Revving up a Data-Driven Culture: Anthony Bucci

DSC_0067Three co-founders. A start-up. A long-term commitment to experimentation and testing. Business began to blossom, and today, the organization is entering a period of hyper-growth. This has been Anthony’s enviable experience shepherding In the beginning, nobody needed to convince co-founder Anthony of data’s value, but he has found it’s not necessarily leadership he needs to persuade to make testing and experimenting a company-wide effort.

Anthony has learned letting institutional knowledge for testing reside with top leadership is not an effective organizational strategy. While all levels within a company need to be involved in testing efforts, he encourages businesses to identify a process, define a framework, then “make sure someone with the bandwidth can at least own it.”

Speaking from the position of leadership, Anthony has more to say about fitting data, testing and experimentation into a business’s mindset. Give him a listen.

Blowing a Lot of Hot Air Over Big Data

Break freeShopycat. A feature for scanning the social media preferences of a customer’s Facebook friends and suggesting gift ideas sold on’s website. While Walmart has never shied from using analytic technology, it sort of missed the use-the-data digital boat when it came to focusing primarily on the customer experience. It isn’t alone. Difficultly integrating channels is an omni-channel challenge for many businesses with a brick-and-mortar arm. But Walmart is planning to make the shift to a data-driven organization (in fits and starts; selling certain items only online is not a great idea.) Walmart is hoping eighty-seven newly hired “engineers and coders” are going to help turn around the game it’s currently losing playing catch-up with (don’t lose more customers to) customer-centric Amazon.

Why Walmart Is Worried About Amazon

Let’s automate data prep; let’s ditch the internal chain of command that strangles experimenting with new ways to gather and use new data sources; let’s look at AI technology so resulting information and insight is built into the reporting process. That creative, forward-thinking analysts wish for intelligent tools to benefit a company is a clue they’re not just data jockeys and might be deserving of some attention. Big data tools now exist, or are in development, to answer most of the wishes. One thing is missing. Guess what.

Analytics Wishlist: Five Tools, Capabilites Analysts Wish Existed

Big data technologies are helping humans identify their own health troubles and find solutions. It makes sense that those with beloved barking companions wish for a similar technology geared to their four-footed buds. Now, your dog can wear a little ninety-nine buck device called Whistle. Whistle monitors your pet’s activity and compares the data to a large pool of other data to help you spot problems before they become serious. Score one for big data. (Warning: seriously adorable puppy alert)

Whistle Uses Big Data to Help Keep Your Dog Healthy

Is Verizon your telecom provider? If yes, did you know that since April 25 and until July 19, under a court order based on the “so-called ‘business records’ provision of the Patriot Act, 50 USC section 1861,” the NSA is collecting lots of personal datafrom your phone usage. Some folks mind the kind and quantity of personal data they are handing over, sometimes without even knowing they are doing it. Others accept that privacy in the big data world is becoming extinct. That’s a good thing, right? Up until it’s a bad thing.

Who’s Watching You? Not Just the NSA.

And Now for Something Completely Different

The art of air in motion: a real-time data visualization.

Wind Map

photo by: aussiegall

6 Steps to Begin Using the Data

Steps to Big Data SuccessThe possibilities in big data technology are exciting, but if you know very little about what these information technologies can do for your business, just thinking how to use them can feel like heading out with a plastic straw to fight a behemoth. Can you just walk away from the field? No. Big data technologies are here to stay, and businesses that wish to remain competitive need to embrace a big data mind set. These steps can get you started.

1. Forget the hype.

Every field has its own jargon. Insiders know it, outsiders don’t. It’s awkward to be the outsider still puzzling what data silos are while the jargon-laden conversation you’re listening to has moved on. Don’t let the jargon and all the technology-talk distract you, and definitely don’t let it dissuade you, from your goal.

Consider that ‘big data’ is merely a label people apply to an evolution in technology that provides much more granular information about your audience and allows you to refine—perhaps expand or automate—many of the ways you do business. Because providers of services use this label, it helps you find solutions that take advantage of new technologies. Beyond that, ‘big data’ is simply a slick term that garners attention. Don’t worry about it.

Many of the solutions you might find valuable help solve the same problems businesses have always faced. And, while the scope and scale of what new technologies can accomplish have grown dramatically, the reasons for the solutions have changed little. Trust you will learn the jargon along the way (just look at how familiar you are with the jargon in this simple article!). Trust there are individuals who can help you understand exactly what a big data solution can do for you.

2. Identify your problems.

All businesses have problems that lead to questions about improvement, whether improvement means increasing customer satisfaction or coordinating what you do online with what you do through other channels. You probably know what your problems and questions are. So itemize them, prioritize them. Do you need to find ways to undertake a more sophisticated approach to testing and optimization? Would it really help to automate your search engine strategies and PPC campaigns? Maybe you want to build a review system you can merge reviews with a variety of product-related applications. Perhaps you most want to build a comprehensive cross-selling platform based on relevance. Start with your problems, then …

3. Identify appropriate solutions.

You can employ a good data scientist(s) to help you develop applications in house. Many businesses find it more cost effective to contract with third-parties. Start learning what third-party solutions related to your problem are available. Many will focus on automated and ‘black box’ applications which are often easier to deploy. Talk to other businesses, attend conferences that associations and providers hold, share case stories from others who have successfully incorporated big data strategies. Be a good shopper, and keep in mind, a big data solution may not be the right answer to all of your questions.

4. Take stock of the data available to you.

This is usually an iterative process with identifying your big data solutions. How much in-house data do you have? From where does it come? How easy is it to access? Will you need to start collecting different data? Would it be valuable to start taking advantage of unstructured sources of data? Do you have or will you need to tap into outside data resources? Do you have data resources you never thought of as resources? Intelligence within your business and careful discussions with third-party providers can help you identify the value of what you have and suggest what you need.

5. Educate the people in your business.

Not so long ago, many organizations resisted incorporating analytics into operations. The big data phenomenon is to analytics as a skyscraper is to a house. One of the more difficult problems is getting everyone in your business to agree these new technologies have value and will work. Leadership often worries dramatic changes might fracture the cohesion of the company and change models that have always worked well; these are real and justifiable, if perhaps frustrating, concerns. You may become enthusiastically convinced a big data solution is going to revolutionize your organization’s effectiveness, but the history of institutional intelligence can be a tough nut to crack.

Help other departments understand how these solutions can actually make everyone’s work lives a little easier. Encourage interdepartmental communication and cooperation. Develop presentations and circulate articles so others can see the value of these changes. Reassurance that big data can change the efficiency and efficacy of how people accomplish their tasks without changing the business goals can go a long way to achieving support.

6. Keep an open mind.

An open mind is going to benefit everyone in your business today. It is even more important as you look to the future. In the upcoming years,  as this technology is refined and that technology is invented, the big data landscape is going to expand and change dramatically. Every business needs to pay attention to the evolution of these solutions and be willing to experiment toward optimizing the most effective ways to conduct business.

As you head out, plastic straw in hand, remind yourself that few things feel too big and threatening when you start breaking them down into manageable pieces.

You can do it.

My Kingdom for a Smoothly Run Conference

Today's "Underappreciated Technology of the Day"Right now, I am in Sweden, preparing to keynote a conference, thinking that the organizers are probably worrying about managing all the details. Every event organizer hopes their event will satisfy all their constituents but know how challenging that can be. They want to do their best to make the conference run more comfortably for the attendee and more efficiently for the hosting organization (while maximizing ROI) and speakers delivering the best content.

Planning and executing flawless events has never been an easy mission and lots of credit goes to those talented event organizers who pull it off regularly. However, what if it could be made easier? Today’s event organizers are flooded with more data than ever but with fewer resources to handle all these data sources.

On the other side of that coin, I speak at fifty-sixty conferences, give or take, every year. I know what poor conference experiences feel like. The experience a host serves up is critical, and how event planners use the data they collect can make or break the experience for attendee and organizer alike. Increasingly, big data strategies could help manage all the logistics associated with events—and they can do it in real-time, as the conference is taking place.

I was invited as one of the many “VIP influencers” to speak at IBM’s SmarterCommerce Summit (Glen Gilmore explains what this means). During and following the conference, many of us related our enthusiasm via social media methods of blogs and tweets. IBM neither asked nor required anyone to blog or tweet about the event, but many did. It was difficult not to share enthusiasm for the ways IBM understands how commerce can get smarter (see Bryan Kramer’s reactions).

People are doing many mind-blowing things with big data technologies, but IBM addressed a matter near and dear to my conferencing heart, and I would like to share my enthusiasm: I have never attended an event run more smoothly.

At the conference, Alliance Tech demonstrated to me how they accomplished this feat. They use RFID technology, embedding sensors in badges to help organizers equipped with iPads manage a variety of tasks:

Track the real-time behavior of people at conference trade booths to evaluate a range of key metrics to encourage more at-show sales and develop an intelligent show strategy:

  • Ascertain the number and quality of leads individual exhibitors are generating
  • Monitor the flow of individuals through the conference spaces as well as keep track of audience numbers and compare them with session evaluations to determine the popularity and value of individual speakers.
  • Evaluate through social media the opinions and comments of people involved in the event to learn customer reactions and preferences.

Information on what is happening in real time helps organizers do things like negotiate the number of breakfasts needed each morning given the attrition rate of participants. Are more chairs needed in a late afternoon session? Does partitioning need to be rearranged to increase room size? Was a person who is criticizing a speaker actually sitting in the session? This information and more is at staff’s fingertips the second they need it.

Social media tools can expand an event organizer’s understanding of what is happening then and there. To demonstrate how these applications fit in, IBM partnered with several companies to set up a social media command center. Whom did they monitor on the dashboard? Every participant.

Smarter Commerce 2013-05-21 (01)

OneQube [] (the left, white half of the dashboard), a company specializing in relationship management and engagement in Twitter chats and hashtags, displayed real-time information on all mentions and tweets for each participant. At one point, I ranked as a Jedi in the volume of real-time impressions; kind of cool since i hadn’t ever been a Jedi before. 🙂 That along side the Foreigner concert IBM put on, gave me real flashbacks to the late 1970s.

Smarter Commerce 2013-05-21 (03)

MutualMind [] (the right, black half of the dashboard), a social media monitoring and analytics company, set up an example of real-time analytics that can help businesses understand their customers in social context.

Smarter Commerce 2013-05-21 (02)

Eric Gore describes the specifics of MutualMind’s analytics.

In addition to its live feeds, MutualMind sent me a copy of “My Personal Profiler” document.

Smarter Commerce 2013-05-21 (MutualMind 01)

A number of bloggers who were at the conference have a hundred thousand+ followers. I am not one of those bloggers. But when it comes to the “klout score,” a measure of influence, I scored very high among the attendees, not because I have the biggest social reach, but because the people who follow me are skew very influential.

MutualMind also prepared a word cloud of my audience’s topics; this draws from the frequency of words they put in their Twitter profile to show who they are and what they are interested in. Many people’s profiles are filled with words related to “life” and “love” such as ‘coffee’ or ‘sailing.’ I was surprised to learn what my word audience topic cloud looked like.

Smarter Commerce 2013-05-21 (MutualMind 02)

Almost every word is indicative of my area of interest and occupation. This word cloud suggests my Twitter connections are in line with the audience IBM wanted to reach during this conference and demonstrates what others find as notable value in the content I shared.

Smarter Commerce 2013-05-21 (MutualMind 03)

From social media tools like these, event organizers can work with a level of business intelligence that hasn’t been possible before. Who is influencing whom? What are they saying that would help planners plan more effectively? What do participants want?

Logistics for a single event are complicated, but managing conference logistics as IBM is doing takes commerce to a whole new, smarter level. As someone who speaks at fifty-six conferences each year, I would be thrilled if all event planners were applying data in this way.

photo by: kevin dooley

Using Data in Realtime: an Interview with Alex Miller, QVC

Entering HyperspaceLucky are those who do not need to convince their business’s leadership of the value of using big data strategies to shape relationships with the customer within and across digital platforms. In 1986, the shopping channel QVC began broadcasting—in essence, operating in real-time. As Alex explains,

If you’ve ever gone backstage behind QVC and you’ve watched the live show from the producer’s desk, you understand you are in data Nirvana. It’s flowing data on three or four different screens; they are helping us understand: What is the customer really thinking right now? What are they interested in? What they like, what they don’t like? As a company, we’ve always been awash in data.

In taking the next step from analytics to the possibilities the big data era offers businesses, even organizations that value data-driven stories to improve customer relationships will have kinks to smooth out. The biggest challenge Alex identifies is how to balance the ways of using enormous amounts of data while continuing to place a high value on twenty-seven years of institutional knowledge. At times, it comes down to “letting the data tell you what it is really trying to tell you and not trying to shape the data to tell you what you want to hear.”

Listen to Alex talk about testing and experimentation as a data-driven company negotiates becoming more data-driven.

photo by: Éole

Not-to-miss links for 5/27/13

not-to-miss-linksMicrosoft Xbox gets the living room?

With Google Fiber currently installed (or installing) in select places and Google Glass in the works, can anyone doubt who will win in the long term? For just about any room you name? Well, hopefully not one. Besides, if you’re going to fork over your data, it’s easier to do so when there isn’t a face recognition system continually connected in your living room.

Creepy much?

The Xbox One hears all, sees all, and steals Google’s dreams

Cartography used to be biased; now it’s ‘honest’?

Maybe. Debate aside, Google wants to make sure when it processes massive amounts of data, it delivers one of big data’s most attractive promises–an instantaneous, intimate digital experience tailored just for you.

Why the new Google Maps is the most honest form of cartography

Overcoming our ideas of Privacy

The more we participate in the digital world, the more public our lives become. Unprecedented deceasing privacy is the cost. It’s not just an ethical matter, it also affects personal identity. Where do you draw the line in your life?

How technology redefines norms

Will your job be replaced by a robot?

Worry a little more whether big data and robotic technologies are going to leave people jobless and role-less. Once you are done worrying, remember that economies always cycle when new technologies create a new playing field and people architect their futures.

Driverless cars, pilotless planes … will there be jobs left for a human being?

Use the Data Roundup: May 20th 2013

not to miss links for the week1. Love the line about running up to the line with privacy and how Google Now was scary last year but applause-worthy this year.

Google Sensors Are Data Mining I/O Attendees – And They Don’t Care

2. Think about how companies who collect your data get it for free. At least one person isn’t happy about that.

A Bit(e) of Me

3. An issue-conscious app can help you decide which companies you might prefer to buy from or boycott. Let your conscience (and lots of data) be your guide.

Soon, You’ll Know As Much About What You Buy As the Company That Made It

4. A change in size leads to a change of state. A change in quantity leads to a change in quality. More is not just more; more is different, and the way we live and the way we think are about to change. Watch an interesting presentation to get a thinker’s grasp on big data.

The Economist’s Data Editor: Big data may be too hyped, but here’s how it will change the world
The video is about 30 minutes long.

How to Adopt a Data Driven Culture with Slava Sambu, OfficeMax {Video}

We took a few moments to sit together at the Monetate Agility Summit to chat about what it takes to get your organization to use the data to enhance the customer experience. This video interview is just 5 minutes long:

One of the things I admire most about the OfficeMax culture is their use of YouTube to test which video would be used on TV for their Penny Pranks campaign a few years back. This is an organization that understands how to use the data.

Tips on becoming a Data-Driven Organization

You might be grappling with how to justify a shift to data-driven strategies within your organization. The most likely reason you’re grappling is that your business culture is resistant—perhaps highly resistant—to change. You are in good company (as it were). Slava of Office Max offers some advice to facilitate your discussions with senior leadership and other heads of departments.

When describing the nature of a corporate culture that values and supports an effective digital strategy, Slava identifies three must-have attributes for any data-driven organization.

Find the language appropriate to the way your organization ‘speaks,’ and help leadership understand how a high level of cooperation within the company and a focus on data promotes business goals.

1. You want a culture of inclusion. Everyone needs to understand what things have to happen to accomplish the strategy. Everyone needs buy-in; this includes creative, marketing, analytics and senior leadership.

2. You want a culture of ownership. Everyone needs to own the results testing and optimization tactics generate. Everyone needs to understand them and how the organization is going to use them to accomplish the broader strategy.

3. You want a culture of responsibility. Across the board, strategies need clarifying, tactics need defining. Determining success means defining success. Data teams always need to outline what tests and optimization will accomplish within the larger business strategy, and then deliver on the promises. If developments necessitate change, teams need specific ways they can reevaluate and possibly adjust the strategy.

Slava has a lot more to say, too. Just watch the video.

How is Big Data Different From Previous Data?

Comparing apples to orangesThe three qualities that distinguish big data from all previous information-producing methods—big, unstructured and real-time —suggest a world of possibility. Businesses are creating and applying big data solutions in unprecedented ways that not only help them maximize profits, but also redefine their relationships with their customers.

Why get so excited? Is big data really so different from the kind of large-scale data processing that came before?

Sampling versus All the Data

Until recently, businesses analyzed massive amounts of data using statistical sampling techniques. This produced subsets of data the business could then analyze to infer information and make predictions based on those results. With today’s big data toolset, companies can analyze massive volumes of data all at once.

Big data not only puts businesses in the attractive position of being able to use massive quantities of data without sampling, it renders previous information structures impotent and requires new perspectives and technologies for turning data into information.


More often than not, companies have collected data and analyzed it later. Today, data analysis can take place in real-time. Businesses who can respond in real-time have the huge advantage of agility. An agile organization can act immediately on information to expand the business value of their data, no matter the speed at which it comes into the business.

There is a chance any dataset could be “dirty” (contains data that is not accurate). This is not new; it has long been one of the issues associated with data collection. As a result, businesses have always needed to understand the importance of listening to the data—not just the data providing good information, but also data generating more problems than it is solving. With big data technologies, an agile business can evaluate and correct potentially costly errors quickly, in real-time.

Data Sources

Prior to the big data era, businesses were constrained to using only structured data sources. These sources generate data suitable for relational databases. With big data technology, a business can start tapping into the huge pool of unstructured data now becoming available: video files; audio files; images; texts; tweets; Facebook posts and other yet to be created.


Data processing on a massive scale used to be cost prohibitive for most businesses. Big data can now become the great equalizer for businesses large and small. The cost structure and growing availability of big data solutions make them accessible to a greater number of businesses. As the technology continues to develop, big data can offer a Global 5 million, not just a Fortune 100, solution.

Business Structures

Big data does not change how we need to apply information from new data sources to long-standing business issues, but it does give companies a far more finely-tuned edge for honing business intelligence, and this is the arena in which business efforts to apply the information make all the difference.

Because big data is new, because it requires business cultures to rethink how big data will change the way their organizations operate, businesses that want to benefit from big data solutions must have an organized way to integrate all areas of data usage and information application (e.g., conversion rate marketing, across channels and silos). To accomplish this through experimentation, creative development and application, businesses must have buy-in from higher level superiors and C-level officers.

New Possibilities

Big data creates new possibilities of how we process data to generate useful information. Previously, analytics was a way of discovering information that already fit into the framework of how companies processed what they collected. Big data changes everything.

Explaining how it views big data, IBM writes, “Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make your business more agile, and to answer questions that were previously considered beyond your reach. Until now, there was no practical way to harvest this opportunity.”

What is Big Data?

data in cloud comicThe nature of big data suggests a world of possibility, and businesses are applying information derived from big data in ways that are redefining their relationships with their customers and helping them maximize profits. But businesses are lacking a big-data language they can understand. A technology-based language doesn’t help most ‘normal,’ non-technical, business folks ‘get it.’

All businesses can or do generate huge amounts of data. Most do not have a real plan for what to do with that data. If you don’t understand what big data means, how can you apply big-data-generated information to your business? How will you know which big data tools will make a difference?

That’s where we hope to be of service. We wrap a language and a business perspective around the world of big data to help you develop big-data business strategies.

We start with some simple labels to define big data.

Big, Unstructured and Real-time

People usually define big data by three qualities: it’s big; it can come from unstructured sources; you can use it in real-time.


Big. Big data is … big. The-mind-can’t-comprehend-it big. We now generate every two days an amount of data equivalent to all the data in the Library of Congress before 2003. In just one minute, 639,800GB of global IP data are transferred:


135 botnet infections
6 new Wikipedia articles are published
20 new victims of identity theft
204 million emails sent
1300 new mobile users are added
47,000 applications are downloaded
$83,000 in sales take place on Amazon
61,141 hours of music is streamed on Pandora
100 new accounts are created on LinkedIn
3000 images are uploaded to Flickr (20 million are viewed)
320 new Twitter accounts are created (100,000 tweets are sent)
277,000 people log in to Facebook (6 million view a Facebook page)
2 million search queries are entered into Google
30 hours of video is uploaded to YouTube (1.3 million videos are viewed)

As soon as you read these numbers, they are out of date; the staggering volume of digital data we are creating is growing at a phenomenal rate.

When you have massive amounts of data coming from multiple channels and across silos, how do you use it? This is an important business question: what you need to know influences the data sets you relate to each other and the best formats for presenting information in a way you can quickly understand it so you can act on it.

Unstructured. The variety of data available to us is impressive. About ten percent of it comes from structured data sources and can be processed by conventional means. Ninety percent comes from unstructured sources, and processing it requires new technologies. As digital technologies for data-mining and text-analyzing develop, we increasingly use these data sources that aren’t well-suited to relational database formats.

Structured data can come from sources inside or outside a company, from utilities, government agencies and GPS-enabled devices to radio-frequency identification chips (RFIDs), site search and website clicks. These are primarily structured data sources.

Unstructured data comes from from videos, audio files (for example, telephone conversations, audio recordings of presentations), images, texts, tweets, Facebook posts and more.

One of the most powerful aspects of big data is its ability to accomplish the equivalent of comparing apples and oranges without having to normalize them as fruit across datasets.

Real-time. Ideally, some online transfers should take place almost instantaneously. If someone just used your credit card illegally, you hope your bank discovers that immediately, not at the end of the month. The speed at which you can distill useful information from your data and execute a decision confers agility. An agile business has the advantage of being able to respond immediately, in real-time, as opportunities present themselves. Big data technology makes this possible.

big data is big unstructured realtime

IBM, a leader in creating and providing big data technology, defines big as Volume, unstructured as Varied and Velocity as the speed at which the technology can stream data into the business so the business can use the data immediately. These are great definitions; they are just aimed at a more technologically-literate audience. Business people do not use this language, so we substitute these with more intuitive terms.

IBM includes Veracity—the accuracy of the data—as an important big data quality. While this is a critical concern, from our point of view, accuracy is an inherent problem associated with all data, not a distinguishing feature of big data.

“Big Data is really about new uses and new insights, not so much the data itself,” says Rod A. Smith, an IBM technical fellow and VP for emerging internet technologies.

Businesses require the technical expertise of data scientists to extract, manage and refine information from data sources. Technical considerations usually fall outside our purview.

We care about how business people make sense of the information big data generates and how you can apply big data information to your business decisions.

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