How We Can Fix Australia's High Energy Prices

Gavin Mooney

This is the third post in a series looking at the hot topic of Australian power prices. In this post, we’ll look at what can be done about the high power prices in Australia.

In Part 2 we found that cause of the price increases over the last decade could be attributed to the following bill components:

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

A lack of national energy policy?

Many have blamed the current problems on the lack of a national energy policy. In its submission to the Finkel review, chairman of the Australian Energy Market Commission (AEMC) John Pierce stated that the energy sector “has suffered from a long vacuum around national, co-ordinated policy decisions. This has resulted in pervasive uncertainty which makes it difficult for business and consumers to invest – and undermines the reliability of power supply.

Increased supply of reliable energy is needed and this should ideally be selected based on price rather than targets or incentives. I doubt we will see rational investors queueing up to support a new coal-fired power station.

Absence of clear policy is almost certainly a contributor to supply side issues and rising wholesale prices but ACCC chairman Rod Sims said focusing solely on investment uncertainty ignored a “hell of a lot” of other factors.

In his September 2017 National Press Club address, Mr. Sims presented a diagram showing a number of issues to address to make electricity more affordable. The issues are aligned with how much each part of the value chain has contributed to electricity price increases. What is interesting is how widely this list differs from much of the current popular and political debate around energy affordability in Australia.

1. Network

The network cost, the largest component of residential energy bills and the greatest contributor to price rises over the last decade, is probably the thorniest one to address.

Past decisions about network investment are mostly locked-in and will weigh on electricity prices for years to come unless there is a significant change in the funding model.

Network companies submit funding requests to the energy regulator every five years and the regulator determines how much they are allowed to invest, which effectively determines how much they can charge consumers for delivery of electricity. The network companies have traditionally been allowed to appeal any parts of the regulator’s decision that they didn’t like, with no downside risk.

The appeals process has tended to be very successful: according to the regulator, appeals against its decisions between 2008 and 2013 resulted in network company revenue increases of approximately $3.5 billion. This appeals process, known as the Limited Merits Review, was abolished in August this year.

The only other way to reduce network costs under the current funding model would be to reduce the size of regulated asset bases, as suggested in the Finkel Review. But it is unlikely network companies would support any reconsideration or write off of their asset values. This could become increasingly problematic if grid defection (where consumers disconnect from the power grid and become self-sufficient in energy) increases, as the overall network costs would then be shared between fewer end consumers.

2. Retail

The problem here is around consumers not being aware that better offers exist. Consumers can be made more aware of price comparison tools as well as options available to them for managing financial hardship.

Following a meeting with the Prime Minister in August, eight energy retailers have agreed to contact customers who have reached the end of their discounted plan and outline what alternative offers are available. They also committed to developing simpler fact sheets and comparison rates so that consumers can more easily compare the offers available on the market.

In the UK market, there are now third party switching services like Flipper that automatically switch consumers onto the best deal throughout the year. Customers don’t pay Flipper unless they are saved at least £50 per year. Services such as these have the potential to bring huge benefits to Australian consumers.

3. Wholesale (generation)

Currently there is insufficient competition in wholesale markets as well as a high degree of vertical integration with the largest retailers (“gentailers”). More generation capacity is needed, preferably from non-vertically integrated new entrants and in the regions where supply shortfall is most likely (New South Wales, Victoria and South Australia).

Large-scale renewable energy projects will diversify ownership and reduce wholesale prices. This is already starting to happen, with prices forecast to fall steeply in 2018-2022 due to the entry of 6,000MW of renewable energy capacity.

4. Gas prices

To lower the wholesale cost of electricity, the cost of gas needs to be addressed.

As we showed in Part 2, the price of gas is increasingly determining the wholesale price of electricity. Prime Minister Malcolm Turnbull managed to convince the gas producers to supply enough additional gas to the domestic market to cover a predicted shortfall this summer. This will likely avoid price spikes but to lower the cost, more generation capacity is needed.

We can also reduce our reliance on gas up to 25% through energy efficiency measures and fuel shifting, according to a recent ClimateWorks report.

5. Generator bidding behaviour

A recent report by Schneider Electric into spot prices in NSW indicated that bidding practices by generators, including AGL and Origin, were adding about a $30 premium to spot prices over and above what a fair fundamental value would be. This has led Energy Minister Josh Frydenberg to request an investigation by the regulator into generator behaviour.

The AEMC has now confirmed a proposition to change the settlement period from half an hour to five minutes from 1st July 2021. It is widely believed this will reduce generator gaming of the system, lower wholesale costs and drive investment in fast response technologies such as batteries as well as encouraging consumer participation via demand response.

6. Demand response

A significant chunk of what consumers are charged is to ensure the grid can deliver at peak times, such as on a very hot afternoon around 5pm when people get home from work and turn on their air conditioner. But over the whole of 2012, the electricity network experienced “peak demand” for less than 40 hours.

Instead of building additional generation infrastructure to cope with this, most people agree that reducing demand makes more sense. The uptake of solar panels (and now battery storage) are already helping with this. Energy programs that reward customers who make themselves available to briefly turn off the power at times of stress on the grid are also seen as a key way to better manage demand.

7. The National Energy Guarantee

One of the 50 recommendations in the Finkel review was a Clean Energy Target. The government decided to adopt the other 49 recommendations but not this one. Instead, it has introduced the National Energy Guarantee (NEG). Much is still to be determined about the NEG and there has been a focus on the modelling used and whether it would actually lower energy costs.

At this stage is remains more of an idea than a policy and will likely lead to more policy uncertainty in the short term with at least another 12 months of planning, debate and consideration of the policy. It has also been criticised in its current form for not being ambitious enough and likely bringing about an end to investment in large scale renewable energy.

What can consumers do?

Regardless of industry and government policy, consumers can take steps to reduce their power bills immediately.

1. Start shopping around

A report from the AEMC in July found about 70% of people were not shopping around for the best deals on their power bills, even though this could save households over $500 a year. Further, if consumers allow themselves to slip off their discounted plan onto a standing offer, the cost could be even higher.

The annual cost to households of accepting a standing offer from one of the big three retailers instead of the best offer in the market has been estimated at $830 in Victoria, $900 in Queensland and $1400-$1500 in NSW and SA.

2. Reduce energy consumption

This could be achieved by fitting more efficient LED lighting (government rebates are available and LED replacements for 12v halogen downlights are available for free in Victoria under the VEET scheme), using blinds to cool the house and reduce air conditioner usage, or washing clothes in cold water and drying them on a line. More tips are available online.

Solar panels also help reduce a household’s energy consumption. There are schemes available to help households that cannot afford the high upfront cost or are renting or community schemes for those without a roof.

3. Switch to a time-of-use tariff

Consumers who are able to shift their energy consumption away from peak times (such as evenings) can save money on a time-of-use tariff. This can include running energy-hungry appliances such as dishwashers and washing machines at night.

Battery storage can also drastically reduce peak costs by charging batteries during off peak times (or free of charge during the day if the house has solar panels) and discharging the batteries in the evening to avoid drawing power from the grid.

Wrapping up

Just as there is no single cause of the high energy prices in Australia, there is no silver bullet to resolve the problem. Work is already being done to reduce prices and the effects of these changes should be felt in the coming years.

Read the first two posts in this series: Do Australians really pay the highest power prices in the world? and An explanation for the high power prices in Australia.


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.

Four Essential Technologies Powering The Digital Supply Chain

Richard Howells

Growing customer expectations for personalized products and immediate service are making supply chains more complex. And as businesses extend their reach globally, processes are further complicated. We see that industry boundaries are blurring due to new business models enabled by the digital economy.

More than ever, the entire supply chain network needs access to vital information, real-time data analytics, and internal and external collaboration tools to drive this digital transformation.

So, where can businesses turn?

The evolving digital world requires innovative answers. Fortunately, technologies are emerging and converging to help address these challenges faster than ever before. Here are some examples.

Internet of Things

The Internet of Things (IoT) is generating massive volumes of data, connecting everything from the products we buy to the cars we drive to the homes we live in. With products and assets becoming more connected and intelligent, the easier it’ll be to efficiently integrate predictive, automated activities with business processes. And as functions get smarter, new business models – based on data from goods, assets, machines, and vehicles – will begin taking hold, ushering in an era of new and radically adaptable businesses.

Machine learning and artificial intelligence

The wave of Big Data flooding business is helping make assets smarter through embedded, easy-to-consume machine learning capabilities. Machine learning uses sophisticated algorithms to “learn” from, and make sense of, this data. Machine learning is the core of artificial intelligence (AI). It continuously learns and improves, every time you feed in new data by accessing, analyzing and finding patterns in Big Data in a way that is beyond any human capabilities. The ability to continuously monitor data and make precise, intelligent predictions has a massive impact on business success. Organizations are taking advantage of insights based on artificial intelligence and business analytics to support competitive capabilities such as predictive maintenance and usage-based billing.

Predictive analytics

Within Big Data is an abundance of unstructured contextual information – weather, traffic, social media trends, and demand signals – that offer companies real-time, 360-degree views of their supply chains. Businesses are using this information to identify new opportunities and mitigate risks as the entire value chain becomes more transparent. By leveraging this data to support predictive analytics, decision-makers can pinpoint trends and optimize operations faster than ever – a critical competitive advantage in today’s fast-paced environment.

Blockchain

Blockchain, though a young technology, has the potential to accelerate supply chain digitalization by securing transactions, ensuring traceability and chain of ownership, and shoring up cybersecurity. In fact, according to Gartner’s latest Hype Cycle for Supply Chain Execution (July 2017) – Blockchain was rated “transformational” but with a market penetration of “less than 1%.” The key is to identify use cases that involve improved transparency, greater traceability, enhanced performance, and secure transactions.

Laying the foundation for your digital supply chain

With innovative technologies providing a roadmap for the future, companies are beginning to see the full potential of a digital supply chain. To make this a reality, knowing when and how to use and combine these technologies to solve specific business problems is key.

IoT, for example, generates huge amounts of data. Predictive analytics and machine learning process this data to make it smarter. And by leveraging artificial intelligence, the data can be used to automate processes, with blockchain ensuring the processes remain traceable and secure.

To learn more about how to enable a smart, connected digital supply chain of one for today’s digital economy, download the IDC Info brief on  Digital Supply Chain of ONE.

Follow me @howellsrichard

This article originally appeared on Forbes SAPVoice.


Richard Howells

About Richard Howells

Richard Howells is a Vice President at SAP responsible for the positioning, messaging, AR , PR and go-to market activities for the SAP Supply Chain solutions.

Innovation In The Chemical Industry: Real-World Examples

Stefan Guertzgen

A recent S.M.A.C. Talk Technology Podcast delves into the trends that make the global chemical industry tick and how its progressive use of technology appears to be reshaping grassroots businesses within the sector.

Hosted by Brian Fanzo and Daniel Newman, the 15-minute audio interview of industry expert Thorsten Wenzel, vice president of the worldwide chemical business unit of SAP, illuminates some practical success stories.

Without a doubt, Wenzel possesses a cutting-edge and global understanding of the chemical sector, where the forward-looking innovation resides and misconceptions about the industry’s willingness to embrace technology. He points out that industry analysts have too often claimed chemical-focused companies had fallen behind other industries.

“A digital transformation is not really new for the chemical industry,” Wenzel says. “We are doing that since 25 years, and if you think about it, there’s lots of truth about that at the plant level where a lot of automatization efforts and digitalization efforts were done in the last 20 years already.

“But on the other side, if you talk to analysts and compare industries, it seems to be that the chemical industry is somehow a laggard and little bit delayed in comparison to other industries, which are way more advanced in that. So this is somehow contradictory, but I can tell you, wherever I go, whenever I talk to customers, digital transformation and IoT topics are on top of the agenda.”

He also sees things such as predictive maintenance, shutdowns, turnaround, outages, and profitability as driving force issues going forward. But Wenzel enjoys the unique talent of breaking down complex theoretical ideas into tangible lessons. And real-life success stories are things non-theorists can really wrap their heads around.

Technology transforms businesses in practical ways

During the podcast, Wenzel provides examples that make sense to real meat-and-potatoes business decision-makers. During his time in the chemical industry, he watched as a paint outfit completely shifted its marketing strategy and to some extent, its customer base by integrating virtual technology.

“Let me just give you one example: This is Asian Paints from India, which was the classical producer selling their paints and coatings via the classical channels; wholesale, distribution, the big supermarkets,” Wenzel says. “And they confirmed … They changed their business model from a just producing-oriented model to a more service-oriented model. That means today, Asian Paints is a company which visits the big customers they have, like companies with big corporate offices, offices that would like to change their interior, who want to paint their offices in a new way.”

Asian Paints, Wenzel says, changed directions by integrating virtual design applications. These programs allowed them to go into high-end corporate spaces, photograph, image, and create design proposals for the customer. They transformed from a one-dimensional manufacturer to a “service-oriented” outfit that went beyond just selling paint products. Basically, virtual design helped them become profitable on two fronts.

In the agricultural industry, organizations like Monsanto have morphed from product producers and sellers to developing hands-on relationships with salt-of-the-earth farmers.

“Monsanto is doing something where they really use machine learning for seed optimization,” Wenzel says. “They let the machine bring out the seeds, put on the fertilizer, the plant protection chemicals, and then see which plants grow best and what do we have to do from the seeds producer perspective to really have the optimum seed portfolio for our customers, plus plant protection, plus disease protection. So that’s an interesting thing we are seeing with these customers, both based on machine learning.”

By using machine learning, farmers can convey images directly to Monsanto, which can advise them on plant-protection and seed protocols. Just as IoT, Big Data, and blockchain provide beginning-to-end technology that has reformed much of the retail industry, the chemical sector is immersed in stakeholder connectivity.

Regardless of insider and outsider differences of opinion about the chemical industry embracing technology, digital transformation is having a profound impact on businesses and the economic advancement of people everywhere. That extends from the chemical product manufacturer to the end customer. In effect, things like digital boardrooms put all the key stakeholders in the same virtual space.

Take 15 minutes while enjoying your beverage of choice and immerse yourself in the cutting-edge thinking of this S.M.A.C. Talk Technology Podcast featuring SAP chemical industry expert Thorsten Wenzel.

Hear the full episode here. Learn how to innovate at scale by incorporating individual innovations back to the core business to drive tangible business value by reading Accelerating Digital Transformation in Chemicals.


Stefan Guertzgen

About Stefan Guertzgen

Dr. Stefan Guertzgen is the Global Director of Industry Solution Marketing for Chemicals at SAP. He is responsible for driving Industry Thought Leadership, Positioning & Messaging and strategic Portfolio Decisions for Chemicals.

Hack the CIO

By Thomas Saueressig, Timo Elliott, Sam Yen, and Bennett Voyles

For nerds, the weeks right before finals are a Cinderella moment. Suddenly they’re stars. Pocket protectors are fashionable; people find their jokes a whole lot funnier; Dungeons & Dragons sounds cool.

Many CIOs are enjoying this kind of moment now, as companies everywhere face the business equivalent of a final exam for a vital class they have managed to mostly avoid so far: digital transformation.

But as always, there is a limit to nerdy magic. No matter how helpful CIOs try to be, their classmates still won’t pass if they don’t learn the material. With IT increasingly central to every business—from the customer experience to the offering to the business model itself—we all need to start thinking like CIOs.

Pass the digital transformation exam, and you probably have a bright future ahead. A recent SAP-Oxford Economics study of 3,100 organizations in a variety of industries across 17 countries found that the companies that have taken the lead in digital transformation earn higher profits and revenues and have more competitive differentiation than their peers. They also expect 23% more revenue growth from their digital initiatives over the next two years—an estimate 2.5 to 4 times larger than the average company’s.

But the market is grading on a steep curve: this same SAP-Oxford study found that only 3% have completed some degree of digital transformation across their organization. Other surveys also suggest that most companies won’t be graduating anytime soon: in one recent survey of 450 heads of digital transformation for enterprises in the United States, United Kingdom, France, and Germany by technology company Couchbase, 90% agreed that most digital projects fail to meet expectations and deliver only incremental improvements. Worse: over half (54%) believe that organizations that don’t succeed with their transformation project will fail or be absorbed by a savvier competitor within four years.

Companies that are making the grade understand that unlike earlier technical advances, digital transformation doesn’t just support the business, it’s the future of the business. That’s why 60% of digital leading companies have entrusted the leadership of their transformation to their CIO, and that’s why experts say businesspeople must do more than have a vague understanding of the technology. They must also master a way of thinking and looking at business challenges that is unfamiliar to most people outside the IT department.

In other words, if you don’t think like a CIO yet, now is a very good time to learn.

However, given that you probably don’t have a spare 15 years to learn what your CIO knows, we asked the experts what makes CIO thinking distinctive. Here are the top eight mind hacks.

1. Think in Systems

A lot of businesspeople are used to seeing their organization as a series of loosely joined silos. But in the world of digital business, everything is part of a larger system.

CIOs have known for a long time that smart processes win. Whether they were installing enterprise resource planning systems or working with the business to imagine the customer’s journey, they always had to think in holistic ways that crossed traditional departmental, functional, and operational boundaries.

Unlike other business leaders, CIOs spend their careers looking across systems. Why did our supply chain go down? How can we support this new business initiative beyond a single department or function? Now supported by end-to-end process methodologies such as design thinking, good CIOs have developed a way of looking at the company that can lead to radical simplifications that can reduce cost and improve performance at the same time.

They are also used to thinking beyond temporal boundaries. “This idea that the power of technology doubles every two years means that as you’re planning ahead you can’t think in terms of a linear process, you have to think in terms of huge jumps,” says Jay Ferro, CIO of TransPerfect, a New York–based global translation firm.

No wonder the SAP-Oxford transformation study found that one of the values transformational leaders shared was a tendency to look beyond silos and view the digital transformation as a company-wide initiative.

This will come in handy because in digital transformation, not only do business processes evolve but the company’s entire value proposition changes, says Jeanne Ross, principal research scientist at the Center for Information Systems Research at the Massachusetts Institute of Technology (MIT). “It either already has or it’s going to, because digital technologies make things possible that weren’t possible before,” she explains.

2. Work in Diverse Teams

When it comes to large projects, CIOs have always needed input from a diverse collection of businesspeople to be successful. The best have developed ways to convince and cajole reluctant participants to come to the table. They seek out technology enthusiasts in the business and those who are respected by their peers to help build passion and commitment among the halfhearted.

Digital transformation amps up the urgency for building diverse teams even further. “A small, focused group simply won’t have the same breadth of perspective as a team that includes a salesperson and a service person and a development person, as well as an IT person,” says Ross.

At Lenovo, the global technology giant, many of these cross-functional teams become so used to working together that it’s hard to tell where each member originally belonged: “You can’t tell who is business or IT; you can’t tell who is product, IT, or design,” says the company’s CIO, Arthur Hu.

One interesting corollary of this trend toward broader teamwork is that talent is a priority among digital leaders: they spend more on training their employees and partners than ordinary companies, as well as on hiring the people they need, according to the SAP-Oxford Economics survey. They’re also already being rewarded for their faith in their teams: 71% of leaders say that their successful digital transformation has made it easier for them to attract and retain talent, and 64% say that their employees are now more engaged than they were before the transformation.

3. Become a Consultant

Good CIOs have long needed to be internal consultants to the business. Ever since technology moved out of the glasshouse and onto employees’ desks, CIOs have not only needed a deep understanding of the goals of a given project but also to make sure that the project didn’t stray from those goals, even after the businesspeople who had ordered the project went back to their day jobs. “Businesspeople didn’t really need to get into the details of what IT was really doing,” recalls Ferro. “They just had a set of demands and said, ‘Hey, IT, go do that.’”

Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants.

But that was then. Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants. “If you’re building a house, you don’t just disappear for six months and come back and go, ‘Oh, it looks pretty good,’” says Ferro. “You’re on that work site constantly and all of a sudden you’re looking at something, going, ‘Well, that looked really good on the blueprint, not sure it makes sense in reality. Let’s move that over six feet.’ Or, ‘I don’t know if I like that anymore.’ It’s really not much different in application development or for IT or technical projects, where on paper it looked really good and three weeks in, in that second sprint, you’re going, ‘Oh, now that I look at it, that’s really stupid.’”

4. Learn Horizontal Leadership

CIOs have always needed the ability to educate and influence other leaders that they don’t directly control. For major IT projects to be successful, they need other leaders to contribute budget, time, and resources from multiple areas of the business.

It’s a kind of horizontal leadership that will become critical for businesspeople to acquire in digital transformation. “The leadership role becomes one much more of coaching others across the organization—encouraging people to be creative, making sure everybody knows how to use data well,” Ross says.

In this team-based environment, having all the answers becomes less important. “It used to be that the best business executives and leaders had the best answers. Today that is no longer the case,” observes Gary Cokins, a technology consultant who focuses on analytics-based performance management. “Increasingly, it’s the executives and leaders who ask the best questions. There is too much volatility and uncertainty for them to rely on their intuition or past experiences.”

Many experts expect this trend to continue as the confluence of automation and data keeps chipping away at the organizational pyramid. “Hierarchical, command-and-control leadership will become obsolete,” says Edward Hess, professor of business administration and Batten executive-in-residence at the Darden School of Business at the University of Virginia. “Flatter, distributive leadership via teams will become the dominant structure.”

5. Understand Process Design

When business processes were simpler, IT could analyze the process and improve it without input from the business. But today many processes are triggered on the fly by the customer, making a seamless customer experience more difficult to build without the benefit of a larger, multifunctional team. In a highly digitalized organization like Amazon, which releases thousands of new software programs each year, IT can no longer do it all.

While businesspeople aren’t expected to start coding, their involvement in process design is crucial. One of the techniques that many organizations have adopted to help IT and businesspeople visualize business processes together is design thinking (for more on design thinking techniques, see “A Cult of Creation“).

Customers aren’t the only ones who benefit from better processes. Among the 100 companies the SAP-Oxford Economics researchers have identified as digital leaders, two-thirds say that they are making their employees’ lives easier by eliminating process roadblocks that interfere with their ability to do their jobs. Ninety percent of leaders surveyed expect to see value from these projects in the next two years alone.

6. Learn to Keep Learning

The ability to learn and keep learning has been a part of IT from the start. Since the first mainframes in the 1950s, technologists have understood that they need to keep reinventing themselves and their skills to adapt to the changes around them.

Now that’s starting to become part of other job descriptions too. Many companies are investing in teaching their employees new digital skills. One South American auto products company, for example, has created a custom-education institute that trained 20,000 employees and partner-employees in 2016. In addition to training current staff, many leading digital companies are also hiring new employees and creating new roles, such as a chief robotics officer, to support their digital transformation efforts.

Nicolas van Zeebroeck, professor of information systems and digital business innovation at the Solvay Brussels School of Economics and Management at the Free University of Brussels, says that he expects the ability to learn quickly will remain crucial. “If I had to think of one critical skill,” he explains, “I would have to say it’s the ability to learn and keep learning—the ability to challenge the status quo and question what you take for granted.”

7. Fail Smarter

Traditionally, CIOs tended to be good at thinking through tests that would allow the company to experiment with new technology without risking the entire network.

This is another unfamiliar skill that smart managers are trying to pick up. “There’s a lot of trial and error in the best companies right now,” notes MIT’s Ross. But there’s a catch, she adds. “Most companies aren’t designed for trial and error—they’re trying to avoid an error,” she says.

To learn how to do it better, take your lead from IT, where many people have already learned to work in small, innovative teams that use agile development principles, advises Ross.

For example, business managers must learn how to think in terms of a minimum viable product: build a simple version of what you have in mind, test it, and if it works start building. You don’t build the whole thing at once anymore.… It’s really important to build things incrementally,” Ross says.

Flexibility and the ability to capitalize on accidental discoveries during experimentation are more important than having a concrete project plan, says Ross. At Spotify, the music service, and CarMax, the used-car retailer, change is driven not from the center but from small teams that have developed something new. “The thing you have to get comfortable with is not having the formalized plan that we would have traditionally relied on, because as soon as you insist on that, you limit your ability to keep learning,” Ross warns.

8. Understand the True Cost—and Speed—of Data

Gut instincts have never had much to do with being a CIO; now they should have less to do with being an ordinary manager as well, as data becomes more important.

As part of that calculation, businesspeople must have the ability to analyze the value of the data that they seek. “You’ll need to apply a pinch of knowledge salt to your data,” advises Solvay’s van Zeebroeck. “What really matters is the ability not just to tap into data but to see what is behind the data. Is it a fair representation? Is it impartial?”

Increasingly, businesspeople will need to do their analysis in real time, just as CIOs have always had to manage live systems and processes. Moving toward real-time reports and away from paper-based decisions increases accuracy and effectiveness—and leaves less time for long meetings and PowerPoint presentations (let us all rejoice).

Not Every CIO Is Ready

Of course, not all CIOs are ready for these changes. Just as high school has a lot of false positives—genius nerds who turn out to be merely nearsighted—so there are many CIOs who aren’t good role models for transformation.

Success as a CIO these days requires more than delivering near-perfect uptime, says Lenovo’s Hu. You need to be able to understand the business as well. Some CIOs simply don’t have all the business skills that are needed to succeed in the transformation. Others lack the internal clout: a 2016 KPMG study found that only 34% of CIOs report directly to the CEO.

This lack of a strategic perspective is holding back digital transformation at many organizations. They approach digital transformation as a cool, one-off project: we’re going to put this new mobile app in place and we’re done. But that’s not a systematic approach; it’s an island of innovation that doesn’t join up with the other islands of innovation. In the longer term, this kind of development creates more problems than it fixes.

Such organizations are not building in the capacity for change; they’re trying to get away with just doing it once rather than thinking about how they’re going to use digitalization as a means to constantly experiment and become a better company over the long term.

As a result, in some companies, the most interesting tech developments are happening despite IT, not because of it. “There’s an alarming digital divide within many companies. Marketers are developing nimble software to give customers an engaging, personalized experience, while IT departments remain focused on the legacy infrastructure. The front and back ends aren’t working together, resulting in appealing web sites and apps that don’t quite deliver,” writes George Colony, founder, chairman, and CEO of Forrester Research, in the MIT Sloan Management Review.

Thanks to cloud computing and easier development tools, many departments are developing on their own, without IT’s support. These days, anybody with a credit card can do it.

Traditionally, IT departments looked askance at these kinds of do-it-yourself shadow IT programs, but that’s changing. Ferro, for one, says that it’s better to look at those teams not as rogue groups but as people who are trying to help. “It’s less about ‘Hey, something’s escaped,’ and more about ‘No, we just actually grew our capacity and grew our ability to innovate,’” he explains.

“I don’t like the term ‘shadow IT,’” agrees Lenovo’s Hu. “I think it’s an artifact of a very traditional CIO team. If you think of it as shadow IT, you’re out of step with reality,” he says.

The reality today is that a company needs both a strong IT department and strong digital capacities outside its IT department. If the relationship is good, the CIO and IT become valuable allies in helping businesspeople add digital capabilities without disrupting or duplicating existing IT infrastructure.

If a company already has strong digital capacities, it should be able to move forward quickly, according to Ross. But many companies are still playing catch-up and aren’t even ready to begin transforming, as the SAP-Oxford Economics survey shows.

For enterprises where business and IT are unable to get their collective act together, Ross predicts that the next few years will be rough. “I think these companies ought to panic,” she says. D!


About the Authors

Thomas Saueressig is Chief Information Officer at SAP.

Timo Elliott is an Innovation Evangelist at SAP.

Sam Yen is Chief Design Officer at SAP and Managing Director of SAP Labs.

Bennett Voyles is a Berlin-based business writer.

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

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Survey: Four Ways Machine Learning Will Disrupt Your Business

Dan Wellers and Dirk Jendroska

We are entering the era of the machine learning enterprise, in which this subset of artificial intelligence (AI) capabilities will revolutionize operating models, shake up staffing methods, upend business models, and potentially alter the nature of competition itself. The adoption of machine learning capabilities will be limited only by an organization’s ability to change – but not every company will be willing or able to make such a radical shift.

Very soon, the difference between the haves and the have-nots of machine learning will become clear. “The disruption over the next three to five years will be massive,” says Cliff Justice, principal in KPMG’s Innovation and Enterprise Solutions team. Companies hanging onto their legacy processes will struggle to compete with machine learning enterprises able to compete with a fraction of the resources and entirely new value propositions.

For those seeking to be on the right side of the disruption, a new survey, conducted by SAP and the Economist Intelligence Unit (EIU), offers a closer look at organizations we’ve identified as the Fast Learners of machine learning: those that are already seeing benefits from their implementations.

Machine learning is unlike traditional programmed software. Machine learning software actually gets better – autonomously and continuously – at executing tasks and business processes. This creates opportunities for deeper insight, non-linear growth, and levels of innovation previously unseen.

Given that, it’s not surprising that machine learning has evolved from hype to have-to-have for the enterprise in seemingly record time. According to the SAP/EIU survey, more than two-thirds of respondents (68%) are already experimenting with it. What’s more, many of these organizations are seeing significantly improved performance across the breadth of their operations as a result, and some are aiming to remake their businesses on the back of these singular, new capabilities.

So, what makes machine learning so disruptive? Based on our analysis of the survey data and our own research, we see four primary reasons:

1. It’s probabilistic, not programmed

Machine learning uses sophisticated algorithms to enable computers to “learn” from large amounts of data and take action based on data analysis rather than being explicitly programmed to do something. Put simply, the machine can learn from experience; coded software does not. “It operates more like a human does in terms of how it formulates its conclusions,” says Justice.

That means that machine learning will provide more than just a one-time improvement in process and productivity; those improvements will continue over time, remaking business processes and potentially creating new business models along the way.

2. It creates exponential efficiency

When companies integrate machine learning into business processes, they not only increase efficiency, they are able to scale up without a corresponding increase in overhead. If you get 5,000 loan applications one month and 20,000 the next month, it’s not a problem, says Sudir Jha, head of product management and strategy for Infosys; the machines can handle it.

3. It frees up capital – financial and human

Because machine learning can be used to automate any repetitive task, it enables companies to redeploy resources to areas that make the organization more competitive, says Justice. It also frees up the employees within an organization to perform higher-value, more rewarding work. That leads to reduced turnover and higher employee satisfaction. And studies show that happier employees lead to higher customer satisfaction and better business results.

4. It creates new opportunities

AI and machine learning can offer richer insight, deeper knowledge, and predictions that would not be possible otherwise. Machine learning can enable not only new processes, but entirely new business models or value propositions for customers – “opportunities that would not be possible with just human intelligence,” says Justice. “AI impacts the business model in a much more disruptive way than cloud or any other disruption we’ve seen in our lifetimes.”

Machine learning systems alone, however, will not transform the enterprise. The singular opportunities enabled by these capabilities will only occur for companies that dedicate themselves to making machine learning part of a larger digital transformation strategy. The results of the SAP/EIU survey explain the makeup of the evolving machine learning enterprise. We’ve identified key traits important to the success of these machine-learning leaders that can serve as a template for others as well as an overview of the outcomes they’re already seeing from their efforts.

Learn more and download the full study here.  

 


Dan Wellers

About Dan Wellers

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

Dirk Jendroska

About Dirk Jendroska

Dr. Dirk Jendroska is Head of Strategy and Operations Machine Learning at SAP. He supports the vision of SAP Leonardo Machine Learning to enable the intelligent enterprise by making enterprise applications intelligent. He leads a team working on machine learning strategy, marketing and communications.