I attended a presentation by Jeff Kaplan of Thinkstrategies two weeks ago titled "SaaS today and in the future". He provided a convincing case that SaaS is a reality today. Furthermore, the market is driven by genuine user needs and changing preferences. SaaS/Managed Services may replace but can also augment existing processes. For SaaS, service reliability, lower TCO and greater ROI are critical. He advised companies to think strategically, but start small and expand incrementally.
Thinkstrategies has created a web-site that has a list of over 1900 SaaS companies in 80 application and industry categories. The gorilla among these is of course Salesforce.com.
Check out Thinkstrategies web-site for lots of insights and news, and Jeff Kaplan's blog is not only an excellent font of ideas, but also lists several other SaaS blogs.
Wednesday, December 12, 2007
Sunday, November 25, 2007
SaaS makes sense in many cases
As Robert Preston points out in this Informationweek column Software as a Service is making sense not only for such applications as CRM and ERP, but also for system management, Business Intelligence and Supply chain management.
Gartner predicts that 25% of all business software will be delivered as a service by 2011, up from 5% today.
Gartner predicts that 25% of all business software will be delivered as a service by 2011, up from 5% today.
Saturday, November 24, 2007
End of the best of breed in BI software firms
Business Intelligence software is hot. This year, three of the best-known BI companies have been scooped by the giants. Oracle acquired Hyperion, SAP is buying Business Objects and IBM this announced this month, that it is adding Cognos to its string of acquisitions.
The software industry is now dominated by these giants - Microsoft, IBM, SAP and Oracle (excellent Business Week piece). Only SAS, Microstrategy and Teradata are left among the best of breed BI companies.
The software industry is now dominated by these giants - Microsoft, IBM, SAP and Oracle (excellent Business Week piece). Only SAS, Microstrategy and Teradata are left among the best of breed BI companies.
Monday, November 5, 2007
Sugar Daddy post on Craiglist has legs
This was my post on October 10: "I believe that "Freakonomics" has sold 3 million copies worldwide. The authors, Levitt and Dubner are keeping up their creative output with their blog, and I don't miss glancing at it with my morning coffee. This entry from yesterday, although borrowed from another source (Craigslist) is a hoot. Enjoy!"
Whether the Craigslist ad itself is a creative piece of copy (i.e.fake), and even though the response may be a bit sexist, you have to agree that it is quite funny and well-written. There is even some economic analysis in the response cited in the Freakonomics post.
I hear the post has found wide readership in New York and especially on Wall Street. Furthermore, the story has been picked up by some media heavyweights from the Times to the BBC News to Scientific American.
A friend of mine checked out the original Craigslist ad. He found several other humerous responses to the lady looking for a Sugar Daddy.
Readers: If you read anything funny, and even if it has a smidgen of economics, please share it by posting the link as a Comment on my blog.
Whether the Craigslist ad itself is a creative piece of copy (i.e.fake), and even though the response may be a bit sexist, you have to agree that it is quite funny and well-written. There is even some economic analysis in the response cited in the Freakonomics post.
I hear the post has found wide readership in New York and especially on Wall Street. Furthermore, the story has been picked up by some media heavyweights from the Times to the BBC News to Scientific American.
A friend of mine checked out the original Craigslist ad. He found several other humerous responses to the lady looking for a Sugar Daddy.
Readers: If you read anything funny, and even if it has a smidgen of economics, please share it by posting the link as a Comment on my blog.
Saturday, October 27, 2007
The Long Tail theory
Lately, I have become a fan of the "Long Tail" and am looking for its application in various business models.
The phrase "Long Tail" was first used to describe certain business and economic models by Chris Anderson in 2004. Examples are Amazon and Netflix. These are businesses with the distribution power to sell a greater volume of otherwise hard to find items at small volumes than of popular items at large volumes. The term Long Tail is also generally used in statistics, for example to display wealth distributions.
From Chris Anderson's blog: The Long Tail
The Long Tail, in a nutshell
The phrase "Long Tail" was first used to describe certain business and economic models by Chris Anderson in 2004. Examples are Amazon and Netflix. These are businesses with the distribution power to sell a greater volume of otherwise hard to find items at small volumes than of popular items at large volumes. The term Long Tail is also generally used in statistics, for example to display wealth distributions.
From Chris Anderson's blog: The Long Tail
The Long Tail, in a nutshell
" The theory of the Long Tail is that our culture and economy is increasingly shifting away from a focus on a relatively small number of "hits" (mainstream products and markets) at the head of the demand curve and toward a huge number of niches in the tail. As the costs of production and distribution fall, especially online, there is now less need to lump products and consumers into one-size-fits-all containers. In an era without the constraints of physical shelf space and other bottlenecks of distribution, narrowly-targeted goods and services can be as economically attractive as mainstream fare ". The graphical representation looks like this:
Thursday, October 25, 2007
Regression Analysis and Randomized Experiments
It has been a while since my last blog entry. Frankly, I missed blogging.
Needless to say, only regular blogs with interesting content get read. So, I will have to become more disciplined.
In this blog, over the past two months, I have made reference to two very useful and interesting books, Tom Davenport's "Competing on Analytics" and Ian Ayre's "Supercrunching". Prof. Davenport's book was first out of the gate in early March 2007 while Professor Ayre's book came out in August. In a recent entry his own blog, Professor Davenport has brought out some good points about Supercrunching. Two analytical techniques that are quite useful and get some space in Supercrunching are Regression Analysis and Randomized Experiments. And of course, the main take-away, for me, are the many good examples of data mining that have worked.
Needless to say, only regular blogs with interesting content get read. So, I will have to become more disciplined.
In this blog, over the past two months, I have made reference to two very useful and interesting books, Tom Davenport's "Competing on Analytics" and Ian Ayre's "Supercrunching". Prof. Davenport's book was first out of the gate in early March 2007 while Professor Ayre's book came out in August. In a recent entry his own blog, Professor Davenport has brought out some good points about Supercrunching. Two analytical techniques that are quite useful and get some space in Supercrunching are Regression Analysis and Randomized Experiments. And of course, the main take-away, for me, are the many good examples of data mining that have worked.
Wednesday, October 10, 2007
Finding a mate using economic analysis
I believe that "Freakonomics" has sold 3 million copies worldwide. The authors, Levitt and Dubner are keeping up their creative output with their blog, and I don't miss glancing at it with my morning coffee. This entry from yesterday, although borrowed from another source is a hoot. Enjoy!
Friday, October 5, 2007
Google, Power and Transperency
"Who is afraid of Google" is the cover story in the Aug. 30, 2007 issue of The Economist. It is a superb article. We all agree that Google is in the data business: Between your search history (Google search), your mail (Gmail), browsing history (Google toolbar), your financial transactions (Google payments), your blog habits (Blogger) and all other behaviors reported by Adsense cookies and Google analytics, it can be argued that Google has a "complete" view of many of our online behaviors. It is becoming the custodian of a wide and intimate range of information about individuals.
We will soon find out what society will tolerate.
We will soon find out what society will tolerate.
Evidence-based medicine
A fascinating book I recommend is Jerome Groopman's How Doctors Think? Maybe you are wondering why am I mentioning it in this blog. Well, there is a connection to Analytics.
Dr.Groopman believes that today’s physicians are increasingly encouraged to behave as if they were computers, and to reason from flowcharts and algorithms. This is intended to produce better diagnoses and fewer errors; it is also embraced by insurance companies, who use it to decide which tests and treatments to approve. This approach can be useful for “run-of-the-mill diagnosis and treatment — distinguishing strep throat from viral pharyngitis, for example,” Groopman writes. But it can be limiting for difficult cases.
Another observation: Why are doctors such good writers? Atul Gawande and Michael Crichton are two names that come readily to mind. Dr. Groopman himself writes regulary for The New Yorker. Check out his web-site which has links to many of his pieces and to his blog.
Dr.Groopman believes that today’s physicians are increasingly encouraged to behave as if they were computers, and to reason from flowcharts and algorithms. This is intended to produce better diagnoses and fewer errors; it is also embraced by insurance companies, who use it to decide which tests and treatments to approve. This approach can be useful for “run-of-the-mill diagnosis and treatment — distinguishing strep throat from viral pharyngitis, for example,” Groopman writes. But it can be limiting for difficult cases.
Another observation: Why are doctors such good writers? Atul Gawande and Michael Crichton are two names that come readily to mind. Dr. Groopman himself writes regulary for The New Yorker. Check out his web-site which has links to many of his pieces and to his blog.
Sunday, September 30, 2007
Business by numbers
Whenever I get the chance, I like to read The Economist magazine. The September 15th issue has this fascinating article on Using Algorithms in Business. A key theme of the piece is that the speed and processing power of computers translates into executing tasks with blinding speed using vast amounts of data.
These are few of the several interesting examples of the use of algorithms from the article: Logistics planning at UPS; handling customer calls at call-center operator Convergys; routing information on the Internet; the Queuing of departing planes at an airport....
These are few of the several interesting examples of the use of algorithms from the article: Logistics planning at UPS; handling customer calls at call-center operator Convergys; routing information on the Internet; the Queuing of departing planes at an airport....
Saturday, September 22, 2007
Global Incident map
I found this Mashup thanks to an entry in Vinnie Mirchandani's blog ( see link to the right). I will have more examples of cool mashups when I return after a hiatus of a few days.
Mapping people's tastes
Analytics is invading the area of soft stuff, thanks to the web, and here is the latest example: The Internet startup, Matchmine, is trying to turn user's preferences into a usable set of data. There is some smart money behind Matchmine. The Kraft Group, well known as the owners of the New England Patriots, is sinking $10 million into this venture.
Thursday, September 20, 2007
In Regressions We Trust
In the introduction to his book, "Super Crunchers" (see blog entry from a few days back), Ian Ayres leads off with the story of Orley Ashenfelter. Ashenfelter crunches numbers. Using decades of weather data, he found that low levels of harvest rain and high average summer temperatures produced the greatest Bordeaux wines.
In fact, he reduced his theory to a formula:
Wine quality = 12.145 +0.00117 winter rainfall + 0.0614 average growing season temperature - .00386 harvest rainfall. Guess what? He has been very accurate, predicting that the 1989 vintage would be the best in a long time and 1990 would be even better.
Bill James did the same thing for baseball, as explained in Michael Lewis's "Moneyball".
In newspapers, where I have worked, some publishers have had success in finding causal relationships between various factors such as the weather, sports team's success and so forth to predict store and vending machine sales. And they are using these models to plan their newspaper distribution.
Ayres concludes that in field after field, "intuitivists" and traditional experts are battling Super Crunchers, and that is a big part of his book.
In fact, he reduced his theory to a formula:
Wine quality = 12.145 +0.00117 winter rainfall + 0.0614 average growing season temperature - .00386 harvest rainfall. Guess what? He has been very accurate, predicting that the 1989 vintage would be the best in a long time and 1990 would be even better.
Bill James did the same thing for baseball, as explained in Michael Lewis's "Moneyball".
In newspapers, where I have worked, some publishers have had success in finding causal relationships between various factors such as the weather, sports team's success and so forth to predict store and vending machine sales. And they are using these models to plan their newspaper distribution.
Ayres concludes that in field after field, "intuitivists" and traditional experts are battling Super Crunchers, and that is a big part of his book.
Friday, September 14, 2007
Did Belichick go too far with Analytics?
Even if you are not a football fan, by now you have probably heard about videogate. The NFL expressly prohibits a team from video-taping on the field. Alas, My hometown team, the three-Super Bowl powerhouse, the Patriots, got caught last Sunday against the Jets, despite the fact that they had been warned. Coach Bill Belichick and the team have been punished severely, and the coach for his part, has taken full responsibility and apologized to the team, the owners and the fans.
What does this have to do with Analytics? I mentioned in a previous entry that Tom Davenport's in his excellent book, "Competing with Analytics" cites the Patriots and the RedSox (baseball) as big disciples of using Analytics on the field and to run their business. ( See this CIO feature article by Davenport ).
Teams routinely have staff on the sidelines trying to decipher the hand signals the opposing team's coaches are using to instruct the players on the field. All part of the game to get an edge. Every team does this. But using the the video-tape with the formations on the field as the game is progressing can provide a team with more accurate data and an advantage.
Now, there is some question whether the Patriots have been successful in doing this for the game in progress, or is Belichick so data-driven that he just wanted to add more data to his vast database to analyze and use in future games. In this case, the information gleaned is the specific hand signals a particular coach is likely to use. After all, the Patriots meet the Jets at least twice each year. Last year, they also met in the playoffs.
Perhaps, more teams have been video-taping on the sidelines. But Belichick got caught.
What does this have to do with Analytics? I mentioned in a previous entry that Tom Davenport's in his excellent book, "Competing with Analytics" cites the Patriots and the RedSox (baseball) as big disciples of using Analytics on the field and to run their business. ( See this CIO feature article by Davenport ).
Teams routinely have staff on the sidelines trying to decipher the hand signals the opposing team's coaches are using to instruct the players on the field. All part of the game to get an edge. Every team does this. But using the the video-tape with the formations on the field as the game is progressing can provide a team with more accurate data and an advantage.
Now, there is some question whether the Patriots have been successful in doing this for the game in progress, or is Belichick so data-driven that he just wanted to add more data to his vast database to analyze and use in future games. In this case, the information gleaned is the specific hand signals a particular coach is likely to use. After all, the Patriots meet the Jets at least twice each year. Last year, they also met in the playoffs.
Perhaps, more teams have been video-taping on the sidelines. But Belichick got caught.
Thursday, September 13, 2007
Is Intuition losing ground to data mining?
I am still reading Tom Davenport's "Competing with Analytics". Now comes this book mentioned in last week's Newsweek: Ian Ayres' "Supercrunchers". Add this book to my reading list.
Ayres' thesis is that increasingly, expertise and intuition will be replaced by objective, data-based decision making, made possible by virtually inexhaustible supply of inexpensive information.
Do Amazon's computer's know what we'll like even before we figure it out for ourselves. A couple of examples in the Newsweek article are intriguing: - Are some auto dealers already using data to calculate just how far they can push their customers on price and loan rates? - Are airlines using an algorithm to predict which customers are most vulnerable to being lured away by a competitor and give them, not the airline's own customers, priority in rebooking?
Think of examples in your own business? Your thoughts?
Newsweek also provides a book review
Ayres' thesis is that increasingly, expertise and intuition will be replaced by objective, data-based decision making, made possible by virtually inexhaustible supply of inexpensive information.
Do Amazon's computer's know what we'll like even before we figure it out for ourselves. A couple of examples in the Newsweek article are intriguing: - Are some auto dealers already using data to calculate just how far they can push their customers on price and loan rates? - Are airlines using an algorithm to predict which customers are most vulnerable to being lured away by a competitor and give them, not the airline's own customers, priority in rebooking?
Think of examples in your own business? Your thoughts?
Newsweek also provides a book review
Wednesday, September 12, 2007
More on Web 2.0
The term Web 2.0 has been with us for almost three years. The publisher, O'Reilly introduced the term at the first Web 2.0 conference in 2004. This excellent O'Reilly piece points out that by Sep. 2005, Google had more than 9.5 million citations for Web 2.0.
An excellent example of Web 2.0, which is often cited is that Britannica Online is Web 1.0 while Wikipedia is Web 2.0. Another example we are all familiar with is the personal web-site versus blogging.
I think a quote from this 2005 Wired article puts it well: " Web 1.0 was commerce; Web 2.0 is people". Among other qualities, Web 2.0 sites harness collective intelligence, customer self-service, and a light-weight user interface.
For a quick summary, this Wikipedia entry is good. Some Web 2.0 features have been present in web applications even before the term was coined: for example Amazon allowed customers to write reviews. And there are no real standards defining what is truly a Web 2.0 web-site.
An excellent example of Web 2.0, which is often cited is that Britannica Online is Web 1.0 while Wikipedia is Web 2.0. Another example we are all familiar with is the personal web-site versus blogging.
I think a quote from this 2005 Wired article puts it well: " Web 1.0 was commerce; Web 2.0 is people". Among other qualities, Web 2.0 sites harness collective intelligence, customer self-service, and a light-weight user interface.
For a quick summary, this Wikipedia entry is good. Some Web 2.0 features have been present in web applications even before the term was coined: for example Amazon allowed customers to write reviews. And there are no real standards defining what is truly a Web 2.0 web-site.
Thursday, September 6, 2007
Web 2.0 and BI
Of late, we are getting inundated with Web 2.0 technologies. The term has been around since 2004, the year of the first Web 2.0 conference. I will summarize my understanding of Web 2.0, and take a look at some of the more popular Web 2.0 web-sites, in another entry in this blog.
However, pertinent to this blog and what caught my eye is this article in DM Review magazine of the impact of Web 2.0 on BI.
more on this shortly ....
However, pertinent to this blog and what caught my eye is this article in DM Review magazine of the impact of Web 2.0 on BI.
more on this shortly ....
Tuesday, September 4, 2007
Business Analytics - A definition
My good friend, Rich Webb ( he is a BI practitioner who knows SAP inside out), and I were having a discussion yesterday on what exactly is Analytics. We agreed that it would be good to come up with a definiton we could agree on. I cringe when I hear someone say that it is "data mining". No... It is a term that is broadly used for many different processes that support decision support.
So, I turned to the web for the answer. This is a short definition from a popular Datawarehousing vendor "..all programming that analyzes data about an enterprise's business activities and customer information and presents it so that better and quicker business decisions can be made".
Wikipedia has an interesting entry on "Business Analytics", with several topical examples from E&J Gallo Winery and Capital One to Netflix. Many of the examples we hear about are enterprises that market and sell to consumers. However, analytics to improve team performance or getting "getting optimum performance for money spent", has also been used in Sports. One of the earliest examples was described in Michael Lewis's best-seller, "Moneyball" which described the use of analytics by the Oakland Athletics. My two hometown teams, the Boston Red Sox and the New England Patriots have found success using analytics. Tom Davenport, in his book, "Competing .." describes this application of analytics by sports teams.
So, I turned to the web for the answer. This is a short definition from a popular Datawarehousing vendor "..all programming that analyzes data about an enterprise's business activities and customer information and presents it so that better and quicker business decisions can be made".
Wikipedia has an interesting entry on "Business Analytics", with several topical examples from E&J Gallo Winery and Capital One to Netflix. Many of the examples we hear about are enterprises that market and sell to consumers. However, analytics to improve team performance or getting "getting optimum performance for money spent", has also been used in Sports. One of the earliest examples was described in Michael Lewis's best-seller, "Moneyball" which described the use of analytics by the Oakland Athletics. My two hometown teams, the Boston Red Sox and the New England Patriots have found success using analytics. Tom Davenport, in his book, "Competing .." describes this application of analytics by sports teams.
Friday, August 31, 2007
Why this blog?
I became interested in the science of decision support and analytics ever since I took my first Operations Research course in graduate school. Since that time, I have periodically dabbled in Business Intelligence and Analytics throughout my working life.
A few days ago, I got a copy of Tom Davenport's "Competing on Analytics", and that was the inspiration to learn more about this topic, share some ideas and hopefully learn from other fans of Analytics. Join me for the ride!
A few days ago, I got a copy of Tom Davenport's "Competing on Analytics", and that was the inspiration to learn more about this topic, share some ideas and hopefully learn from other fans of Analytics. Join me for the ride!
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