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10 Trends Change Leaders Can’t Ignore In 2014

Patti Johnson

Bob Wright, the founder of the Dallas Social Venture Partners, wanted to meet the growing magnifying business trends 2014needs of the Dallas community by sparking the interest of a new generation of social innovators. Bob and a few partners decided to create an event like no other—no conference with static agenda, no talking heads, and no formal event. It had to begin building a long-term community commitment to new generations. This one-of-a-kind event became the bigBANG!

Bob said, “We lived by the belief that we can’t own and control this. We have to turn loose of the steering wheel and let others be part of shaping it. We crowd-sourced the creation of this experience because we wanted a broader circle to feel responsibility for it.”

Bob and his partners invited about twenty-five select social innovators to the first discussion and told them to invite anyone else that they felt should be included. Interest spread and seventy-five people showed up. That meeting resulted in four Spark Clubs, which were idea-generating groups that all helped develop the bigBANG!

They found a new way to build interest and commitment based on the dramatic change in how we want to connect, interact and participate with others.

We can’t own and control this. We have to turn loose of the steering wheel and let others be part of shaping it.

Leading or participating in a change is likely one of your biggest challenges in 2014. I have summarized ten trends that will cause waves this year. Ask yourself: 1) What can I learn about this trend? 2) What opportunities does it present in my organization?, and 3) How can I incorporate this trend in our change today?

Trends in what we want

1. Desire for meaning

Meaning and purpose build a lasting commitment to change—not just compliance or reaching a metric. Meaning is defined as a commitment to something bigger than self. Today there is a growing emphasis on ‘what’s in it for us’ more than just ‘what’s in it for me’ which can have a very short shelf life.

2. The real deal

In our over-advertised, Photo-shopped, create-your-brand culture, it is expected that ‘who you are’ and ‘who you say you are’ align. Authenticity—the truthfulness of origins, attributions, commitments, sincerity, devotion, and intention – is essential for anyone building commitment to a change. It’s also an essential ingredient in finding meaning in our work.

3. Fast and bite-sized

There is growing evidence that social media and changing technology are rewiring our brains with shorter attention spans than ever before. And, the exploding trend toward mobile means we are engaged all of the time, but not for long. The forty page presentations and lengthy emails aren’t the answer.

4. Customized by me for me

We design our own car features and phones, custom build athletic shoes, and create a display of our unique interests on Pinterest. This growing trend drives the shift from “one size fits all”, or your market segment, to “one size fits me”. Individuals want the bigger meaning, but the application must be individualized to stick.

This growing trend drives the shift from “one size fits all”, or your market segment, to “one size fits me”. Individuals want the bigger meaning, but the application must be individualized to stick.

5. Grapevine becomes primary

The grapevine, or word of mouth, is becoming the communication channel of choice. Research tells us that we listen to the recommendations of those we know much more than to campaigns or packaged communications. According to an Ernst & Young study, “Peer recommendations—not paid-for advertising, whether on social media platforms or in print—are what count.” Your change needs a word of mouth strategy.

6. Retro communication

As we spend more hours in front of a screen, the more unique human interaction becomes. We use technology for convenience, speed, efficiency and even cost. Human interaction can be simple or obvious, yet is often forgotten.  Direct human interaction is a key differentiator that drives engagement and positive word of mouth. Know when technology works for you and when it gets in your way.

Trends that affect how we work together

7. Upside-down hierarchy

Social media has had a dramatic effect on leveling the playing field by allowing anyone to have a voice, platform and a following. Our stories and information don’t need to be filtered through an “expert” or an official source. The hierarchy and the command-and-control environment in business are giving way to a culture with more flexible and collaborative leadership unrelated to title or years of experience. An organic, flexible change plan is essential.

Human interaction can be simple or obvious, yet is often forgotten.  Direct human interaction is a key differentiator that drives engagement and positive word of mouth.

8. Peer power

Crowd funding allows anyone to be an investor. Companies like Lego are crowdsourcing ideas for new designs from customers and there are increasing avenues to share our assets with each other. A self-created group can solve, invest and share without a traditional hierarchy. Find areas of your change that can be crowd sourced and designed by a broader group and then act upon it. You’ll drive up engagement.

9. Virtual reality

Technology continues to enable a new era of virtual collaboration and sharing. Virtual collaboration from anywhere in the world can be a strategic advantage in your change rather than a challenge to be managed.  While not new, the virtual opportunity is so often underplayed.

10.  Demographic tsunami 

In the four generation workplace, millennials will make up approximately 36 percent of the 2014 U.S. workforce and become almost half by 2020. Boomers are retiring at record numbers. For the first time a generation is entering the workforce engaged in technology well beyond what their employers use today. We all know this demographic change is upon us, yet are we redefining how we start and lead changes as a result? Our success will depend on it.

These trends are based on research from Patti Johnson’s upcoming book, Make Waves: Be the One to Start Change at Work and in Life to be released in May 2014. 

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The Future Of Supplier Collaboration: 9 Things CPOs Want Their Managers To Know Now

Sundar Kamak

As a sourcing or procurement manager, you may think there’s nothing new about supplier collaboration. Your chief procurement officer (CPO) most likely disagrees.
Forward-thinking CPOs acknowledge the benefit of supplier partnerships. They not only value collaboration, but require a revolution in how their buying organization conducts its business and operations. “Procurement must start looking to suppliers for inspiration and new capability, stop prescribing specifications and start tapping into the expertise of suppliers,” writes David Rae in Procurement Leaders. The CEO expects it of your CPO, and your CPO expects it of you. For sourcing managers, this can be a lot of pressure.

Here are nine things your CPO wants you to know about how supplier collaboration is changing – and why it matters to your company’s future and your own future.

1. The need for supplier collaboration in procurement is greater than ever

Over half (65%) of procurement practitioners say procurement at their company is becoming more collaborative with suppliers, according to The Future of Procurement, Making Collaboration Pay Off, by Oxford Economics. Why? Because the pace of business has increased exponentially, and businesses must be able to respond to new market demands with agility and innovation. In this climate, buyers are relying on suppliers more than ever before. And buyers aren’t collaborating with suppliers merely as providers of materials and goods, but as strategic partners that can help create products that are competitive differentiators.

Supplier collaboration itself isn’t new. What’s new is that it’s taken on a much greater urgency and importance.

2. You’re probably not realizing the full collective power of your supplier relationships

Supplier collaboration has always been a function of maintaining a delicate balance between demand and supply. For the most part, the primary focus of the supplier relationship is ensuring the right materials are available at the right time and location. However, sourcing managers with a narrow focus on delivery are missing out on one of the greatest advantages of forging collaborative supplier partnerships: an opportunity to drive synergies that are otherwise perceived as impossible within the confines of the business. The game-changer is when you drive those synergies with thousands, not hundreds of suppliers. Look at the Apple Store as a prime example of collaboration en masse. Without the apps, the iPhone is just another ordinary phone!

3. Collaboration comes in more than one flavor

Suppliers don’t just collaborate with you to provide a critical component or service. They also work with your engineers to help ensure costs are optimized from the buyer’s perspective as well as the supplier’s side. They may even take over the provisioning of an entire end-to-end solution. Or co-design with your R&D team through joint research and development. These forms of collaboration aren’t new, but they are becoming more common and more critical. And they are becoming more impactful, because once you start extending any of these collaboration models to more and more suppliers, your capabilities as a business increase by orders of magnitude. If one good supplier can enable your company to build its brand, expand its reach, and establish its position as a market leader – imagine what’s possible when you work collaboratively with hundreds or thousands of suppliers.

4. Keeping product sustainability top of mind pays off

Facing increasing demand for sustainable products and production, companies are relying on suppliers to answer this new market requirement.

As a sourcing manager, you may need to go outside your comfort zone to think about new, innovative ways to collaborate for achieving sustainability. Recently, I heard from an acquaintance who is a CPO of a leading services company. His organization is currently collaborating with one of the largest suppliers in the world to adhere to regulatory mandates and consumer demand for “lean and green” lightbulbs. Although this approach was interesting to me, what really struck me was his observation on how this co-innovation with the supplier is spawning cost and resource optimization and the delivery of competitive products. As reported by Andrew Winston in The Harvard Business Review, Target and Walmart partnered to launch the Personal Care Sustainability Summit last year. So even competitors are collaborating with each other and with their suppliers in the name of sustainability.

5. Co-marketing is a win-win

Look at your list of suppliers. Does anyone have a brand that is bigger than your company’s? Believe it or not, almost all of us do. So why not seize the opportunity to raise your and your supplier’s brand profile in the marketplace?

Take Intel, for example. The laptop you’re working on right now may very well have an “Intel inside” sticker on it. That’s co-marketing at work. Consistently ranked as one of the world’s top 100 most valuable brands by Millward Brown Optimor, this largest supplier of microprocessors is world-renowned for its technology and innovation. For many companies that buy supplies from Intel, the decision to co-market is a strategic approach to convey that the product is reliable and provides real value for their computing needs.

6. Suppliers get to choose their customers, too

Increased competition for high-performing suppliers is changing the way procurement operates, say 58% of procurement executives in the Oxford Economics study. Buyers have a responsibility to the supplier – and to their CEO – to be a customer of choice. When the economy is going well, you might be able to dictate the supplier’s goods and services – and sometimes even the service delivery model. When times get tough (and they can very quickly), suppliers will typically reevaluate your organization’s needs to see whether they can continue service in a fiscally responsible manner. To secure suppliers’ attention in favorable and challenging economic conditions, your organization should establish collaborative and mutually productive partnerships with them.

7. Suppliers can help simplify operations

Cost optimization will always be one of your performance metrics; however, that is only one small part of the entire puzzle. What will help your organization get noticed is leveraging the supplier relationship to innovate new and better ways of managing the product line and operating the business while balancing risk and cost optimization. Ask yourself: Which functions are no longer needed? Can they be outsourced to a supplier that can perform them better? What can be automated?

8. Suppliers have a better grasp of your sourcing categories than you do

Understand your category like never before so that your organization can realize the full potential of its supplier investments while delivering products that are consistent and of high quality. How? By leveraging the wisdom of your suppliers. To be blunt: they know more than you do. Tap into that knowledge to gain a solid understanding of the product, market category, suppliers’ capabilities, and shifting dynamics in the industry, If a buyer does not understand these areas deeply, no amount of collaboration will empower a supplier to help your company innovate as well as optimize costs and resources.

9. Remember that there’s something in it for you as well

All of us want to do strategic, impactful work. Sourcing managers with aspirations of becoming CPOs should move beyond writing contracts and pushing PO requests by building strategic procurement skill sets. For example, a working knowledge in analytics allows you to choose suppliers that can shape the market and help a product succeed – and can catch the eye of the senior leadership team.

Sundar Kamak is global vice president of solutions marketing at Ariba, an SAP company.

For more on supplier collaboration, read Making Collaboration Pay Off, part of a series on the Future of Procurement, by Oxford Economics.

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Transform Or Die: What Will You Do In The Digital Economy?

Scott Feldman and Puneet Suppal

By now, most executives are keenly aware that the digital economy can be either an opportunity or a threat. The question is not whether they should engage their business in it. Rather, it’s how to unleash the power of digital technology while maintaining a healthy business, leveraging existing IT investments, and innovating without disrupting themselves.

Yet most of those executives are shying away Businesspeople in a Meeting --- Image by © Monalyn Gracia/Corbisfrom such a challenge. According to a recent study by MIT Sloan and Capgemini, only 15% of CEOs are executing a digital strategy, even though 90% agree that the digital economy will impact their industry. As these businesses ignore this reality, early adopters of digital transformation are achieving 9% higher revenue creation, 26% greater impact on profitability, and 12% more market valuation.

Why aren’t more leaders willing to transform their business and seize the opportunity of our hyperconnected world? The answer is as simple as human nature. Innately, humans are uncomfortable with the notion of change. We even find comfort in stability and predictability. Unfortunately, the digital economy is none of these – it’s fast and always evolving.

Digital transformation is no longer an option – it’s the imperative

At this moment, we are witnessing an explosion of connections, data, and innovations. And even though this hyperconnectivity has changed the game, customers are radically changing the rules – demanding simple, seamless, and personalized experiences at every touch point.

Billions of people are using social and digital communities to provide services, share insights, and engage in commerce. All the while, new channels for engaging with customers are created, and new ways for making better use of resources are emerging. It is these communities that allow companies to not only give customers what they want, but also align efforts across the business network to maximize value potential.

To seize the opportunities ahead, businesses must go beyond sensors, Big Data, analytics, and social media. More important, they need to reinvent themselves in a manner that is compatible with an increasingly digital world and its inhabitants (a.k.a. your consumers).

Here are a few companies that understand the importance of digital transformation – and are reaping the rewards:

  1. Under Armour:  No longer is this widely popular athletic brand just selling shoes and apparel. They are connecting 38 million people on a digital platform. By focusing on this services side of the business, Under Armour is poised to become a lifestyle advisor and health consultant, using his product side as the enabler.
  1. Port of Hamburg: Europe’s second-largest port is keeping carrier trucks and ships productive around the clock. By fusing facility, weather, and traffic conditions with vehicle availability and shipment schedules, the Port increased container handling capacity by 178% without expanding its physical space.
  1. Haier Asia: This top-ranking multinational consumer electronics and home appliances company decided to disrupt itself before someone else did. The company used a two-prong approach to digital transformation to create a service-based model to seize the potential of changing consumer behaviors and accelerate product development. 
  1. Uber: This startup darling is more than just a taxi service. It is transforming how urban logistics operates through a technology trifecta: Big Data, cloud, and mobile.
  1. American Society of Clinical Oncologists (ASCO): Even nonprofits can benefit from digital transformation. ASCO is transforming care for cancer patients worldwide by consolidating patient information with its CancerLinQ. By unlocking knowledge and value from the 97% of cancer patients who are not involved in clinical trials, healthcare providers can drive better, more data-driven decision making and outcomes.

It’s time to take action 

During the SAP Executive Technology Summit at SAP TechEd on October 19–20, an elite group of CIOs, CTOs, and corporate executives will gather to discuss the challenges of digital transformation and how they can solve them. With the freedom of open, candid, and interactive discussions led by SAP Board Members and senior technology leadership, delegates will exchange ideas on how to get on the right path while leveraging their existing technology infrastructure.

Stay tuned for exclusive insights from this invitation-only event in our next blog!
Scott Feldman is Global Head of the SAP HANA Customer Community at SAP. Connect with him on Twitter @sfeldman0.

Puneet Suppal drives Solution Strategy and Adoption (Customer Innovation & IoT) at SAP Labs. Connect with him on Twitter @puneetsuppal.

 

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About Scott Feldman and Puneet Suppal

Scott Feldman is the Head of SAP HANA International Customer Community. Puneet Suppal is the Customer Co-Innovation & Solution Adoption Executive at SAP.

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!

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Erik Marcade

About Erik Marcade

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

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Strengthening Government Through Data Analytics

Dante Ricci

When it comes to analyzing data, you could say that there is a clash in culture due to disconnect within the government workforce. This is partly due to the fact that many organizations don’t have people in place with the right technical skill sets. But government can uncover hidden insights to drive better results and create more value for citizens.

The need has never been greater to empower knowledge workers with a comprehensive – yet simple – integrated platform that helps unlock the real value in data for smarter decision-making.

Governments move toward constituent-centered platforms

The fact is, leading government organizations have begun to transform by using consumer-grade solutions to garner better insights from data. The key lies in self-service and automated analytics that do not require technical skill sets. Such solutions enable government personnel at all levels to shift from asking IT for historical reports to a real-time and predictive view that considers multiple data points to deliver a personalized view.

Poised with the right technology and collaborative mindset, governments can uncover new insights to make life better, safer, and healthier, when:

  1. Technology is intuitive and easy to use.
  2. Personnel can make decisions based on a combination of historical and real-time data rather than decisions based on historical perspective alone.
  3. Collaborative technology can include constituent insight and ideas for better decision making.

Digital transformation of government removes that massive barrier between agencies and departments using a platform that shares data and removes the friction that slows down the entire process. The result is that agencies are able to do more, produce better results, and still save money. Digital by default is the key. The rewards are significant for those who successfully leverage analytics: stretching their competitive advantage, driving innovation, and improving lives.

Predictive solutions that appear before your eyes

Digitalized governments run frictionless with decisions based on real contextual insights. Analytics help leaders see problems before or as they occur. That real-time connection identifies potential problems and gives management time to correct them. As real-time data becomes available through input from sensors, transactions, constituents, and other information channels, decisions can be made at the moment of opportunity.

Putting it together

What happens when you need to make decisions, but your data is two years old? What if you need to rewrite a policy that focuses on performance and cost — but you have no information about costs?

Those sorts of problems occur every day. In the first scenario, your decision may be wrong because the data changed. In the second scenario, the policy update may be late. Both potential outcomes reflect negatively on performance and can negatively impact the safety and quality of citizens’ lives. These are both examples of the friction that occurs within governments. They are also the reasons why relevant and timely data is necessary.

The power and tools that a digital government wields are transformative. The rewards for government are many: lower costs, improved services, safer communities, and a better overall quality of life.  Services become seamless. Systems become fluid. Operational costs drop and better outcomes occur.

In short, you make better decisions when they are based on facts and context, not feelings. People who need help get help quickly. Operational issues become identified and fixed. People are happy. And isn’t that the way government should work?

Are you ready for change?

Read about more about SAP’s perspective on digital government here.

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About Dante Ricci

Dante Ricci is the Global Public Services Marketing & Communications lead at SAP. His specialties include enterprise software, business strategy, business development, cloud computing and solution selling.