Dave's Adventures in Business Intelligence

Author Note: This blog post was originally a guest entry at The Decision Factor, a site that appears to have ceased publication. I have reproduced it here. It was fun to write, and I hate to see good content go missing. The original post was published in 2012 but I believe the content is still relevant today.

While the touch-panel displays on Star Trek: The Next Generation certainly foreshadowed the iPad, the focus of my discussion today is around another blog: “Five Leadership Lessons from James T. Kirk,” published by Forbes Magazine.

While Captain Kirk had his flaws—making his character all the more interesting—he certainly was the unquestioned leader of the Enterprise. I enjoyed reading the article and think the specific lessons outlined also apply to business intelligence.

I’ll share the first two with you today and save the others for a future post.

Never Stop Learning

When Kirk ran the Enterprise, the Federation was much younger. Their mission was to seek out and explore, encounter new civilizations, and learn from them. The opening monologue said it all:

Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before.

Sounds like good advice for business intelligence professionals too, right?

In order to deliver effective results, we have to first understand the business. Whether we work for a large company or a small start-up, knowing the business (and the data) is the first step towards providing business value. It doesn’t help to design solutions in a vacuum that the business won’t understand, won’t use, and doesn’t need.

As a business intelligence professional, I look forward to those times when I get sent to the far reaches of our enterprise (see what I did there? 😉 ), so that I can directly observe business processes in action. The lessons learned might not provide an immediate benefit. It might be months or even years, before I can put something I have learned to good use. What’s important is that I do interact with the business and learn from that experience.

Have Advisors with Different Worldviews

Captain Kirk was blessed with a diverse crew, not only on the bridge of the Enterprise but throughout the ship. This was no accident. James Roddenberry, the visionary behind what ultimately became one of the biggest TV and movie franchises of all time, intended this to show how a diverse crew of different ethnicities, genders, and planetary origins could act together in towards a common goal. Spock and Dr. McCoy could hardly have been more different, yet each was able to provide valuable input to Captain Kirk’s decisions. They each supported his role as their captain and leader in their own way, often in direct opposition with each other.

In the business intelligence role, it’s just as important for us to seek out and explore diversity. Before designing a system, I need to talk to everyone who might use the system and gather their input. Getting only one side of the story could lead to incomplete requirements, which in turn leads to wasted time and money. In this day and age (much less the 23rd century), we can’t afford to do much of either.

Stay tuned for more business intelligence lessons from Star Trek

In a few weeks I’ll return with the final three leadership lessons from Star Trek that have implications for business intelligence professionals. In the meantime, I wish you success in exploring the world of business intelligence.

I spent yesterday at the BI2014 event and had a very productive day. I delivered a presentation that compared Universe Designer to Information Design Tool and discussed some of the pros and cons of switching or converting universes. It was a small crowd, but I did get to meet Miss Universe from BOB and also Raphael Branger who delivered an excellent talk on various ways to help select the right BI tool. I have also had several folks comment on my LSU backpack. 😉 I use the same backpack for almost all of my conferences because it’s quite likely to be the only one there, making me easier to find for folks who I haven’t met yet.

I attended a session on Mobi yesterday that was encouraging. Some of our projects that have tried to use Mobi have observed some performance issues, and apparently that has been addressed for the next (6.0) release of Mobi. The folks that build that tool are in an interesting situation… they have to try to take content that wasn’t necessarily designed for mobile device and render it there. On complex documents (those with lots of different blocks and charts, or even just crosstabs) the rendering process became complex. From what was suggested during the talk the Mobi folks have figured out a different way to interact with the Web Intelligence API that should show noticeable improvement. I’m looking forward to seeing that in action.

I also attended a session that was supposed to be an introduction to analytics but turned instead into a review of the KXEN acquisition that was made last fall. The presenter suggested that KXEN rendered most of what he was going to share obsolete because a user doesn’t need to know anything about the underlying analytics anymore. At some point I would still like to get a better understanding of the concepts.

I haven’t done much of anything outside of the conference yet, simply because I only flew in Wednesday and the jet lag is still affecting me some. It always seems to be easier to go West – even really far West such as Melbourne – than to head East. Oh well, it will be easy to go home. 😎

I’m going to be at the SAP Insider BI 2014 event in a few weeks in Nice, France. It’s my third time travelling to the “old continent” to present at a BI conference, but my first in a long time. If you’re in the neighborhood, please stop by and introduce yourself!

If you’re as old as I am, you might recognize the blog title was inspired by a song from the band Gallery…

Author Note: This post was originally a guest post published on “The Decision Factor” blog. Since that site seems to have disappeared I am re-posting it here. The original publication date was November 1, 2012, but I believe the content is still relevant.

What’s the purpose of a business intelligence (BI) dashboard? It’s not just to look sexy. The primary purpose of a dashboard is to convey information. A secondary purpose is to inspire a behavioral change based on the information that’s being conveyed. Nobody wants to be “red” on a dashboard reviewed by executives, so they’ll change their behavior in order to get into the “green” area.

But humans are a creative species. What happens if their behavior changes in an unanticipated way?
Continue reading “Lessons in Business Intelligence: Be Careful What You Wish For”

Stephen Few weighed in on what is the proper definition of big data yesterday, and it’s an interesting read. If you don’t want to click through, I will summarize in one sentence: “Big data is nothing special, it’s just data.” Obviously Stephen’s opinions have not stopped (and won’t stop) people from using the term.

Next up on my blog reading list this morning was a trip to FiveThirtyEight.com. The headline article this morning was titled, “The Story Behind the Worst Movie on IMDB.” I’m guessing that IMDB doesn’t really qualify as “big data” as they have “only” 2.8 million titles in their database. 🙂 But the story wasn’t about big data, it was about the worst movie in the database as determined by public rankings. I would have expected the soundly panned “Battlefield Earth” (and it was one of the worst with an overall rating of 2.4), the unfortunate Halle Berry stinker “Catwoman” (3.3) or perhaps even the Paris Hilton vehicle “The Hottie and the Nottie” (which I’m somewhat ashamed to admit I even knew about and brings in a lowly rating of 1.8).

It turns out the worst rated movie was not any of these, but instead was a Bollywood production called “Gunday” which has a rating of 1.4. Over 91% of the posted ratings are one star! What happened? Was the movie really that terrible?

For the full story, click through to the story on fivethirtyeight. In summary: an entire country decided they didn’t like the movie and decided to do something about it.

…the movement has since become an online alliance of bloggers focused on protecting Bangladesh’s history and promoting the country’s image. That includes protesting “Gunday,” because of the film’s reference to the Bangladesh Liberation War as the Indo-Pak war. In its first 11 minutes, the movie claims that India alone defeated Pakistan, and implies that an independent Bangladesh was simply a result of the fight.

What happens when an entire country decides that a movie is bad? The movie becomes perceived as historically bad. More from the article:

For Paris Hilton’s “The Hottie & the Nottie” — currently rated second-worst of all time — to take over IMDb’s bottom spot, the next 41,000 voters would have to give it a 1.

Last year I wrote a blog post titled Is External Data Always Good?. This is one more example of how social media / crowd-sourced data can be skewed by a concentrated effort. Is “Gunday” really the worst movie of all time? Probably not. Most professional critics were not nearly as harsh, especially when compared to Paris Hilton’s effort. One user reviewed Paris’s acting by saying, “Paris Hilton’s acting made me lose braincells.” The reviews on IMDB were not spammers; they were unique individuals. They just happened to be part of a focused effort to trash a movie they perceived as historically inaccurate. (Please note: I am not making any assessment as to the accuracy of the film. I am far from an expert in that area so I’m neither endorsing nor rejecting the movie.)

Ultimately I think the article from FiveThirtyEight wraps it up the best.

Crowdsourcing can be a tremendously powerful way to get a consensus understanding of the world. Because the sample size is so large, there’s an assumption that whatever it yields is robust and true. But even with oversight, aggregated rankings are subject to unforeseen biases. Crowds are always big — but they’re not always wise. Sometimes it’s impossible to control which crowds are being sourced.

Big data is just data. But you still have to understand where it’s coming from in order to benefit from it.