Hype & High Expectations For Cloud Computing, Part 2

Chris Mark

Cloud computingCloud computing is a much hyped but often misunderstood technology that is gaining traction in different industries around the world. Businesses are integrating the cloud into countless systems, from HR to finance. Full adoption and acceptance of cloud computing, however, are still far away.

A recent global survey by Knowledge@Wharton and SAP’s Performance Benchmarking team reveals that while the hype and excitement surrounding cloud computing is reaching a fever pitch, many businesses are still expressing concerns over cloud security and IT integration issues. The survey also shows that while many people agree that the cloud is revolutionizing business, they still do not fully understand how it works.

How will these tensions surrounding the cloud be resolved? How will the cloud transform businesses in the future? What kinds of benefits will the cloud bring, and is it worthy of the current hype? Knowledge@Wharton discussed those questions and the survey results with David Spencer, vice president at SAP, and Don Huesman, managing director at the Wharton Innovation Group.

An edited transcript of the conversation appears below.

Knowledge@Wharton: Both of you have spelled out of the value of cloud computing. But one of the counterintuitive findings in our survey showed that while many people believe that cloud computing is important, they don’t seem to understand much about it. Don, why do you think this is the case?

Huesman: I just mentioned the Gartner “hype cycle.” Gartner showed 2012 as the time when the hype slipped off the peak and headed towards “the trough of disillusionment,” which they think is a necessary phase for any type of effective technology before it reaches what they refer to as “the plateau of productivity.” And Gartner is predicting that to happen with cloud computing over the next two to five years.

Related to this “hype cycle,” I think that there is a tendency, particularly in the United States, to look for technical solutions to multi-dimensional problems and get very excited about the solutions, until we begin to see some limitations. Then we get very disappointed, until we eventually discover that there is still a decent amount of utility to take advantage of in these technical solutions. So, in this case, I don’t know that the first-mover advantage in this space is very strong because I think close followers can also take advantage of the new capabilities that are emerging.

Knowledge@Wharton: Dave, what’s your view?

Spencer: I think one of the reasons there is general confusion has to do with the fact that there are different definitions that are used when referring to cloud computing. For example, there is SaaS (software as service), there is a virtualization of an environment, there are also hosting environments. This leads to confusion because there are different kinds of cloud solutions. In fact, at SAP we try to describe it in terms of value across our customers’ entire enterprise, and even beyond. We talk about our cloud portfolio consisting of four main elements: apps, cloud platform, infrastructure/lifecycle management, for investment protection, and finally, the business network, which refers to networks of buyers and sellers doing business in entirely new, social ways, all enabled by cloud computing.

Knowledge@Wharton: Interesting. Perhaps this lack of understanding could be related to this finding from our survey: 18% of companies said they had extensively or completely adopted cloud computing, but half the respondents had minimal or no adoption. Could this general misunderstanding about cloud computing be related to the fact that not many people are using it?

Spencer: If I look at the customers that I represent, most have adopted some kind of cloud solution or at least have looked at it. Now, they may not have deployed it 100% because they may have started out using the cloud solution in smaller organizations or smaller businesses processes, but every day I see people looking at deploying some kind of cloud solution.

I think the other factor is that if you’re looking at larger organizations, they would have already made sizeable investments in their IT infrastructure, so quickly moving to a cloud solution may not be the best investment for them right now. What a lot of companies are looking at is called the hybrid solution, where they are taking select business processes and putting them into the cloud, while still leveraging their on-premise IT infrastructure at the same time.

Huesman: Dave has touched on an important point here. I think there is often resistance on the part of IT departments in some companies towards the concept of the cloud. This resistance is based on concerns about security, reliability, dependability and the robustness of the solutions that are being offered. But I think all those concerns are overstated. The current resistance reminds me of when the personal computer was introduced. Large companies resisted its deployment for a very long time until personal computers were being purchased by CEOs. At that point, the IT organizations had to figure out a way to integrate them successfully. I think we’re seeing a similar dynamic now where there is resistance for legitimate concerns, but that’s being trumped by consumerization.

Knowledge@Wharton: Do you expect to see CEOs in the cloud soon?

Huesman: Oh, I’ve seen them there every day.

Spencer: On my side, I can say that we run our business in the cloud 100%. Every single business process in the SAP cloud business unit, from travel to HR, is being run in the cloud.

Knowledge@Wharton: Dave, for those who are resisting cloud solutions, some of the biggest concerns seem to be around security and integration. In fact, 67% of survey respondents identified those two issues as the ones that concerned them the most. How do you deal with this?

Spencer: We try to address the security issue head-on to understand our customers’ exact concerns. Now, there are different privacy laws in different countries, which we’ve been able to satisfy. But there are some companies and government agencies that have very strict policies around what can be run on the cloud and what cannot. So, we try to address these issues. But at the end of the day, it really comes down to that fact that some people are just going to be cloud laggards. For those people who are going to be at the back-end of the curve in deployments, you just have to make sure they are comfortable when they’re ready.

Knowledge@Wharton: What do you think, Don?

Huesman: We were one of the first organizations at Penn to attempt to outsource our student email to a cloud service provided by Microsoft, but we had a bad experience early on. It was so bad that we had to move back to our previous system. That early mover experience leaves people nervous about making the move again. But now we’re at a point where outsourcing e-mail is something that can be done in a more reliable fashion.

These issues make IT directors and IT workers believe that it’s better to work through the late night hours to repair and reconfigure hardware and software services rather than wait on the phone anxiously hoping that someone else in another distant city is fixing the issue. It’s a different position to be in psychologically. It may also be a challenge for IT employees to be able to work in partnership with a cloud services company. Not all people will be ready for this shift. It’s certainly a period of transition in the IT industry.

Knowledge@Wharton: Dave, do you encounter some of the issues that Don just described? How do you deal with them?

Spencer: We deal with these issues every single day. We look at this as a true partnership: The clients working with SAP have to feel comfortable that they’re working with a responsive business that is going to continue to deliver innovation and improve security. Our customers want a business partner that can handle all aspects of the cloud. For example, SAP has to proactively deal with issues related to deploying business applications on personal mobile devices and controlling the data that’s out there. That’s one area where SAP is very advanced.

This is part two of a three-part series. Stay tuned for part three.


Chris Mark

About Chris Mark

Chris Mark is the Executive Director, Design & User Experience at SAP. His specialties include business strategy, program management, management consulting, go-to-market strategy and strategic planning.



Innovation Without Boundaries: Why The Cloud Matters

Michael Haws

Is it possible to innovate without boundaries?

Of course – if you are using the cloud. An actual cloud doesn’t have any boundaries. It’s fluid. But more important, it can provide the much-needed precipitation that brings nature to life. So it is with cloud technology – but it’s your ideas that can grow and transform your business.USA --- Clouds, Heaven --- Image by © Ocean/Corbis

Running your business in the cloud is no longer just a consideration during a typical use-case exercise. Business executives are now faced with making decisions on solutions that go beyond previous limitations with cloud computing. Selecting the latest tools to address a business process gap is now less about features and more about functionality.

It doesn’t matter whether your organization is experienced with cloud solutions or new to the concept. Cloud technology is quickly becoming a core part of addressing the needs of a growing business.

5 considerations when planning your journey to the cloud

How can your organization define its successful path to the cloud? Here are five things you should consider when investigating whether a move to the cloud is right for you.

1. Understanding the cloud is great, but putting it into action is another thing.

For most CIOs, putting a cloud strategy on paper is new territory. Cloud computing is taking on new realms: Pure managed services to software-as-a-service (SaaS). Just as legacy computing had different flavors, so does cloud technology.

2. There is more than one way to innovate in the cloud.

Alignment with an open cloud reference architecture can help your CIO deliver on the promises of the cloud while using a stair-step approach to cloud adoption – from on-premise to hybrid to full cloud computing. Some companies find their own path by constantly reevaluating their needs and shifting their focus when necessary – making the move from running a data center to delivering real value to stakeholders, for example.

3. The cloud can help accelerate processes and lower cost.

By recognizing unprecedented growth, your organization can embark on a path to significant transformation that powers greater agility and competitiveness. Choose a solution set that best meets your needs, and implement and support it moving forward. By leveraging the cloud to support the chosen solution, ongoing maintenance, training, and system issues becomes the cloud provider’s responsibility. And for you, this offers the freedom to focus on the core business.

4. You can lock down your infrastructure and ensure more efficient processes.

Do you use a traditional reporting engine against a large relational database to generate a sequential batched report to close your books at quarter’s end? If so, you’re not alone. Sure, a new solution with new technology may be an obvious improvement. But how valuable to your board will you become when you reduce the financial closing process by 1–3 days? That’s the beauty of the cloud: You can accelerate the deployment of your chosen solution and realize ROI quickly – even before the next full reporting period.

5. The cloud opens the door to new opportunity in a secure environment.

For many companies, moving to the cloud may seem impossible due to the time and effort needed to train workers and hire resources with the right skill sets. Plus, if you are a startup in a rural location, it may not be as easy to attract the right talent as it is for your Silicon Valley counterparts. The cloud allows your business to secure your infrastructure as well as recruit and onboard those hard-to-find resources by applying a managed services contract to run your cloud model

The cloud means many things to different people. What’s your path?

With SAP HANA Enterprise Cloud service, you can navigate the best path to building, running, and operating your own cloud when running critical business processes. Find out how SAP HANA Enterprise Cloud can deliver the speed and resources necessary to quickly validate and realize solid ROI.

Check out the video below or visit us at

Connect with us on Twitter: @SAPServices


Michael Haws

About Michael Haws

Michael Haws is the Vice President of HANA Enterprise Cloud at SAP. His specialties include Enterprise Resource Planning Software & Services, Onshore, Nearshore, Offshore--Application, Infrastructure and Business Process Outsourcing.


Consumers And Providers: Two Halves Of The Hybrid Cloud Equation

Marty McCormick

Long gone are the days of CIOs and IT managers freely spending money to move their 02 Jun 2012 --- Young creatives having lunch and conversation. --- Image by © Hero/Corbisexisting systems to the cloud without any real business justification just to be part of the latest hype. As cloud deployments are becoming more prevalent, IT leaders are now tasked with proving the tangible benefits of adopting a cloud strategy from an operational, efficiency, and cost perspective. At the same time, they must balance their end users’ increasing demand for access to more data from an ever-expanding list of public cloud sources.

Lately, public cloud systems have become part of IT landscapes both in the form of multi-tenant systems, such as software-as-a-service (SaaS) offerings and data consumption applications such as Twitter. Along with the integration of applications and data outside of the corporate domain, new architectures have been spawned, requiring real-time and seamless integration points.  As shown in the figure below, these hybrid clouds – loosely defined as the integration of data from systems in both public and private clouds in a unified fashion – are the foundation of this new IT architecture.


Not only has the hybrid cloud changed a company’s approach to deploying new software, but it has also changed the way software is developed and sold from a provider’s perspective.

The provider perspective: Unifying development and operations

Thanks to the hybrid cloud approach, system administrators and developers are sitting side by side in an agile development model known as Development and Operations (DevOps). By increasing collaboration, communication, innovation, and problem resolution, development teams can closely collaborate with system administrators and provide a continuous feedback loop of both sides of the agile methodology.

For example, operations teams can provide feedback on reported software bugs, software support issues, and new feature requests to development teams in real time. Likewise, development teams develop and test new applications with support and maintainability as a key pillar in design.
After seeing the advantages realized by cloud providers that have embraced this approach long ago, other companies that have traditionally separated these two areas are now adopting the DevOps model.

The consumer perspective: Moving to the cloud on its own terms

From the standpoint of the corporate consumer, hybrid cloud deployments bring a number of advantages to an IT organization. Specifically, the hybrid approach allows companies to move some application functionality to the cloud at their own pace.
Many applications naturally lend themselves to public cloud domains given their application and data requirements. For most companies, HR, indirect procurement, travel, and CRM systems are the first to be deployed in a public cloud. This approach eliminates the requirement for building and operating these applications in house while allowing IT areas to take advantage of new features and technologies much faster.

However, there is one challenge consumers need to overcome: The lack of capabilities needed to extend these applications and meet business requirements when the standard offering is often insufficient. Unfortunately, this tempts organizations to create extensive custom applications that replicate information across a variety of systems to meet end user requirements. This development work can offset the cost benefits of the initial cloud application, especially when you consider the upgrades and support required to maintain the application.

What this all means to everyone involved in the hybrid cloud

Given these two perspectives, on-premise software providers are transforming themselves so they can meet the ever-evolving demands of today’s information consumer. In particular, they are preparing for these unique challenges facing customers and creating a smooth journey to a hybrid cloud.

Take SAP, for example. By adopting a DevOps model to break down a huge internal barrier and allowing tighter collaboration, the company has delivered a simpler approach to hybrid cloud deployments through the SAP HANA Cloud Platform for extending applications and SAP HANA Enterprise Cloud for hosting solutions.

Find out how these two innovations can help you implement a robust and secure hybrid cloud solution:
SAP HANA Cloud Platform
SAP HANA Enterprise Cloud


Marty McCormick

About Marty McCormick

Marty McCormick is the Lead Technical Architect, Managed Cloud Delivery, at SAP. He is experienced in a wide range of SAP solutions, including SAP Netweaver SAP Portal, SAP CRM, SAP SRM, SAP MDM, SAP BI, and SAP ERP.

Unlock Your Digital Super Powers: How Digitization Helps Companies Be Live Businesses

Erik Marcade and Fawn Fitter

The Port of Hamburg handles 9 million cargo containers a year, making it one of the world’s busiest container ports. According to the Hamburg Port Authority (HPA), that volume doubled in the last decade, and it’s expected to at least double again in the next decade—but there’s no room to build new roads in the center of Hamburg, one of Germany’s historic cities. The port needed a way to move more freight more efficiently with the physical infrastructure it already has.

sap_Q216_digital_double_feature1_images1The answer, according to an article on ZDNet, was to digitize the processes of managing traffic into, within, and back out of the port. By deploying a combination of sensors, telematics systems, smart algorithms, and cloud data processing, the Port of Hamburg now collects and analyzes a vast amount of data about ship arrivals and delays, parking availability, ground traffic, active roadwork, and more. It generates a continuously updated model of current port conditions, then pushes the results through mobile apps to truck drivers, letting them know exactly when ships are ready to drop off or receive containers and optimizing their routes. According to the HPA, they are now on track to handle 25 million cargo containers a year by 2025 without further congestion or construction, helping shipping companies bring more goods and raw materials in less time to businesses and consumers all across Europe.

In the past, the port could only have solved its problem with backhoes and building permits—which, given the physical constraints, means the problem would have been unsolvable. Today, though, software and sensors are allowing it to improve processes and operations to a previously impossible extent. Big Data analysis, data mining, machine learning, artificial intelligence (AI), and other technologies have finally become sophisticated enough to identify patterns not just in terabytes but in petabytes of data, make decisions accordingly, and learn from the results, all in seconds. These technologies make it possible to digitize all kinds of business processes, helping organizations become more responsive to changing market conditions and more able to customize interactions to individual customer needs. Digitization also streamlines and automates these processes, freeing employees to focus on tasks that require a human touch, like developing innovative strategies or navigating office politics.

In short, digitizing business processes is key to ensuring that the business can deliver relevant, personalized responses to the market in real time. And that, in turn, is the foundation of the Live Business—a business able to coordinate multiple functions in order to respond to and even anticipate customer demand at any moment.

Some industries and organizations are on the verge of discovering how business process digitization can help them go live. Others have already started putting it into action: fine-tuning operations to an unprecedented level across departments and at every point in the supply chain, cutting costs while turbocharging productivity, and spotting trends and making decisions at speeds that can only be called superhuman.

Balancing Insight and Action

sap_Q216_digital_double_feature1_images2Two kinds of algorithms drive process digitization, says Chandran Saravana, senior director of advanced analytics at SAP. Edge algorithms operate at the point where customers or other end users interact directly with a sensor, application, or Internet-enabled device. These algorithms, such as speech or image recognition, focus on simplicity and accuracy. They make decisions based primarily on their ability to interpret input with precision and then deliver a result in real time.

Edge algorithms work in tandem with, and sometimes mature into, server-level algorithms, which report on both the results of data analysis and the analytical process itself. For example, the complex systems that generate credit scores assess how creditworthy an individual is, but they also explain to both the lender and the credit applicant why a score is low or high, what factors went into calculating it, and what an applicant can do to raise the score in the future. These server-based algorithms gather data from edge algorithms, learn from their own results, and become more accurate through continuous feedback. The business can then track the results over time to understand how well the digitized process is performing and how to improve it.

sap_Q216_digital_double_feature1_images5From Data Scarcity to a Glut

To operate in real time, businesses need an accurate data model that compares what’s already known about a situation to what’s happened in similar situations in the past to reach a lightning-fast conclusion about what’s most likely to happen next. The greatest barrier to this level of responsiveness used to be a lack of data, but the exponential growth of data volumes in the last decade has flipped this problem on its head. Today, the big challenge for companies is having too much data and not enough time or power to process it, says Saravana.

Even the smartest human is incapable of gathering all the data about a given situation, never mind considering all the possible outcomes. Nor can a human mind reach conclusions at the speed necessary to drive Live Business. On the other hand, carefully crafted algorithms can process terabytes or even petabytes of data, analyze patterns and detect outliers, arrive at a decision in seconds or less—and even learn from their mistakes (see How to Train Your Algorithm).

How to Train Your Algorithm 

The data that feeds process digitization can’t just simmer.
It needs constant stirring.

Successfully digitizing a business process requires you to build a model of the business process based on existing data. For example, a bank creates a customer record that includes not just the customer’s name, address, and date of birth but also the amount and date of the first deposit, the type of account, and so forth. Over time, as the customer develops a history with the bank and the bank introduces new products and services, customer records expand to include more data. Predictive analytics can then extrapolate from these records to reach conclusions about new customers, such as calculating the likelihood that someone who just opened a money market account with a large balance will apply for a mortgage in the next year.

Germany --- Germany, Lower Bavaria, Man training English Springer Spaniel in grass field --- Image by © Roman M‰rzinger/Westend61/CorbisTo keep data models accurate, you have to have enough data to ensure that your models are complete—that is, that they account for every possible predictable outcome. The model also has to push outlying data and exceptions, which create unpredictable outcomes, to human beings who can address their special circumstances. For example, an algorithm may be able to determine that a delivery will fail to show up as scheduled and can point to the most likely reasons why, but it can only do that based on the data it can access. It may take a human to start the process of locating the misdirected shipment, expediting a replacement, and establishing what went wrong by using business knowledge not yet included in the data model.

Indeed, data models need to be monitored for relevance. Whenever the results of a predictive model start to drift significantly from expectations, it’s time to examine the model to determine whether you need to dump old data that no longer reflects your customer base, add a new product or subtract a defunct one, or include a new variable, such as marital status or length of customer relationship that further refines your results.

It’s also important to remember that data doesn’t need to be perfect—and, in fact, probably shouldn’t be, no matter what you might have heard about the difficulty of starting predictive analytics with lower-quality data. To train an optical character recognition system to recognize and read handwriting in real time, for example, your samples of block printing and cursive writing data stores also have to include a few sloppy scrawls so the system can learn to decode them.

On the other hand, in a fast-changing marketplace, all the products and services in your database need consistent and unchanging references, even though outside the database, names, SKUs, and other identifiers for a single item may vary from one month or one order to the next. Without consistency, your business process model won’t be accurate, nor will the results.

Finally, when you’re using algorithms to generate recommendations to drive your business process, the process needs to include opportunities to test new messages and products against existing successful ones as well as against random offerings, Saravana says. Otherwise, instead of responding to your customers’ needs, your automated system will actually control their choices by presenting them with only a limited group of options drawn from those that have already received the most
positive results.

Any process is only as good as it’s been designed to be. Digitizing business processes doesn’t eliminate the possibility of mistakes and problems; but it does ensure that the mistakes and problems that arise are easy to spot and fix.

From Waste to Gold

Organizations moving to digitize and streamline core processes are even discovering new business opportunities and building new digitized models around them. That’s what happened at Hopper, an airfare prediction app firm in Cambridge, Massachusetts, which discovered in 2013 that it could mine its archives of billions of itineraries to spot historical trends in airfare pricing—data that was previously considered “waste product,” according to Hopper’s chief data scientist, Patrick Surry.

Hopper developed AI algorithms to correlate those past trends with current fares and to predict whether and when the price of any given flight was likely to rise or fall. The results were so accurate that Hopper jettisoned its previous business model. “We check up to 3 billion itineraries live, in real time, each day, then compare them to the last three to four years of historical airfare data,” Surry says. “When consumers ask our smartphone app whether they should buy now or wait, we can tell them, ‘yes, that’s a good deal, buy it now,’ or ‘no, we think that fare is too expensive, we predict it will drop, and we’ll alert you when it does.’ And we can give them that answer in less than one second.”

When consumers ask our smartphone app whether they should buy now or wait, we can tell them, ‘yes, that’s a good deal, buy it now’.

— Patrick Surry, chief data scientist, Hopper

While trying to predict airfare trends is nothing new, Hopper has told TechCrunch that it can not only save users up to 40% on airfares but it can also find them the lowest possible price 95% of the time. Surry says that’s all due to Hopper’s algorithms and data models.

The Hopper app launched on iOS in January 2015 and on Android eight months later. The company also switched in September 2015 from directing customers to external travel agencies to taking bookings directly through the app for a small fee. The Hopper app has already been downloaded to more than 2 million phones worldwide.

Surry predicts that we’ll soon see sophisticated chatbots that can start with vague requests from customers like “I want to go somewhere warm in February for less than $500,” proceed to ask questions that help users narrow their options, and finally book a trip that meets all their desired parameters. Eventually, he says, these chatbots will be able to handle millions of interactions simultaneously, allowing a wide variety of companies to reassign human call center agents to the handling of high-value transactions and exceptions to the rules built into the digitized booking process.

Port of Hamburg Lets the Machines Untangle Complexity

In early 2015, AI experts told Wired magazine that at least another 10 years would pass before a computer could best the top human players at Go, an ancient game that’s exponentially harder than chess. Yet before the end of that same year, Wired also reported that machine learning techniques drove Google’s AlphaGo AI to win four games out of five against one of the world’s top Go players. This feat proves just how good algorithms have become at managing extremely complex situations with multiple interdependent choices, Saravana points out.

The Port of Hamburg, which has digitized traffic management for an estimated 40,000 trucks a day, is a good example. In the past, truck drivers had to show up at the port to check traffic and parking message boards. If they arrived before their ships docked, they had to drive around or park in the neighboring residential area, contributing to congestion and air pollution while they waited to load or unload. Today, the HPA’s smartPORT mobile app tracks individual trucks using telematics. It customizes the information that drivers receive based on location and optimizes truck routes and parking in real time so drivers can make more stops a day with less wasted time and fuel.

The platform that drives the smartPORT app also uses sensor data in other ways: it tracks wind speed and direction and transmits the data to ship pilots so they can navigate in and out of the port more safely. It monitors emissions and their impact on air quality in various locations in order to adjust operations in real time for better control over environmental impact. It automatically activates streetlights for vehicle and pedestrian traffic, then switches them off again to save energy when the road is empty. This ability to coordinate and optimize multiple business functions on the fly makes the Port of Hamburg a textbook example of a Live Business.

Digitization Is Not Bounded by Industry

Other retail and B2B businesses of all types will inevitably join the Port of Hamburg in further digitizing processes, both in predictable ways and in those we can only begin to imagine.

sap_Q216_digital_double_feature1_images4Customer service, for example, is likely to be in the vanguard. Automated systems already feed information about customers to online and phone-based service representatives in real time, generate cross-selling and upselling opportunities based on past transactions, and answer customers’ frequently asked questions. Saravana foresees these systems becoming even more sophisticated, powered by AI algorithms that are virtually indistinguishable from human customer service agents in their ability to handle complex live interactions in real time.

In manufacturing and IT, Sven Bauszus, global vice president and general manager for predictive analytics at SAP, forecasts that sensors and predictive analysis will further automate the process of scheduling and performing maintenance, such as monitoring equipment for signs of failure in real time, predicting when parts or entire machines will need replacement, and even ordering replacements preemptively. Similarly, combining AI, sensors, data mining, and other technologies will enable factories to optimize workforce assignments in real time based on past trends, current orders, and changing market conditions.

Public health will be able to go live with technology that spots outbreaks of infectious disease, determines where medical professionals and support personnel are needed most and how many to send, and helps ensure that they arrive quickly with the right medication and equipment to treat patients and eradicate the root cause. It will also make it easier to track communicable illnesses, find people who are symptomatic, and recommend approaches to controlling the spread of the illness, Bauszus says.

He also predicts that the insurance industry, which has already begun to digitize its claims-handling processes, will refine its ability to sort through more claims in less time with greater accuracy and higher customer satisfaction. Algorithms will be better and faster at flagging claims that have a high probability of being fraudulent and then pushing them to claims inspectors for investigation. Simultaneously, the same technology will be able to identify and resolve valid claims in real time, possibly even cutting a check or depositing money directly into the insured person’s bank account within minutes.

Financial services firms will be able to apply machine learning, data mining, and AI to accelerate the process of rating borrowers’ credit and detecting fraud. Instead of filling out a detailed application, consumers might be able to get on-the-spot approval for a credit card or loan after inputting only enough information to be identified. Similarly, banks will be able to alert customers to suspicious transactions by text message or phone call—not within a day or an hour, as is common now, but in a minute or less.

Pitfalls and Possibilities

As intelligent as business processes can be programmed to be, there will always be a point beyond which they have to be supervised. Indeed, Saravana forecasts increasing regulation around when business processes can and can’t be digitized. Especially in areas involving data security, physical security, and health and safety, it’s one thing to allow machines to parse data and arrive at decisions to drive a critical business process, but it’s another thing entirely to allow them to act on those decisions without human oversight.

Automated, impersonal decision making is fine for supply chain automation, demand forecasting, inventory management, and other processes that need faster-than-human response times. In human-facing interactions, though, Saravana insists that it’s still best to digitize the part of the process that generates decisions, but leave it to a human to finalize the decision and decide how to put it into action.

“Any time the interaction is machine-to-machine, you don’t need a human to slow the process down,” he says. “But when the interaction involves a person, it’s much more tricky, because people have preferences, tastes, the ability to try something different, the ability to get fatigued—people are only statistically predictable.”

For example, technology has made it entirely possible to build a corporate security system that can gather information from cameras, sensors, voice recognition technology, and other IP-enabled devices. The system can then feed that information in a steady stream to an algorithm designed to identify potentially suspicious activity and act in real time to prevent or stop it while alerting the authorities. But what happens when an executive stays in the office unusually late to work on a presentation and the security system misidentifies her as an unauthorized intruder? What if the algorithm decides to lock the emergency exits, shut down the executive’s network access, or disable her with a Taser instead of simply sending an alert to the head of security asking what to do while waiting for the police to come?

sap_Q216_digital_double_feature1_images6The Risk Is Doing Nothing

The greater, if less dramatic, risk associated with digitizing business processes is simply failing to pursue it. It’s true that taking advantage of new digital technologies can be costly in the short term. There’s no question that companies have to invest in hardware, software, and qualified staff in order to prepare enormous data volumes for storage and analysis. They also have to implement new data sources such as sensors or Internet-connected devices, develop data models, and create and test algorithms to drive business processes that are currently analog. But as with any new technology, Saravana advises, it’s better to start small with a key use case, rack up a quick win with high ROI, and expand gradually than to drag your heels out of a failure to grasp the long-term potential.

The economy is digitizing rapidly, but not evenly. According to the McKinsey Global Institute’s December 2015 Digital America report, “The race to keep up with technology and put it to the most effective business use is producing digital ‘haves’ and ‘have-mores’—and the large, persistent gap between them is becoming a decisive factor in competition across the economy.” Companies that want to be among the have-mores need to commit to Live Business today. Failing to explore it now will put them on the wrong side of the gap and, in the long run, rack up a high price tag in unrealized efficiencies and missed opportunities. D!


Erik Marcade

About Erik Marcade

Erik Marcade is vice president of Advanced Analytics Products at SAP.


Why Workplace Leadership Is About To Get Its First Major Makeover In 100 Years

Mark Crowley

“The difficulty lies not so much in developing new ideas as in escaping from old ones.” ~ John Maynard Keynes

Our common and traditional approach to leadership hasn’t significantly evolved since the dawn of the industrial age. When it comes to managing people in a work environment, we’ve always treated workers like any other input: Squeeze as much as much out of them as possible and pay them as little as possible.

This idea was introduced nearly a century ago, when the expansion of the U.S. economy largely was based on industrial machinery. Workers were required to perform relatively non-challenging tasks and were easily replaceable. Companies motivated workers primarily with money, paying by the piece to reward those who produced the most widgets.

But as we fast-forward to today’s business world, shaped by rapidly evolving technology and the far greater importance of institutional knowledge, creative thinking, and sophisticated collaboration, the value of each employee has grown exponentially more important. Companies are focusing on innovation and unique differentiation – and almost exclusively are looking at people, not machines, to provide it.

As workers have become increasingly more critical to the overall success of their organizations, what they need and expect in exchange for their work also has profoundly changed. Money no longer inspires performance as it once did. Being paid equitably will always be important as a driver of job engagement and productivity, of course, but people across the globe now have aspirations in their jobs that were virtually unimaginable in an earlier age.

Extensive research confirms that people want to grow and develop in the roles. They want to feel valued and appreciated by their leaders, and to know their work has significance. And just as Abraham Maslow predicted 70 years ago, they seek to feel fulfilled and even maximized by the work they do.

That leadership practices have remained essentially unchanged through this evolution – and have failed to fully respond to the 21st-century workplace – has much to do with a deeply entrenched status quo. Many organizations, along with their long-in-the-tooth leaders, have failed to embrace workers as being their most important stakeholder. Instead, they cling to the threadbare paradigm that employees are a costly input, rather than human beings who associate their life’s happiness with their contentment at work. Thus far, they’ve failed to see that more fully supported workers are more loyal, productive and drive an expanded bottom-line.

But I believe the stars are now perfectly aligned to force a massive change in how we collectively seek to motivate human performance in the workplace. Here are three important reasons why leadership is about to be greatly transformed, why the change will be long sustained – and what key practices will define the highly successful manager for the foreseeable future. The one hint I’ll give you now is that future leaders in all workplaces will be required not just to have strong minds, but also generous and caring hearts. I’m dead serious.

Traditional leadership practices are failing, and businesses are paying the price

I recently interviewed Dr. Jim Harter, Gallup’s director of research, and learned that only 30% of U.S. workers today admit to being engaged in their jobs. In its “State of the American Workplace” report released early this month, Gallup reveals that the main reason an astounding 7 in 10 workers are disengaged at work is because they’re not getting proper support from their leaders.

For an article I wrote for Fast Company Magazine, Harter explained the gap: “Workplaces in general have paid a lot of attention to process and far less to people. Too often employees are given managerial roles tied to success in a previous role, or as a reward for their tenure. It’s unrelated to whether they can effectively support and positively manage human beings.”

What Harter’s 27 years of research experience has taught him is that people will continue to be unhappy in their jobs (and therefore greatly underperforming) just as long as their leaders fail to be their advocates. For things to change, therefore, organizations must start promoting people into management roles who have a stronger inclination to mentor and care about their employees rather than compete against them.

According to a worldwide study by Towers Watson, the single highest driver of engagement today is whether or not workers feel their managers are genuinely interested in their well-being. Less than 40% of workers now feel that support.

As further evidence that our leadership practices have the effect of undermining rather than driving productivity, the Conference Board reports that 53% of all U.S. workers today effectively hate their jobs.

The next generation of workers demands a far more nurturing form of leadership

If we’ve reached a tipping point in workplace leadership (which I believe we have), it’s because a new generation of workers has arrived on the scene that simply won’t tolerate a work environment that fails to support them and their needs. Said another way, organizations will be unable to attract and retain this young talent if they don’t adopt far more authentically supportive management practices. (Inevitably, this will be good news for all workers, regardless of their age).

If you don’t know already, the millennials (born 1980-2003) are the largest generation in U.S. history. Totaling 17 million more people than the baby boomers (the last pig in society’s python), this group is just coming of age. Their impact on influencing major changes to workplace leadership is just being felt – and it only will get stronger in ensuing decades as they grow older and inevitably assume senior manager and ultimately CEO roles.

While derided by some (boomers mostly) as an unambitious, video-game playing generation still living in their parent’s homes, millennials are the best-educated age group ever. And collectively, they have very different values than their predecessors. They’re highly self-confident, very concerned about the well-being of others, and group-oriented. It might surprise you that they’re also extremely generous group; a spirit of service permeates the entire generation.

But here’s what’s most important. To these young workers, money is far less important. Instead, they have a strong desire to find meaning through their work. In a recent study, 88% of millennials rated “opportunity to have an impact on the world” important when choosing an employer. These incredibly high aspirations will ensure workplace leadership practices are fully reinvented.

Organizations that don’t change will be at a great competitive disadvantage

In just the past few months, I’ve visited companies like Google (where the median age of employees is just 29) and SAS – organizations routinely ranked by the Great Place To Work Institute (and Fortune Magazine) as America’s “Best Companies To Work For.’’

There are two important things you need to know about firms like these, which place  extremely high value on people:

  1. They’re helping to reinvent leadership. What these companies have in common is that they give employees a meaningful voice in how the business gets run. They place great value on trust – so much so that people have discretion on when they begin and end their workdays, and when they take their breaks. They’re also uncommonly generous, and provide perks and benefits many traditional CFOs would reject as being blatant profit killers. Workers are encouraged to contribute to projects outside of the scope of their normal roles (partly to ensure they have some variety in their day) – and are routinely made to know how their work and efforts contribute to the success of the firm.
  1. They have high engagement, very low turnover, and consistently outperform competitors in financial performance and shareholder return. Several recent studies have shown that companies where employees are happiest and better supported consistently achieve significantly higher profits. SAS, for example, has had 37 consecutive years of record profitability, and Google’s stock price has appreciated nearly 700% over the past 8 ½ years (since its IPO) compared to just 51% for the Dow Jones average. What all firms on the “Best Companies To Work For List” are proving is that highly supported human beings are more loyal, more creative, and sustainably drive far greater financial results. This exceptional and broad success will force competitors to adopt similar leadership practices; shareholders will demand it.

The future of workplace leadership

Workplace leadership is failing today largely because it has yet to acknowledge the importance of “emotional currency™” – a form of reward that makes people feel important, supported, valued, developed and appreciated. In fact, science now has proved that it’s our feelings and emotions that determine our level of engagement in life, what motivates us, and what we care most about.

Where once the idea of appealing to the hearts in workers was seen as heresy, we’ve come to understand that it’s always been essential. The greatest advice I can give you is this: “When you lead from the heart, people will follow.”

For more on what makes a great leader, see Working And Leading With Purpose.

This post was sponsored by and first published on

The post Why Workplace Leadership Is About To Get Its First Major Makeover In 100 Years appeared first on TalentCulture.

Photo Credit: solalta via Compfight cc