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Dr. Charles Stryker

TransUnion: Transformation and the Path to Economic Development

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TransUnion: Transformation and the Path to Economic Development
By Charles W. Stryker

The “computer age” of the late 1960s and early 70s marked an historical period that witnessed hyper growth in today’s version of the Big Data and Analytics ecosphere.  Early Information Industry adopters of computing capabilities were able to capitalize on their first mover advantage to lead their sectors in the marketplace.  One company that embraced technology from the beginning of the computer age is TransUnion.  TransUnion got started in 1968. Originally, TransUnion was established as a rail car holding company.

The first acquisition TransUnion made that set the company on the path of credit information was, according to Wikipedia, “the Credit Bureau of Cook County, which possessed and maintained 3.6 million card files.”

Referring to the early consolidation in this burgeoning credit information industry, Mark Furletti of the Federal Reserve Bank of Philadelphia, wrote that, “Also during this decade, the industry harnessed the power of computers and databases to process, organize, and report on credit data. Those agencies that adopted computer technology realized operating efficiencies that allowed them to move data faster and attract more business. This, along with the costs associated with migrating to computer-based systems, compelled smaller operations that were not yet automated to sell their files and exit the industry.”

Consolidation in the 1970s led to the establishment of three main credit reporting agencies that would compete for market share for the next nearly 50 years.  All competitors used strategic acquisitions to build data volumes.  Today TransUnion, one of the original three, is using Big Data and Analytics best practices to better serve its customers and to advance the company’s core capabilities and core data assets.

To help understand how TransUnion is able to lead the credit/risk information sector’s Big Data and Analytics strategy, we had a conversation with TransUnion’s CEO, Jim Peck. Jim talked about TransUnion’s strategy of embracing Big Data and Analytics as a cornerstone of the company’s business plan.  He said he knew the future would require TransUnion to continue to build its data assets and also go a step further to embrace the added value that strong technology and analytics would bring to the success of the company.

“I still believe that you have to have the data, the content.  If you don’t have that, your analytics are meaningless. But the analytics and technology transform the data into actionable insights that help our customers make smarter decisions,” said Peck.

“To answer the challenge, we completely overhauled our technology.  We built a platform that was going to allow programmers to ingest data, clean the data, act on the data, integrate the data, amass the data, and in our case, in a global way, prepare to do the analytics on top of it.”

Peck was determined to have TransUnion be the market leader so he looked for ways to have the analytics edge engrained in the company culture.

“We decided that the answer was to bring in industry experts to lead specific vertical markets and appoint leaders who really understand sectors like financial services, credit card markets, or the mortgage, auto or insurance industries.  These people fundamentally understand these sectors so they know the problems, and the opportunities, facing these businesses.  They can articulate needs and help drive much better decisions around risk or policy setting.”

Before Peck’s arrival at TransUnion, Experian and Equifax had moved into the credit information industry leadership roles, especially in the 1980s and 1990s.  As Jim Peck himself says, “TransUnion was rolling forward and doing a good job, but it was a market follower as opposed to a market leader.”

Peck believes that the Big Data practices TransUnion has undertaken have, over time, propelled the company to a leadership position in the Information Industry.

“The Big Data story here, I think, is that TransUnion was a very good company, but it was sitting on wonderful data assets and needed to evolve for the company to take advantage of all these assets. And so, when I came on board I had a clear vision of what we needed to do to unlock its value in meaningful ways.”

TransUnion is very customer responsive these days, which Jim Peck attributes to both culture and smart technology choices.  “We’ve organized the information and we’ve built the tools that will allow our customers to look at all our data and see how the decisions they make compare to the rest of the industry.  They can play with different parameters, allowing them to predict different outcomes. Maybe they could expand their portfolio by lending in different ways, or examine other solutions from the data.  And, with our technology they can do this in minutes or hours, where it used to take weeks.

“This kind of collaboration expands our customer’s addressable market, and also benefits the end consumer.  What produces this value, frankly, is analytics. It’s all analytics. For the customer, the analytics might produce certain kinds of scores based on certain kinds of data.  From this point, our customer can say with confidence that ‘this person appears to be this kind of risk right now.’ With that information, our bank customer can take this group of people and safely give them better offers of credit. That’s really what our customers in the banking sector are trying to do.  We allow our customers to precisely decide what kind of individuals they really want to do business with and not treat everyone generically.  That’s really important when you’re dealing with someone who’s historically been “underbanked” – our data can evaluate the risk to the bank and help them get better credit terms.”

“That’s really a powerful spot to be in and we believe at the same time it promotes good things for society.   We believe that the more information an organization has, the better they will be able to do business and we believe the more the consumer understands their own situation, the better they’ll be able to control getting access to credit and insurance.  We call this Information for Good.”

TransUnion operates in over 30 countries, and has strategically focused on countries like India, Colombia and South Africa, that have the social and economic foundation to increase the middle-class standards-of-living.  According to Peck, “If you go to a country that’s struggling with institutions providing credit, it’s really hard for that society to develop.  When you can’t borrow or lend money, people don’t get access to things they need for social mobility and advancement.  We provide the best information and analytics possible so that banks and lending institutions can make credit granting decisions.  As a company, we want to embrace that and keep advancing the ball.  We believe that we can help keep the wheels of commerce turning and even improve the standard of living for people.  That mission helps everyone.”




Big Data and Analytics Panel Discussion: The State of Big Data

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Big Data and Analytics Panel Discussion: The State of Big Data

By Charles W. Stryker

In the fall of 2016, VDC hosted an event, VDC Connect, in New York City to bring together the leading thinkers in the Big Data and Analytics ecosphere.  VDC Connect provided a unique opportunity for leading executives to share with each other and the selected audience of invitees the lessons they have learned in bringing their firms into the world of Big Data and Analytics.


The first panel, reported in a previous blog, illustrated the dramatic corporate transformations occurring that are data-centric and revolutionizing industries. This second panel was designed to describe the current state of Big Data and Analytics  in the most comprehensive and informed manner, inviting executives who are at the center of driving the Big Data and Analytics implementations for global brands. We asked them to share their thinking about the current state of Big Data and Analytics.


Neil Isford, IBM General Manager, Cognitive Industry Solutions, started the discussion.  In his position, Neil is responsible for all sales and go-to-market strategies for a set of cognitive solutions for the 14 major industries that IBM serves around the world. His toolkit to do this work includes the Watson capability, which has already become a household name.  He also has the broad spectrum of analytics products that IBM owns and supports. As reported in the press, Cognitive Solutions has been described by IBM as their future growth engine. Neil is a point person to make that happen for IBM.  According to Neil…

“If we just look at the last couple years, I think the biggest change is the ability to start leveraging unstructured data. It’s leveraging what the industry now calls “Cognitive Systems”, systems that can perform natural language processing and deep learning capabilities to create business value from what is 80% of the data that exist. That’s not just structured text and emails; it’s everything that’s encoded in language, videos, and it’s no longer a future promise. We’re seeing companies do it today.  In the medical field, today’s doctors can treat cancer with access to all the research and the medical records available throughout the world.  Oil and gas companies use Big Data to educate their engineers so they see all the studies and all the tests that have been done so they can better service an oil rig. Insurance companies use it to better sell insurance over the web. It’s no longer a future promise. This is today.

“Big Data has evolved.  It used to be a data governance issue.  I think we’re getting our hands more around how to define the data, who gets to see the data, who can change the data.  Better tools and better processes help.  Now, I think the data security and privacy issues are the ones that need more focus.  The threat is both external and internal and it needs attention from both external and internal sources.

“We have coined a new term, ‘embodied cognition’, that applies to many devices out there now that have been dumb and now there are great opportunities to make them smart: the automobile, for example.

“Think about the ability to take any piece of hardware but now have it interact; have it benefit from cognitive services, like conversation. Now think about the fact that the automobile now knows when you get in.  It sets the seat, the climate, the entertainment, and knows where you’re going from your calendar.  It knows the weather conditions; it knows the road conditions, etc.

“We’re starting to see hotel chains utilizing robots.  While these robots aren’t quite at an affordable price point yet, where we’re seeing them everywhere, I think there’s a huge opportunity with Avatars where they’re software embodied.  As such, they can react to your voice or your emotions.  They can look like a human or they can be symbolic where they will change colour based on mood.

“We’re also starting to see very interesting opportunities to improve customer experience as we apply cognitive capabilities to things like physical spaces – from operating rooms for surgeons to where a financial advisor might bring his client for optimum effect.  I was with a company last week where we built an avatar demo for a cruise ship company. Think about embodying the cruise ship cabin with the ability to react to every aspect of your day. . Embodied cognition holds tremendous opportunities as we advance the Internet of Things (IOT).  We will have this cognitive capability improve many aspects of our life in this new world.”


Hank Weghorst is CTO of Avention.  Avention was known as the owners of the OneSource product suite. Hank is responsible for all design implementation related to building one of the best Big Data and Analytics platforms for the enterprise B2B marketplace. Hank is the holder of many software patents both in communications and, in three dimensional imagery which, when it began, was probably one of the most intensive data driven businesses that existed. Many of the computer effects that people watch today are based on the patents that Hank holds.

As Hank put it, “The biggest transition that we’ve gone through recently is a business change whereby the awareness of C-level executives has been raised concerning the value that data can bring to their businesses decision making.  Big Data has taken on corporate significance; it has become a pull by companies instead of a push by suppliers. In the last few years things have switched and now it’s more likely that an initiative from the top will produce value through Big Data, whether it’s to find efficiencies or drive new revenue.

“Increasingly, I’ve been asked to look at business problems in terms of possible data centric solutions. We look at the data we have internally and the data that is or should be available in the marketplace and need to bring it all together.  That’s a beautiful thing for the data world, because now all of a sudden there’s exposure up and down the stack. There’s actually support from the top levels down. And, after having been someone who’s pushed and pushed for years from the bottom up, it’s nice to finally feel some lifting.

“Frustration in the organization happens because of the decentralization of the problem.   What I mean by that is we’ll be dealing with a functional group that really wants to attack this problem but realizes that half the data we need is in other functional groups. So the data is siloed and the problems are siloed.

“Then you get the other end of the spectrum which is top down.  A Big Data initiative appears to be so large that nobody can solve it. Sometimes the project is too big and it becomes hard to identify the problem that needs to be solved.  We use best practices to steer more toward smaller functional problems with data that is within the purview of the group that actually has the initiative and the wherewithal to get it done. Success with this approach encourages more top down support.

“Success creates centralized initiatives with a top down push. It’s really interesting that people in functional silos really want this to happen but yet can’t get access to data because it’s three hops away and they have to issue a recommendation to have IT plan for it and get budget for it. Many people feel frustrated because they know they can drive value immediately from the Big Data project. We find out what data is within their purview and then what can we bring to them in terms of external data to the organization.  We put it together with the client in a way that can show immediate value.

“I am often asked how my experience in the movie making business relates to the data business.  There are similarities when you consider that we had a visual database that described everything we wanted to show, including textures and colors.  Where we are with the data world for B2B with sales and marketing type data is the equivalent of making a picture of the prospect. The next step is to make a movie of that prospect or customer. In other words, how does that company or person change over time?

“If we make a movie of a sales prospect, we will want to have enough data to know when a major event occurs in the company.  There are studies done in the B2B sales world that say as much as 80% of net new buying by companies is event based: they get a new executive in charge; they open a new office; or, they produce a new product.  You tend to make technology purchases in relationship to new initiatives.

“Events happen over time. So if we’re not collecting information over time, then we’re missing the opportunity to identify key change events. What happens over time?  Now, if you relate that to the difference between a photograph and a movie, clarity becomes apparent.  For example, If I was to hand you a photo of Mohammed Ali you would say, ‘that guy looks like he would be a pretty good puncher’.  If I hand you a video of an Ali fight, there would be absolutely no doubt in your mind that he is a good puncher. And so we will grow up as an industry, just as we grew up in the film world.   I think the data world in this industry is going to grow up from characteristics styled data to time series based data.

“Another aspect to consider is the impact of “The Internet of Things”. Even though it is such a buzz word today, it’s going to create an enormous amount of data that’s going to be usable in many ways.  The future of data looks very good!”


Rick Erwin is the president of Audience Solutions for Acxiom. Audience Solutions is the core data business of Acxiom.  In this capacity, Rick develops strategy, growth and profitability programs for Acxiom. He is immersed in working with global enterprise clients that have been Acxiom’s customers for, in some cases, decades.  In other cases, Rick also deals with brand enterprises, when they are focused on digital transformation.

As Rick put it, “The arc of this phenomenon of Big Data is awfully reminiscent of the arc of the phenomenon of the Internet. It’s just the data content side of the same sort of arc, and what I mean by that is if this was the late 1990’s we could be assembled to figure out what’s happening with this new thing called the Internet that’s transforming business. The Internet is a part of most business processes in almost every company.  When it comes to Big Data, we can see all this fabulous progress we’ve made, but we also see how early on we are.

“The biggest thing that we see is the shift of the advertising and marketing business to one that was predominantly based on the performance of a medium to now one that will be predominantly based on the performance of an audience or the individual in an audience.  This shift from media based to audience based is causing the kind of disruption that is really wrenching and pulling apart business models across the enterprise.

“We live in the world of marketing and advertising.  Typical e-commerce managers have a ton of anonymous users visiting their properties and these anonymous users probably get some kind of identifier like a cookie dropped on their browser or a mobile identifier.  If that same user comes back on a different device, they look like a different person to that e-commerce manager.

“We have this enormous Big Data identity resolution system called Abilitec. Abilitec is able to resolve any form of consumer identity that’s ever appeared back to a single numeric identifier. That numeric identifier can be put on a bank’s internal customer database so that the bank can identify you as one customer across all their lines of business.

“In just the past 6 months we’ve enabled this system that processes a billion identity records an hour.  Now the e-commerce manager can see hundreds of millions of anonymous digital identifiers that have visited one of their properties.  Now, for the first time, they can get a portrait of how a single human being navigates their web properties and that’s a huge leap forward.  It’s kind of non-sexy to talk about how we enabled it in the background, but in terms of the value it creates for marketers and advertisers, it’s huge.  That’s the way we tackle the big moves in Big Data.  We try to do things that may not seem very exciting in the back office but it produces leverage for our marketer clients in the front office.

“I’m fascinated by the natural gulf that always happens by the state of the art technology and then the ability or the willingness for humans to do something with it.  I look for things that I think might help bridge that gulf. The Internet of Things will create an enormous amount of data that’s going to be used.  It will be interesting to see what we can do with it all.”


Randy Bean is Contributing Big Data Author for the Wall Street Journal & Forbes and CEO of New Vantage Partners, LLC.  Randy is a contributing Big Data author that you read about in the press all the time. And for those of you more immersed in the topic, he’s also a contributing author to the Harvard Business Review and the MIT Sloan Management Review. Randy is the most recognised author in the field of Big Data and Analytics.

“Because I write a lot, I always have to be thinking of what is the story that holds people’s interest. So let me tell you my story briefly. I started as a COBOL programmer.  I wasn’t interested in the programming, but was interested in all this data that was being assembled and organised.  When I asked colleagues what they were doing with this data, they said they were storing it.  So to me it seemed like a tremendous missed opportunity to gain insight into the information that the organisation had at its fingertips.

“Fast forward to 2011, when I picked up a publication on Big Data. My first reaction was, isn’t this what I’ve been doing for the past several decades?   Part of that answer was no in that there is a whole set of new tools and technologies that really empower the business today that weren’t available earlier.

“Big Data programs are proliferating.  According to a survey we conducted of Fortune 500 executives, 63% of firms reported having a Big Data program in production, up from just 5% in 2012.   63% of firms reported that they expect to invest greater than 10 billion dollars in Big Data in 2017.  Significantly, 54% of firms reported they appointed a chief data officer, up from 12% in 2012.  That points to the centrality of data in organizations. 70% of firms say data is of critical importance to their firms, up from 21% in 2012.  This development illustrates the fact that the concept of Big Data and Analytics is being elevated in importance in the minds of boards of directors and the C Suite.

“We do a lot of work within the financial services industry, which is probably the largest investor and has the biggest impact in terms of total investment in Big Data Analytics.  Recently I wrote a story about American Express and how they’ve been able to streamline the credit process through Big Data Analytics.   They are able to look at 10 years of data down to the most minute level of credit transaction and make decisions in milliseconds. Now they can look at somebody’s complete credit before approving each and every transaction.  That’s something that’s extraordinary.  It hadn’t been able to be achieved before and it both streamlines credit approval processes and helps mitigate credit risk as well.

“Big Data Analytics can be used to fight famine, fight disease, and address many other social issues.  There are a lot of interesting things from the social perspective that Big Data Analytics can address.  For example, I was talking with one of the major banks the other day and they said this concept is very important for big corporations as well because they have a lot of data that can be used for positive social purposes. Good social responsibility can also be good business.  This social imperative of Big Data in corporate America is something we’re going to hear more about in the coming days and years.”






Transformation Through Big Data

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Transformation Through Big Data
By Charles W. Stryker

VDC Connect was an event organized by Venture Development Center at the Time, Inc. headquarters in lower Manhattan.  This event was an opportunity to bring together top information industry leaders who are embracing the development of Big Data initiatives in their companies.  The first panel discussion focused on the transformational experiences of three leading media companies.  Each company was represented by the C-level executive with the responsibility to grow their company through the use of Big Data strategies.

Three themes emerged from the first panel.  The first was “Transformation”.  Each panel participant is intimately involved in a transformational change in their company.  Secondly, each panelist recognized that he was witnessing a culture change surrounding the company’s transformation.  Finally, the presenters agreed that the use of Big Data analytics was central to the success of the transformation.

The first presenter was Joe Ripp, Executive Chairman of Time, Inc.  We asked Joe to talk about his experiences bringing a transformational change to Time, Inc., one of the largest and comprised of many of the most recognizable print medium brands in the world (People, Time, InStyle, Sports Illustrated, etc.).

Joe explained the background behind Time’s decision to embark on a Big Data strategy.  He said that the Company needed to find a way to answer advertisers who were demanding more and more information about the effectiveness of their ads.  Joe explained that traditional magazine publishers can’t measure advertising effectiveness accurately.  “The advertisers were demanding answers: ‘How effective was my ad?  Did it change the perception of my brand? Am I getting reasonable return for my investment?’

“Those questions are radically transforming the whole media landscape. Billions of dollars are being diverted into new types of media, not because they’re better, but because they can measure better.”  Joe was convinced that Time Inc had to adapt, to transform itself into a modern, relevant, digital media company that could compete and succeed in the 21st Century.

“Transformation is very hard!” said Joe Ripp.  “You must ask yourself, ‘Do you have a culture of transformation and do you have a culture of change?’ If you don’t, you’re going to fail!”

Joe’s conviction about embracing change is compelling.  As he put it, “Culture trumps strategy every day of the week. You must make sure that if you’re in the organization, accepting change is imperative.  If someone cautions, ‘We don’t do it that way’, you have a problem.  If you look around the corner and say, ‘That’s not going to affect us’, then you have a problem. If you have an organization that’s telling you why it won’t work, then you have a problem. You need to have an organization that’s embracing all the things that are different and move forward.

“You used to look forward and see competitors coming at you five years out, seven years out.  Now you look out thirty days and can’t see them coming at you. So you have to be prepared and understand that disruption is going to be an everyday event. And you must build the kind of culture-based organization that’s not fearful of that but embraces it and understands it. It’s an exciting time to embrace change. If you get that right, then transformation can happen.”

“For Time Inc., the next big thing is the whole distributed content world.  We will produce 40,000 videos this year.  But for us and all major media companies, the challenge is customer attention.  The average attention span of a human being right now is 7 seconds. The average attention span of a goldfish is 8. So the problem that media companies have is, how do you break through that clutter? The thing that makes it even more challenging is people are being distracted by devices all the time. Digital distraction is a real problem for media companies.  How do you break through that clutter?  And, as we’re trying to engage our consumers, how do we know my ad is getting through? There’s more clutter in advertising going on now than ever before in the history of man. So advertisers are asking questions like how much engagement was there? Was the ad actually viewable?  Was it viewed by a bot or not?”

Following Joe Ripp was Mark Roszkowski.  Mark is Senior Vice President and Head of Corporate Development, Strategy & Strategic Partnerships at AOL.  Mark has been at the center of Verizon’s acquisition of AOL and he has been actively managing that merger.  Mark is now in the center of completing AOL’s acquisition of Yahoo. The combined companies will have over 1 billion active users and a global digital delivery network and financial capacity of Verizon.

Mark described the transformational nature of the thinking that was essential to getting the acquisitions right.  “We had a strong belief that content was a key attractor and builder of audiences and communities but, over time, we felt that it was important to supplement and / or support that content delivery with platforms that enabled distribution, personalization, engagement and monetization.   Ultimately that’s all underpinned by insights that are driven from data.

“The transition we’re on is content oriented.  Content has become commoditized to some extent and we believe we can enable not only ourselves to build great brands and promote those brands globally, but leveraging our platform to then help other brands build their businesses globally on our platform of great tools, technology and data that we can bring to the table.  There’s a massive opportunity bringing together great content, massive distribution and great data that personalizes, engages, and hopefully monetizes consumers.  But first and foremost you have to figure out what data do you actually have.  Is it useful? Where does it sit? Is it silent?

“We’re investing in the Internet of Things, the combination of mobile connectivity and sensors that essentially pulls data from anything that you can imagine.  You can think about the connected house, all the data that’s being developed through consumer interactions with dishwashers or refrigerators or stereo systems or media devices within the household.  Ultimately, as you leverage all that data, we see the intersection of what we call conversational user experiences leveraging the device in your pocket.   We look at your device such that the combination of all the data and artificial intelligence we provide will be able to drive what we would call notification. The machine that’s going to think for you and predict for you and notify you of where you need to be, why you need to be there.  It will tell you you’re out of paper towels.  Then the paper towels are just going to show up on your front doorstep.  You get a text and click to accept the purchase.

“We’re still spending too much time in front of the TV.  Driving towards addressability is huge. It dictates efficacy, whether you call it contribution or ‘controversion’.  The point is that addressability allows you to measure impact.

“It’s going to be a really interesting time for the next 25 years.”

The final panellist for the session was Matt Marolda, Chief Analytics Officer of Legendary Entertainment.  Legendary is known for the movies it produces, such as Jurassic World, Straight Outta Compton, Godzilla or The Dark Knight trilogy, to name a few.

When the CEO of Legendary made a commitment to transform the way film is developed, created and marketed using Data and Analytics, he called on Matt. Matt previously was the founder of StratBridge where he created an analytics platform for sports teams to make better decisions about player acquisition, game preparation, and in-game strategies and tactics.

As Matt explained it, “If we can use data analytics to reduce media spend by being more efficient and more targeted, then that’s a material impact for our business.  It goes right to our bottom line. It begs the question of what other benefits can come from analytics. What films should we produce?  How should we cast them?  What are the optimum release dates?  Previously, all these questions used a very intuition based approach.  Using analytics, then, we’ve provided answers to all those key business questions and others as well.

“We’re trying to take the data that we have and drive towards informed action, whether it’s a decision or a marketing intervention. And the crux of it all is being able to understand people on a fundamental level which means on an individual level. That approach impacts everything we do.

“When it comes to the marketing side of things, data for us is all about trying to understand people at a microscopic level to deliver the right message at the right time.  We strive to do it with precision so we can tailor creative to impact what messages we serve to what segments of people really down to groups of hundreds.

“We don’t want to treat customers as a monolithic audience.  We look at them as a collection of many segmented groups. That way, we can tweak the creative to be much more targeted.

“So data is the currency for us in all those actions and without that data, we wouldn’t be able to get that precision.

“My challenge was that as soon as I walked into Legendary, more or less the first day, I had to deal with people who are very creative.  Their jobs were to make movies and tell stories.  While I was about to enable them with the ability to have data infused into everything, natural and understandable trepidation existed.

“My analogy was with sports.  I explained there was never a point in which analytics created a player. But analytics always tried to put the player in the best position to succeed. And so that attitude enabled the data to actually become a viable part of our strategy at Legendary.  I think that without that attitude, there would have been rejection from the beginning.  The challenge is always to treat the data with respect.  The key is once you have corporate cognisance about the power of data, then you are able to fold it into the rest of the business in a way that’s not intimidating and not threatening.  That way everyone in the organization can actually realize its potential.”

All three executives who framed their individual experiences transforming culture within challenging corporate environments represent the disruptive kind of thinking that is propelling Big Data Analytics into the center of corporate growth strategies for the future.





The Next Era: The Computer Age

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The Next Era:  The Computer Age
By Charles W. Stryker

The foundation of the Big Data ecosphere was built from the mid nineteenth century on the backs of innovative, first to market industry leaders like D&B, Reuters and AP.  These early Founding Fathers of Big Data leveraged technological advancements to achieve short-term business goals.  They likely had no idea that their first-to-market strategies of 150 years ago would ensure their company’s leading competitive position today.

Forbes has pointed to the November 1967 paper by B. A. Marron and P. A. D. de Maine as the starting point for tracking the development of the modern Big Data world.  In an article entitled, “Automatic Data Compression”, the authors state that ”The ‘information explosion’ noted in recent years makes it essential that storage requirements for all information be kept to a minimum.” The paper goes on to describe “a fully automatic and rapid three-part compressor which can be used with ‘any’ body of information to greatly reduce slow external storage requirements and to increase the rate of information transmission through a computer.”

With the inception of computer technology, a new world of opportunity opened up that would constitute the next wave of Big Data development.  Once again, as with the companies that supported the first era of Big Data history, the computer era produced several key leaders that emerged as beacons of Big Data development.  Also, within this era of Big Data development came the notion of analytics and how computers would jump start the future of what is now termed “Cognitive Computing”.

The concept of “integrity” formed a significant part of the success equation for the three Founding Father companies we examined earlier.  We saw that customers of these early Founding Father companies were reticent about switching suppliers of mission critical information because they came to depend on the integrity of the information to stay ahead of the competition.  In the second era, the computer era, integrity plays an equally significant role in securing the long term loyalty of a growing customer base.  Acxiom’s Vice President Global Executive for Privacy and Public Policy, Sheila Colclasure, puts it this way:  “For Acxiom, our integrity is central to our success – we’ve built trust over time. You can trust Acxiom to ensure the ethical use of data and also to be dependable, accountable, sustainable, and to deliver.  Our clients and partners trust and depend on Acxiom.”

Acxiom is a company today that processes massive amounts of data on behalf of its clients and it continually enriches its own data repository.  Throughout its half century history, Acxiom has emerged as a leading Founding Father of the Big Data ecosphere and warrants a special place in the second era of Big Data history.

According to Terry Talley, Acxiom Senior Fellow, “Acxiom was born in 1969 and it was actually a spin-off of an IT department of a bus company.  It was the birth of the active use of computers for all kinds of things.  The bus company spun off this capability and they started a company that was to do data processing of all sorts.”

Acxiom began life in Arkansas at a time when the Democratic Party in that state wanted to figure out how to leverage data to find voters.  At that time, the Party was trying to figure out how to do effective mailings for campaigns.  Acxiom was hired to work on the political campaign.  That job started a path of processing data for customers that would quickly became the Acxiom differentiator.  Acxiom became the “go-to” source for direct mail campaigns of all kinds.

The direct marketing industry really got going under the leadership of Acxiom.  In 1970, people used physical mail for outreach to prospective customers.  For Acxiom, the challenge was first acquiring a significant amount of data that wasn’t readily available, in particular the names and addresses of the people in the United States.  The next step after that required a more sophisticated investigation as customers began asking for more specificity about the individuals they wanted to reach.  The notion of a demographic descriptor entered the equation and Acxiom responded by refining the mailing list with added value information such as gender, ethnicity, and income levels.  Acxiom’s ability to respond to these data appends became a part of the story of the growth and sustainability of Acxiom.  The Acxiom historians agree that the Company’s success grew from this ability, early on, to provide targeted programs that would allow its customers to identify and reach the most appropriate prospects.

Charles Morgan, the founding executive credited with guiding Acxiom through the formative years, wrote an interesting history of the Company in a book titled, “Matters of Life and Data”.  When relating the stories that formed Acxiom in the beginning years he points out that when the Company was called upon to work a political direct marketing campaign, there were significant challenges that needed to be overcome.  “Back then, voting records were usually buried away in individual courthouses, so it took a massive manpower effort to mine this data and bring it together in one place. That was step one. Step two was for us to buy a white-page telephone list from a company called Metro Mail and match the union membership rolls to the voting data. Step three was … to set up phone banks to start calling these union members, to find out where they stood on a particular issue, and whether or not they needed assistance getting to the polls.”

The significance of this groundwork showed up in the Democratic Presidential election of 2008.  Morgan described the early work of the Company as the beginnings of the ground game that allowed Obama and the Democrats to win presidential decisions some three decades later. “It was, he said, “the data gathering skill and large scale name and address processing that would one day put our small company on the world map.”

Acxiom began to apply its computer processing acumen to other marketing challenges. Morgan describes an interesting early business deal the company did with Sam Walton.  “Sam wanted cash register tapes from every one of his stores on his desk at 8 o’clock every morning. With those tapes, he could see what every department in every store had sold the day before. The reason he wanted this information is that he didn’t have any cash, and that’s part of the brilliance of Sam Walton’s story – he knew that if he had really good information, he didn’t have to keep so much merchandise in inventory. Sam had no money, so his buyers would go to Spalding Sporting Goods and say, “Spalding, we’re going to buy ten thousand dollars’ worth of basketballs, but we want four weeks from the time we get them in our distribution center to pay you for them.” Because of his tight inventory research, Sam knew he could sell that many basketballs in about three weeks and he got his money the day they were sold. So by the time they were all sold, he would have money in his bank account and still didn’t have to pay Spalding for another week.”

For Acxiom, as the company grew in size and capability, it constantly strived to add more and more computing power to the analytics efforts.  Terry Talley stated that, “the essential problem is Big Data is always at the edge of what you could possibly do in a cost effective manner. What Acxiom did was some very creative things around using collections of less expensive hardware, typically used gear, and string them together in what we would now think of as something as horizontal scaling.”

Acxiom built many of the early computer-based solutions to be able to take on increasingly demanding direct marketing campaigns.  For example, the Company produced its own version of relational databases that were optimized for highly targeted direct marketing campaigns.

When Acxiom customers learned to rely on the high value mailing lists and effective marketing campaigns that were produced by leading edge software analytics, no competitor could easily unseat Acxiom and today the Company enjoys a loyal customer base comprised of some of the largest brands in the world.




The Founding Fathers of Big Data: Early Founders Wrap-up

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The Founding Fathers of Big Data – Early Founders Wrap-up
By Charles W. Stryker

Louis Tappan, Julius Reuter and Moses Beach all laid the groundwork for their respective companies more than a century and a half ago.  Dun & Bradstreet, Thomson Reuters and Associated Press are key Big Data players today because of their entrepreneurial skills and keen understanding of new market opportunities in the mid-1800s.  For each of these Founding Fathers of Big Data, there were similarities in the nature of the challenges they faced in growing their burgeoning businesses.  However, the obstacles to success that they faced were distinctly different.  The solutions were unique in their ability to provide the company with a leverage that worked for the short term and, as it turns out ultimately, for the extremely long term as well.

So what was the magic that worked for these early Founding Fathers?  Clearly it wasn’t just a technology solution alone because soon all competitors would be able to access the same technologies that propelled the market leaders to their successes. For all Founding Father companies we examined, there was a social impetus that drove the entrepreneurs to be the first with a solution.

The mid-nineteenth century was marked by a flood of new commercial activity extending West and South in the U.S. attributable to events such as the California Gold Rush and the opening of the Erie Canal.  While typewriters and carbon paper allowed The Mercantile Agency to build a dominant capability in credit reporting by providing wide geographical distribution of credit report copies, another component was required to cement its winning position throughout the decades.  That factor was developed from the outset, because The Mercantile Agency was there first.  The long term success of the company – even as it morphed through various name changes to arrive at D&B –  was based on developing a relationship of trust with the customer and to be first. Why would any company concerned with the risk of doing business with an unknown company, thousands of miles away, use a new supplier that had never demonstrated their skill in accurately identifying the bad guys from the good?

Similarly, Julius Reuter saw the benefit of using emerging technology to accomplish what no other company could do.  The challenge was commensurate with the times:  stock traders in England and Europe were increasingly hungry for stock market news and quotes.   It was essential to Reuter that he provide the solution.  It turned out that the right solution was an underwater telegraph cable across the English Channel.  He was the first to procure commercial time on the cable to transmit stock prices and quotes from London to the mainland and back again.

Once Reuter was able to show his clients that he could provide them with the most current stock quotes, using an alternative source would be risky for the client. Reuter was the gold standard because he was there first. This phenomenon of making oneself an indispensable solutions provider for the customer became a key component to the long term success of all three companies we have looked at as Founding Fathers of Big Data from the nineteenth century.

Finally, Associated Press provided our third example of the birth of Big Data.  The problems posed by distance and speed of information delivery framed the challenge faced by Moses Beach and his publishing competitors in New York.  The newspaper race to cover the Mexican American War was fraught with logistical impediments as reporters on scene tried to get their first hand report of the battles to a news hungry population in the U.S.  By sharing the costs of news transmission through telegraph lines and private carriers, the AP was able to establish an impenetrable cartel that would stand the test of time for a century and a half.

So the key to short term success for all three of our Founding Father companies we have examined was to implement a technologically-based solution to capitalize on a new business opportunity and to be the first to do it.  If you are first in the information industry, you can expect to have decades of success. This characteristic of the information industry is unique as compared to other technology segments where being first rarely produces a market leader.




The Founding Fathers of Big Data: Associated Press

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The Founding Fathers of Big Data – Associated Press
By Charles W. Stryker

The Associated Press is another Founding Father of Big Data that has lasted for more than a century and a half and not only does it survive today but it leads all competitors in its chosen information industry sector.

The Associated Press was created in the same timeframe that saw the birth of D&B as well as Reuters.  While D&B was making a name for itself in the credit information business and Reuters was entrenching its financial news delivery leadership capabilities in Europe, AP was getting started as a unique monopoly creating a new more efficient way to publish news at scale.

The Associated Press got its start at a meeting of six New York publishers who gathered at the behest of David Hale, publisher of The New York Journal of Commerce.  On the agenda for the meeting was the financial challenge of covering the Mexican-American War which was draining the resources of all six competitors.

Moses Beach, publisher of the New York Sun, proposed that his company’s efforts to gather and report on news from the war be shared with his New York competitors and, in return, all benefitting from the reports would share the expenses Beach incurred in the process.

That day, the Associated Press was born.

Beach saw the telegraph as the pivotal technology that could overtake the traditional ground and sea-based modes of news dissemination like the pony express, mail boats and carrier pigeons.

As with other Founding Father organizations discussed earlier, the Associated Press coupled a changing social or market environment with a technology based solution.  However, once achieved, AP’s market leadership was sustained through a century and a half by barriers to entry.

In the beginning the purpose of the Associated Press as an organization was strictly financial.  On the surface, the association looked to be a cost sharing arrangement only.  However, as it turned out, the sharing agreement was in fact the blueprint for a very effective and durable business model.  By sharing all the news that arrived by telegraph wire and dividing the expenses evenly, each member was spared the dangers of losing wire-borne information to a higher bidder.

AP realized that if it could secure exclusive access to news stories before they got published elsewhere it would mean that its association members could scoop their competition every time.  As it now had become a highly trusted news source, the Associated Press could rely on a committed and very loyal customer base to support the AP model, even in the face of competitive alternatives.

As with other markets that rely on information timeliness and accuracy, once AP garnered the lead in news collection it was difficult for any competitor to unseat it.  This market phenomenon has kept the Associated Press viable and vigorous for nearly 170 years.



The Founding Fathers of Big Data: Thomson Reuters

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The Founding Fathers of Big Data – Thomson Reuters
By Charles W. Stryker

The first group of Founding Fathers of Big Data were entrepreneurs of the mid nineteenth century who exhibited exceptional creativity to go along with unique market conditions.  In my last blog we looked back at the beginning of the business credit information industry.  D&B, originally known as The Mercantile Agency, used innovations like the typewriter and carbon paper to capitalize on the rapid national expansion of business throughout the U.S.

New companies were being formed driven by the Westward Expansion of the U.S. through industrial events such as the opening of the Erie Canal and the California Gold Rush.

The  completion of the Erie Canal in 1825, “spurred the first great westward movement of American settlers, gave access to the rich land and resources west of the Appalachians and made New York the preeminent commercial city in the United States. Within 15 years of the Canal’s opening, New York was the busiest port in America, moving tonnages greater than Boston, Baltimore and New Orleans combined.” *

Further, the California Gold Rush began on January 24, 1848, when gold was found by James W. Marshall.  Once the news of the discovery reached the East it started a migration of 300,000 people who wanted to find their own fortune.  With the migration came a commercial infrastructure that demanded business ventures and credit reporting requirements.

So businesses needed an honest intermediary to make a statement about the reputation and quality of these new businesses.  During this time period, businesses typically operated at a local level only. They would get an assessment of the credit worthiness of a business just from walking by the building and talking to the owner.  Or, they would talk to mutual acquaintances about past experiences. The D&B solution provided a trusted information source that enabled companies to expand their business interests beyond the local level and hence throughout the U.S.

While D&B was setting the scene for a 175 year success story, another of the Big Data Founding Fathers was making his mark in Europe.  While the environments were distinctly different, the success factors were the same.

The next Founding Father for our review is Julius Reuter, the founder of Reuters News Service and currently the world’s leading news aggregator, Thomson Reuters.  As with D&B, Reuters is a story of a technological solution to a business challenge – Reuters has not just survived for 175 years, the company has ascended to the top of its competitive space.

When we look at the two central drivers that underlie both success stories, a consistent theme emerges.  First, there is a technology explosion that these entrepreneurs recognized could provide an initial competitive advantage amid dynamic market conditions. Second, the confluence of technological innovation coupled with dramatically changing market conditions created a perfect environment for the entrepreneur to capitalize on a business opportunity.  Because the Founding Fathers are first, these entrepreneurs tend to spawn natural monopolies that can last for hundreds of years.

Julius Reuter’s story was similar to the D&B story because he started his company at a time when technology was becoming available that would enable his business to advance ahead of any competition.  In Reuter’s case, he realized that society had an appetite for owning stock equities. There was a desire by investors to own and trade equities on many stock exchanges.  People in London thought there were good opportunities in continental Europe; therefore, they wanted to see current quotes on either the Paris Bourse or, the oldest stock exchange in the world, the Amsterdam Bourse.   Conversely, people in continental Europe thought there were opportunities not to be missed on the London Stock Exchange.

The problem with servicing these intercontinental equity trading opportunities was time.  It took days to get stock closing prices because typically the closing prices were passed using the mail boat system that sometimes took days to get a few miles.  The technology for delivering the information that allowed people to effectively buy and sell equities didn’t exist. Julius Reuter realized that international stock trading was a growing trend and that by improving the delivery time of critical stock pricing data, he could dominate the business of disseminating stock quotes.

Reuter earned his place as a Founding Father of Big Data when he developed the solution to allow timely distribution of financial news and stock prices between London and continental Europe.  His solution was to use the recently established telegraph network to carry stock information.  To complete the link between London and Europe, Reuter himself invested in the cable project that spanned the English Channel.

Like D&B with the critical edge of being the first to collect reliable credit information in the context of a huge market expansion, Reuters was the first to overcome a technological challenge at a time when there was a rapidly expanding appetite for current stock market information.  These are the two key aspects that characterize a true Founding Father of Big Data:  technological solutions for an information service while capitalizing on a rapidly changing market environment.

Next time, we will address the contribution to the Founding Fathers group by Associated Press.




The Founding Fathers of Big Data: part 1

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The Founding Fathers of Big Data – Dun & Bradstreet Challenges
By Charles W. Stryker

This is the first in a series of posts that will examine the Founding Fathers of Big Data – specifically the companies and people which helped shape and create the notion of Big Data as we know it today.

When we look back at the formation of the Big Data ecology, we need not look very far back – to the mid 1800’s. Some of the leading data companies of today began when modern American commerce was in its infancy. Companies that today can boast of being leading information sector operators like D&B, Thomson Reuters and Associated Press all began roughly at the same time.

The mid 1800’s, Europe was characterized by a period of social, political, cultural and industrial upheaval and change. In the U.S., the same air of innovation and industrial competitiveness was also emerging. Although thousands of miles and the Atlantic Ocean separated the continents of Europe and North America, the challenges were similar and the solutions were – though different in methodology – formed from the same need to overcome obstacles to growth.

Louis Tappan established the Mercantile Agency in 1849 to consolidate credit information as business ventures were proliferating faster than merchants could evaluate on their own. Over the years the Mercantile Agency morphed into the Dun and Bradstreet Company, today known as D&B, the recognized name worldwide for business credit information.

Louis Tappan, like other entrepreneurs who were responsible for laying the foundation for the modern Big Data ecosphere, were driven in their respective businesses by one or more technological innovations. By today’s standards these innovations seemed trivial but in the early days these technological advances made for profound changes that allowed them to overcome logistical barriers and propel them to a place that the competition could never reach.

Today, D&B remains the clear leader in its field. It is very likely that some of the decisions made by the founding fathers at D&B more than 165 years ago are still at work today keeping the Company ahead of the competition.
What D&B shows through this sustained leadership in a part of the Big Data ecosphere is that the entrepreneurs who capitalize on opportunities – born out of challenges in the day-to-day running of the business – can serve as the bedrock to build information businesses that last hundreds of years.

Technological innovation, while an important component in longevity of an information business, is not sufficient to ensure success. The other part of that is it has to be tied to a period of dramatically changing market conditions. In the 1850’s an explosive industrial growth was underway in the U.S. as business expanded West and South from the Northeast. As commerce spread to Chicago and then followed the Gold Rush, the need to track business creditworthiness followed in step. When business dealings were merchant-to-merchant in local communities, credit confidence was easily obtained by reputation in the local community. As commerce expanded, another solution was required.

D&B’s ability to quickly establish satellite offices and recruit local business analysts was key to the company’s early success. By employing rudimentary technology improvements of the time such as adopting the typewriter to produce credit reports and adopting crude but effective copying techniques, D&B was able to supply communities across the country with company credit reports.
Distributed commerce was the social event that propelled D&B into its leadership role.

In the next installment, we will examine the factors that have sustained D&B’s competitive edge over the years and look at some of the other “Founding Fathers” of today’s Big Data ecosphere.