Monthly Archives: March 2014

Buffett’s Billion Dollar Bracket Bet

Lightning
Lightning photo courtesy of cnx.org.

The NCAA tournament has become a cultural phenomenon where everyone suddenly becomes a college basketball expert whether or not we’ve ever watched a game. This expertise has raised to a fever pitch this year as Quicken Loans has offered 1 billion dollars to anyone who provides a perfect bracket. But why?

This contest, underwritten by Warren Buffett’s Berkshire Hathaway, is often described as a one-in-9 quintillion change of winning, or 2^63rd power based on there being 63 games played by 64 teams in this single-elimination tournament. However, this model is obviously wrong since we know that some of these teams are better than others. Even the most casual NCAA bracket filler knows that a 1-seed (presumably one of the top 4 teams in the country) always beats a 16-seed (which is typically one of the worst 4 teams in the tournament). Similarly, a 2-seed almost always defeats a 15-seed with rare exceptions. After this point, the expectations start get a little trickier and the March Madness descends into full effect.

Even so, we know that top seeds tend to be safe well into the second week of the tournament. So, given that the NCAA games are not a pure coin toss, what are the real odds of filling out a bracket perfectly?

There are a few ways to go about this estimate. One is to go through historical data and look at how the NCAA bracket has carried out over time, then use the odds that each seed moves to the next round as the basis of a win expectancy at each round. This is the approach that the quant in me wants to take and it is definitely the most tempting way to go. However, a couple of basic problems keep me from taking that approach.

First, this approach lacks the specific context of how college basketball exists in 2014. Comparing NCAA tournament results from 50 years ago, when freshmen weren’t allowed to play college basketball and John Wooden’s UCLA Bruins owned the tournament to today’s world where “one-and-done” freshmen are often the best players on their team and talent is more distributed throughout the country seems to be an unfair comparison. Also, seeds are determined very differently, with power rankings, automatic berths, and decision makers changing on a year-to-year basis. The tournament today is very different today than it was even 10 years ago. In addition, we know that there are specific biases in seeding that seem to be errors, such as Louisville’s seeding as a 4-seed even as many experts believe that they are a top-4 team. These individualized biases make a deep longitudinal study an interesting historical exercise, but not necessarily the best predictive model.

Second, and more importantly, I’m on a plane right now and don’t have access to the numbers.

So, in the lack of true quantitative evidence, I created a simple qualitative model where I estimated the ability to choose the correct winner of each game. We can assume that almost everybody will bet on the 1 seeds to win the first round and be correct, so this initial assumption changes the odds from 1 in 9 quintillion to about 1 in 600 quadrillion. (Quicken Loans may as well just hand the money away right now…)

In my model, 1-16 game was a 99% chance of choosing the winner, a 4-13 game was treated as an 80% change of winning, while an 8-9 game or a semifinal or final game was treated as a 55% chance of picking the winner, since there’s almost always some level of information that shows that there is a favorite. Basically, as the talent differential gets smaller, the picks are increasingly due to chance. Put that together and the odds start changing significantly.

When I did this back-of-the-envelope calculation, I came up with much lower odds of 1 in 298 billion to get a perfect bracket. These odds are still astronomically high, but start to get closer to the real number. I’m sure that Warren Buffett went through a similar process, discounted this number significantly, then provided his insurance policy accordingly.

But this model has a flaw (now that I’m back on the ground in Orlando). It assumes that you will always choose the higher seed, whereas this isn’t always the case. Ed Feng of Grantland and Stanford identified a much better model that takes into account both the potential outcome that either the higher or lower seed would win. With his model, the odds are 1 in 4.5 billion. That’s still a really high number. In contrast, your odds of being killed by lightning are 1 in 280,000 (http://www.ehow.com/info_8607019_chances-being-hit-lightning.html). Yes, you’re 16,000 times more likely to be killed by lightning than to win.

So, how much would this policy for a billion dollars actually be? If you’ve got 15 million players for the billion dollar bracket, you’d expect a 1 in 300 chance to win. So, the back of an envelope approach says that you could expect to come out ahead by providing an insurance policy for a bit over $3 million.

You can start to play with the numbers a bit more to be more conservative, but it’s hard to price the maximum breakeven at much more than $5 million based on reasonable assumptions. A gut feeling says that Berkshire Hathaway probably felt comfortable with charging $5-$10 million as a policy for Quicken Loans. Based on Buffett’s philanthropic nature, let’s call it $5 million.

Now, for the next part. Does this make sense for Quicken Loans? According to Dan Gilbert, Quicken expects to get 15 million new leads from this process, meaning 15 million new potential customers for mortgages and other loans. Again, playing the back of the envelope card, assume that Quicken gets an average loan of $150,000 from each closed deal. Based on a 30 year loan, 6% interest and 3% inflation, Quicken gets about $98,000 in discounted interest. Add closing costs and let’s just say Quicken makes $100,000 per loan.

So, to break even on the insurance policy, all Quicken really needs to do is find 50 mortgages out of all of this. Can Quicken Loans convert 1 in every 300,000 qualified contacts into a mortgage? Probably so, based on their brand name and the assumption that their sales force knows how to qualify and close interested parties.

But in this context, all of the marketing around the billion dollar bracket suddenly makes more sense. Even if you include the marketing costs and all of the other effort that Quicken is putting into this, the end result is that they are getting millions of people’s verified contact information for what ends up being a small fraction of their potential value.

Now that you know the real numbers behind the Quicken bracket, the story changes considerably. The real story isn’t “Can you win a billion dollars based on a 1 in 9 quintillion chance of winning?” The real question is “Can Quicken Loans get, say, 250 new mortgages out of their marketing campaign to justify the marketing and insurance efforts they’ve put in place?”

And at the end of the day, everybody wins. Warren Buffett makes another 5 million dollars. Quicken Loans probably makes 50 million dollars. Yahoo gets its marketing money. And we all continue to get an online platform that helps us to continue our crack-like addiction with March Madness. Nobody loses. (Unless you’re a competing mortgage provider.)

Do HR Organizations Really Need Big Data?

Big Data Funnel
Big Data photo courtesy of hrringleader.

Over the past couple of years, the hottest trend in enterprise technology has been the evolution of HR applications from basic benefits, payroll, and workforce management to a variety of applications covering a much wider set of needs – from finding potential employees and predicting the need for specific skills to optimizing employee capabilities to the appropriate offboarding and succession of core talent. To get a strategic advantage, HR departments are being asked to use “Big Data” to “Moneyball” and quantify their approaches. But is this really the right way to go?

To determine this, consider what Big Data really is. Big Data is a set of technologies designed to store, process, and analyze data that does NOT fit into traditional spreadsheets, databases, and other basic structured data sources. Depending on whether you need your data to be faster, bigger, or more varied, you may be looking for specialized high velocity messaging solutions, cloud-based and multi-tenant storage, high performance analytic engines, Social Network Analytics, sentiment and natural language processing, or video analytics. This is the world of Big Data. A practical definition of Big Data would be 5+ terabytes of data, including some aspect of machine data, interactions, video, or high velocity streaming data.

In this context, is HR looking for solutions that can hold hundreds of terabytes of data and provide real-time analysis? Or are you really looking for some analytic insight for existing data? Chances are that you need a little bit of both depending on the maturity of your current HR data, the maturity of your current analytic capabilities, and your appetite for new and emerging technologies. But you should start with basic analytics and traditional data discovery tools before talking about Big Data.

For your current HR data, you have probably invested in some level of HRIS system to keep track of your employees and define your cost or profit centers. In addition, you have some level of workforce management to track hours worked and to seek what level of resources you have in-house to carry out key projects. This data, in and of itself, is already a wealth of data that is often underutilized to provide greater insight for your organization. As a basic example, consider that all of your employees have usernames and passwords for one or more applications, including email, ERP, CRM, document management, marketing asset management, and many other potential use cases. What happens when you start tracking your application usage on an employee-specific or department-specific basis? You may find out that you need to build a new office, or at least invest in new application licenses and network bandwidth, even before employees fully realize for themselves the extent to which their own work may be hampered or degraded.

Organizations that have invested more deeply into HR, training, market research, and succession management may have even more data regarding the skills of their employees, the ability to benchmark internal talent against readily available talent, and the relative volatility of performance for each position. The value of this data can quickly be increased by integrating tactical decisions and communications with higher-level KPIs to seek how the best employees work or if there are fundamental gaps that internal employees have relative to the market. This approach can also detect potentially troubling aspects in the organization, such as if employees start losing key skills or performance as they continue to work in an organization, or if they fail to learn skills at the same rate as the general market. This may indicate a need for cultural or development changes within the company.

It is important to realize, though, that these approaches are NOT Big Data, but a combination of data integration and analytics capabilities that likely exist already in mid-sized to large enterprise organizations. To get insight like this, start working both with IT and line of business executives to build out the potential value of these approaches and take advantage of the business intelligence initiatives that your company has built out for financial and operational insight. In fact, by being the visionary who understands how to bring human resource insights to a higher level, you may get the HR “Big Data” result you are looking for with just a bit of internal resource allocation. And given the choice of Big Results or Big Buzzwords, good HR professionals should choose results every time.

A Beginner’s Guide to Pinterest, 2014

Pinterest: Not Just B2C Anymore


Pinterest: Not Just for B2C Anymore

Pinterest is one of the fastest growing places to be on social media now, and there’s a lot you can do on it. If you’re thinking about starting a Pinterest account for your business, though, you’ll get more out of it when certain things are already in place:

  • a website on your own domain that Pinterest can verify. This will let you take advantage of Pinterest Analytics for all images hosted on your domain. With such a website, you can also implement rich pins, which will make pins of your content stand out on your followers’ Pinterest feeds.
  • prior content, especially content that can be hosted on your verified website. This includes images, slideshows, videos, audio recordings, reports or whitepapers, and blog posts (especially those with accompanying images; if you’re not already including relevant images in your blog posts, start thinking about doing so!).

As Jay Baer (no relation, as far as I know!) said, “Content is fire, social media is gasoline.” But what can you do if those parts of your content strategy aren’t ready yet? You can still get started on Pinterest!

  • Create your account. Fill out your bio and add an icon (ideally at a 160×165 resolution). Keep your bio simple, but readable; use keywords so that you can be found in Pinterest search but write for humans, not for Google search. Use your company logo for your icon, if you have one. The red and white pin icon is the Pinterest equivalent of the Twitter egg icon. It’s important to make your Pinterest page look like you’re participating in the community.
  • Follow relevant people and companies.You can connect your Twitter, Google+, Gmail, and Yahoo accounts to your Pinterest. This will let you see if any known-to-you colleagues are already on Pinterest. You can also use Pinterest’s search function to find new-to-you people and companies to follow. Type in relevant keywords and terms, click on pertinent results, and then you can choose to follow all of an account’s boards, or just specific boards. What are boards? More detail on boards in a little bit.
  • Be conversational. When somebody comments on something you’ve pinned, respond! If somebody you’re following posts an interesting pin, comment to their pin and participate in the discussion. A repin doesn’t necessarily require a response, but it’s worth paying attention to what the pinner is saying about your pin, especially if they’ve taken the effort to change the text you originally pinned with. You’ll get the most out of Pinterest by being social and community-oriented.

This is a familiar idea from our previous Twitter for Beginners post; create your account, follow, comment, share (whether by retweeting or repinning). The big difference: in order to share things on Pinterest, you need to create boards on your account.

What’s a board? A board is a collection of pins, usually created with a specific theme in mind. It can be run by just one account, or it can be a group board. There are boards for social media, big data, data warehouse, Platform as a Service. (The first three of these links have primarily relevant results. The last one, Platform as a Service, has a fair number of results, but not all of them are relevant. It’s a good opportunity for someone in the PaaS space to get in there and create a quality PaaS board!)

Following other companies’/peoples’ boards is good fodder for thinking about what sort of boards you’d like your account to have. What are others pinning? What kinds of boards are they creating? Who are they following? Does any of it resonate with the type of content your followers would like to see and the message you would like to share?

What should you share? Again, similarities between what you can share on Twitter and Pinterest; just slightly different approaches. You have more space in Pinterest descriptions (up to 500 characters); use it wisely to provide guidance and recommendations that you can’t provide on Twitter.

  • Share relevant things that you create. You can create boards specifically to showcase your own content; you can even pin said content to multiple boards. And you’re not limited to images – you can pin videos and slides, too. You probably have more images as part of your company content than you think – charts and graphics from existing whitepapers and blog posts, screenshots of your website or images of your product or service in action, photos from events, staff photos and bios.
  • Share relevant things that others create. You cement your business’ reputation as an expert in your industry, and you show that you’re a member of the community by pointing out when others have made awesome things. It’s also a great way to supplement your own content. Just be sure to credit properly generously share the wealth.

Once you’ve started pinning content to your boards, it’s also worth considering following some of the people who comment to your pins, and those who repin your pins. Look at their boards and take their comments to you in context – are these potential or existing customers? What do their interests tell you about them, and why your products and services are important enough to them to interact with you?

So if those are the similarities, what are the big differences between what applies to Twitter and what applies to Pinterest?

  • Images. On Twitter, image dimensions and orientation don’t matter that much, nor do you have to include an image with every tweet. On Pinterest, you cannot pin without including an image, a video, an audio file, or a slideshow. And tall images will display more prominently in Pinterest feeds than wide ones will. You do want to be careful with ultra-tall images such as some infographics – Pinterest will hide a portion of those images behind an “Expand Pin” trigger if they’re really long. Their proportions can also affect your followers’ ability to repin and to comment on those images – if your image’s width-to-height ratio is less than about 1:3, it may be too long for easy repinning. Still, infographics are quite popular on Pinterest.
  • Hashtags. Pinterest search does not currently support hashtags. Adding hashtags to your bio, board descriptions, and pins doesn’t help your account show up more in search results; it’s the keywords that matter. Make sure that you use appropriate keywords in your descriptions, and in the file names of your blog posts and associated media. Hubspot wrote a great guide to Pinterest SEO about a year ago (it’s the #1 Google search result for “Pinterest SEO”), but some things have changed since then – especially around hashtags. Their example of the #KnowlesChapel hashtag search only yields five results today; searching for the two words “Knowles Chapel” yields 104 results. Time for an update!
  • Using Pinterest on the go. With 75% of all traffic to Pinterest coming from mobile apps, there is a lot of pinning activity being done on phones and tablets! However, on mobile Pinterest, you cannot change descriptions of repins, or add your own description of pins of web content. So, be aware that many of your followers will likely be pinning on the go and only able to use your text description! The more complete your description, the more likely your pin will place high in relevant Pinterest search results.

So you’ve already set up your Pinterest account and are pinning, repinning, and conversing away, great! If you haven’t yet, get started – at last count (July 2013), Pinterest had 70 million users, and you probably have an opportunity to own your niche. If you’d like to learn best practices for using these tools, or have further questions, please contact us at connect@datahiveconsulting.com to schedule a free consultation.

The Power of One is the Future of Marketing

soccer ball
Soccer ball photo courtesy bigfeet98.

This morning, I saw an interesting press release from Informatica stating that they were working with Everton Football Club. So, I don’t usually care about specific press releases and I don’t follow the English Premier League, so why did I care?

What got my attention was that Everton is taking all of their data from their retail stores, website, marketing data, ticketing, and on-site systems to work on individualized marketing approaches. Everton believes that a top challenge is to maintain and grow personalized relationships with fans and this may be more true in sports than in any other vertical. After all, for those of us who are sports fans, we know that our relationships with our teams are personal and often lifelong. And, to be sexist, there are a lot of guys out there who don’t like clothes shopping, yet have taken time out of their day to buy a sports jersey!

But to be less flippant, there are also bigger ramifications here based on the Power of One. The Power of One is the basic idea that each person has a unique and special relationship with their social graph and their vendors and sources. It’s not a new concept, but it is one that has been superseded in recent years by a purely data-driven concept of marketing. There’s nothing wrong with data-driven activities: one of my hobbies on my business card is Moneyballing everything! But Everton’s use of data is interesting in that it takes the next step: using data to develop a more personalized relationship with each fan and getting back to the Power of One.

People make consumer decisions based on their personalized view of the world and not just from being part of a category, such as an 18-35 male fan making between 35,000 and 50,000 pounds. By understanding every single fan on a personal level, Everton is also going to be able to react to fan interest more quickly and provide new resources for fans as they are requested. That’s the key business imperative being met here: creating a more responsive and on-demand enterprise based on scalable cloud resources.

Both the Force.com based database and the Informatica Cloud integration and data management platforms are good choices in our opinion because that they will allow Everton to scale these efforts out as they use additional data sources and start using new inputs and channels to communicate with fans. Last year, Informatica had announced Informatica Vibe, a virtualization of their data machine to emphasize that Informatica data management could be rationalized, simplified, and cloud-enabled. But behind the marketing, it’s proof points like this that occur months after the flashy product announcement that provide greater insight.

At DataHive, we focus on Social Big Data for Human Insight. All three parts of that matter:

  1. You have to be social and participate with each person on an individual level.
  2. You have to use Big Data technologies both to scale your interactions and to increase the depth of interaction through video and educational materials. (In sports, an “educational material” might be a highlight film. Education doesn’t have to be boring!”)
  3. And you have to gain human insight, in this case by moving from a marketing approach of using demographic and psychographic information to focusing on the individual fan and the Power of One.

Ultimately, that’s what makes this announcement interesting to us as it represents the type of work that we have started doing with other clients. We both congratulate Everton FC on its marketing vision and look forward both deploying and documenting additional Power of One marketing efforts in the near future.

What Happens in Vegas is TDWI and the Future of BI


Las Vegas Sign photo courtesy Esquenta.com.br.

In late February, I had the pleasure of attending TDWI Las Vegas as an observer. A key differentiator between TDWI (The Data Warehousing Institute) and many of the other tradeshows I attend in the Big Data and Analytics space is that TDWI focuses on deep subject matter expertise taught by luminaries such as:

The quality of education leads both to a more informed end user audience, and to more interesting conversations in class, in the media room, and on the presenters’ floor compared to other shows that I attend.

In that context, I found it interesting to compare Jill Dyche’s keynote, “The New IT: How the Next Wave is Changing BI” with what I actually saw from presenters and sponsors to see if vendors are getting the message and how end users need to close the gaps.

Although you should watch all of Dyche’s great talk, there are several points that especially resonated with me.

First, although businesses have the challenge of changing with their employees and transforming their technology and infrastructure faster than ever before, there is a counterchallenge from IT, financial, and HR executives who may regard new technology deployments as little more than an excuse for resume building. New technologies can be viewed as an attempt by employees to simply build their own skills for their next job, rather than as a capability that will improve corporate outcomes.

This mindset towards technology is indicative of the traditional world of IT where you can “set it and forget it,” and technology assets are seen as permanent investments. However, this “old world of IT” attitude is less relevant to business than it ever has been before. As technological evolution accelerates and corporate pressures increase, companies must stay nimble and be willing to try new solutions that will scale and include the insights that companies need on a forward-facing basis. Dyche recommends including new data or functionality every 3 to 4 months in your BI environment as part of this process.

Second, BI maturity currently has less to do with technology and everything to do with delivery. DataHive believes that there is a new era of business intelligence arriving where network analysis, data topology, contextual sentiment analysis, facial and video analysis, metadata creation and curation, cognitive intelligence, dynamic visualization, sensory inputs, and advanced data engagement will augment traditional quantitative and statistical analysis. However, we are still a few years away from an environment where all of these tools are readily available since these are admittedly future-facing capabilities. (As a hypothetical example, consider that humans can smell one part per billion of certain compounds. This would be considered a “Big Data” detection issue for traditional visual and analytic tools, but we take it for granted as a sensory ability.) Current analytic environments are still best served by providing the analytic tools that have existed over the past 30 years to a broader end user audience that is seeking greater insight from data.

Third, business is getting its own IT funding and Millennials have less patience than previous generations. Both of these trends demonstrate the desire for departments and individuals to take control of their own IT, rather than wait for direction and guidance from a centralized IT function. These trends lead to a business environment that seeks faster delivery for personalized and specific functionality. For business end users, it is much more important to support specific needs than to implement a platform that supports holistic enterprise needs. Although we may solve this challenge with a platform, we also need to identify and enable the point capabilities that will end up supporting our key users.

Because of this change in technology, Dyche pointed out, “who thinks IT is strategic anymore?” CIOs want to shed commodity technologies that they are known for supporting. Strategically and selfishly, we all know that once our skills and responsibilities become commoditized, we are no longer critical to the success of our company. Anyone who has ever been outsourced or laid off can understand this pressure very personally; CIOs are no different from anyone else in trying to avoid this trend. In today’s environment, strategy and culture drive CIO decisions more than traditional technology. This means that CIOs have to be service brokers and service integrators simply to stay current. The broker model is no longer a strategic differentiator; it is now table stakes for CIOs. Technology is ubiquitous. It makes no sense to fully centralize IT.

Fourth, IT-business alignment is more important than ever, but it is also more of a cliche than ever. Every IT department claiming that they do it, but many are just providing lip service without putting appropriate business criteria in place to assure alignment. In Dyche’s key note, she spoke about a regional bank CIO that made this alignment concrete by defining four basic criteria for new projects: decrease cost structure, increase customer satisfaction, increase customer acquisition, or increase revenue per transaction. Any project outside of those goals would not get funded. This is the other side of new IT: in addition to being personalized, it also has to affect top-line or bottom-line growth. We no longer live in a world where technical excellence or academic curiosity can drive big technology projects. There has to be a business initiative that drives analytics and technical projects. You can be a profit center or a cost center: choose to be a profit center.

So, given these key trends, how did the vendors compare to both this vision and presentation of the future of IT and analytics? I’ll tell you who stood out to me both based on product and end user reactions later this week.

Social Strategy: Look Up and Look Down

Flying to Vegas

Social Strategy from Milwaukee, Chicago, and the stars

One of the downsides of being a technology “expert” is the constant travel from show to show as I meet with vendor executives and corporate IT managers to keep on top of the latest trends, offerings, and use cases in social, analytics, mobility, and the cloud. It means a lot of time away from doing hands-on work and away from my chosen developer and line of business technology user communities.

But even so, I’ve never quite gotten over the miracle of air travel. The photo for this blog is a picture of Jetblue 777 to Las Vegas while flying over Milwaukee, with Chicago out in the distance. And all you see are lights upon lights upon lights. For all of the crazy things that we do as humans, we are the species that literally lights up the earth. (My alma mater, Amherst College, would be proud as our motto is “Terras Irradient”, which literally means to light up the earth.)

To create these concentrations of light, which are readily visible from space, takes immense amounts of power, miles and miles of transmission cables and wiring, and thousands, if not millions, of hours of manpower to take care of these oceans of lights. We take it for granted every night that we see a streetlamp go on or work extra hours in our offices and homes, but up here at 34,789 feet, you start to see the scope of just how immense this network of light can be.

And that’s just what you when you look down. When you look up, you can see something even more amazing on clear nights. The stars are just a bit brighter up here and each little pinprick of light typically represents a star larger and brighter than the sun that has traveled for hundreds or thousands of years just to get to us in that very moment. The power needed to make that little spot of light is greater than exists in our entire solar system, yet all we see is a tiny twinkle that we might miss from night to night if we blink or never look up.

Looking up and looking down, I think of two different phenomena that we don’t always take advantage of as social creatures. In looking down, it is easy to just think of the light that we see outside our own doors and to ignore the infrastructure that makes this all possible. Instead of just trying to think of how to make our own individual lights brighter, think about the big picture: how do our lights get there and how are they connected? And how do we bring our individual lights come together? That is when our light burns brightest; when we take advantage of the power of being together and learn the specific characteristics of what strengthens networks and when we make sure that these networks stay together,

And in looking up, stars are so powerful that they help in unexpected ways. It’s highly unlikely that these stars were designed expressly to provide directional guidance for the lifeforms on a plant thousands of light-years away, but when you burn brightly enough and seek to inspire, you can affect other people in unexpected ways. From my perspective, this is the value of fame. Fame for its own sake is, frankly, pretty meaningless. It is only when fame is used to inspire, guide, and change the world that fame really becomes useful. Likewise, it’s easy to get carried away in yet another Like or another retweet, but social fame only means something if it helps people out. Getting 1,000 retweets for acting like a drunken fool may be entertaining, but it doesn’t make you a star with enduring value. We as a “social” society get caught up in the ephemeral nature of social shares rather than providing meaningful insight, especially in the social marketing world. But in today’s day and age, marketing is fundamentally about educating, not about going viral.

So, as you think about how to make a difference, think about looking down and looking up. Build networks and provide guidance and inspiration. Light up the earth and be a star. By keeping those simple thoughts in mind, you can avoid the pitfalls of this increasingly connected world we live in, stay grounded, and use technology to help others.

Look up, look down, and be social.