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JUN 2016

Data’s Big Promise:    


By Malgorzata "Gosia" Glinska Program Director, Global Innovators' Roundtable, Batten Institute

KEY INSIGHTS Know your purpose Connect data to strategy


here are many ways to think about the recent explosion of digital technolo-

gies and data. Not surprisingly, the ubiquity of personal information that can be easily and cheaply collected from online and offline transactions, social

media, and sensors embedded in a growing array of physical objects such as TVs and smartphones, can trigger excitement but also suspicion, anxiety, and fear.

Organizations that sweep up, store, and analyze that information are often unsure of how to use it.

The leaders of some of the world’s top firms who gathered for the spring 2016 Innovators’ Roundtable approach the vast quantities of structured and unstructured data—often called “big data”—as an opportunity to create value for their customers and, in the process, unlock new ways to grow their businesses.

Leverage text data for new product development

The roundtable, hosted by Darden’s Batten Institute for Entrepreneurship and Innova-

Augment objects with digital features

Capital One, Celgene, Corning, Danaher, Eastman Chemical, IBM, Recast Energy,

Rethink your business model Try customer-centric marketing Support data-driven decisionmaking Promote collaboration, creativity, and entrepreneurship

tion in Washington, DC, brought together senior leaders from 3M, Abundant Power, Siemens, and Smithfield.

Led by Darden professors Rajkumar Venkatesan, Yael Grushka-Cockayne, and

Edward D. Hess, the executives explored the use of data and analytics to make better

decisions, to lower costs, to predict and better meet customer needs, and to create innovative products, services, and business models. They also discussed the challenges their organizations and industries face as they become increasingly data driven.

This Batten Briefing examines several best practices that emerged from the daylong roundtable discussion.


Data, Data Everywhere:

THE NEW DRIVERS OF INNOVATION THE RECENT EXPLOSION of sensors, wireless connectivity, cloud computing, and

BIG DATA The term “big data” refers to structured and unstructured information flowing from inside and outside of companies that can be mined for insights. The size of the big-data data­ sets exceeds the ability of typical data infrastructures to capture, store, and analyze them and requires advanced

other digital technologies is generating unprecedented amounts of never-beforeavailable data.

Companies churn out vast quantities of transactional and consumption data, capturing information about their customers, suppliers, and operations. Physical objects, from wind turbines to jet engines, create their own massive data trails. And so do

billions of consumers everywhere, while they browse, search, communicate, buy, and share on social media platforms. All that data can be captured, transmitted, and stored at near-zero cost.1 It can also be mined for actionable insights.

technologies. Before the recent explo-

Democratization of Data

sion of digital technologies, companies

Not so long ago, only the pioneering companies such as Amazon, LinkedIn, and

used data and analytics mostly to improve internal business decisions. Today, big data is used primarily to create customer-facing products and services.


Google had access to what we now call big data. In the mid-2000s, they started

investing in analytics to develop data-driven, customer-facing products and services, like LinkedIn’s People You May Know and Jobs You May be Interested In, and Amazon’s targeted suggestions for things to buy.2

Creating new products and services based on data analysis is no longer the domain of large information firms and online retailers. Today, companies in every industry can—and should—capitalize on the potential of big data.

Historically, only a few organizations could leverage the capabilities of Global Positioning System (GPS). Now, it's in every phone and other wearables, empowering everyone in the same way to innovate based on GPS data.” Richard Williams, SVP and CIO, Celgene

What’s Driving This? The emergence of powerful, low-cost computer technology and advanced analytic

techniques is improving the means to glean insights from data at price points that

are a fraction of what they were only a few years ago. Open-source advanced analytical platforms and tools, such as Hadoop and NoSQL, are widely available. Conse-

quently, companies of all sizes either own or can access massive datasets, which they can analyze to create value. “They can access data anytime and anywhere and look for interesting consumer insights,” said Darden professor Rajkumar Venkatesan.

Data is also increasingly shared for collaboration with partners and customers. Inside large companies, data sharing happens across business functions. Increasingly, data

and analytic tools are no longer confined to the IT departments; they affect strategy, marketing, product development, and finance.3

All this creates unprecedented opportunities to innovate.



Data-Driven Innovation: START WITH THE QUESTION

DATA AND ANALYTICS ARE FAST BECOMING THE NEW BASIS of competitive advantage. Business leaders in all industries are trying to harness the power of data to

drive the development of breakthrough products and services, reveal hidden markets,

All innovation efforts should connect to the purpose of your company. Why do you innovate? Toward what end are you using data? Does it really serve your purpose?”

predict unmet needs, and spark other innovations.

There’s a good reason big data is all the rage; companies have never had this much

information about their customers, competitors, and markets. But big-data analysis is a relatively new field. The reality is that turning data into business insights poses huge challenges, the least of which are technological. The following best practices can help business leaders overcome barriers to success.

Know Your Purpose

Gertjan Bartlema, VP Corporate

It’s easy to get caught up in the hype surrounding the unprecedented volume of

Franchise Operations, Celgene

never-before-examined data and be dazzled by this “new, shiny thing,” as Will

Brunt, Senior Vice President of Marketing and Chief Innovation Officer, put it. “Too often, big data becomes the goal.”

Big data is certainly touted as a way to boost innovation. But before business leaders start capitalizing on the insights gleaned from the torrents of data they collect

and analyze—and before they innovate—they should have a clear understanding of the “why.” As Celgene’s VP of Corporate Franchise Operations, Gertjan Bartlema, noted, “All efforts should connect to the purpose of your company. Why do you

innovate? Toward what end are you using data? Does it really serve your purpose?” In other words, big data and analytics are most effective when they are tied to the company mission and meaningfully connected to strategy.

Celgene’s mission is to deliver innovative, life-changing drugs to its patients. Therefore, using data to, for example, dramatically cut drug-development time and cost makes perfect sense.


Freeland, C., et al. 2014. “Inequality, the Second Machine

Age and the 401(k) Society.” New Perspectives Quarterly. 31 (2): 74-77. 2

Davenport, Thomas, H. 2013. “Analytics 3.0.” Harvard

Business Review. 91 (12): 64-72. 3

Thomas H. Davenport. Big Data at Work: Dispelling the

Myths, Uncovering the Opportunities. Boston: Harvard Business Review Press, 2014. 4

Thomas H. Davenport. Big Data at Work.


Connect Data to Strategy HOW CAN COMPANIES BUILD A BRIDGE between data analysis and strategy?

Again, asking questions is a good place to start. “Having a healthy involvement of

analytics to not only answer the questions, but also at the stage of asking the ques-

tions, that’s when you can really influence strategy decisions with data,” said Darden professor Rajkumar Venkatesan. “People who know the context and the constraints

Having a healthy involvement of analytics to not only answer the questions, but also at the stage of asking the questions, that's when you can really influence strategy decisions with data.” Rajkumar Venkatesan, Darden School of Business

that their organizations face should be asking, ‘What are the questions that are really important to us? What do we want to know?’”

The next step involves understanding which items of data potentially contain the

answer. According to Venkatesan, this requires an iterative, experiment-driven culture. “You take a big problem and split it into smaller pieces,” he said. “You involve all stakeholders—operations, strategy, marketing—and decide what is the analysis you’re going to do in the next two weeks, what are the expected outputs, and then see what happens. Then you ask, what is the next experiment we need to do to go

forward? That back-and-forth allows different business functions to understand each other better.”

A large used-car retailer looking to change its pricing strategy is a case in point. Instead of adding a flat markup on all cars, the company wanted to change the

markup by the car model. “One thing they try to do is look at different car models and regions and see if they can implement this strategy,” said Venkatesan. Finance According to the 2016 international survey of senior innovation executives, BUSINESS LEADERS ARE INCREASINGLY RECOGNIZING THE STRATEGIC VALUE OF DATA AND ANALYTICS.


of U.S.­- based executives agreed

that using big data and analytics to improve strategic knowledge and inform decision-making is key to successful innovation. Source: GE Global Innovation Barometer 2016.

and marketing worked together to figure out the best markup for each car. Based

on the past internal data, they knew how long each car stayed in the lot. If it sold

immediately, then the markup was okay; if the price had to be reduced significantly

before the car sold, it meant that the markup was too high. Using data, the company ran fast experiments in two-week cycles in different markets to see which prices worked best.


Keeley, Larry, et al., Ten Types of Innovation: The Discipline of Building Breakthroughs. Hoboken: Wiley, 2013.


Redmore, Seth. 2015. "Start from the Question: A Guide to Unstructured Text Analysis." Business Intelligence

Journal. 20 (4): 20-27. 7

Zhenning, Xu, Gary L. Frankwick and Edward Ramirez. 2016. “Effects of Big Data Analytics and Traditional

Marketing Analytics on New Product Success: A Knowledge Fusion Perspective.” Journal of Business Research. 69 (5): 1562-1566. 8

Barbash, Fred. 2015. “Keurig's K-Cup Screw-up and how it K-pitulated to Angry Consumers.” The Washington Post.


Parmar, Rashik, et al. 2014. “The New Patterns of Innovation: How to Use Data to Drive Growth.” Harvard Business

Review. 92 (1/2): 86-95.






Wilson, H. James. 2015. “Information Technology (A Special Report).” The Wall Street Journal.

Leverage Text Data

FOR NEW PRODUCT DEVELOPMENT INNOVATION IS A RISKY BUSINESS. According to the Doblin Group, a staggering 95% of all innovation efforts fail to return cost of capital.5

In large consumer-goods and retail companies innovation seems to be dead. “They

don’t have the big hits these days,” said Venkatesan. “It all comes from small compa-

nies. To find those companies with cool new products and fund them or buy them as soon as possible, large firms need unstructured data.”

Unstructured text analysis, or text mining, can help large enterprises to not only

stay on top of new start-ups entering their markets to identify the best targets for acquisitions, but it can also help firms significantly increase the rate of success of their own product rollouts.

AUGMENT OBJECTS WITH DIGITAL FEATURES To gather even more data in a variety of contexts, companies are increasingly augmenting their products with sensors, microprocessors, and wireless connectivity. Companies can then use the data those objects generate to improve

You have to think outside of your own walls if you want to have more innovation. You have to find people who have an aligned interest in solving problems that are similar to your problems.” Jennifer Stewart, VP Corporate Innovation, Eastman Chemical

their products and services or to create new ones.9 For example, Progressive Insurance offers an innovative service called Snapshot, which uses a digitally enhanced device that plugs into the car and is capable of recording

In fast-moving industries and markets, new-product success requires a great deal of information from many stakeholders. Unstructured data coming from social media, e-mail, news, patents, and research papers can help companies listen to their customers, partners, and competitors.6

Analyzing data flowing from social media, for example, offers companies never-

before-available insights into customer preferences, needs, and behaviors. Product

managers can now access real-time information about people’s sentiments regarding their products. They can use that knowledge to modify new products fast, adding desirable features and removing the undesirable ones.7

A failure to develop a smart approach to external text data can have profound implications for new product success. Take Keurig, a company that used to dominate the single-serve coffee market. In 2014, Keurig launched a new coffee brewing system,

eliminating refillable K-cups and other desirable features, even though its customers had been vocal on social media about what they wanted.8 Text mining could have

helped the company develop a product precisely aligned with its customers’ needs and prevent a huge drop in sales.

mileage, night driving, and heavy breaking. Depending on how they drive, Snapshot users see the cost of their insurance go up or down.10 Progressive Insurance relies on Snapshot to capture driving behavior, determine customer risk profiles, and decide on competitive pricing. Another example is intelligent garments, like a hospital gown that is equipped with sensors that wirelessly monitor a patient’s blood pressure, temperature, and other information to provide more efficient care.11



products and services but also their business models. For example, firms that used

Your competitors today are not necessarily your threats. It’s important to realize that your threats in the digital world may be organizations that you least suspect. They’ll turn your model on its head.” Richard Williams, SVP and CIO,

to make money selling and servicing industrial equipment can now rethink their

customer value proposition. In addition to selling reliable jet engines, gas turbines, and medical equipment, they can offer customers all kinds of efficiencies and

performance improvements by combining data generated by that equipment with advanced analytics.

Take Siemens. The company’s industrial data analytics platform, Sinalytics, generates new value for its customers by predicting and preventing equipment faults, thereby

saving energy, reducing costs, and increasing operating efficiency. One of Siemens’s customers, a Spanish railway company, operates more than 20 Siemens high-speed trains. As a result of predictive maintenance, the trains running between Barcelona and Madrid have achieved a punctuality rate of 99.9%.


Disruptive technology can create new markets. Uber and Lyft combined mobile and cloud technology with data analytics and disrupted the cab industry.”


Victor Brown, Distinguished Engineer, Director, Office of the CTO, IBM

Digital Disruptors The new data-driven products and services can run the gamut from incremental improvements to game-changing, disruptive innovations.

79% Creating new business models

56% Developing new products and services

Source: 2014 IBM Innovation Survey.

In banking, for example, hundreds of data-driven start-ups using a smartphone platform are disrupting the traditional banking model, doing to banks what Uber did

to the taxi industry.12 While there is no one single disruptor, hundreds of start-ups

are unbundling banking by providing individual services such as loans, credit checks,

and wealth-management robo-advisors. Among popular providers are PayPal, Credit Karma, and Wealthfront. And new, disruptive payment technologies like Apple Pay

and Square are taking over lower-end banking transactions, causing an exodus from physical-branch transactions to mobile banking.13 12

Mathews, Simon. 2015. “The Uberization of Banking.” The Financial Brand.

uber-financial-services-banking-disruption/ (Accessed 23 May 2016) 13




Try Customer-Centric Marketing THE AVAILABILITY OF HIGHLY GRANULAR CUSTOMER DATA enables a marketing approach that focuses on the customer. Unlike channel- or product-centric market-

ing, the customer-centric approach strives to understand customers and their needs.

“It’s about ‘How does this product fit into our customers lives and how is it going to improve their lives?’” said Venkatesan.

Data is great, but you cannot make money off of it if there isn’t value for the customer. Go back to the marketing fundamentals: for whom and why? Based on that, you can offer valuable products and services that customers are willing to pay for.” Rajkumar Venkatesan, Darden School of Business

People want stuff to work. They don’t sit around thinking about their credit cards. They don’t want to be encumbered with messages that companies are sending them. They want to get what’s relevant to them, at the right time, without having to push a button.” Sherri Gilligan,

Having deep customer knowledge helps companies develop meaningful connections

SVP Card Marketing, Capital One

and improve customer experience, which results in higher customer engagement,

loyalty, and retention. It also drives sales by meeting the needs of consumers with

perfectly customized, relevant offers, and delivering them at the right place and the right time. Instead of flooding customers with lots of one-size-fits-all digital communications, customer-centric marketing uses fewer, more targeted messages.

As technology rapidly changes, so do customer expectations. Today’s customers want


and time. Having deep, meaningful, data-driven insights about customers can help


powerful services, delivered at the swipe of a smartphone screen, at the right place


companies do just that.


Today, technology offers companies direct access to customers and their preferences. The ease of data collection is shaping innovation, as hypotheses can be tested more efficiently and thoroughly than ever before.” Yael Grushka-Cockayne, Darden School of Business


agree that data-driven marketing is critical for the ability of companies to compete in the global economy


say that breaking down the silos of data between internal departments to ensure the flow of information is the biggest challenge to their data-driven marketing efforts.

Source: Alfieri, Paul. “Data Driven and Customer Centric: Marketers Turning Insights into Impact.” Forbes Insights, 2015.


Support Data-Driven Decision-Making IN ORDER TO FULLY CAPITALIZE ON BIG DATA, companies certainly need to

recruit and retain deep analytical talent. But they also need to adopt new approaches to decision-making and management.14 This may be easier said than done.

Executives still rely more on experience, intuition, and advice than data to make COMPANIES USING BIG DATA FOR INNOVATION ARE


more likely to beat the competition.

According to IBM’s 2014 innovation survey of more than a thousand business leaders, companies whose innovation processes are driven by data and analytics are 36% more likely to outperform their competitors in revenue growth and operating efficiency.

significant business decisions that have enormous impact on their organizations.

According to a recent survey conducted by the Economist Intelligence Unit, barely one-third of executives said they relied primarily on data and analytics when they made their last big decision.15

Organizations are not designed to be data driven yet. They have lots of data, but they don’t know how to leverage it.” Liu Qiao, Technical Director, Software, Electronics and Mechanical Systems Laboratory, 3M

Thanks to data and powerful analytics, business leaders can measure and know more about their businesses than ever before. This leads to better predictions and smarter

decisions.16 For example, using data to test different scenarios before making a deci-

Source: Marshall, Anthony, Stefan Mueck, and Rebecca Shockley, 2015. “How Leading Organizations Use Big Data and Analytics to Innovate.” Strategy & Leadership. 40 (5): 32-39.

sion makes perfect sense. But organizations trying to integrate data and analytics with decision-making face enormous cultural challenges and inertia.17

Executives who want to change the culture into one that is data driven should start by asking, “What does the data say?” and then follow with, “Where did the data

come from?” and “What kinds of analyses were conducted and how confident are we 14

McAfee, Andrew, and Erik Brynjolfsson. 2012. “Big Data:

The Management Revolution.” Harvard Business Review. 90 (10): 60-68. 15

DiFilippo, Don, and Paul Blase. 2014. “Gut & Gigabytes:

Capitalizing on the Art and Science of Decision Making.” PwC. 2014. (Accessed 23 May 2016) 16

McAfee, Andrew, and Erik Brynjolfsson. 2012.


Buluswar, Muruli, et al. 2016. “How Companies are Using

Big Data and Analytics.” McKinsey & Company. http:// (Accessed 23 May 2016)



McAfee, Andrew, and Erik Brynjolfsson. 2012.


DiFilippo, Don, and Paul Blase. 2014.


in the results?”18

As more companies are using data and analytics to make faster and better decisions,

business leaders should be aware of potential pitfalls. When it comes to big datasets, it is possible to find correlation between any pair of unrelated variables. Sometimes,

experts say, data needs to be ignored. Therefore, in order to makes sense of big datasets, expertise and experience will remain critical.19

Promote Collaboration, Creativity & Entrepreneurship BIG DATA IS FAST BECOMING THE NEW BASIS OF INNOVATION. But innovation is a messy process with uncertain outcomes, and it requires the right culture.

While start-ups, by their very nature, are innovative, large established corporations

that are good at strategy execution are notoriously bad at out-of-the-box thinking.

In a small organization, it is vital to have innovative ideas. However, as companies grow, it’s more difficult to innovate. That’s why large companies need to create pathways to promote innovation.”

Being a huge corporation is no excuse to be slow and not innovative. We have everything in place to encourage everybody to be innovative. It goes back to people management, empowerment, and respect for all ideas, no matter how crazy they are.”

Geneviève Ménard, SVP, Organizational Excellence, Celgene

Kurt D. Bettenhausen, SVP Corporate

They also are less agile than start-ups. Companies trying to leverage data and analytics to drive innovation should be able to quickly respond to data-driven insights. Therefore, leaders in large firms need to work hard to build an entrepreneurial culture that fosters agility and innovation.

Technology, Siemens For example, innovative organizations such as Siemens, IBM, and Capital One have specific mechanisms to promote collaboration, creativity, and entrepreneurship.

Siemens holds hackathons, where even the most junior employees win innovation awards. Respect for innovative ideas, however crazy they may seem, permeates its culture.

Capital One took steps to build an agile, entrepreneurial culture by creating small, five-to-eight-member squads that operate like mini start-ups. While the leaders

figure out which problems to solve, squads collaborate with each other to figure out the best solutions to those problems. Even though squads have a high degree of

decision-making autonomy, which is highly motivating, they are tightly aligned with Capital One’s mission.

And IBM has an internal crowdfunding mechanism to pitch and fund new ideas. Employees are given $2,000 of “IBM money,” which they can use to support the

It takes lots of ideas and lots of failed experiments to generate a big, valuecreating innovation; therefore, innovation failures have to be viewed as learning opportunities.” Edward D. Hess, Darden School of Business

projects they believe have the most potential.


Innovation in the Age of Digital Technologies: HUMAN VERSUS MACHINE WHILE THERE’S AN UPSIDE TO TECHNOLOGY AND DATA, the prospect that pow-

erful computers and sophisticated algorithms will displace knowledge workers looms large. Thanks to the exponential advances in cognitive computing and deep learning, machines such as IBM’s Watson can already make better and faster decisions than humans can.

The experts’ value is that they understand the context—that’s when they are the true experts. They understand the problems customers are facing now and what problems they’ll face down the road.”

Should innovation experts be afraid that smart machines will make them obsolete?

Jesper Frederiksen, VP and CIO,

zations need most. So far, no computer can see the big picture and figure out where


Not if you ask Thomas H. Davenport, a professor at Babson College and a research

fellow at the MIT Center for Digital Business. Davenport doesn’t see automation as a threat, but instead as an opportunity for augmentation. He invites organizations

to adopt an “augmentation mindset,” which embraces smart machines as partners in collaboration and creative problem solving.20

Computers will always be faster, better, and more efficient than people at certain

tasks such as analyzing massive datasets and uncovering hidden patterns. But if the

war for talent is any indication, it’s human vision, insight, and creativity that organithe real opportunities and challenges lie.

As companies become increasingly data driven, the role of experts will certainly

shift. According to MIT’s Andrew McAfee and Erik Brynjolfsson, domain experts

will be valued not because they know the answers but because they know what questions to ask.21

Experts define the problems, articulate a vision, and provide motivation. A machine can’t do that.” Only people—experts—can tell what is right or wrong. They bring a broader, ethical perspective to innovation.”

Even though the best recipe for innovation seems to be humans working alongside

Shannon Smith, Founder and CEO,

the edge, and how to reinvent processes to make the most of both types of talent.” 22

Abundant Power


Jennifer Stewart, VP Corporate Innovation, Eastman Chemical

smart machines, challenges abound. As McKinsey research attests, business leaders will need to understand “where machines can do a better job, where humans have

Final Thoughts DATA IS RESHAPING BUSINESSES AND INDUSTRIES and changing the ways

companies create and capture value. Experts are convinced that the big-data movement will affect almost all spheres of business—from finance, marketing, and HR management to machine repair.23 But most organizations are not yet ready to be

data driven.

Organizations are still learning how to overcome challenges associated with big-

ESSENTIAL READING “Analytics 3.0.” Thomas H.

Davenport. Harvard Business Review,

data management, such as security and privacy, not to mention the shortage of deep

December 2013.

To succeed in the data-driven economy, business leaders need to first develop clarity

Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Thomas H.

analytical talent.

about their company’s purpose and find meaningful connections between data and

strategy. They also need to rethink how they develop and market new products and services so that they leverage data to solve real customer problems.

Companies also need more flexible and agile processes that can speed up data-based

Davenport. Harvard Business Review Press. Boston, MA, 2014.

experimentation and new product development. And last but not least, they need to

build a culture that encourages and rewards data-driven decision-making, collaboration, and entrepreneurship.

Cutting-Edge Marketing Analytics: Real World Cases and Data Sets for Hands On Learning. Rajkumar Venkatesan,

Paul Farris, and Ronald T. Wilcox.

Pearson Education. Upper Saddle River, NJ, 2015.

“Innovative Analytics: How the World’s Most Successful Organizations Use Analytics to Innovate.” Anthony Marshall, Stefan Mueck, and Rebecca Shockley. IBM Institute for Business Value. 2014.


Davenport, Thomas H., and Julia Kirby. 2015. “Beyond Automation: Strategies for Remaining Gainfully Employed in

the Era of Very Smart Machines.” Harvard Business Review. 93 (6): 58-65. 21

McAfee, Andrew, and Erik Brynjolfsson. 2012.


Chui, Michael, James Manyika, and Mehdi Miremadi. 2015. “How Many of Your Daily Tasks Could Be Automated?”

“The New Patterns of Innovation: How to Use Data to Drive Growth.” Rashik Parmar, et al. Harvard Business Review, January– February, 2014.

Harvard Business Review. (Accessed 23 May 2016) 23

McAfee, Andrew, and Erik Brynjolfsson. 2012.



For the past six years, senior executives from some of the world’s largest and most innovative companies



Liu Qiao, Technical Director, Software,

Shannon Smith, Founder and

have been getting together to talk

Electronics and Mechanical Systems

Chief Executive Officer

about innovation in an interactive


and candid environment. They are members of the Innovators’ Roundtable, an initiative of Darden’s Batten Institute for Entrepreneurship and Innovation. Led by Darden’s


Gertjan Bartlema, Vice President

Sherri Gilligan, Senior Vice President

Geneviève Ménard, Senior Vice

Card Marketing

President Organizational Excellence

top-ranked faculty, they explore the latest research on corporate innovation, share best practices, and discuss common challenges.

Corporate Franchise Operations

Richard Williams, Senior Vice President


and Chief Information Officer

Gautam Meda, Research Director, Modeling & Simulation and Asia


The eighth Innovators’ Roundtable,

Research, Science & Technology

hosted by the Batten Institute on

Sam S. Zoubi, Senior Manager,

and Chief Information Officer,

7 April 2016 at the United States

Modeling & Simulation

President, Danaher Labs

Jesper K. Frederiksen, Vice President

Institute of Peace in Washington, D.C., brought together executives


from eleven corporations. This Bat-


Jennifer Stewart, Vice President

Victor Brown, Distinguished Engineer,

ten Briefing expands on the themes

Corporate Innovation

Director, Office of the CTO



that emerged during the discussions facilitated by Professors Rajkumar Venkatesan, Yael Grushka-Cockayne

Matthew Markee, President

and Edward D. Hess. Future Innovators’ Roundtables will convene in the Bay Area, China, India, and other locations.

c o p y r i g h t i n f o r m at i o n

Kurt D. Bettenhausen, Senior Vice President, Siemens Corporate Technology

SMITHFIELD FOODS, INC. Will Brunt, Senior Vice President Marketing and Chief Innovation Officer


BATTEN BRIEFINGS, June, 2016. Published by the Batten Institute at the Darden School of Business, 100 Darden Boulevard, Charlottesville, VA 22903.

Yael Grushka-Cockayne

Edward D. Hess

Assistant Professor of Business

Professor of Business Administration,


Batten Executive-in-Residence

email: ©2016 The Darden School Foundation. All rights reserved.

Rajkumar Venkatesan Bank of America Research Professor of Business Administration

UVA Darden Batten Inst: Data's Big Promise  

There are many ways to think about the recent explosion of digital technologies and data. Not surprisingly, the ubiquity of personal informa...

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