See Data, Feel Data, Touch Data...for free?

Much has already been said about the growth of free alternatives to Microsoft Office - between Google, Zoho and others, the competition leads predictably to questioning the incumbent as well as continued innovation from Redmond.

Meanwhile, Google may also be seeking to make a dent in the area of data visualization. Building on last year's acquisition of Gapminder's Trendanalyzer, Google released a data visualization API, essentially a platform to create interesting displays based on structured data stored in Google Docs.

Initially, there's simply a "cool" factor at work here - "If I could get that salary list, I could post a piles-of-money gadget around the office!" But are there competitive implications? It's interesting that for as many years as it's taken for real on-line competition for Office to emerge, there could be a viable alternative in the much younger data visualization space much sooner.

There are so many questions - What are Google's long-term intentions in this space? Will it be a drag for the leading BI vendors, or will it help popularize the concept and "raise all boats"? Will Google's experience in search engines mean we can expect it to lead the way with unstructured data visualization?

Deregulation of Utility Computing and my Gmail account

I may be jumping the gun on this one a bit since there isn’t as of yet a “Computing Utility” the way natural gas, telephone and electricity are currently piped into my home. Thus, there is no need to deregulate the industry the way the natural gas industry was in the 1980s. But will there be?

Google last week announced their foray into utility computing with their Google App Engine. Google is opening up their computing horsepower to allow scalable, web-based application development for anyone. And it’s free. They aren’t the only ones doing providing utility computing. Amazon has been providing a similar platform called Elastic Compute Cloud (EC2) for a “resizable” computing capacity cloud and their Simple Storage Service (S3) for inexpensive storage services.

The idea of utility computing has been batted around as an idea for a while, but Nicholas Carr’s book “The Big Switch” makes an interesting correlation with the switch manufacturers made 100 years ago from providing their own electricity to tapping into the expanding power grids. Carr makes a compelling case that this is the direction of computing for businesses and consumers.

If you aren’t familiar with Carr, he is a bit of a lightning rod in the IT industry based on his controversial point of view of IT. He was just named #93 on the Ziff Davis Most Influential People in IT. Not everyone necessarily agrees with Carr’s view of IT, but he has forced the industry to take a look in the mirror and question the value being provided.

So you may be asking yourself, what does this post have to do with DIG and why did I start on the topic of utility computing? Honestly, there is not direct relationship beyond I have been having some “constructive” budgetary discussions with a client around disk storage sizing. When I got home tonight I asked myself “This has to be easier”, thus my research on utility computing. Why is it that I can get 6.6 gigabytes of free storage from Google for my email but not enough storage for a data mart? (btw – this is a hypothetical question and doesn’t need to be answered via a comment).

(sigh)

Prediction Markets Explained

Last week, Mark Lorence posted a topic for discussion on prediction markets and questioned if it would have been an effective tool for British Airways in the opening of the T5 terminal in London. I wanted to provide a quick follow up, as the topic of prediction markets was in the NY Times yesterday with references to different organizations that are using them to predict sales forecasts, store openings and project completion dates.

If you have an interest in the software and services companies who provide platforms to facilitate a prediction market, you should check out Inkling Markets, Consensus Point and NewsFutures. Each company provides the technology and infrastructure to setup and manage prediction markets. To give you a sense of the type of problems that a prediction market can be used for take a look at the Inkling Markets home page. They have examples such as "Improve Forecasting of Performance Indicators", "Expose Quality Problems" and "Predict Risk in Your Supply Chain". All real issues that many organizations need to address.

If you want to see how a prediction market may work for something like sports, politics or weather, I would recommend taking a look at TradeSports.com. You could argue this is simply a gambling website since the trading is performed with real money, but if you look a little closer you will find some interesting information. For example, according to the current "2008 Democratic Presidential Nomination", the current trading price for Barrack Obama is 85.5, which means that 85.5% of the market predicts that he will be the democratic nominee. In other words, the "market" strongly believes he will be the nominee. If I were to purchase options at this price and he were nominated, I would earn $14.5 per block of shares ($100 - $85.5) I purchased. If he did not receive the nomination, I would lose my entire investment since the value would be $0 when the market expires, which should be August 28th at the DNC.

Bo Cowgill from Google, who is a speaker at the DIG 2008 conference, runs Google's internal prediction markets. He is also an expert on the topic and operates his own blog on the topic of prediction markets. Also take a look at Midas Oracle. We are looking forward to hear Google's story from Bo at the conference.

One interesting side note is that there is a market on TradeSports.com for Google's Lunar X project and if it will be won on/before 12/31/2012. The current price is 24.3.

In Search of BI Mashups

An area that has had a tremendous impact on the consumer aspect of the web is the concept of a “mashup”. The history of the term goes back to DJs and mixers combining different songs together to create new music. The term has evolved to more generically represent an application that is built by combining two or more data sources (if this isn’t the definition of a business intelligence application, I am not sure what is). The Senior Director of Engineering at Adobe put it best when he said

“a lot of talk about Web 2.0, web mashups, Ajax etc., which in my mind are all facets of the same phenomenon: that information and presentation are being separated in ways that allow for novel forms of reuse.” - Sho Kuwamoto

The same statement can be applied to enterprise data…separate the organization’s data from the different ways it can be presented. Where mashups come into play is when enterprises start presenting this data beyond grids and charts. In addition, as I have discussed on this blog, enterprises can combine traditional and non-traditional data sources to provide further context. Thus, the case for BI mashups.

If you perform a quick search for examples of BI mashups, you primarily find sample applications from different BI platform vendors. The first example I came across was from open source BI vendor Pentaho, which combines sales data with Google Maps to plot customer performance. Additional examples from Information Builders and Oracle offer similar examples. The trend with the majority of these examples is that they plot spatial data into geographic maps to show enhanced visualization. Not quite what Tufte would recommend, but certainly an enhancement over traditional BI. Adding non-structured data into the mix such as blogs and customer surveys through RSS feeds would enhance the experience even more.

For the technical audience, here is a very in-depth article by Larry Clarkin and Josh Holmes on mashups including examples, architectural components and key considerations when developing your first enterprise mashup. There is a wealth of information within the article, but one of the key elements applicable to a BI mashup is providing “rich visualization of data” for users that they won’t get from a typical chart or grid of data. If you are considering your first enterprise mashup, I would get familiar with this article as a first step.


There are some great resources available if you are looking for more examples of mashups. The most well known site is Programmable Web, which tracks interesting mashups, Web 2.0 applications and new web platforms. And if you have a short attention span and would prefer to see a video, check out this YouTube video.

A New Type of CIO

I read an interesting article last week in the Wall Street Journal about Douglas Merrill, Google's Chief Information Officer. To say the least, Merrill is not your typical CIO. Granted, Google is not your typical type of organization. Here are a few snippets and comments from the article that I found interesting.

"Mr. Merrill's group lets Google employees download software on their own, choose between several types of computers and operating systems...."

This isn't totally off the wall, but certainly unique. They are a company focused on innovation and technology, so it isn't surprising that they wouldn't "constrain" anyone from getting the resources they need.

"We're a decentralized technology organization...Google's model is choice. We let employees choose from a bunch of different machines and different operating systems, and [my support group] supports all of them. It's a bit less cost-efficient - but on the other hand, I get slightly more productivity from my [Google's] employees."

The decentralization and the idea of choice certainly go hand in hand. The cost-efficiency comment is interesting and it doesn't sound like something that they necessarily quantify. I also assume that Mr. Merrill is being extremely sarcastic when he says he gets slightly more productivity out of Google employees. Based on the number of tools that Google produces for consumers, I would say that they are quite productive and innovative. I made the comment the other day to someone that I can't keep up with all the new things that they constantly release! On the topic of security, Mr. Merrill had the following response.

"The traditional security model is to try to tightly lock down end-points...we put security into the infrastructure. We have programs in our infrastructure to watch for strange behavior."

"When I talk to Fortune 100 CIOs, they want to understand, 'What is your security model? Is it really as reliable? What's the catch?' I already had to build security standards because search logs are really private. Very few [Google employees] have access to consumer data, [and those who do] have to go through background checks."

What I find most interesting about Mr. Merrill's comments is the fact that fortune 100 CIOs immediately have questions about security, primarily because of Google's approach to employee "choice". Google has shown that they can provide a best-of-breed infrastructure that is stable and secure. My guess is that most CIOs struggle to successfully provide a decentralized environment without ending up on the front page of the newspaper because their systems have been
compromised.

The last comment I will make about Mr. Merrill is that he has a fascinating academic background, especially for a CIO. He studied social and political organization at the University of Tulsa and a masters and doctorate degree in Physcology from Princeton University. His IT knowledge came through practical experience at RAND, Price Waterhouse and Charles Schwabb. Certainly politics and physcology play into the role of a successful CIO.

When I look at Google's approach to information technology and management, their approach is around the principles of the organization: decentralized, autonomy and a focus on innovation. Those principles may not make sense for every organization, but they clearly work for Google. Do I think that every physcology major is going to be the next CIO at company XYZ? No. Do I think that there are lessons to be learned from Google and Douglas Merrill, absolutely.

If you are interested in listening to Mr. Merrill speak to how Google eats their own dog food, take a look at the YouTube video below. He and CEO Eric Schmidt discuss how they use Google Apps internally in an effective and collaborative manner while meeting business and consumer needs, including security. Google Apps is a great example that relates back to the three themes of DIG: having organized and accessible data, providing robust analytic tools, and providing a massively collaborative environment.

Comments are welcome. I would be interested to hear related experiences and if you feel that IT is helping enable your business the way that Google is enabling theirs.

E2.o as the Catalyst for Organizational Evolution

Last month, Fast Company’s Fast 50 highlighted Google as the top selection in their list of the world’s most innovative companies. This past weekend, I read through Harvard Business Review’s April 2008 cover story titled Reverse Engineering Google’s Innovation Machine by Bala Iyer and Tom Davenport.

Noting these two recent cover stories from two of the more popular business management periodicals of our day, I would say that Google has captured the attention of the best of today’s business management minds. We are preoccupied with the company because they are unflinchingly trying (successfully at that) to manage complexity using a nontraditional management approach - an approach which encourages flexibility and widespread experimentation in the face of chaos. The HBR article goes on to highlight six traits that Google has embraced to “Build Innovation into Organizational Design”.

The article states, “Innovating on internet time requires dynamic capabilities to anticipate market changes and offer new products and functions quickly. Google has made substantive investments in developing the capacity to innovate successfully in this fast-changing business environment. The company is pioneering approaches to organizational culture and innovation processes …”

One of the six traits that the article highlights is Google’s ability to “Use Data to Vet Inspiration”. The company is known to be very analytical but the article cites their advanced use of both internal prediction markets (300) and an idea management system to vet their thoughts. Google is using the foremost of E2.o tools to democratize the management input process and to fully harness the intellectual capital of their entire company.

This makes Google very interesting to me. First because I am an advocate of E2.o and want to study any business that is attempting to incorporate social computing to augment business management!

However, the second reason is because I want to understand Google’s management approach, itself - a unique culture that encourages innovation - or adaptation. To this point, I refer to Eric Beinhocker’s book, The Origin of Wealth, in which he expounds on organizational adaptation. In our world of increasing complexity, we must use all of the information available to us as a means to educate our organizations to the evolving dynamics of the marketplace. Only by understanding one’s changing market does an organization stand the chance to survive and adapt to the next generation. This organizational learning is fueled by equipping all aspects of a business to “exploit and explore” their interactions within their current marketplace.

Briefly, I see E2.o tools as the catalyst to our getting to this fully-enabled next generation approach to business management. With E2.o tools, our organizations can harness, prioritize, and make sense of all of the information that is bombarding us on a daily basis. By doing so, we can begin to adapt continuously. Google may actually be leading the charge on something quite remarkable.

Join the dialog. What do you think?

(As an aside, Google will be joining us this May at DIG2008. I am excited to hear from Bo Cowgill on the company's use of internal prediction markets. Check out the short case study overview.)

R. Todd Stephens, Bo Cowgill and Euan Semple to Speak on Enterprise 2.0 at DIG 2008

I am pleased to announce that R. Todd Stephens, Bo Cowgill and Euan Semple will all be speaking on the topic of Enterprise 2.0 at DIG 2008. Each will be presenting case studies from organizations where they have adopted E2.0 for competitive advantage.

R. Todd Stephens, who is a Senior Technical Architect at AT&T, will discuss AT&T's success with adopting collaborative and social technology. R. Todd's case example will present a 3-tiered program to adopt social platforms and how AT&T has shown business value as adoption grows within the organization. R. Todd has also been actively participating on the Talk DIG blog, which we like to see!

Bo Cowgill, an Economist at Google, will be speaking about Google's use of internal prediction markets. Google has the largest corporate implementation of prediction markets, which they utilize to capture the "wisdom of crowds". If you aren't familiar with the topic of mass collaboration, James Surowiecki wrote the book Wisdom of Crowds, which makes the case that in the proper setting, large groups of people can make better decisions than individual experts. Google is using markets internally to identify winning project ideas based on how employees trade options on the success or failure of a project.

In our final case study Euan Semple, a social computing advisor, will discuss how the BBC has established in an internal social network to improve efficiency and increase innovation. Euan will discuss what tools the BBC leverages to improve collaboration and communication that impacts the corporate culture, individual behaviors and provide the ability to get things done! The BBC has leveraged this platform to even extend the conversation beyond the four walls of the organization and make everyone a marketer for the BBC. Euan also blogs on the topic of social networks and technology at the aptly named "The Obvious?".

We are excited to have R. Todd, Bo and Euan speak about their experiences in knowledge in the area of E2.0.