Brite Conference 2013: Brands, Innovation, Technology - Pt 1

Luisa Ruppert

Last week I had the pleasure of attending Columbia Business School’s Brite Conference around Brands, Innovation, and Technology with representatives of the school as well as well-known brands such as Intel, Vimeo, PepsiCo, SAP and more.

What follows is an overview of the Day One Agenda:

The Content Imperative

After a warm welcoming from Dean Prof. Glenn Hubbard we enjoyed the first talk of the day: Steve Rubel, SVP of Global Strategy and Insights of public relation’s firm Edelman spread awareness about the importance of content.

Issues of valuable content creation include that there is “too much content and not enough time” to read or share it all. Nodding heads in the audience. Underlined was this statement by the difference between “news we read and news we say we read”. Content does not always have to be self-created and the Associated Press leads the example when they opened up their Twitter feed for promoted tweets.

Companies should not be afraid or ashamed of ‘paid content’, just the contrary. Paid content is all about syndication, integration which leads into product placements leveraging services like Buzzfeed as well as co-creation of content through sponsorships. “Content is no longer optional – it’s imperative and it will become the primary way we advertise” which is why we still need our media agencies to ensure reach and trust of content as we face, from a messaging mindset, a “media advertising shift to an editorial”.

Innovating Media Models for a Mobile Consumer

Next up was Liz Schimel from the Meredith National Media Group was joined by Ava Seave from the Quantum Media Group to discuss ‘Innovating Media Models for a Mobile Consumer’. Liz stated that in her company they don’t see any decrease in print but an increase in digital media popularity which might come as a surprise to some publishers. She pointed out the importance of SEO in content creation and that pictures and videos are extremely important in mobile advertising to attract consumers’ attention.

That was followed by a recommendation for an across-platform approach with both traditional and digital media: “Creativity through collaboration” is what counts. In relation to content creation the statement was clear: “Brands are becoming publishers themselves”. Liz furthermore recommends an integrated approach to content creation for innovation: Mobile, print, and digital.

The Truth about Mobile Advertising: Does it even work?

The third presentation and last before the first networking break was the business school’s own Prof Miklos Sarvary who shed light on the truth about mobile advertising. His very university-like talk was filled with insightful results of his recent research and working paper ‘A Field Study of Mobile Display Advertising Effects on Consumer Attitudes and Intentions’.

Not surprisingly he found that mobile ads have a higher CTA (call-to-action) but a five times lower conversion rate than on desktop as well as that the time spent surfing on mobile phones has increased four times in the past four years. An interview conducted just a few days before the conference can be found here.

Fun fact: North Korea is not spending significantly on mobile advertising; whereas the top spending countries are the UK, Norway, the US, Denmark, and Japan. Prof Sarvary concluded with the outcome that mobile ads work as memory cues, reminding the consumer of prior campaigns or info about products and work best for high-involvement, utilitarian products. But there is hope for hedonistic products using location-based mobile advertising, the professor suggests.

Using Gamification to Engineer a New Payment Economy

Michael Hagen self-appointed ‘Chief Rockstar’ of LevelUp, a mobile payments platform created by Cambridge-based start-up SCVNGR, enlightened the audience about how to use gamification in the new payment economy.

He drew attention to ‘Interchange Zero’ – and the cost of moving money: $50 billion equals 2-20% what it costs for a business when consumers pay with a card, the expense of interchange. ‘Interchange Zero’ is the theory that the cost of moving money (credit card fees) converges to zero over time. Michael’s idea is that companies like DwollaISIS, LevelUp, Google Wallet, and Square are disrupting cost of commerce via mobile tech: Mobile phone > wallet; which means an increased competition and incentivized consumers to use alternative payment forms.

Although some attendees were complaining on Twitter about the missing connection to games I understood that the motivating factors for alternative forms of payment came from games like World of Warcraft. One example for that is the app Scoutmob that proved if a coupon is waiting for a consumer they are more likely to spend four times as much at the restaurant. The three gamification techniques introduced were:

  • Sunken reward + transactions = Scoutmob
  • Progression dynamics + transactions = Punch card
  • Transactions + game mechanics = New money

In conclusion the future of mobile advertising lies in appointment dynamics: Incentivize behavior via smart mobile prompt. An interesting question came up at the end on how to prevent the consumer from ‘gaming’ meaning taking advantage of special offers and no purchase otherwise.

Michael’s answer was that it depends on the design and strategy of those offers as well as segmentation (specialized targeting) of customers: “Know your customers.” Sometimes offers can be non-money but aimed at prestige such as an occasional free upgrade when purchasing the platinum membership.

How Brick and Mortar Can Leverage the Mobile Future

Next was a panel by Rick Ferguson of Aimia and the business school’s Matthew Quint about how brick and mortar can leverage the mobile future. A study confirms 21% of consumers have used their mobile phone while physically shopping at a store. It is mostly used to retrieve information and advice like price comparisons and reviews.

The good news is that 58% purchase in-store even if they find it cheaper online. Most likely due to excellent customer service, my opinion, and well-designed loyalty programs are a reason, too. A conclusive advice was to train employees on mobile assisting not to ask customers to leave if they compare prices in-store.

One of the attendees told about an incident with Pearle Vision in Brooklyn where she was asked to leave the store after taking pictures of the products. This, of course, caused a huge uproar in the conference’s Twittersphere however it was promptly met by an apology by the optometrist on Twitter and the customer was promised that her complaint will be forwarded to the store management and operations team. Well done, Pearle Vision!

Interactive Workshop: Strategic Planning for Social Media Marketing

Just before lunch Ric Dragon from DragonSearch started his interactive workshop about strategic planning for social media marketing. He presented his framework of social media management strategies recommended:

  • Brand Maintenance
  • Community Building
  • Influencer Marketing
  • Thought Leadership
  • Big Splash

Read about those in detail here. He also spoke about a brand persona study, which showed that people project personas onto brands and it’s the marketers’ job to shape that perception. Google was the hip, young Asian guy, Starbucks the soccer Mom and BP a grumpy old man. For live, realtime mindmapping Ric used the tool mindmeister to involve the audience interactively.

Some more advice for a company’s social media strategy plan was to use keywords, pathways to other websites to discover communities to add to extend reach. That is one of the reasons why the job of the community manager is the hottest of the year, says Ric. His four stages of social media activity types are: 1. build digital real estate 2. make connections 3. create content and 4. engagement .

Lastly, but not least, he suggests that we should move from one-way storytelling to dynamic storytelling and referenced Coca-Cola’s Jonathan Mildenhall and his Coca-Cola Content 2020 Project as a best practice. Coca-Cola says that through dynamic storytelling they will double their revenue by 2020. All the templates that Ric used during his talk can be found here.

Creating a Culture of Rapid Experimentation

Next up after lunch was Kaaren Hanson from Intuit about creating a culture of rapid experimentation. We live in a new age of culture where you are constantly trying to learn new ideas shortening the cycle of discovery. Kaaren’s advice is to “fall in love with the solution not the problem”. Keeping an open mind to multiple ideas is key for innovating.

Bring in your customers early in the process to drive innovation. Listen to the customer! And experimentation keeps your employees engaged and feel valued which ultimately impacts revenue. She showcased an example of how rapid experimentation helped farmers in India to find best prices for their crops. Intuit as doubled down on rapid experiments in last two years from a handful of experiments to 1300+ today.

In order to drive innovation Kaaren uses only small teams: “If you need more than two pizzas to feed a team, it is too large.”  And her last piece of advice: “Risk of not starting to experiment is much greater than risk that might come from experimenting.”

Can Live Music Be Like My iPod?

This was followed by a most welcomed musical interlude by Shuffle Concert. The seven head ensemble plays what the audience chooses, like the shuffle function on music players. “From Baroque, Classical and Romantic to Jazz, Pop and Broadway, SHUFFLE Concert performances offer an exciting fusion of great music, for every musical taste.”

Beat the Back Button: How Obama, Disney, and Crate & Barrel use A/B Testing to Win

Pete Koomen, co-founder and president of Optimizely, was the next on stage shedding light on how the Obama campaign, Disney and Crate & Barrel profited from A/B testing. He started with showing the audience how important it is to choose the right email subject line. Here are his six tips:

  • Define quantifiable success matrix and have your team agree on what success means
  • Explore before you refine. If you start & refine, you may miss best option.
  • Less is more. Reduce choice. Sometimes the most successful experiments involve taking things off of a web page.
  • Words matter. Focus on your CTA (call-to-action). Rule: At some point any change results in improvement.
  • Fail fast, e.g. Crate & Barrel found adding star ratings on their website decreased conversions.
  • Start today, it’s never too late to start testing.

Examples from the Obama campaign followed. The word ‘Hey’ was the most effective in the subject line of the fundraising campaign. A picture of a family and a ‘Learn more’ button drove the most traffic.

The results of testing buttons and media led the Obama campaign to a 40% increase in email sign ups. Surprising to most of the audience was that images had a better result than videos probably due to longer loading times and that audio requires loudspeakers or headset. The example from Disney was that after removing images about a specific show on the ABC Family website engagement increased 600%.

Also an interesting result from the 170,000 tests carried out is that the success of a CTA message depends on the customer’s status; prospects react differently than already loyal customers. That’s why segmentation is essential. Understand your audience and validate that!

The Power of (Big) Data in a Networked World

The succeeding speaker was the executive director of Brite himself, David Rogers, talking to us about the power of (big) data in a networked world. Big data for him consists of social data, mobile date and the Internet of things.

One example of how companies can benefit from analysing big data is Walmart; the supermarket is adapting their product display in accordance to weather analysis provided by the Weather Company. Another mentioned example is the US Center for Disease Control and Prevention that uses Twitter data to track the spread of the flu. David says that there are three ways to use big data: Insight, Innovation, and Strategy.

It’s not only big corporations benefiting from it but the common people as well: Watson, a soon to be released diagnostic tool app for doctors,  has now analysed two million research articles and 1.5 million patient records to make predictive recommendations for cancer patients.

David also assured that big data doesn’t make the human redundant: “To unleash power of big data we must combine data, tools, algorithms, and humans.” The big advantage of the human is still creativity and intuition which cannot (yet) be subsidised by computers. David’s slides can be found here.

The Century of the Asian Consumer

Bernd Schmitt from the Institute on Asian Consumer Insight started with telling us that the Asian consumer is the reference point for commerce and marketplace of the future. He specifically pointed out India, China, and south-east Asia where immense growth is occurring at lightning speed and by mid of this century China’s economy will be 2-3 times the size of the US’s. By 2020 54% of middle class consumers will live in Asia, brands should keep that in mind when thinking about message prioritization.

It is essential for companies to understand the diversity of the region, the similarity and differences of the Asian consumer due to the broad diversity and variety of cultures. Asian consumer behavior instead of the US one will dictate initial product and marketing decisions for major brands in the not so far future, Bernd said. Furthermore brands have to accept that the Asian consumer collective is directly related to family (India), friends, youth culture (South Korea), and nation (North Korea).

One example would be the one-child policy in China that makes it less collectively and as individual as American. Also the Asian landscape is changing for the future, leaning more towards a city mindset. Bernd reminded us that Asians love luxury brands but are also focused on value but at the same time not all Asians are the same, the general stereotype no longer exists due to globalisation.

If brands plan to expand their reach it is notable that a pan-Asian strategy will require a detailed assessment, market by market; with attention to those emerging. One advantage would be that English is official business language in most Asian countries and expanding. His final advice: Think global, act local!

Disrupting the Future: Is Higher Education #Over?

The last talk of Day One was by Sree Sreenivasan, Chief Digital Officer of Columbia University. He started off with encouraging us to “ABC – Always Be Collecting” and share as appropriate and recommended to use the Dark Sky app which uses state-of-the-art weather forecasting to predict when it will rain or snow to the min.

Furthermore he starts a tweet challenge telling attendees to mention everyone on Twitter he talks about. First one was Salman Kahn as Sree was introducing the topic with the Kahn Academy and its success of online education. It’s only one example of how MOOCs are destined to disrupt poverty with making education available to everyone (with Internet access). At Columbia it is also intended to be used for preparation of students for a more in-depth in-class lecture.

Some of the benefits of MOOCs he mentioned include: It provides experience with new learning platforms to benefit on-campus learning, brand-building for particular programs, and learning and retraining opportunities for alumni. He introduces three options for online learning: CourseraedX and Udacity. He quoted Prof Hitendra Wadhwa on online education: “Inspire, not just inform!” You can find his slides here.

And after some wine and networking a great first day ended. Up next, watch for Day Two at the Brite Conference 2013.

Follow the conference on Twitter @Briteconf and check out their Storify compilation.


About Luisa Ruppert

I am a recent graduate of International Management from Germany and have been working for SAP as an intern since April 2011 in Galway, Ireland and since March 2012 in New York. I am interested in social media, marketing, advertising, current affairs, technology news, politics and photography. In my spare time I love going to Broadway shows or a good movie as well as strolling around this exciting city.



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

Sundar Kamak

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

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

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

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

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

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

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

3. Collaboration comes in more than one flavor

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

4. Keeping product sustainability top of mind pays off

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

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

5. Co-marketing is a win-win

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

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

6. Suppliers get to choose their customers, too

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

7. Suppliers can help simplify operations

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

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

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

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

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

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

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


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

Scott Feldman and Puneet Suppal

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

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

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

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

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

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

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

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

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

It’s time to take action 

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

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

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



About Scott Feldman and Puneet Suppal

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

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

Erik Marcade and Fawn Fitter

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

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

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

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

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

Balancing Insight and Action

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

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

sap_Q216_digital_double_feature1_images5From Data Scarcity to a Glut

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

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

How to Train Your Algorithm 

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

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

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

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

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

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

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

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

From Waste to Gold

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

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

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

— Patrick Surry, chief data scientist, Hopper

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

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

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

Port of Hamburg Lets the Machines Untangle Complexity

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

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

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

Digitization Is Not Bounded by Industry

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

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

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

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

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

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

Pitfalls and Possibilities

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

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

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

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

sap_Q216_digital_double_feature1_images6The Risk Is Doing Nothing

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

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


Erik Marcade

About Erik Marcade

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


Strengthening Government Through Data Analytics

Dante Ricci

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

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

Governments move toward constituent-centered platforms

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

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

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

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

Predictive solutions that appear before your eyes

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

Putting it together

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

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

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

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

Are you ready for change?

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


About Dante Ricci

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