become process steps for algorithms anytime soon.

In a world where technology change is constant and unpredictable, those organizations that make the fullest use of uniquely human skills will win. These skills will be used in collaboration with both other humans and AI-fueled software and hardware tools. The degree of humanness an organization possesses will become a competitive advantage.

This means that today’s companies must think about hiring, training, and leading differently. Most of today’s corporate training programs focus on imparting specific knowledge that will likely become obsolete over time.

Instead of hiring for portfolios of specific subject knowledge, organizations should instead hire—and train—for more foundational skills, whose value can’t erode away as easily.

Recently, educational consulting firm Hanover Research looked at high-growth occupations identified by the U.S. Bureau of Labor Statistics and determined the core skills required in each of them based on a database that it had developed. The most valuable skills were active listening, speaking, and critical thinking—giving lie to the dismissive term soft skills. They’re not soft; they’re human.


This doesn’t mean that STEM skills won’t be important in the future. But organizations will find that their most valuable employees are those with both math and social skills.

That’s because technical skills will become more perishable as AI shifts the pace of technology change from linear to exponential. Employees will require constant retraining over time. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is already outdated by the time students graduate, according to The Future of Jobs, a report from the World Economic Forum (WEF).

The WEF’s report further notes that “65% of children entering primary school today will ultimately end up working in jobs that don’t yet exist.” By contrast, human skills such as interpersonal communication and project management will remain consistent over the years.

For example, organizations already report that they are having difficulty finding people equipped for the Big Data era’s hot job: data scientist. That’s because data scientists need a combination of hard and soft skills. Data scientists can’t just be good programmers and statisticians; they also need to be intuitive and inquisitive and have good communication skills. We don’t expect all these qualities from our engineering graduates, nor from most of our employees.

But we need to start.

From Self-Help to Self-Skills

Even if most schools and employers have yet to see it, employees are starting to understand that their future viability depends on improving their innately human qualities. One of the most popular courses on Coursera, an online learning platform, is called Learning How to Learn. Created by the University of California, San Diego, the course is essentially a master class in human skills: students learn everything from memory techniques to dealing with procrastination and communicating complicated ideas, according to an article in The New York Times.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing.

Although there is a longstanding assumption that social skills are innate, nothing is further from the truth. As the popularity of Learning How to Learn attests, human skills—everything from learning skills to communication skills to empathy—can, and indeed must, be taught.

These human skills are integral for training workers for a workplace where artificial intelligence and automation are part of the daily routine. According to the WEF’s New Vision for Education report, the skills that employees will need in the future fall into three primary categories:

  • Foundational literacies: These core skills needed for the coming age of robotics and AI include understanding the basics of math, science, computing, finance, civics, and culture. While mastery of every topic isn’t required, workers who have a basic comprehension of many different areas will be richly rewarded in the coming economy.
  • Competencies: Developing competencies requires mastering very human skills, such as active listening, critical thinking, problem solving, creativity, communication, and collaboration.
  • Character qualities: Over the next decade, employees will need to master the skills that will help them grasp changing job duties and responsibilities. This means learning the skills that help employees acquire curiosity, initiative, persistence, grit, adaptability, leadership, and social and cultural awareness.


The good news is that learning human skills is not completely divorced from how work is structured today. Yonatan Zunger, a Google engineer with a background working with AI, argues that there is a considerable need for human skills in the workplace already—especially in the tech world. Many employees are simply unaware that when they are working on complicated software or hardware projects, they are using empathy, strategic problem solving, intuition, and interpersonal communication.

The unconscious deployment of human skills takes place even more frequently when employees climb the corporate ladder into management. “This is closely tied to the deeper difference between junior and senior roles: a junior person’s job is to find answers to questions; a senior person’s job is to find the right questions to ask,” says Zunger.

Human skills will be crucial to navigating the AI-infused workplace. There will be no shortage of need for the right questions to ask.

One of the biggest changes narrow AI tools will bring to the workplace is an evolution in how work is performed. AI-based tools will automate repetitive tasks across a wide swath of industries, which means that the day-to-day work for many white-collar workers will become far more focused on tasks requiring problem solving and critical thinking. These tasks will present challenges centered on interpersonal collaboration, clear communication, and autonomous decision-making—all human skills.

Being More Human Is Hard

However, the human skills that are essential for tomorrow’s AI-ified workplace, such as interpersonal communication, project planning, and conflict management, require a different approach from traditional learning. Often, these skills don’t just require people to learn new facts and techniques; they also call for basic changes in the ways individuals behave on—and off—the job.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing. As science gains a better understanding of how the human brain works, many behaviors that affect employees on the job are understood to be universal and natural rather than individual (see “Human Skills 101”).

Human Skills 101

As neuroscience has improved our understanding of the brain, human skills have become increasingly quantifiable—and teachable.

Though the term soft skills has managed to hang on in the popular lexicon, our understanding of these human skills has increased to the point where they aren’t soft at all: they are a clearly definable set of skills that are crucial for organizations in the AI era.

Active listening: Paying close attention when receiving information and drawing out more information than received in normal discourse

Critical thinking: Gathering, analyzing, and evaluating issues and information to come to an unbiased conclusion

Problem solving: Finding solutions to problems and understanding the steps used to solve the problem

Decision-making: Weighing the evidence and options at hand to determine a specific course of action

Monitoring: Paying close attention to an issue, topic, or interaction in order to retain information for the future

Coordination: Working with individuals and other groups to achieve common goals

Social perceptiveness: Inferring what others are thinking by observing them

Time management: Budgeting and allocating time for projects and goals and structuring schedules to minimize conflicts and maximize productivity

Creativity: Generating ideas, concepts, or inferences that can be used to create new things

Curiosity: Desiring to learn and understand new or unfamiliar concepts

Imagination: Conceiving and thinking about new ideas, concepts, or images

Storytelling: Building narratives and concepts out of both new and existing ideas

Experimentation: Trying out new ideas, theories, and activities

Ethics: Practicing rules and standards that guide conduct and guarantee rights and fairness

Empathy: Identifying and understanding the emotional states of others

Collaboration: Working with others, coordinating efforts, and sharing resources to accomplish a common project

Resiliency: Withstanding setbacks, avoiding discouragement, and persisting toward a larger goal

Resistance to change, for example, is now known to result from an involuntary chemical reaction in the brain known as the fight-or-flight response, not from a weakness of character. Scientists and psychologists have developed objective ways of identifying these kinds of behaviors and have come up with universally applicable ways for employees to learn how to deal with them.

Organizations that emphasize such individual behavioral traits as active listening, social perceptiveness, and experimentation will have both an easier transition to a workplace that uses AI tools and more success operating in it.

Framing behavioral training in ways that emphasize its practical application at work and in advancing career goals helps employees feel more comfortable confronting behavioral roadblocks without feeling bad about themselves or stigmatized by others. It also helps organizations see the potential ROI of investing in what has traditionally been dismissed as touchy-feely stuff.

In fact, offering objective means for examining inner behaviors and tools for modifying them is more beneficial than just leaving the job to employees. For example, according to research by psychologist Tasha Eurich, introspection, which is how most of us try to understand our behaviors, can actually be counterproductive.

Human beings are complex creatures. There is generally way too much going on inside our minds to be able to pinpoint the conscious and unconscious behaviors that drive us to act the way we do. We wind up inventing explanations—usually negative—for our behaviors, which can lead to anxiety and depression, according to Eurich’s research.

Structured, objective training can help employees improve their human skills without the negative side effects. At SAP, for example, we offer employees a course on conflict resolution that uses objective research techniques for determining what happens when people get into conflicts. Employees learn about the different conflict styles that researchers have identified and take an assessment to determine their own style of dealing with conflict. Then employees work in teams to discuss their different styles and work together to resolve a specific conflict that one of the group members is currently experiencing.

How Knowing One’s Self Helps the Organization

Courses like this are helpful not just for reducing conflicts between individuals and among teams (and improving organizational productivity); they also contribute to greater self-awareness, which is the basis for enabling people to take fullest advantage of their human skills.

Self-awareness is a powerful tool for improving performance at both the individual and organizational levels. Self-aware people are more confident and creative, make better decisions, build stronger relationships, and communicate more effectively. They are also less likely to lie, cheat, and steal, according to Eurich.

It naturally follows that such people make better employees and are more likely to be promoted. They also make more effective leaders with happier employees, which makes the organization more profitable, according to research by Atuma Okpara and Agwu M. Edwin.

There are two types of self-awareness, writes Eurich. One is having a clear view inside of one’s self: one’s own thoughts, feelings, behaviors, strengths, and weaknesses. The second type is understanding how others view us in terms of these same categories.

Interestingly, while we often assume that those who possess one type of awareness also possess the other, there is no direct correlation between the two. In fact, just 10% to 15% of people have both, according to a survey by Eurich. That means that the vast majority of us must learn one or the other—or both.

Gaining self-awareness is a process that can take many years. But training that gives employees the opportunity to examine their own behaviors against objective standards and gain feedback from expert instructors and peers can help speed up the journey. Just like the conflict management course, there are many ways to do this in a practical context that benefits employees and the organization alike.

For example, SAP also offers courses on building self-confidence, increasing trust with peers, creating connections with others, solving complex problems, and increasing resiliency in the face of difficult situations—all of which increase self-awareness in constructive ways. These human-skills courses are as popular with our employees as the hard-skill courses in new technologies or new programming techniques.

Depending on an organization’s size, budget, and goals, learning programs like these can include small group training, large lectures, online courses, licensing of third-party online content, reimbursement for students to attain certification, and many other models.

Human Skills Are the Constant

Automation and artificial intelligence will change the workplace in unpredictable ways. One thing we can predict, however, is that human skills will be needed more than ever.

The connection between conflict resolution skills, critical thinking courses, and the rise of AI-aided technology might not be immediately obvious. But these new AI tools are leading us down the path to a much more human workplace.

Employees will interact with their computers through voice conversations and image recognition. Machine learning will find unexpected correlations in massive amounts of data but empathy and creativity will be required for data scientists to figure out the right questions to ask. Interpersonal communication will become even more important as teams coordinate between offices, remote workplaces, and AI aides.

While the future might be filled with artificial intelligence, deep learning, and untold amounts of data, uniquely human capabilities will be the ones that matter. Machines can’t write a symphony, design a building, teach a college course, or manage a department. The future belongs to humans working with machines, and for that, you need human skills. D!


About the Authors

Jenny Dearborn is Chief Learning Officer at SAP.

David Judge is Vice President, SAP Leonardo, at SAP.

Tom Raftery is Global Vice President and Internet of Things Evangelist at SAP.

Neal Ungerleider is a Los Angeles-based technology journalist and consultant.

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

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HR In The Age Of Digital Transformation

Neha Makkar Patnaik

HR has come a long way from the days of being called Personnel Management. It’s now known as People & Culture, Employee Experience, or simply People, and the changes in the last few years have been especially far-reaching, to say the least; seismic even.

While focused until recently on topics like efficiency and direct access to HR data and services for individual employees, a new and expanded HR transformation is underway, led by employee experience, cloud capabilities including mobile and continuous upgrades, a renewed focus on talent, as well as the availability of new digital technologies like machine learning and artificial intelligence. These capabilities are enabling HR re-imagine new ways of delivering HR services and strategies throughout the organization. For example:

  • Use advanced prediction and optimization technologies to shift focus from time-consuming candidate-screening processes to innovative HR strategies and business models that support growth
  • Help employees with tailored career paths, push personalized learning recommendations, suggest mentors and mentees based on skills and competencies
  • Predict flight risk of employees and prescribe mitigation strategies for at-risk talent
  • Leverage intelligent management of high-volume, rules-based events with predictions and recommendations

Whereas the traditional view of HR transformation was all about doing existing things better, the next generation of HR transformation is focused on doing completely new things.

These new digital aspects of HR transformation do not replace the existing focus on automation and efficiency. They work hand in hand and, in many cases, digital technologies can further augment automation. Digital approaches are becoming increasingly important, and a digital HR strategy must be a key component of HR’s overall strategy and, therefore, the business strategy.

For years, HR had been working behind a wall, finally got a seat at the table, and now it’s imperative for CHROs to be a strategic partner in the organization’s digital journey. This is what McKinsey calls “Leading with the G-3” in An Agenda for the Talent-First CEO, in which the CEO, CFO, and CHRO (i.e., the “G-3”) ensure HR and finance work in tandem, with the CEO being the linchpin and the person who ensures the talent agenda is threaded into business decisions and not a passive response or afterthought.

However, technology and executive alignment aren’t enough to drive a company’s digital transformation. At the heart of every organization are its people – its most expensive and valuable asset. Keeping them engaged and motivated fosters an innovation culture that is essential for success. This Gallup study reveals that a whopping 85% of employees worldwide are performing below their potential due to engagement issues.

HR experiences that are based on consumer-grade digital experiences along with a focus on the employee’s personal and professional well-being will help engage every worker, inspiring them to do their best and helping them turn every organization’s purpose into performance. Because, we believe, purpose drives people and people drive business results.

Embark on your HR transformation journey

Has your HR organization created a roadmap to support the transformation agenda? Start a discussion with your team about the current and desired state of HR processes using the framework with this white paper.

Also, read SAP’s HR transformation story within the broader context of SAP’s own transformation.


Neha Makkar Patnaik

About Neha Makkar Patnaik

Neha Makkar Patnaik is a principal consultant at SAP Labs India. As part of the Digital Transformation Office, Neha is responsible for articulating the value proposition for digitizing the office of the CHRO in alignment with the overall strategic priorities of the organization. She also focuses on thought leadership and value-based selling programs for retail and consumer products industries.