Tag Archives: Experience

How Technology Enhances The Customer Experience

Mention the word fintech to veteran financial services executives and watch the hairs on the backs of their necks stand up.

Fintech is a broad term that applies to new digital financial technologies, from cryptocurrencies to mobile wallets, as well as the startups attempting to use those new technologies to blast centuries-old financial institutions out of the water.

Recognizing the existential threat, leaders of 233-year-old U.S. financial giant Bank of New York Mellon (BNY Mellon) became convinced that continuous IT-enabled innovation was essential. To do that right, the IT team reorganized around specific capabilities—190 so far. Each capability has an owner who serves as a kind of CEO of that service and who is free to make any changes deemed necessary for success.

Like any radical change, BNY Mellon’s effort has seen its share of growing pains. For example, some take to the ownership roles better than others. And employees have required significant coaching throughout.

Several years in, however, a fundamental shift has taken place at the bank established by U.S. founding father Alexander Hamilton. “Change is no longer some big project,” says Jeanne Ross, principal research scientist at MIT’s Center for Information Systems Research, who has studied BNY Mellon’s efforts. “Change is what you do every morning when you get out of bed.”

Just about every industry is facing its own version of fintech these days, forcing organizations to disrupt their established ways of doing business or face disruption by an upstart unburdened by legacy processes and technology. It’s the age of digital transformation, which business consultancy Capgemini calls “the ultimate challenge in change management because it affects not only industry structures and strategic positioning, but also all levels of an organization (every task, activity, process) as well as the extended supply chain.” Dramatic increases in connectivity and improvements in technologies such as artificial intelligence, cloud computing, and advanced analytics let companies optimize their processes continuously, but usually not without making enormous changes first.

SAP Q317 DigitalDoubles Feature2 Image2 How Technology Enhances The Customer ExperienceTo make the most of frequent and successive waves of technology innovation, organizations must build adaptability into their structures, their functions, and their individual employees. That calls for new approaches designed to make transformation real and continuous. “The ability to develop a culture of change where people rely less on habits and more on imagining what’s possible every day is going to be part and parcel of being a great company,” says Ross.

Unfortunately, the traditional command-and-control architecture of most businesses was not built for continuous adaptation. “The speed with which we need to take a good idea and get it in place is so much faster than before, which is why we are having this moment of truth,” Ross says. “Traditional approaches that rely on a lot of hierarchy to make changes are too slow.”

For years, most change efforts have been top-down, episodic, all-encompassing “big bang” attempts to alter systems, processes, and cultures. Executives announced a restructuring or an acquisition or the implementation of new technology and brought in external change management consultants to try to get people to adapt to new ways of working. It rarely succeeded.

Despite significant investment in the change management discipline and a library of books on the subject, just a quarter of change management initiatives succeed long term, according to a 2013 survey by consultancy Willis Towers Watson.

Digital transformation isn’t going much better. Worldwide spending on digital transformation technologies will grow to US$ 1.2 trillion in 2017, up 17.8% over 2016, according to IDC. But fewer than 2 in 10 respondents to a recent survey by the SAP Center for Business Insight and Oxford Economics have seen substantial or transformational value from their technology investments so far. And just 12% say that digitalization has affected their organizational structure in a meaningful way.

Furthermore, even though 84% of the C-level executives surveyed ranked digital transformation as “critically important” to the survival of their businesses, just 3% have completed transformation efforts that span the entire organization.

For digital transformation to deliver value, an entire organization needs to buy into new ways not just of working, but also of thinking. “It’s not about bringing consultants in. It’s about really designing systems that enable an organization to adapt innately,” says Pravir Malik, founder of organizational change development firm Deep Order Technologies and author of Connecting Inner Power with Global Change: The Fractal Ladder and The Fractal Organization: Creating Enterprises of Tomorrow.

Companies are experimenting with new approaches that encourage and support the flexibility required to embrace continuous transformation. Some are rethinking how they operate. Others are investing in helping employees become more adaptable. Still others are clarifying their mission in a way that makes room for individuals to drive change themselves.

Ultimately, gaining the ability to change constantly will help both organizations and employees over the long term. Change becomes less episodic, less massive, and less jarring; there is no end state, no go-live. Instead, the organization is always moving, but at a step-by-step pace that makes it easier for employees to adapt.

However, evolving into this state of constant, fluid change isn’t easy. It only works if you have the right approach and methodologies.

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Changing Mindsets

Indeed, as companies tackle digital transformation, traditional highly structured change management programs can actually do more harm than good, says Tom Weeks, senior consultant with The Arbinger Institute, a consultancy that works with organizations to encourage change from within. “The change program becomes the change rather than the results you’re trying to achieve,” he says.

Such change efforts can create a short-term view. As a result, says Weeks, “they drive short-term change, but they don’t change people’s minds. You can force the issues and try to make change happen for change’s sake. But eventually the effort loses energy.”

“Everyone is surprised by that,” adds Weeks. “But it’s just nature at play. We’re hardwired to resist change. If you’re not shifting fundamental mindsets, it doesn’t matter how much money or how many resources you put behind it.”

In her behavioral research, Stanford University psychologist Carol Dweck has focused on two types of mindsets that she sees in most organizations: a fixed mindset and a growth mindset. People with fixed mindsets believe that their basic qualities, like intelligence or talent, are static.

Those with a growth mindset think that talents and capabilities develop over time through effort—a way of thinking that Dweck says creates more individual resilience and adaptability. People in the latter group tend to be better at collaboration, problem solving, and, naturally, continuing change.

The good news, according to Dweck, is that the growth mindset can be a learned behavior. She points to Microsoft as a company attempting to do just that. Microsoft CEO Satya Nadella has publicly stated that the corporate mission “starts with a belief that everyone can grow and develop; that potential is nurtured, not predetermined; and that anyone can change their mindset.”

SAP Q317 DigitalDoubles Feature2 Image4 How Technology Enhances The Customer ExperienceMicrosoft’s leaders are emphasizing learning and creativity with programs like hackathons in which the best projects are funded and their originators rewarded. The company is more explicitly rewarding risk-taking and the pursuit of stretch goals. When Microsoft’s foray into artificial intelligence, the chatbot Tay, was hacked, the CEO sent the team an e-mail of encouragement rather than rebuke.

Rather than limiting leadership development programs to those easily identified as having innate management potential, Microsoft says it is moving a broader swath of employees up and across teams, augmenting their skills, and expanding their work experiences. The most valuable employees are not necessarily the smartest people in the room, as in the past, but those who are the most adaptable—and capable of bringing that out in others.

While Dweck’s mindset work focuses on peoples’ ability to learn and grow, at The Arbinger Institute, consultants focus on an individual’s ability to work productively and with others. Arbinger’s methodology differentiates between an inward mindset, which causes people to be self-centered—seeing other people as objects or tools to either help or hurt them—and an outward mindset, which engenders more connection with and understanding of others as human beings.

Those with an outward mindset can work more collaboratively and productively. That’s incredibly important in an environment of change, such as when Raytheon Missile Systems was trying to integrate a series of mergers that were rife with infighting.

The company overcame the battles by working with all 12,000 employees on shifting their mindsets. Employees worked to uncover their part in company problems and devised ways to work collaboratively with others to solve them and hold themselves accountable for results. When tasked by company leaders to cut $ 100 million in expenses in two months or face layoffs, employees worked together to uncover alternatives.

They began to look beyond their own individual roles and needs, and focused instead on the needs of their colleagues and of the organization as a whole, says Weeks. That resulted in some big, organization-wide changes that went far beyond cost savings and helped increase sales dramatically.

Typically, companies like Raytheon come to Arbinger for help changing mindsets after they’ve struggled with failed change for a while. But that’s beginning to change, says Weeks, and that’s the ideal.

One company is offering employees training on the outward mindset approach before the launch of its six-year transformation effort. “If employees don’t have the right mindset, you can push change as much as you want, but eventually there will be a snap back. What’s required is people who want to hold themselves accountable at a higher level.”

Flexibility by Design

Neuroscientists are not surprised by the shift toward employee-centric rather than top-down change. They have proven that a brain’s “plasticity”—its ability to restructure and learn new things—is enduring. An old dog can learn new tricks. But when change is forced upon people, they quickly become overwhelmed, which activates the fight-or-flight response in the primitive emotional center of the brain, the amygdala.

They bottle up that instinctive response and it reemerges as anxiety, depression, and poor health if not managed. And not only are those potentially toxic emotions harmful to the individual, they are contagious in the organization.

The secret is to create conditions in which people direct more of the change themselves. When individuals solve a problem on their own, for example, their brain releases a rush of neurotransmitters that can create good feelings associated with the change.

One way to create this kind of personal change ownership is by taking a design thinking approach. The iterative, human-centric design concept that was first developed in the early 1970s has become a popular approach to developing products and services for customers. But design thinking principles can also bring new systems and processes to an organization.

SAP Q317 DigitalDoubles Feature2 Image5 How Technology Enhances The Customer ExperienceThat was the case when furniture maker Herman Miller began exploring the potential of an office chair connected to the Internet of Things (IoT) three years ago. Instead of designing a new chair, Herman Miller came away with the foundation for an organizational transformation from hard goods maker to service provider. This is the latest fundamental shift in a company that has evolved from traditional Queen Anne-style furniture maker in the 1930s to office designer in the 1970s to ergonomics innovator in the 1980s and 1990s, says Chris Hoyt, design exploration leader at Herman Miller.

Taking a design thinking approach meant interviewing a wide cross section of stakeholders. The interviews revealed that simply putting a sensor into a desk chair did not make business sense, but putting one into the company’s sit-to-stand desk—and creating a series of IoT-enabled services around it—did. The exercise turned out to be an entry point into an entirely new business model.

“Design thinking wasn’t new to Herman Miller, but there was a lot of skepticism about whether integrating technology into its furniture made business sense,” explains Kurt Dykema, co-founder and director of technology at product innovation and business strategy consultancy Twisthink, which worked with Herman Miller. “This process guided them through a transformation where they have to think about selling a digital experience and monetizing that instead of just selling a capital good and then being done with it.”

For example, none of Herman Miller’s back office operations was built to support the IoT subscription models it planned to offer with the desk. But the design thinking approach created consensus around IoT business value and helped to clarify the organizational changes required to capitalize on the new opportunity.

“It forced them through the process of retooling the business to sell and maintain digital experiences,” Dykema says. Herman Miller launched its Live OS furniture line in June, with the smart desk as the first product, and plans for more to follow.

Getting Agile

Like many companies that incorporate a design thinking approach to organizational change, the performance car division of Daimler AG, Mercedes-AMG, married its process with agile development methods.

Agile turns conventional change management on its head. Rather than making big changes all at once, agile uses an incremental approach to creating software that gives users a chance to use and react to new functionality as it is developed and to validate its value (as opposed to the more traditional waterfall approach where users don’t experience a solution until it is finished).

With agile, there is no predetermined end state. Instead, change is constant, but never so rapid that it becomes overwhelming.

At Mercedes-AMG, clickable prototypes were produced and tested with users weekly and their feedback was funneled back into development streams, continuously improving the resulting system. Based on early success at Mercedes-AMG, Daimler’s enterprise IT organization launched a similar program to develop new digital services for the enterprise.

SAP Q317 DigitalDoubles Feature2 Image6 How Technology Enhances The Customer ExperienceAt BNY Mellon, the adoption of agile development methods has enabled the company to introduce an incredible amount of systems change—but two weeks at a time.

The product of years of mergers and acquisitions, BNY Mellon had operated in product silos, each with their own systems and processes. The company wanted to develop a digital platform from which it could orchestrate a more unified and innovative customer experience. The goal was to put one of America’s oldest financial institutions on equal footing with some of the newest and most nimble newcomers in fintech.

Agile was a new way of working for the IT organization, which was accustomed to introducing releases a couple of times a year rather than a couple of times a month. So IT leaders invested significant time and money helping employees adopt new skills and adapt to the changes.

Eventually, agile enabled the bank to introduce new systems to its 52,000 employees in phases for their ongoing input, fine-tuning the systems over time to best meet employees’ needs and better ensure their adoption. It’s led to the creation—and ongoing enhancement—of an open-source, cloud-based platform that serves as a portal for both internal employees and customers. This app store will provide access to all BNY Mellon’s products and services as well as capabilities from select fintech and established financial services partners.

Increasing Autonomy

Though making change constant relies heavily on individual employees, leaders still have an important role to play. They need to provide the alignment with organizational principles that, when combined with individual autonomy, can create the kind of fluid and adaptive organization required for digital transformation, according to Mark Bonchek, CEO of Shift Thinking, a consultancy that works with leaders and organizations to update their thinking for a digital age.

The U.S. military takes this kind of approach on the battlefield, putting in place a doctrine that authoritatively guides soldiers but gives them autonomy and requires judgment in action to respond to rapidly changing conditions.

In business, organizations are adapting this principle by giving employees guidance on how to take action without requiring them to first seek approval. For example, when Suresh Kumar took over as CIO of BNY Mellon, he reorganized IT around end-to-end IT and business services. IT leaders subdivided each service into smaller components, each with its own leader. These hundreds of services leaders maintain their own service strategy document that covers the current state as well as a one- to three-year improvement plan.

Each service leader is measured on user experience. And because the services are highly interdependent, leaders are also judged on the experience of other service leaders who depend on their service.

As a result, BNY Mellon’s top IT leadership no longer directs team members, but coaches them. Early on, only about a third of the service leaders were successful. The IT group ultimately developed a maturity model for the approach to foster leader development.

Leading a service is as much a mindset as it is a job, says Kumar. The goal of the new approaches—agile software development, physical reorganization, increased autonomy and responsibility—is to create a digital foundation of services linking the bank to its customers and external partners and fostering ongoing digital transformation. The shift began in the IT organization, but the plan is to expand it enterprise-wide and to bring partners and customers into the loop as well.

The Power of Language

In the digital transformation era, companies need a new strategic narrative to help drive a mindset of constant change. A strategic narrative describes the shared purpose that all stakeholders are working toward, says Bonchek. That creates a shared purpose that everyone can wrap their minds—and ultimately their behaviors—around.

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For example, BNY Mellon’s working narrative is that “we believe each of us has the power to improve lives through investing.” And that applies not only to the investment of capital, but investing in people, in ideas, and in the future. At a high level, the theme helps reorient employees’ thinking and behaviors as they consider new ways the bank might differentiate itself.

The Importance of Being Resilient

If an organization is going to adapt itself to constant change, employees need tools to manage the psychological stress that comes with it.

Luckily, personal adaptability is something that you can teach. That’s just what Wendy Quan, a former in-house change management professional, does. As the founder of The Calm Monkey, she’s working with organizations from Google to the government of Dubai, helping them implement self-sustaining mindfulness meditation programs.

Quan used mindfulness and meditation practices to increase her own resilience during cancer treatment. “It alters your experience of a change,” she explains, “even when things around you aren’t changing the way you want them to.”

In 2011, she began conducting mindfulness training for a handful of executives working on a seven-year business and technology transformation project at Pacific Blue Cross. The leaders found the training so valuable that they made it available to the entire workforce.

Quan used the sessions to help employees experience the change on their own terms rather than feeling victimized. She focused change-specific meditations on becoming aware of one’s own perceptions about change, recognizing emotions and their impact on behaviors, learning how to mindfully choose reactions, and cultivating calm and clarity.

Quan surveyed employees after the training. The percentage of employees who rated their personal resiliency as low at the beginning decreased from 40% to just 2% while those who characterized themselves as highly resilient increased by a factor of 600% to 72%. And 83% said that meditation has moderately to significantly helped them through a significant transition.

“Change management methodologies favor the corporate perspective,” says Quan. “But it’s really important to focus on helping people be more self-aware of how they’re journeying through the change.”

Deep Order Technologies’ Malik also focuses his approach to resiliency training on self-awareness. He built a mobile app that enables employees to register what they’re feeling throughout the day. Recording emotional states gives employees a better understanding of what drives their own behaviors and how to cope with their feelings.

Leaders can then look at the aggregated, anonymized readings to identify patterns across the organization. Those patterns give leaders a good idea of the overall orientation of employees going through a change at a given point in time and whether they are poised to go along with it or resist.

Change the Ways of Changing

There is no simple solution to making change easier. A combination of new approaches at the organizational and individual level will be required to adapt to the constant change demanded by the digital future.

These approaches are all in the early adoption phases in most companies. Ironically, they are, in and of themselves, significant changes that must be absorbed. But the speed of digital change is relentless. “It’s just getting faster and faster,” says Quan. “And what companies are seeing is that stress and the inability to adapt to change cause reduced performance and increased absenteeism and disability rates. Leaders who see these trends know they need to pay attention,” says Quan.

Those that don’t? “They’ll go away. They’ll be history,” says Ross. “I don’t think this is an issue they can ignore.” D!

About the Authors

Andreas Hauser is Senior Vice President, Strategic Design Services and AppHaus Network, at SAP.

Paul Kurchina is a community builder with the Americas’ SAP Users’ Group (ASUG) who focuses on digital transformation and change.

Stephanie Overby is a Boston-based business and technology journalist.

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


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Digitalist Magazine

Study: Music Improves Customer Experience, Even in Serious Settings

Music can enhance the customer experience even in nontraditional retail environments, suggests a study released Thursday by
Mood Media and the
Society of Composers, Authors and Music Publishers (SACEM). The study was conducted in France.

Customers had a more favorable experience in five business locations — including gas station, optical, banking, sports apparel and pharmacy locations, the study found.

“It’s undeniable that music has an amazing ability to connect on an intimate and personal level,” said Danny Turner, global senior vice president of creative programming at Mood Media.

“Brands that understand the connectivity between brand and in-store experience, facilitated by the incredible power of music to forge an emotional bond, are well on their way to elevating their customer experience,” he told CRM Buyer.

84878 620x346 small Study: Music Improves Customer Experience, Even in Serious Settings

Click Image to Enlarge

Businesses should consider overhead music as important as store layout, lighting or other key design elements, said Valentina Candeloro, international marketing director at Mood Media.

Mood Media has begun designing music programs for an increasingly diverse body of retail locations, she told CRM Buyer, including auto dealerships, credit unions, apartment buildings and retirement home communities.

When researchers designed the study, data indicated that 90 percent of French people listened to music every day, but only 70 percent of businesses played music, Candeloro noted.

Some of the non-retail businesses, like pharmacies, opticians and banks, were concerned about the impact music would have, given the more serious nature of transactions or activities taking place in their locations, she said.

“The results of this study revealed and quantified the impact and potential that music offers across a wide array of business types,” said Jean-Felix Choukroun, director of customer relations at SACEM.

Music Markers

Seventy percent of study respondents reported a more positive perception of a business when music was playing overhead, while 65 percent said that music at the location helped differentiate the business from the competition.

Ninety-three percent of employees at those locations preferred music over no music at work.

When customers at more serious locations, like banks and pharmacies, were asked if they wanted music, only 33 percent said they thought music would be appropriate.

However, 76 percent of the customers who experienced music at those types of locales said they thought the music was complementary and compatible with the businesses.

In-Store Atmosphere

Music absolutely can have a positive impact in driving retail traffic and keeping customers engaged at a particular location, said Nikki Baird, managing partner at
RSR Research.

“The gist is, it absolutely helps,” she told CRM Buyer. “It leads to shoppers staying longer and being in a more pleasant mood.”

Research has shown that you need a minimum two-hour loop of in-store music to prevent employees from being driven crazy by repetition and turning the music off, Baird noted.

In-store or in-business music can have a definite positive impact on the net promoter score of a location, which reflects the willingness of customers to recommend that business to others, noted Cindy Zhou, principal analyst at Constellation Research.

For example, the lobby music of W Hotels — Starwood Hotels’ hip hospitality brand — has become popular enough to spawn its own Spotify playlist, she told CRM Buyer, as well as a microsite just for W music fans.
end enn Study: Music Improves Customer Experience, Even in Serious Settings

David Jones is a freelance writer based in Essex County, New Jersey. He has written for Reuters, Bloomberg, Crain’s New York Business and The New York Times.

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Interconnect the Traveler’s Journey to Provide a Relevant Customer Experience  

taveling Interconnect the Traveler’s Journey to Provide a Relevant Customer Experience  

Millions of people take to the roads, the skies, and the tracks every day to get from point A to point B. Not only are customers taking advantage of various transportation methods, but they are taking advantage of services before and after, whether it’s booking their tickets or checking into a hotel.

Today’s customers are more technology savvy because of the availability of smartphones, open traffic and transport information/data, real-time planning and info, and new innovative apps created by start ups. Because of the increase in mobile technology, customers now have more choices when it comes to comparing prices, choosing alternative routes, and seeing the current status of transport.

Traditionally, transport operators aren’t as savvy as customers, but if they don’t adapt, they will be taken over by the key trends that are disrupting the current business model:

—User/customer focused. By connecting to passengers with fast applications and real-time data, you can create “in-the-moment” experiences and provide individualized marketing. Operators will then be able to deliver in-context, targeted offers that reflect each customer’s preferences.

—Integrated intelligence. Physical assets will sense demand via APIs and IoT devices and stream data in real time. This data can be modeled to predict and avoid disruptions.

—Commercials. More operators such as railways, buses, and ferries will follow airlines in adopting e-tickets. Pay-as-you-travel will increase, enabled by well-managed APIs.

—Automation and safety. The adoption of IoT will result in more assets being monitored for their health and performance. Transportation companies can consolidate, analyze, visualize, and predict information about incidents, delays, repairs, and maintenance.

The travel industry has the opportunity to use data to develop closer relationships with customers. To do this, you need to know where the customer is in their journey and provide offers based on that context. By personalizing service, you can increase revenue, and attract and retain new customers.

With our predictive analytics, streaming analytics, and API-led integration solutions, you can interconnect the traveler’s journey to provide a relevant customer experience. To find out how, check out our new travel solutions page.

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New Mobile App Promises Full B2B E-Commerce Experience

Insite Software on Tuesday released the InsiteCommerce Mobile App, describing it as the first fully configurable white label mobile app built for leading manufacturers and distributors.

mobile b2b New Mobile App Promises Full B2B E Commerce Experience

The app supports everyone involved in the B2B e-commerce experience, Insite said — from customers to channel partners, to field sales and support teams.

Companies purchasing the app can tailor its functions to specific roles and responsibilities by delivering customer-specific product catalog and data, pricing and product recommendations, and order and reorder capabilities.

“There’s a combination of customizations and configurations driven by a single instance of the InsiteCommerce Admin Console across Web and mobile apps,” said Karie Daudt, VP of marketing and customer experience at Insite.

“We customize the color scheme, icons and certain images in each build of a private labeled application to suit the branding standards of each customer,” she told CRM Buyer.

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Private labeling of each application is done internally, and “doesn’t require any code customization or additional implementation effort for our customers,” Daudt said.

The app includes a biometric login capability, customizable alerts, bar code scanning, GPS capabilities, speech-to-text and enhanced security.

Among the app’s prebuilt features are product catalog search, order status check, and the ability to add items to a cart and check out.

The app is available for iOS and Android.

Integration, Integration, Integration

The InsiteCommerce Mobile App works with Insite Software’s e-commerce platform, which integrates with leading enterprise resource planning, customer relationship management and Web content management systems.

It automatically builds experience based on a business’ existing InsiteCommerce instance.

“Any new customer can extend their reach with a native mobile solution when they roll out an InsiteCommerce system,” Daudt remarked.

Companies with a mobile-first implementation strategy can “focus on implementing a light version of the branded mobile application first, then execute a more complete integration of e-commerce, including integration with their ERP and other core business functions,” she said.

Insite partners with each client to manage and deploy its apps to the iOS and Google Play app stores, Daudt noted.

“This lets our customers maintain their branding standards and achieve app store presence while still complying with Apple’s rigorous approval standards.”

Use Cases

Manufacturers or distributors who want to improve their customer experience and better enable their direct and channel teams to serve the customer would benefit from the InsiteCommerce Mobile App, Daudt said.

“For B2B companies, much of their customer and team experience is in the field, out at a job site, or traveling through a sales territory,” she noted. “They need key data available to them and easy to use in their moment of relevance, across any mobile device.”

Among the possible use cases for the Insite Mobile App, according to Daudt, are the following:

  • Direct sales reps in the field needing to look up end-customer order or delivery details or other information, or place an order on a customer’s behalf;
  • Direct service technicians in the field needing to look up a detailed product tech spec or order a replacement part; and
  • Direct shipping clerks or delivery drivers taking a picture of a shipment at the outbound dock or upon delivery to the customer, and attaching it to the order as proof of delivery.

The InsiteCommerce Mobile App “may be attractive for existing Insite customers,” said Rebecca Wettemann, VP of research at Nucleus Research.

However, “I don’t see a broader reach than that,” she told CRM Buyer. “Unless I’m a frequent purchaser from a vendor, I’m unlikely to download their app.”
end enn New Mobile App Promises Full B2B E Commerce Experience

Richard%20Adhikari New Mobile App Promises Full B2B E Commerce ExperienceRichard Adhikari has been an ECT News Network reporter since 2008. His areas of focus include cybersecurity, mobile technologies, CRM, databases, software development, mainframe and mid-range computing, and application development. He has written and edited for numerous publications, including Information Week and Computerworld. He is the author of two books on client/server technology.
Email Richard.

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Leading with Customer Experience, Value, Technology, and Credibility

rsz bigstock golden trophy cup on table 155670149 1 Leading with Customer Experience, Value, Technology, and Credibility

When I was an industry analyst, I always felt that the most enlightening and valuable research came from first hand, end user feedback. Who better to hear from than practicing professionals doing real world work? Pleasing customers with enterprise software isn’t for the faint of heart and if you really want unvarnished insights, end users should be the core of your critical feedback loop.

It’s for this reason the team at TIBCO is so excited to see the results of The Wisdom of Crowds® Business Intelligence and Enterprise Planning Market Studies delivered by Dresner Advisory Services, LLC. This research speaks directly to the end user community on a wide variety of categories to unearth a complete view of market realities, plans, and perceptions from users in all roles and across industries.

This month Dresner Advisory Services announced its 2017 Industry Excellence Awards based on high vendor ratings in their most recent research. TIBCO Spotfire achieved awards as a Customer Experience Leader and a Value Leader, while TIBCO Statistica received the Technology Leader and Credibility Leader awards. Both solutions were acknowledged for their overall strength in sales, support, consulting services, and more. Vendors who are awarded Customer Experience and Technology leaders are executing at a high level for sales and service, as well as product and technology. Credibility and Value leaders have customers who reflect a high level of confidence and sense of value for the price paid.

Dresner’s Wisdom of Crowds research started in 2010 and dives deep when appraising vendors performance by tracking 33 different criteria across 7 topic areas that include, Sales Experience, Value for Price Paid, Technology/Product, Technical Support, Consulting Services, Customer Recommendation, and Vendor Integrity.

The Wisdom of Crowds research examines the details of our industry and surfaces positive trends that point to great progress for Business Intelligence and Analytic consumers. When reviewing the the Value dimension of the Dresner report a positive trend emerges: Since 2012, respondents to the survey are scoring the vendors with progressively higher value scores year over year. Keeping up with this competitive landscape puts pressure on solution providers, making it harder to compete and in the case of Spotfire even more satisfying to be among the leaders in this area.

Dresner tracks 12 different criteria to score product quality and usefulness, which includes robustness/sophistication of technology, completeness of functionality, reliability of technology, scalability, integration of components within product, integration with third-party technologies, overall usability, ease of installation, ease of administration, customization and extensibility, online training, forums and documentation, and ease of upgrades and migration to new versions. All saw increases in 2017 except ease of upgrades again. This trend points to increased competition and maturity in the market, making it more difficult to rise to leadership positions in the research.

The vendor credibility model employed by Dresner combines the value for price paid as scored by the user along with a vendor’s integrity score (honesty and truthfulness in all dealings) and recommendation score (customers willingness to recommend the vendor) to create an overall confidence dimension. The value and confidence dimensions position where a vendor is placed in the overall rankings. TIBCO Statistica placement among credibility leaders is an award to be proud of considering the competition and the scoring criteria.

The 2017 Industry Excellence Awards speak highly of TIBCO’s analytic strategy and our Connected Intelligence approach to digital transformation. To differentiate and maintain competitive advantage, smart companies should rely on solutions that lead in Customer Experience, Value, Technology, and Credibility.

Read more about the 2017 Excellence Awards here.

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Xiaomi Opens First Offline Experience Store In Northwestern China

Xiaomi’s first offline experience store in the northwestern region of China opened in Wangfujing Outlets, Hohhot, Inner Mongolia.

On the first day of the opening of this new store, it welcomed 12,000 customers and realized sales of CNY596,000.

This is the eighth store under the cooperation between Wangfujing Group and Xiaomi and it is also the first Xiaomi store that opens in Wangfujing Outlets.

With an operating area of 215 square meters, the new store includes a 125-square-meter customer experience zone, a 50-square-meter product sales zone, and a rest area. Products displayed in the store include Xiaomi’s smartphones, laptops, home appliances, and electronic product accessories.

Yang Haiyan, general manager of Hohhot Wangfujing Outlets, said that the arrival of Xiaomi further improves the brand quality of Hohhot Wangfujing Outlets and expands their category operating models. The emerging Internet electronic products will offer better shopping experience to local consumers.

So far, Wangfujing Group has become the largest commercial group partner of Xiaomi. During the first half of 2017, Xiaomi stores opened in Wangfujing achieved accumulated sales of CNY150 million and the sales expect to reach nearly CNY400 million for the entire year.

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An Inside-Out Approach to ERP can Deliver a Modern Customer Experience

websitelogo An Inside Out Approach to ERP can Deliver a Modern Customer Experience

Posted by Anand Misra, Principal Product Marketing Manager

For businesses today still running siloed, departmental solutions of yesterday, there are daily challenges meeting the needs of the modern consumer. The answer for many is to turn their ERP system inside out.

Consumers today have virtually unlimited options for researching and purchasing products, with online sales and new digital channels providing not only transparency into pricing but the actual shopping experience for millions of shoppers around the world. That ubiquity of information has raised expectations and most businesses are having a hard time delivering on.

A chief culprit for the challenge in delivering an omnichannel customer experience is the ERP system itself. Traditionally, ERP software was built to serve the needs of employees, not today’s consumers, let alone the partners and vendors that are a critical part of any modern enterprise. Today’s customers expect accurate inventory information, cross-channel order history and flawless order execution. These are inherently difficult for the legacy ERP systems from the ‘90s that too many businesses are still running on today. Those systems were designed around departmental processes, rather than around the customer and many of the newer versions of those older systems struggle to cast of the legacy of their origins. When the internet emerged with new platforms to transform the way companies deliver product support and information to customers, most companies just began bolting on ecommerce and content management systems that were disconnected from the system of record. To this day, customer data is still spread across CRM, ecommerce, marketing and multiple systems of record, making it near impossible to reward the most profitable customers, predict demand or ensure repeat business.

The answer for many is to spend hundreds of thousands of dollars trying to integrate these separate systems to support their omnichannel ambitions. The results are mixed, with integrations breaking with software upgrades, a lack of real-time visibility as data transfers are done in batches and companies still left with software designed to support employees rather than customers.

These companies fail to realize the depth to which the need to redesign their core infrastructure. Every aspect of this infrastructure needs to be evaluated to design around a customer-centric model from the beginning. They need to turn the ERP system inside out with the explicit goal of improving the customer experience.

Companies that orient around their customers and directly connect demand to a digitally-enabled supple chain will be the long-term winners. Amazon, the prime example, has built its infrastructure to take advantage of global product and price transparency, even dynamically pricing versus competitors.

Today, a company no longer needs to physically own a product to sell it on its website. If a retailer knows a vendor has inventory, it can take the order without ever possessing the product. And beyond supply chain efficiencies, there was incredible efficiency from operating at scale. As the businesses grow, the incremental costs associated with demand could be handled with far fewer employees and far lower inventory costs.

Newer companies that built (or rebuilt) from the ground up with ecommerce and a digital supply chain reap significant advantages:

  • Visibility into supplier and manufacturer inventory.
  • Responsive, consistently excellent customer service.
  • The ability to track and evaluate customer buying histories, behaviors and preferences.
  • Customer profiling and product recommendations for better targeting.
  • Customer self-service through low-cost online portals.

What started as a challenge for B2C companies is now manifesting in the B2B world. B2B customers that have seen the ease of use, visibility and real-time information provided in the B2C world, couple with a new generation of employees that knows no other way, are forcing B2B companies to reimagine their own processes.

Delivering the best customer experiences requires wholesale changes: in organizational structure, in culture and in IT systems. It requires a more modern infrastructure built around the customer. A modern infrastructure is an investment that will pay off in the years and decades to come. But finally, the ultimate goal is within reach: give customers a personalized, relevant and consistent experience across every channel.

For more on the power of building ERP around the customer, download the white paper Customer Commerce: Turning Your ERP Inside Out.

Learn how NetSuite helps create ubiquitous customer experience, helps differentiate your brand and exceed customer expectations: www.suitecommerce.com

Posted on Wed, August 16, 2017
by NetSuite filed under

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3 Ways Personalized Marketing Improves the Consumer Experience

blog title diverse personas 351x200 3 Ways Personalized Marketing Improves the Consumer Experience

For today’s marketers, personalization is no longer a fancy buzzword. It’s a necessary part of a robust marketing strategy.

Consumers expect custom, one-to-one content – regardless of the device or platform they choose to use at a particular moment. They’re looking to feel a real relationship with the companies and brands they engage with and they aren’t satisfied feeling like just a number. They demand to be treated as a valued individual.

Just how important is personalization? According to a report from Econsultancy, 48% of marketers strongly agree that their growth depends on personalizing the consumer’s experience. On the other hand, only 35% of consumers say that communications from their companies are usually relevant. Therefore, opportunities are plentiful for those marketers looking to bridge that gap.

The best marketers are constantly searching for new and innovative ways to engage their audiences, which ultimately results in conversions and expansions to their bottom lines. Personalization provides not only a way for marketers to improve the overall consumer journey and experience, but to truly add value in the process. All the while these strategies are building the ever-important strong, lasting relationships with each customer.

This personal touch must remain at the heart of almost everything marketers do. As readers of this blog know, consumer experience is considered the next new market differentiator. For a brand to provide the best of the best experience, customized engagement needs to be a key player in the game plan. While personalizing emails is still one of the strongest strategies, there are quite a few others. To start, here are three ways personalized marketing efforts can improve the overall customer journey.

1. Personalized Marketing Based on Geography and Behavioral Data

The digital world is bringing people closer and closer each day. That provides an extremely large amount of data that marketers can analyze and utilize. By simply keeping each individual network at the forefront when developing tactics, marketers can easily reach targeted audience groups. By segmenting according to time zones or by individual behaviors, marketers can better provide content at a time when consumers are going to see it.

For example, one consumer may continuously check email on the train en route to work in the morning; another may check social media on the way home, as a way to unwind. By tracking this data, marketers can tailor their efforts to the time zone and geographical location of each recipient. They then can create and issue more relevant material. That will in turn direct content through a more personalized approach, allowing marketers to show they are not only paying attention to their customers’ locations and preferences, but are also willing to work to improve the consumer experience.

2. Providing Personalized Product Recommendations

Finding ways to further personalize content can be challenging. However, new marketing technology tracks what and when the consumer is purchasing, as well as where they are browsing. These statistics can allow marketers to determine, based on historical data, what products are the most relevant to the consumer, as well as indicate which products, services, or other offers or information will bring about a higher conversion rate.

More importantly, when a consumer opens an email or a social media account and is served with information that resonates with them, they feel increasingly connected to the company. That creates a warmer, more one-to-one consumer experience that they will likely want to have again.

3. Working within the Consumer’s Preferred Channel and Device

Some consumers favor email. Others are more inclined to be social media savvy. And still others like to be targeted via SMS. Today’s customers also use a variety of devices. By paying attention to what people best engage with, marketers know which channels and devices to target.

If a consumer is a mobile-first or mobile-only user, marketers should naturally tailor their marketing tactics toward mobile. By paying attention to where consumers are, companies can better personalize their messaging and reach people where they prefer, creating a better overall consumer experience.

Ready for Advanced Personalized Marketing?

Marketers are inundated with new, highly innovative technology each and every day. It has certainly allowed for greater personalization and a better consumer experience through the data tracking it provides. But only those marketers willing to engage with it can reap the benefits.

Certainly such target-specific labor can be challenging, but it’s also well worth the effort. In today’s competitive landscape, marketers must work to not only differentiate, but also to meet the expectations of consumers who now both want and expect to be treated as unique individuals.

Knowing how personalized marketing can help boost brands is only half the battle. The next step is learning how to implement targeted strategies. Luckily, Act-On has that covered, too.

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Regina Andrew Design Overhauls Its B2B Ecommerce Experience with NetSuite

Posted by Maggie Miller, Senior Commerce Content Manager

Regina%20Andrew Regina Andrew Design Overhauls Its B2B Ecommerce Experience with NetSuite

In 1997, husband and wife team Carla “Regina” Zajac and Jimi “Andrew” Slaven turned their passion for art into Regina Andrew Design, a wholesale manufacturer specializing in lighting, furniture and other home décor. Running on siloed, legacy systems for years, the couple knew the company would ultimately need to improve its inventory management and streamline operations, while continuing to provide a best of class customer experience.

Regina Andrew Design chose the NetSuite unified cloud platform, replacing its legacy systems with NetSuite’s ERP, ecommerce, inventory and order management, CRM and WMS. The unified cloud-based solution allows the company to process orders faster, lower operational costs and deliver an engaging online experience for its B2B buyers.

Optimizing Inventory Management

One of the biggest challenges for the growing company was the inventory management of more than 1,000 SKUs that turn over 30 times a year.

“When we introduced new products it was a lot of manual work,” said James Bonomo, Chief Operating Officer. “Another major issue was that our old system lacked the ability to show real-time inventory data.”

Now that it has a single source of inventory data with NetSuite’s warehouse management solution, Regina Andrew Design has been able to better manage their inventory and increase warehouse efficiencies. An EDI SuiteApp solution from NetSuite partner SPS Commerce streamlines transactions with major retailers such as Neiman Marcus and Lamps Plus. 

B2B Functionality with a B2C Experience

With customers ranging in size from individual designers to large retailers, Regina Andrew Design looked to the website to better support its buyers. Leadership knew they needed to provide an online experience that felt like a B2C website, but with the added functionality B2B buyers need.

They replaced a Magento ecommerce site with NetSuite SuiteCommerce and saw sales increase in the first month. “It was like night and day,” said Bonomo. The new website displays detailed product information, images, related items and other product suggestions.

To support retail partners, the website provides a store locator for consumers interested in their products to search for retailers in their area. Bonomo also likes the integration with FedEx and UPS that offers real-time rates and allows customers to decide how they want orders shipped. With the previous system, it was limited to flat-rate percentages based on zones.

Once a buyer logs into the website they can see their account pricing, get real-time current and future inventory availability and place orders. Account management has also been streamlined. Clients can now view their account balances, apply credits and make payments to outstanding invoices.

Another new feature is the ability for designers to create project lists. Designers can easily manage multiple projects, add items appropriate for each project and purchase. With extensive product information and detailed images, designers can use the website as online tear sheets and even disable pricing information when presenting to clients.

Empowering Sales Representatives 

The SuiteCommerce website has also transformed the role of the sales representatives at Regina Andrew Design. Instead of taking and processing orders manually, sales representatives can focus time on value-add services and building brand loyalty.

“We can’t be everywhere,” said Bonomo. “The new website has empowered our customers and given them the opportunity to order 24/7 – when it’s convenient for them.”

With real-time visibility into what customers are buying, sales representatives can spend time understanding individual customer preferences and serve as more of a consultant to customers. This enables reps to suggest new products to customers that are similar to items they’ve previously purchased. Spending less time on administrative tasks also enables B2B sales reps to spend more time engaging with new buyers to increase awareness and sales of the brand.

“By implementing the NetSuite unified cloud-based system, we have lowered IT costs, streamlined our business and improved the customer experience,” said Bonomo.

Learn more about creating rich and engaging online experiences with SuiteCommerce.

Posted on Wed, June 14, 2017
by NetSuite filed under

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A Continuous Finance Experience

When the Netflix series House of Cards premiered in 2013, it quickly became the most downloaded content in the company’s history – a statistic that came as no surprise to Netflix executives. They had previously examined a vast pool of Netflix data on subscribers’ viewing habits and determined that the show was likely to become a hit even before they purchased it.

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The wisdom behind Netflix’s sure-fire choice came from machine learning, which, loosely defined, is the ability of computers to learn on their own (without being programmed) by using algorithms that churn through large quantities of data.

Machine learning’s talents aren’t limited to picking the next TV blockbuster, either. Consider some of the more down-to-earth uses that we already take for granted today. Have you noticed how spam e-mails have almost disappeared from your inbox? That’s machine learning. Or how you can casually converse with anthropomorphic voices coming from your smartphone? Also machine learning.

But these examples pale when compared to machine learning’s potential for remaking business. Increased data-processing power, the availability of Big Data, the Internet of Things, and improvements in algorithms are converging to power a renaissance in business intelligence.

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The untapped potential of machine learning

Here are some ways that machine learning could transform the core elements of the business ecosystem– and society:

Intelligent business processes. Many of today’s business processes are governed by rigid, software based rules. This rules-based approach is limited in its ability to tackle complex processes. Further, these processes often require employees to spend time on boring, highly repetitive work, such as checking invoices and travel expenses for accuracy or going through hundreds or thousands of résumés to fill a position. If we change the rules and let self-learning algorithms loose on the data, machine learning could reveal valuable new patterns and solutions that we never knew existed. Meanwhile, employees could be reassigned to more engaging and strategic tasks.

Intelligent infrastructure. Our economy depends on infrastructure, including energy, logistics, and IT, as well as on services that support society, such as education and healthcare. But we seem to have reached an efficiency plateau in these areas. Machine learning has the potential to discover new signals in the data that could allow for continuous improvement of complex and fast-changing systems. That gives humans more time to apply their creativity (something that machines may never learn to duplicate) to new discoveries and innovation.

Digital assistants and bots. Recent advances in machine learning technology suggest a future in which robots, machines, and devices running on self-learning algorithms will operate much more independently than they do now. They may come to their own conclusions within certain parameters, adapt their behavior to different situations, and interact with humans much more closely. Our devices – already able to react to our voices – will become more interactive, continuously learning assistants to help us with our daily business routines, such as scheduling meetings, translating documents, or analyzing text and data.

Plan for change

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Although machine learning has already matured to the point where it should be a vital part of organizations’ strategic planning, several factors could limit its progress if leaders don’t plan carefully. These limitations include the quality of data, the abilities of human programmers, and cultural resistance to new ways of working with machines. However, the question is when, not if, today’s data analysis methods become quaint relics of earlier times. This is why organizations must begin experimenting with machine learning now and take the necessary steps to prepare for its widespread use over the coming years.

What is driving this inexorable march toward a world that was largely constrained to cheesy sci-fi novels just a few decades ago? Advances in artificial intelligence, of which machine learning is a subset, have a lot to do with it. AI is based on the idea that even if machines can’t (yet) duplicate the actual structures and thought patterns of the human brain itself, they can at least offer a rough approximation of important functions, such as learning, reasoning, and problem solving.

AI has been around since the 1950s, but it didn’t take off until the late 1990s, when Moore’s Law’s true exponential effects on computing power were realized, and researchers reined in their impulses to build a mechanized brain, focusing instead on using algorithms and machine learning to solve specific problems. Highly publicized machine-learning triumphs by IBM, such as Watson’s drubbing of human contestants on Jeopardy, captured the imagination of the public and business leaders.

Machine learning comes in several flavors, sometimes referred to as supervised learning  (the algorithm is trained using examples where the input data and the correct answers are known), unsupervised learning (the algorithm must discover patterns in the data on its own), and reinforced learning  (the algorithm is rewarded or penalized for the actions it takes based on trial and error). In each case, the machine can learn from data – both structured (such as data in fields in a spreadsheet or database) and, increasingly, unstructured (such as e-mails or social media posts) – without explicitly being programmed to do so, absorbing new behaviors and functions over time.

Machines’ ability to learn puts them on an evolutionary path not unlike our own. They are gaining the ability to speak, listen, see, read, understand, and interact with ever-increasing sophistication. In just the last four years, the error rate in machine-learning–driven image recognition, for example, has fallen dramatically to near zero– practically to human performance levels.

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Machine learning as collaborator

As machine-learning–based skills approach those of human beings, it’s tempting to view their evolution as a zero-sum competition with humans that we are destined to lose.

However, there is another view that says that automation will lead more to collaboration rather than outright replacement. Consulting firm McKinsey & Company argues that while 49% of jobs will be subject to some degree of automation, just 5% will be fully replaced anytime soon. In most cases, says McKinsey, automation will take over specific tasks rather than entire jobs.

McKinsey’s argument is compelling, at least when it comes to knowledge work, because it mirrors the way computing has evolved within the organization. Early mainframes were programmed to perform specific tasks, such as tallying up an organization’s daily receipts. When PCs were first introduced in the 1980s, they were dismissed by businesses as expensive typewriters until packaged spreadsheet software came along, allowing organizations to automate some of their manual accounting tasks at the individual employee level. Knowledge work would never be the same.

Today, most organizations have enterprise software that uses rules-based processing to automate many tasks in departments such as finance and human resources and in warehouses. Yet while the task-based automation of enterprise software has brought tremendous productivity improvements, the software could not learn and improve with experience as humans can.

Until now.

Thanks to advances in computer processing power, memory, storage, and data tools, machine learning can be integrated into the enterprise-software systems that form the heart of most organizational IT infrastructures. This means that the software, using the mastery that it develops in individual tasks, will be able to contribute increasing levels of performance and productivity to the organization over time, rather than merely offering a one-time boost, as most software packages do today.

The strength of machine-learning integration

The improvements the software brings to organizations will not be limited to individual tasks. One of the biggest strengths of enterprise software is its integration– the ability of individual applications to share information and be part of process workflows both within individual departments and across the organization. Integration allows organizations to experiment with new combinations of ever-more intelligent and versatile machine-learning applications and, where possible, let the machines learn how to improve the ways they work with each other and with their human colleagues. Together, these applications form the intelligent enterprise.

Just as individual applications will contribute more productivity to the organization as their embedded machine-learning abilities become more sophisticated, so too will the combinations of those applications evolve to bring more intelligence and flexibility to departmental and organizational processes over time.

Here are some concrete examples of how machine learning is creating value in organizations today:

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Personalized customer service. Organizations can use machine-learning to improve customer service while lowering costs by combining natural-language processing, historical customer service data, and algorithms that continuously learn from interactions. Customers can ask the system questions and get accurate answers, lowering response times and allowing human customer service representatives to focus on higher-priority or more-complex interactions.

Financial-exception handling.
A machine-learning system can be trained to recognize payments that arrive without an order number and match them to invoices based on knowledge of customers’ order and payment histories. This lets organizations reduce the amount of work outsourced to service centers and frees up finance staff to focus on more strategic tasks.

Improved hiring.
A machine-learning system can learn to pluck the most suitable job candidates from the thousands of résumés that organizations receive. It can also spot biased language in job descriptions that might discourage qualified people from applying and rescue other top candidates who fall through the cracks because they don’t fit with traditional hiring models.

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Algorithmic security.
By building models based on historical transactions, social network information, and other external sources of data, machine-learning algorithms can use pattern recognition to automatically spot anomalies. This identification helps detect and prevent fraudulent transactions in real time, even for previously unknown types of fraud. And this type of algorithmic security is applicable to a wide range of other situations, including computer hacking and cybersecurity.

Image-based procurement. Instead of having to log into a procurement system and search manually, employees can simply use a smartphone app to snap a picture of the item they’re looking for– a particular brand and type of laptop, for example– and the system will use machine learning to hunt through its database to find a match or the nearest equivalent. It will then send a message to the employee, who can launch the ordering process with a single click.

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Brand-exposure measurement. Brands spend billions on sponsorships, often without knowing exactly what they are getting for their money. A machine-learning application can sort through thousands of hours of sports video footage or track the action in real time, for example, to tell marketers how often their logo appears on screen, how large it is, how long it appears, and where it is located on the screen. Brands can then quantify their return on investment in the moment.

Contextual concierge.
Let’s say that your flight is suddenly delayed. A travel app on your smartphone can use context-sensitive machine learning to determine how this delay will affect your other travel plans and prompt you with rescheduling options.

Visual shelf management. Employees can take photos of shelves in a store aisle, kicking off a machine-learning process that automatically senses missing or improperly displayed items and prompts the store manager and the warehouse to fill the shelves correctly.

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Manufacturing quality control. By examining video of an assembly line, a machine-learning system can spot defects that a human might miss and automatically reroute the damaged parts or assemblies before products leave the factory.

Drone- and satellite-based inspection. A machine-learning system can sift through thousands of aerial images
of a pipeline, for example, and automatically spot areas that need maintenance or replacement.

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Machine learning needs a platform

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To be sure, organizations will gain tremendous benefits from individual machine-learning applications, even if they are never integrated into a larger whole. However, the benefits become much greater when these applications are on an integrated platform.

The business press has been discussing the power of platforms a lot lately, with iTunes being a well-known example. By creating a set of common software development tools that are available free to anyone who wants them, Apple has enabled developers to create thousands of applications for the iTunes App Store. Developers win because they can easily reach vast numbers of Apple device owners through iTunes. Apple wins because it takes a cut of the revenues for each app it makes available in the App Store.

Platforms are equally important to enterprises, not necessarily because of the profit motive (though some organizations are launching their own public, for-profit platforms similar to iTunes), but because having a platform gives them a base for quickly and cost-effectively combining different applications together, whether they are from different software vendors or are built in house.

No software vendor will ever be able to claim that it offers every machine-learning–enabled application that an organization needs out of the box. But vendors do offer platforms that organizations can use as bases for building out their entire machine-learning infrastructure.

The core of these machine-learning–enabled platforms is application programming interfaces (APIs). APIs are a kind of software version of those universal electric plug adapters that business travelers lug around with them so they can charge their electronic devices wherever they may be in the world. APIs allow software developers to plug into another software vendor’s applications without having to know anything about the complex code at the heart of those applications.

Another benefit of having a unified software platform is that organizations can use it to create a single point of access to data from across the organization. Data is the sole nutrient in a machine-learning diet. Algorithms need to binge on it constantly to lead a healthy and successful life. The larger and richer the data set, the more accurate the results. Having a single platform helps break down the data silos that exist across the organization so that organizations can make the most of machine-learning intelligence.

Organizations don’t need to go it alone

Inevitably, organizations will want to develop machine-learning–based applications that are not available in the marketplace. However, this does not mean that they need to create large internal machine-learning centers of expertise (although having some internal experts is recommended). Service providers can bring the expertise and perspective from within and across industries to help organizations focus on a small set of highly strategic processes that will benefit from machine learning.

The first step toward developing such applications is to determine where to apply machine learning. Organizations need to ensure that it erects barriers to entry against competitors or provides new ways of capturing and retaining customers by improving repurchase cycles or achieving new levels of win rates.

That means focusing investments on the machine-learning problems that will matter most to the industry’s basic competitive economics. Developing those engines will take considerable effort and time, so focusing the enterprise on those one or two projects that will really make a difference matters.

Here are five criteria to determine how to apply machine learning in a way that will create lasting differentiation.

1. The focus area as an appropriate candidate.

Not every facet of business will benefit from machine learning. The greatest potential is in automating high-volume tasks that have complex rules and large amounts of unstructured data.

Is your focus area big and complex enough for machine learning?

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2. A clearly formulated issue. Machine learning works best on specific, well-defined tasks where the desired output and relevant inputs can be clearly stated: given X, predict Y. While it isn’t a magic bullet that will automatically help organizations learn from all the data in their enterprise, machine learning can be valuable in discovering correlations in large amounts of data that humans could never have deduced for themselves.

3. A sufficient quantity of examples to learn from. Machine learning requires a lot of data to be accurate. There must be enough examples for the machine to learn meaningful approximations of the decisions you want to make. This is discovered through experimentation.

4. Meaningful differences within the dataset. If the data you are trying to learn from does not contain meaningful differences, then the algorithm will fail at its mission. Let’s say that you are trying to identify different types of buyers. If the training data does not contain significant differences in buyer characteristics, the algorithm cannot give you useful results.

5. A clear definition of success. Machine learning is always evaluated by measures of performance on a specific task. Typically, the computer will try to optimize whatever performance measure is defined. Clear evaluation criteria for the algorithm are therefore critical. You also need to be certain that the evaluation criteria are actually helpful for solving your business problem.

Key evaluation criteria for machine learning

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The human factor

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Ultimately, the technical barriers to machine-learning adoption will be easier to solve than the human ones. Predictions of steep job losses due to automation are stoking fear and uncertainty about how these self-learning systems will impact our roles and our livelihoods.

These fears must be addressed, and significant investment must be made in change management as business processes and models are reworked to integrate self-learning systems into collaborative human-machine environments.

Indeed, self-learning machines have the potential to become valuable collaborators with humans, augmenting their skills and helping employees become more productive in their current jobs while freeing them from boring, repetitive tasks.

Experts also predict that machine learning will create new roles inside the organization. There is already a shortage of data analysts and those capable of developing the intricate algorithms that machine learning requires. Other new roles will become evident as machine learning integrates deeper into the organization – and not all roles will require a degree in computer science or math. For example, creative thinking, strategy development, quality management, and people development and coaching will be crucial skills in an AI-driven organization, according to a survey by consulting firm Accenture2.

What’s next

When machine learning matures to the point that it can handle unstructured data (still an issue today), when organizations openly share data, and when algorithms begin to interact with each other more freely, machine learning will be embedded in all systems, devices, machines, and software. That will enable highly context-sensitive insight at both the organizational and individual levels. We can only guess at the level of automation that will result, but the impact on business – and society – will be significant.

Already, commercial machine-learning applications based on these technologies are available, and more are being created all the time. That is why business leaders should engage now with trusted providers that can help them evaluate data structures and availability, free up information from siloed systems, and identify the richest areas for machine-fueled insight and improvement. Together, they can address the cultural and change management challenges to take advantage of this new wave of business intelligence.

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Download the white paper Why Machine Learning and Why Now?

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Daniel Wellers is Digital Futures Lead, Thought Leadership Marketing, at SAP.

Jeff Woods is Vice President, Marketing Strategy and Head of Thought Leadership Marketing at SAP.

Dirk Jendroska is Head of Machine Learning Strategy and Operations, SAP Innovation Center Network, at SAP.

Christopher Koch is Director, Thought Leadership Marketing, at SAP.


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