How Is Digital Transformation Changing The Game In The Chemical Industry?

Stefan Guertzgen

In a recent episode of Game Changers, host Bonnie Graham explored digital transformation in the chemical industry. I had the opportunity to participate in this radio program with two other industry experts: Bob Parker, group VP of research direction at IDC Manufacturing Insights and Retail Insights, and Michael Casey, managing director at Accenture North American Chemicals and Natural Resources Industry Group. Here’s what we discussed.

Buzzwords with real-world applications

Cloud and digital are two of today’s big buzzwords. But beyond those words is real technology that is tangible and available today to push ahead businesses and the industry as a whole. We have the opportunity to advance operations and behaviors to make the disruptive changes.

These changes are vital to a business’ future operations and profitability. Conventional business models are being challenged. New technology is entering the game, but it can be difficult to integrate into current operations. Reimagining business models, processes, and how people work will make a big difference in how competitive a business can be in the future.

How to get there

The challenges and the opportunities for new business models, products, and services can create problems. Innovation is accelerating; the problem is that there is no existing roadmap to get from one maturity level or stage to the next. How do you create a roadmap for a place you’ve never been?

A better analogy would be the historic explorers who used a compass or star navigation to figure out where they were headed. In today’s move towards digital innovation, we have a direction, even when we’re walking into completely new territory. Businesses need to abandon limited, conventional thinking during that journey. Refusing to go on the journey of digitization and innovation will simply leave you disrupted. Why? Competitors are not shy about making this exploration.

Digital transformation and maturation in the chemical industry

IDC industry research shows a multi-tiered maturity model. It contains over 100 elements based on over 1,000 companies across the industry. Most businesses are still early in maturity; behind in some areas and ahead in others. But it’s a sign that the market is ready to take off.

Chemical companies, from the CEO down, are making the decision to build technology capabilities; the Economist recently referred to the chemical industry as being in the golden age of materials.

Redefining the industry

In the past, the industry has been based around demand for particular chemicals. Now we’re seeing a shift from products sold in high-volume, well-margined markets. Digital transformation is streamlining the industry. It’s changing markets for commodity chemicals as well as specialty chemicals. Chemicals are now being tailored to their end application.

A third tier is developing beyond commodity and specialty markets, focusing on the versatile molecule. Molecular structures can be mapped, similar to a genome, and allow the industry to develop chemicals tailored for very specific purposes and customers. Having these tight specifications allows for finer control and specialty expertise within the industry.

Commodity chemical companies are losing ground with these new options and must be reimagined to remain competitive. New competitors are springing up all over the world. The commodity companies must adapt or lose out. But whether they move upstream or downstream in the value chain, a new business model is vital to success.

Examples from the industry

But what industry giants are making the shift to digitization and new business models? Here are a few examples discussed during the Game Changers program:

  • Asian Paints previously sold only paints and coatings. They’ve shifted to a downstream position with over 10,000 retailers. They sell color as a personalized experience for the end user.
  • Monsanto’s focus was selling seeds and agricultural chemicals. They’ve shifted to answering pain points for farmers. The company now provides increased yields based on proprietary recipes leveraging advanced analytics that are customized to a farmer’s field.
  • A chlorine company looked at its biggest customers. Instead of remaining in the commodity chemical business, it shifted to producing sensor-based automatic dispensing machines. This made it much easier for customers to keep their water chlorinated without testing and additional work. Instead of having to price based upon a commodity (chlorine), the company could price based upon value (pool cleanliness).

Industry collaboration

Similar businesses regularly run common equipment. What if you could share the data from that equipment to compare how it performs across the industry? You could even receive maintenance tips to improve asset availability.

In-memory engines and cloud computing add unprecedented levels of granularity and speed to data processing and analytics, helping you to gain real-time insight into things such as asset performance across your or your customers’ network in order to make innovative, service oriented business decisions.

Many companies are no longer selling chemicals. They’re selling solutions to customers’ problems. Muntajat in Qatar is selling millions of tons of chemicals without any production assets. It provides chemical logistics for companies. Its shift to more granular customer needs and experiences is creating an effective new business model.

Are you ready to make the change? Take the Digital Readiness Survey to learn where you stand on your Digital Journey and how we can help you plan your platform and roadmap for transition.

Learn more about SAPPHIRENOW and secure your spot today!


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.

Artificial Intelligence: What’s Now And Next In IoT-Driven Supply Chain Innovation

Marcell Vollmer

As with most people, coffee is one of the most important rituals in my morning routine. There’s something about the aroma and taste that kick-starts my ability to have a great day. So imagine my surprise when a favorite coffee shop was closed before I had to jump on an early-morning flight. The employees were in the shop, but the gate locked out coffee aficionados, like me, who really needed that jolt of caffeine.

Although this experience was understandably a letdown, it was also a source of inspiration. Think about it: How many times has your business been “locked out” of an opportunity to change? You see the advantages that can help your operation move forward and accomplish great things; however, there’s something that’s keeping you from crossing that threshold and succeeding.

Such is the case for supply chain automation initiatives. Although the Internet of Things (IoT) is playing a significant role in today’s supply chain, advanced analytics-driven data aggregation platforms are now earmarked as an area to watch. IDC recently reported that 60% of manufacturers will likely leverage an advanced analytics-driven data aggregation platform to improve the speed and accuracy of the fulfillment process this year. However, Gartner gives a stern warning that three out of five factory-level artificial intelligence (AI) initiatives in large global companies will likely stall within the next three years due to inadequate skill sets.

Four AI opportunities that can strengthen your IoT-driven supply chain

IDC’s and Gartner’s predictions are stunning revelations considering the skyrocketing growth of computing capacity and data volumes used to empower supply chain leaders to make smarter decisions. But if done well, supply chain managers can extend their IoT capabilities with artificial intelligence to run operations that are fast, nimble, and intelligent enough to stay competitive in today’s high-speed global marketplace.

1. Extend your IoT platform to build a smarter supply chain

As IoT devices get increasingly smaller and more prevalent in every asset along the supply chain, an impressive volume of data is not fully leveraged – leaving much of the insight it contains in the dark. Personally, I think this common problem is not a problem at all. Instead, it’s a sign that the IoT is maturing to a point where AI is the natural next step to discover and use real-time information in the best way possible.

For example, when a new customer signs a contract, production planning can start automatically. A digital signature triggers warehouses to pick and ship goods needed as outlined in the agreement. Then production is scheduled, and qualified and available human resources are assigned by a system. If employees need to travel to a customer location to install a machine, arrangements are made in parallel. Through AI, the best rates for hotels, flights, and car rentals and dates that fit into everyone’s schedule and time restrictions can be determined immediately.

Once installed, the machine can use Big Data algorithms to learn patterns and behaviors. This approach enables them to detect the threat of malfunctions that require maintenance, define factors impacting performance, and optimize processes and opportunities for automation.

2. Drive profitability with unprecedented optimization and simplification

The struggle against complexity is something that plagues the mind of supply chain managers. From a growing network of suppliers and the risk of corrupt sourcing practices to trade restrictions and just-in-time delivery, automation can help them sleep better at night. Center for Global Enterprise research reveals that the more digital the supply chain, the greater the chance the business can reduce procurement costs by 20%, lower supply chain process costs by 50%, and increase revenue by 10%.

For example, beverage powerhouse Schweppes Australia combated the inaccuracies and inefficiencies of its supply chain by upgrading its entire distribution center management system with AI technology. The paperless system gave supply chain managers greater visibility into every task – from sourcing to last-mile delivery – to eliminate inefficient practices such as over-replenishing pick faces, which often led to delivery delays and suboptimal spend.

By introducing more flexible and efficient practices, Schweppes’ supply chain processes are now 99.9% accurate. Managers monitor shipments, at the click of a button, to pinpoint and evaluate gaps in replenishment, prioritize and sequence order drops, and oversee process status. As a result, the company streamlined its order shipment process to picking by bulk, transferring orders to the staging line, dropping actual orders, and retrieving orders from the staging line.

3. Maximize the potential of every employee involved in supply chain processes

The use of robots in the supply chain is a hot topic. But contrary to widespread fears, the real news is not about eliminating human jobs – it’s about making work more meaningful and challenging for everyone while offsetting a looming labor shortage. In fact, IDC predicted that 50% of fulfillment centers will have co-bots operating next to humans in the picking, packing, and shipping floor to drive productivity up 30% and lower the cost of operations.

For retail heavyweight Amazon, deploying an army of over 30,000 Kiva robots across a few of its warehouses in 2014 saved roughly US$22 million. And if Deutsche Bank is correct, the company will pick up an additional $800 million in savings as more plants are given the opportunity to use the technology.

4. Turn your supply chain into a source for value-add services

Supply chain management should prepare for the future by implementing the IoT and defining new use cases to tap into never-conceived revenue streams. And if there was a reason to get started, hygiene company Hagleitner is an excellent source of inspiration.

For years, Hagleitner has been a reliable bathroom supplier for fast-food restaurants, hospitals, and theaters throughout Austria as well as multiple cruise lines internationally. As the demand for its services grew, the company decided to make its operations more efficient by embedding sensors to track everything from the use of faucets to stock levels of soap, air freshener, and paper towels.

This strategy not only made services more responsive, proactive, and consistent, but the company is also saving warehouse space, meeting demand with greater sustainability, and optimizing logistics processes and personnel assignments. At the same time, its customers are assured that their bathrooms are well-equipped and address every visitor’s bathroom needs.

Artificial intelligence: A natural step in supply-chain innovation

The more supply chain technology matures, the smarter the supply chain will run. While the IoT is helping your supply chain respond faster and more flexibly to market changes, it is still important to look ahead and see how the data you’re generating can take your supply chains to new levels of efficiency, demand forecasting, and speed.

Looking to learn more about how your supply chain can stay ahead of the competition? Read this free IDC white paper, “The Strategic Imperative for an Agile Supply Chain.”


Marcell Vollmer

About Marcell Vollmer

Marcell Vollmer is the Chief Digital Officer for SAP Ariba (SAP). He is responsible for helping customers digitalize their supply chain. Prior to this role, Marcell was the Chief Operating Officer for SAP Ariba, enabling the company to setup a startup within the larger SAP business. He was also the Chief Procurement Officer at SAP SE, where he transformed the global procurement organization towards a strategic, end-to-end driven organization, which runs SAP Ariba and SAP Fieldglass solutions, as well as Concur technologies in the cloud. Marcell has more than 20 years of experience in working in international companies, starting with DHL where he delivered multiple supply chain optimization projects.

Everybody’s Irish On St. Patrick’s Day – But Which Companies Will Win The Day? 

Richard Howells

As my wife is Irish, I have kissed the Blarney Stone, and I live near Boston, I consider myself an honoree Irishman on St. Patrick’s Day. In fact, most cities in the United States make a great effort to “wear the green” on the big day, as proven by a piece on consumer spending for the St. Patrick’s Day holiday here in the U.S. The article quotes Matthew Shays, president and CEO of the National Retail Federation (NRF), who reminds us that this year St. Patrick’s Day falls on a Saturday – which means that “Americans will have more time to splurge a little as they get together with friends and loved ones for a day of festivities.”

This is good news for retailers looking forward to a strong season. A new survey by the NRF and Prosper Insights & Analytics puts 2018 American spending for the holiday at $5.9 billion. This is a new record – up from last year’s record of $5.3 billion.

Record spending

More than 149 million people plan to celebrate the holiday this year – with spending coming in at an average of $39.65 per person, up from $37.92 in 2017. Leading categories of spend will be food (the traditional corned beef and cabbage) and beverages (a fair amount of Guinness, to be sure).

For people celebrating the day, 83% will wear green. Many will also decorate their homes and offices in a St. Patrick’s Day theme. This will lead to a lot of spending beyond the food the beverage categories.

Planning is good, responsiveness is even better   

The fact that St. Patrick’s Day falls on a Saturday this year is, of course, as predictable as the calendar. Companies see it coming, they make plans, and they fire up the supply chain. This is good.

But while having the visibility and preparedness to meet demand is a good thing, what’s differentiating companies more and more is their responsiveness to demand in the moment. Keep in mind that in the grand scheme of things, St. Patrick’s Day is a relatively minor holiday in the U.S. – especially compared to Christmas and Thanksgiving. Spending for St. Patrick’s Day, in fact, is only a fraction of what Americans dedicate to back-to-school spending ($83.6 billion).

The point is that St. Patrick’s Day will sneak up on people – and, people being people, many will put off holiday purchases until the last minute. This tendency is only exacerbated by the fact that today’s consumers ordering online are conditioned to expect same-day and even same-hour delivery. If you can deliver in this regard – your company stands to gain.

To do this, companies need next-generation digital logistics and greater control over end-to-end supply chains. Companies like Amazon – with 70 distribution centers in the United States – have already moved in this direction. But don’t count out the brick and mortars. Walmart, for example, is repurposing its network of physical retail spaces (two-thirds of the U.S. population lives within five miles of one of its outlets) to act as distribution centers. This will help Walmart get more products out the door for same-day/hour delivery.

Kiss me, I’m (7.3%) Irish 

But companies are going even further in the race to deliver what customers want when they want it. Increasingly, competition is moving to the field of personalization.

Let’s say your neighbor hosts a St. Patrick’s Day party every year and his go-to T-shirt reads “Kiss Me, I’m a Quarter Irish.” But then, two days before the party, he receives his DNA analysis – and it turns out he’s not quite as Irish as he thought. He’s not easily disheartened, however – and he still loves St. Patrick’s Day. So for this year’s party, he orders up a custom t-shirt – as well as plates, napkins, and whatnot – that say “Kiss Me, I’m 7.3% Percent Irish.”

If your company can accommodate this order – generating products to the customer’s specifications, on demand and delivered quickly at not much extra cost – your company stands to gain.

To be sure, this is a simplified example of personalization. But today, many companies are using personalization in sophisticated ways. Shoe companies like Nike allow you to design your shoes online to your liking – without major hits on delivery time or cost. Harley Davidson does something similar with its iconic motorcycles. Today, customers can assemble whatever kind of bike they like – and even watch it get made in a purpose-built facility that gives customers an experience they don’t soon forget.

The customer experience 

At the highest level, what companies are competing over is the customer experience. As long as you can deliver what your customers want, when they want it, at a reasonable price, with loads of convenience – your company stands to gain. And by delivering experiences that are uniquely engaging, you’ll also earn your customers’ long-time loyalty.

But the customer experience is no marketing afterthought – though marketing is critical. Effective customer experiences are supported by all aspects of the business – not the least of which is the supply chain function. To drive better customer experiences, today’s supply chains need agility, speed, visibility, and a healthy dose of emerging technology.

For example, many companies are leveraging Internet of Things, sensor technologies, and sentiment analysis to feed customer demand signals directly back into the supply chain for automated replenishment. Others are developing flexible relationships with supply partners through business networks. Still others have integrated 3D printing capabilities into their supply chains to serve customers on demand.

So when you go to a St. Patrick’s Day party this year, pause a moment to wonder where all the “stuff” comes from. Chances are, whatever you see has made its way to you from companies that have beat out the competition with sophisticated digital supply chain capabilities.

You can’t just rely on “the luck of the Irish!”


Looking to learn more about how your supply chain can stay ahead of the competition? Read this free IDC white paper, “The Strategic Imperative for an Agile Supply Chain.”

This article originally appeared on Forbes SAPVoice.



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.

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.


The Differences Between Machine Learning And Predictive Analytics

Shaily Kumar

Many people are confused about the specifics of machine learning and predictive analytics. Although they are both centered on efficient data processing, there are many differences.

Machine learning

Machine learning is a method of computational learning underlying most artificial intelligence (AI) applications. In ML, systems or algorithms improve themselves through data experience without relying on explicit programming. ML algorithms are wide-ranging tools capable of carrying out predictions while simultaneously learning from over trillions of observations.

Machine learning is considered a modern-day extension of predictive analytics. Efficient pattern recognition and self-learning are the backbones of ML models, which automatically evolve based on changing patterns in order to enable appropriate actions.

Many companies today depend on machine learning algorithms to better understand their clients and potential revenue opportunities. Hundreds of existing and newly developed machine learning algorithms are applied to derive high-end predictions that guide real-time decisions with less reliance on human intervention.

Business application of machine learning: employee satisfaction

One common, uncomplicated, yet successful business application of machine learning is measuring real-time employee satisfaction.

Machine learning applications can be highly complex, but one that’s both simple and very useful for business is a machine learning algorithm that compares employee satisfaction ratings to salaries. Instead of plotting a predictive satisfaction curve against salary figures for various employees, as predictive analytics would suggest, the algorithm assimilates huge amounts of random training data upon entry, and the prediction results are affected by any added training data to produce real-time accuracy and more helpful predictions.

This machine learning algorithm employs self-learning and automated recalibration in response to pattern changes in the training data, making machine learning more reliable for real-time predictions than other AI concepts. Repeatedly increasing or updating the bulk of training data guarantees better predictions.

Machine learning can also be implemented in image classification and facial recognition with deep learning and neural network techniques.

Predictive analytics

Predictive analytics can be defined as the procedure of condensing huge volumes of data into information that humans can understand and use. Basic descriptive analytic techniques include averages and counts. Descriptive analytics based on obtaining information from past events has evolved into predictive analytics, which attempts to predict the future based on historical data.

This concept applies complex techniques of classical statistics, like regression and decision trees, to provide credible answers to queries such as: ‘’How exactly will my sales be influenced by a 10% increase in advertising expenditure?’’ This leads to simulations and “what-if” analyses for users to learn more.

All predictive analytics applications involve three fundamental components:

  • Data: The effectiveness of every predictive model strongly depends on the quality of the historical data it processes.
  • Statistical modeling: Includes the various statistical techniques ranging from basic to complex functions used for the derivation of meaning, insight, and inference. Regression is the most commonly used statistical technique.
  • Assumptions: The conclusions drawn from collected and analyzed data usually assume the future will follow a pattern related to the past.

Data analysis is crucial for any business en route to success, and predictive analytics can be applied in numerous ways to enhance business productivity. These include things like marketing campaign optimization, risk assessment, market analysis, and fraud detection.

Business application of predictive analytics: marketing campaign optimization

In the past, valuable marketing campaign resources were wasted by businesses using instincts alone to try to capture market niches. Today, many predictive analytic strategies help businesses identify, engage, and secure suitable markets for their services and products, driving greater efficiency into marketing campaigns.

A clear application is using visitors’ search history and usage patterns on e-commerce websites to make product recommendations. Sites like Amazon increase their chance of sales by recommending products based on specific consumer interests. Predictive analytics now plays a vital role in the marketing operations of real estate, insurance, retail, and almost every other sector.

How machine learning and predictive analytics are related

While businesses must understand the differences between machine learning and predictive analytics, it’s just as important to know how they are related. Basically, machine learning is a predictive analytics branch. Despite having similar aims and processes, there are two main differences between them:

  • Machine learning works out predictions and recalibrates models in real-time automatically after design. Meanwhile, predictive analytics works strictly on “cause” data and must be refreshed with “change” data.
  • Unlike machine learning, predictive analytics still relies on human experts to work out and test the associations between cause and outcome.

Explore machine learning applications and AI software with SAP Leonardo.


Shaily Kumar

About Shaily Kumar

Shailendra has been on a quest to help organisations make money out of data and has generated an incremental value of over one billion dollars through analytics and cognitive processes. With a global experience of more than two decades, Shailendra has worked with a myriad of Corporations, Consulting Services and Software Companies in various industries like Retail, Telecommunications, Financial Services and Travel - to help them realise incremental value hidden in zettabytes of data. He has published multiple articles in international journals about Analytics and Cognitive Solutions; and recently published “Making Money out of Data” which showcases five business stories from various industries on how successful companies make millions of dollars in incremental value using analytics. Prior to joining SAP, Shailendra was Partner / Analytics & Cognitive Leader, Asia at IBM where he drove the cognitive business across Asia. Before joining IBM, he was the Managing Director and Analytics Lead at Accenture delivering value to its clients across Australia and New Zealand. Coming from the industry, Shailendra held key Executive positions driving analytics at Woolworths and Coles in the past. Please feel to connect on: Linkedin: Twitter: