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How CIOs Become Invaluable In The Age Of SaaS

Daniel Newman

With SaaS picking up speed, you may have heard whispers about the future of the CIO. Will the role remain necessary? Will it still serve a critical function in the running of a business, especially when you factor in the emergence of “Everything” as a Service (XaaS)?

The answers are yes, yes, and yes. CIOs are still the glue that holds together incumbent business technology, especially if you factor in external influences like Shadow IT, SaaS, and BYOD. What is it precisely that makes CIOs invaluable in this ever-changing environment? Let’s break it down.

Are CIOs on shaky ground?

SaaS and cloud—basically XaaS—surround how we work and how we consume in today’s world. All you have to do is swipe a credit card to use the latest and greatest application. That’s handy for consumers, but what about for those tasked with procuring IT for companies? Making tech purchasing decisions is no longer a highly centralized process; rather, it’s moving into the spokes of organizations. In fact, many are still feeling the sting of that 2012 Gartner prediction that CMOs will spend more on IT than CIOs by the year 2017. If you haven’t heard of that one, I’d be surprised. It’s been highly discussed, and even CIO Magazine has reported on a proposed “CIO-to-CMO transition of power” as the reverberations from Gartner’s report still rattle some industry leaders.

Whether you agree with the Gartner prediction or not, it’s fair to say it’s stirred up a debate about the viability of the CIO in the age of SaaS and XaaS. There just might be a plus side here: Maybe all this back and forth has started what is actually a healthy discussion about the role of CIOs in this evolving tech space. Longevity is possible, though, if CIOs can re-hone their focus on leveraging their skills to developing robust infrastructure to support company scale, securing complex networks and creating a tech environment where company employees can thrive in productivity; hardly an easy task.

Keys to CIO longevity

It is critical that CIOs are masters of the domain of security, compliance, and—perhaps—a new role: education.

Security. We talk a lot about internal and external security, and for good reason. All that Big Data rolling in and out of IT departments can mean big risks for CIOs, so their security efforts must be on-point at all times. Are data scientists getting to the right information quickly and safely? Is proprietary information gated appropriately? What’s the disaster recovery plan for on-premise data center failures? All these questions and more are important to ask, and there’s no room for error.

Compliance. While using a variety of cloud services for day-to-day company operations can bring versatility to overall operations, it can also bring more compliance issues. CIOs can benefit from reinventing their roles to focus on staying ahead of compliance requirements from a big-picture perspective. That way, there will be no aggravating (and costly) downtime due to noncompliance, and everyone in the C-Suite can breathe easily knowing all those compliance boxes remain checked at all times.

Education. With tools and technology changing at breakneck pace, it is nearly impossible for CIOs to keep up with every new tool out there. No matter how big their team, CIO’s can’t validate every application. On top of that, it isn’t exactly in their best interests to become a bottleneck of productivity. Teaching employees about security and compliance risks is a great way to get them to see the difference between innocently downloading the latest consumer-level app, and inadvertently putting company data at risk.

Plus, focusing on inter-company IT education provides job security for CIOs—the tech landscape is evolving into a more do-it-yourself, BYOD space, but there will always be a need for experts to provide guidance, advice, policy, and oversight.

A role revised

If CIOs can lock down internal and external security risks, help the company stay ahead of compliance requirements that can bog down a company, and become a center of excellence for helping employees maximize the adoption of resources, they will put themselves on a much stronger footing. This is especially important in a world where many have tried to provocatively stir the pot, inferring that CIOs are a fleeting trend.

How do you see the role of the CIO evolving as SaaS and “XaaS” continue to dominate boardrooms and budgets? What’s the C-Suite of the future look like for your company? It’s certainly not a black and white issue—there’s lots of gray area and many components to discuss. I’d love to hear your thoughts.

This post was brought to you by IBM Global Technology Services. For more content like this, visit Point B and Beyond 

The post How CIOs Become Invaluable In the Age of SaaS appeared first on Millennial CEO.

Image credit: StockSnap.io

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About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

Even Chicken Farmers Are Going Digital

John Ward

You’re right, Henrietta; that is surprising.

Chicken farming and digital transformation are probably one of the last pairings you would expect to see in a business blog. But in Ontario, Canada, at least, it appears that chicken farmers – and the larger ecosystem that supports them – are definitely going digital.

Why are they all crossing that road?

Apparently one reason is to help meet the changing demands of the region’s very diverse consumers.

Introducing the CFO

The Chicken Farmers of Ontario (CFO) is a not-for-profit organization that represents more than 1,100 family-run farms – the largest group of commercial chicken farmers in Canada.

“We are a management board regulated by the governments of Ontario and Canada,” explains John Um, director of information technology for the organization. “And we help regulate the production and price of chicken within the province.”

That alone would be a pretty big job. But Um points out CFO works with an extensive value chain across the industry that includes chick hatcheries, chicken farms, corn and soybean growers, and chicken processors. Collectively, they ensure consumers enjoy a reliable supply of safe, healthy, high-quality, Ontario-grown chicken.

These days, the collaboration among the various contributors is increasingly high-tech.

Ensuring the quality of your food

CFO recently partnered with consulting services provider CONTAX, Inc. to complete the initial phases of a software project aimed at automating Ontario’s chicken supply chain. They implemented a core ERP system, a customer relationship management solution, and business intelligence software.

CFO also established an online portal called CFO Connects to improve collaboration across the entire value chain. The new system eliminates more than 50 paper forms that the farmers and other stakeholders once filled out by hand and then had to mail or fax back to CFO.

“Now every farmer is working on a digital platform and submitting the required forms using their computer, tablet, or mobile device,” Um says. The benefits include better traceability from hatchery to table, and greater assurance of food quality for consumers.

Programs target unique market segments

“Our ultimate goal is to satisfy customer needs,” says Um. “And this transformation has been vital to helping diversify our products and promote new growth opportunities for our members.”

In fact, CFO manages several innovative programs that enable their chicken farmers to better target the evolving tastes and preferences of Ontario consumers.

The Specialty Breeds Chicken program supports the demand from the province’s growing ethno-cultural communities for chicken processed with “head and feet on.” Within the Chinese culture, for example, serving the whole chicken symbolizes family unity and a good beginning to the New Year.

Ontario has the largest share of people born outside the country of any province in Canada, and Asia remains the country’s largest source of immigrants in recent years. In establishing the program, CFO conducted consumer focus groups in both Mandarin and English to develop a better understanding of the requirements of the multi-ethnic marketplace.

Even more recently, CFO kicked off the Artisanal Chicken program to address the skyrocketing interest in locally grown foods. (Research reveals that 61% of Canadians polled said purchasing local food is important and nearly half would pay up to 30% more to get it.) This program helps small independent farms fill neighborhood food stores and seasonal markets with locally grown chicken which gives Ontario locavores more options in how and where they buy their food.

The digital future of chicken farming

Um doesn’t think consumer demand or the digital transformation in his industry will be slowing down anytime soon.

“The Chicken Farmers of Ontario dates back to 1965,” says Um, “but we will probably see more change in the next three years than in the past fifty.”

The stakes will be high for farmers and consumers alike. According CFO’s annual performance report, the Ontario chicken industry already grows 209 million chickens annually, contributes more than $3 billion to the economy, and supports around 20,000 full-time jobs.

And that ain’t chicken feed.

For more insight on digital transformation, Turn Your Small Business Into A Live Business.

This story also appeared on SAP Business Trends.

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3D Printing Extends From Building Individual Products To Entire Buildings

Folkert Haag

Digital transformation is sweeping through industries. The building products sector is not immune to these changes. Our industry is projected to grow going forward. However, leaders are taking new approaches to building products, and one area that has gained attention is 3D printing.

American Standard notes that, “3D printing will have a major disruptive effect on the design and construction industry.”

Businesses are producing everything from faucets and doors to entire buildings. But what benefits are they seeing? Is 3D printing increasing digital customer engagement? Is it becoming easier to provide custom work? What are the drawbacks? Let’s look at how 3D printing is disrupting our industry and how to take advantage of the change.

Potential for 3D printing and building efficiencies

The advent of 3D printing brings interesting potential for the building products industry. For many decades, efficiency in construction projects happened by pre-fabricating and duplicating structures. This led to a strong interest in customization to set a building apart from similar copies in the area. Technology, such as 3D printing, that allows for customization gives builders the option of creating inexpensive, custom, quickly sourced products. Winsun Global, an early leader in whole-building 3D printing, is working on the world’s first printed office building. Everything – down to the furniture and interior – will be produced from 3D printing. Business models will be impacted as these innovations become the norm.

Benefits of 3D printing for the building products industry

There are many benefits to implementing 3D printed products in the building industry. Lower costs can be achieved through speed of production. This is true even for customized pieces developed by the customer. This opens up the custom market to those who could not have afforded it before. Inventory can be reduced significantly, as needed parts can be printed onsite, also saving time otherwise spent ordering and waiting for a specific material. Being able to duplicate a facility through 3D printing allows easy installation and use of sensors that can track and control everything from electricity and heat to security. These sensors can improve efficiency and tenant satisfaction while reducing the related costs of operation across the duplicates.

Issues with 3D printed building products

There are still many risks and issues with 3D printed building products. Current capabilities allow only for rough pieces to be printed. Pieces that require exact specifications may require a lot of finishing work to be functional. The newness of 3D printing means standards are still being developed. This can lead to quality-control issues with unforeseen consequences. Even once quality is assured through testing and standards, consumers may still perceive substandard quality. Though it is now a reality, sensors, Big Data, and the Internet of Things still seem like science fiction to many people. If not handled correctly, issues from early 3D printed products and their limitations may stay in consumer memory for years to come.

Forging ahead with 3D printed building products

As 3D printed building products become more common and continue to come down in cost, product and material suppliers must have a solid grasp of the potential opportunities to adapt to the changing landscape. Instead of remaining simply a manufacturing firm, the companies will need to provide technology and innovative solutions. For example, adding appropriate IT assets to keep pace with changes in the digital economy. How? When a new trend starts to take off with DIY communities, digital assets can provide analytics. Whether it’s a new type of window or the ability to design the perfect door for an historic home, you can stay ahead of the curve.

How will 3D printed building products impact your business model?

It’s not just 3D printing that will affect your business model. Digitization, hyperconnectivity, and digital business will also have a tremendous impact. Many other changes to and disruption of the business landscape will cause issues as well. Beyond 3D printing, you’ll need to adjust your business model. You’ll need to use analytics to create a lean, flexible enterprise. Companies that don’t embrace these changes will be less likely to anticipate market changes and will at best be able to survive on reactive decisions with backward-facing information. This will lead to further market losses and poor positioning in the industry. By digitizing your business in a comprehensive fashion, you can position it for success.

Are you ready to position your business for significant success and successful leaner operations?

Early adopters are seeing significant gains as the building products industry goes through disruption. They have a comprehensive response to create a superior customer experience. Wienerberger, for example, is offering a one-stop shop for roofs that includes all materials and installation. Nest is not just a thermostat company; it is orchestrating an ecosystem of home automation partners to empower consumers to optimize their home environments. Improved collaboration and engagement of workers and suppliers provide superior results. The Internet of Things provides new insights and opportunities. Your core workflow, finance, operations, and logistics are optimized for flexibility and profitability.

The businesses that do not digitize are viewed as out of touch. This is causing losses because of everything from slow or nonexistent social media response to poor digital business models.

Is it time to digitize your business, whether you’re adopting 3D printing or other innovative options? Is it time to optimize your operation for top flexibility and agility? Click here to learn more about Digital Transformation in Building Products.

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Folkert Haag

About Folkert Haag

Folkert Haag is the global lead for building materials industries at SAP, and is part of the solution management team of the mill products and mining industry unit.

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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5 Things Pokémon Go Taught Me About The Future Of Marketing

Madelyn Bayer

In case you haven’t been outside lately, there is a game taking over the millennial world right now – it’s called Pokémon Go.

Pokémon Go is a mobile app that you can download for iOS or Android. It’s free to download and play, but you have the option to use real money to buy in-game currency called PokéCoins. PokéCoins are used to purchase Pokéballs, the in-game item you need to catch Pokémon. The game uses your phone’s GPS to obtain your real-world location and augmented reality to bring up Pokémon characters on your screen, placing them on top of what you see in front of you. You—the digital you—can be customised with clothing, a faction (a “team” of players you can join), and other options, and you level up as you play.

On the surface, it’s a fun mobile game whose popularity is as intriguing as it is entertaining, but the superficial fun of the app has led to some real results: Developer Nintendo’s valuation has increased by an estimated $7.5 billion thanks to the game.

With results like that, this app is more than just a game, but a possible whole new realm of digital marketing. I started to research some of the key learnings from Pokémon go from a marketing perspective.

  1. Keep it small and simple. Gone are the days of needing to invest in large ad campaigns and advertising budgets. How many ads did we see leading up to the Pokémon Go launch? Very few. Pokémon Go didn’t invest much into advertising because it didn’t need it – either the ad executives in charge knew that the success of the app would be dependent on the marketing and viral factors listed here, or they didn’t expect the app to be a breakout hit. Regardless, the bottom line is that you don’t need a massive advertising budget to be a great marketer; you just need to be able to connect with people. Simplicity is key: Well-designed websites, e-commerce platforms, apps, and products should welcome new users and make it extremely easy for all to get involved (a lesson learned from breakout social media apps like Instagram and Snapchat).
  1. Have an agile digital platform. If you don’t have an agile digital marketing platform, you will miss the boat. This lesson has been proven time and time again in today’s digital world. The marketing game changes faster than most brands can keep up with – but being able to react quickly to trends like this is essential. Failing fast, minimum viable product, and agile: These are fast becoming key phrases in marketing teams’ vocabulary. Whether you are launching a social campaign, a consumer app, or a large-scale marketing operation, you must be able to stand it up quickly, test it, iterate on it, and send it out quickly.
  1. Loyalty is everything. If you want to increase customer loyalty, you must reward your users for continuing to invest in your product. Pokémon Go players get bonuses and incentives for levelling up, taking on gyms, catching new Pokémon, and even walking. The thrill of finding a rare Pokémon or winning an intense battle is enough to keep users yearning for more, even through the less-active parts of the game. There are definite rewards for continued investment, and that’s what keeps users playing—sometimes at the expense of productivity. When I think of the apps I know and love, this feature is nothing new, but it is very important. Gamification and loyalty are what keep me checking in on the highly addictive Air New Zealand app, for example, tuning in each Tuesday to watch the reverse auctions grab flight seats. Creating an individualised offering to every consumer is a hot trend for retailers right now, and it may also be part of the lessons learned from Pokémon Go.
  1. Appeal to the new generation of augmented reality and virtual-reality natives. Just as Gen Y are considered digital natives because they grew up with Internet access, the emerging gen Z will be known as AR and VR natives – what feels new to us now will be the new normal for kids growing up today. That’s not to say every brand should jump on the AR or VR bandwagon. But learn from what this game has taught us: Why is this game taking over the world? What insights can be adapted to generate positive brand engagement? We have evolved past the age of disruptive placement and are now in an era of behavioral targeting. One of the biggest challenges retailers face is knowing where their customers are at any given point in time. How do they reward their customers at the point of sale? Could the next wave of retail disruption be the gamification of shopping in a virtual reality?
  1. Privacy vs. Personalisation. That old chestnut. According to the SAP New Zealand Digital Experience Report 2016, New Zealanders rated having relevant offers without infringing on privacy amongst the highest consumer experience attributes when considering importance to digital experience satisfaction. This is interesting considering the backlash concerning the data Niantic is actively collecting on Pokémon Go users. It seems this hasn’t deterred users too much; the explanation for this may lie further in the New Zealand Digital Experience report research.

Arguably, Pokémon Go ticks all the boxes when we look at the consumer-rated digital experience attributes listed below – though there may be one exception if we consider recent user safety horror stories that are starting to come out.

So what has all this taught us? It links back to the report: The better the digital experience – defined by the above attributes – the happier consumers are to give up their data. The graphs below show consumers’ willingness to give up certain personal information, depending on whether or not they have a satisfactory digital experience. As we all know, data, or information, is the currency of the future, and lessons like these raise important takeaways for all digital marketers looking to gain real consumer insights and preferences.

If you haven’t already given Pokémon Go a go, see what all the fuss is about. Whether the game is a passing fad or the newest trend of digital marketing is yet to be determined, but it offers some interesting thoughts to consider before you launch your next campaign to consumers.

For more insight on where marketing is headed, see MarTech: The Future Of Digital Marketing.

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Madelyn Bayer

About Madelyn Bayer

In my role as an Industry Value Associate at SAP Australia and New Zealand, I help organisations calculate and realise the value that new systems and technology will have on their operations. My role covers industries spanning utilities, public sector, consumer products and retail with a specific focus around customer engagement and commerce solutions and through this role I have developed a strong understanding of mega trends, cloud computing, enterprise software, the networked economy, Internet of Things, millennials and digital consumers. I am particularly passionate about creating sustainable solutions to solving world problems through technology.