The Myth of BI for the Masses

Glenn Alsup over at the Viewmark Blog has a great post on how it's next to impossible to properly satisfy all user needs with a single analytics tool/data warehouse. I've blogged on this theme before, but it's worth hammering home time and again, since it's diametrically opposed to what the vendors want you to think. The problem with BI is knowing the information requirements prior to users using the system. Given the role of BI is to support decision making, people don't know what they need until they start to work through the issues - the very thing the BI system is supposed to support. No data warehouse design, however big, is ever going to be able to anticipate the specific information requirements needed by a decision-maker, especially if the decision is a strategic one (the real sweet-spot for BI).

My personal view is that it's better to spend money on a team with some great analytical skills than a software solution that ends up as a glorified enterprise reporting tool. In many decision situations, small-scale, non-permanent 'ephemeral' systems (so-called 'personal DSS') thrown together to answer specific questions are more useful than multi-million dollar BI systems. But then that doesn't sell software licenses, consulting or support contracts.

Free Advertising

I'm not usually in the habit of giving free kicks to commercial ventures, but this is worth plugging. Long time associate of the Monash BI group, Martin Kratky runs BI consultancy Intalign. In great news for the BI industry here in Melbourne, Sydney and Brisbane, they are bringing out Stephen Few to run some executive workshops in October. As you may know, Stephen is an academic at UC Berkeley specialising in data visualisation, with several excellent texts dealing with data presentation and the use (and misuse!) of the now ubiquitous dashboard. Stephen also runs consultancy Perceptual Edge, and has a well-read blog at Visual Business Intelligence. He is passionate, doesn't pull his punches and has a message that all BI consultants and developers should hear.

You're a BI What? The Myopic View of BI Vendors

An excellent article that I came across while adding the Digg functionality to this blog yesterday (notice the new Digg It! button below, and the list of BI stories on Digg on the right!) does a wonderful job of outlining some of the major shortcomings of the BI industry at the moment. Neil Raden from consulting outfit Hired Brains and the fingertips behind the Addicted to BI blog, gets stuck in, criticising vendors for a myopic product/customer/sales view of organisations, and being too focused on the software/hardware tool, rather than the all-important decision support. Shades of Peter Keen there, who made the same criticism of DSS developers and vendors back in the 1980s - it's the first 'S' in DSS that's the most important, ie. support should take precedence over the system (since the latter is only a means to achieving the former).

Raden also talks about the potential of Web 2.0 (ugh) concepts that may be of benefit to decision-makers: collaboration, tagging, etc. Although I'm not a fan of the label, I am very supportive of Web 2.0 thinking that sees social interaction and bottom-up creation of content as the key to useful tools on the web. If we can overcome the problems we currently have in getting BI software users to contribute metadata, etc., then some interesting things might happen.

My favourite quote from Neil comes at the end, though, and goes directly to the issue of the provision of support to decision-makers. He makes the point that most business people are tech-savvy, often more aware of the latest tech trends than internal IT support staff. They just won't put up with crappy support:

"Look, I'm playing a 3-D video strategy game with four people in China I don't even know, while I'm downloading data to my iPod, while I'm answering messages in Yahoo messenger. Are you going to tell me I can't have a report for three months because it has to go through QA?"

New Blog Links

I've added links to two new blogs in the sidebar - Stephen Few's Visual Business Intelligence and Andrew Vande Moere's Information Aesthetics, both worth reading.

Criticising Edward Tufte

I'm a huge fan of Edward Tufte, and so are many people who are interested in the graphical presentation of information. He's got a lot of good things to say that BI people should listen to, and he says it in an engaging way. Pictured, right, is Minard's diagram of Napoleon's march on Moscow, used by Tufte as an exemplar of good graphical information presentation.

As with any guru, though, his adherents sometimes get bogged down with the minutae of what he says, rather than the underlying principles he tries to communicate. There's an interesting couple of posts over at Emergent Chaos in response to a criticism of the Minard diagram as a communication tool, and Juice Analytic's follow-up. The original criticism was made by Seth Godin in the following video:

Uncertain about uncertainty

One of the key theories that informs our teaching and research into BI at Monash comes from cognitive science. It states that, for a whole variety of reasons, people don't make rational decisions. Instead, we're subject to so-called cognitive biases. One category of bias has to do with how we think about statistics - as a rule, people are terrible at thinking in ways that are consistent with the laws of Bayesian probability. This is a real problem for BI developers, since most BI tools deal with quantitative values, and hence, statistics and probability. Even worse, just about everyone is subject to these biases, even trained mathematicians, and presumably, BI professionals.

I've just finished watching an excellent talk by statistician Peter Donnelly that covers this issue brilliantly. It's one of the recent TED podcast episodes, that I've referred to before, and runs for about 20 minutes.



If you want to find out more about some of the other (really freaky) cognitive biases that exist, check out our bias page at http://olap.sims.monash.edu.au/research/decision.nsf.

Excel Core Knowledge Wiki

I was just browsing the excellent Juice Analytics blog, where I read a post talking about the creation of a wiki discussing the basic core skills needed to use Excel for data analysis. Surf on over to the Excel Core Knowledge Wiki, learn some things, and perhaps contribute!

Another BI Blog

Just came across another, more established BI Blog called Bounded Rationality, by Mark Madsen. Bit more technically focused than us, and has some interesting things to say about the industry. I particularly like this post on some of the overblown claims some of the vendors put out there.

The Pros and Cons of Choice

This is perhaps not really appropriate as the first substantive post on this blog, given that it's not really about the technology of BI, but thought I'd post it anyway, as I'll forget if I don't do it now. I've been recently getting into some video podcasts from the TED conferences (Technology, Entertainment and Design). One recent episode was a presentation by Malcom Gladwell (author of Tipping Point) whose main theme was the importance of choice - that is, freedom to choose is closely tied to happiness.



Another, more recent episode, was a presentation by Barry Schwartz (author of The Paradox of Choice) whose point was that too much choice can have a number of strongly negative side-effects. In short, too much choice, amongst other things, leads to paralysis and post-decision regret of various kinds.



So why is this relevant to BI? BI systems are developed to help managers make decisions, and by providing them with information, we increase the number of choices available to decision-makers. Schwartz's point, though, would indicate that a naive approach to this is unproductive: simply plugging a manager into a data warehouse isn't going to help them make better decisions. In fact, it may actually make them worse decision makers.

I don't think too many people would disagree that a good BI tool doesn't give managers more information (well, it might, but not as a primary design aim), it helps managers to understand information to be able to make a better decision. BI systems are there to help provide a supportive decision making environment, and do so by adding 'structure' to the decision problem: that is, they help decision makers to focus on important information, while helping to filter out less important (but maybe still relevant) noise. Mark Silver calls this 'decisional guidance'. On the other hand, though, is still the need to allow the decision maker to make a real, free, and often unanticipated, choice.

My point is this: as BI developers, we need to balance the needs of the decision maker to make a free choice, while not overwhelming them with potentially choice-enabling information. BI isn't about building and deploying a data warehouse and an analytic tool suite. It's fundamentally about providing decision support, and sometimes that means restricting choice, rather than enabling it. Getting that balance right, of course, is often easier said than done, and raises all sorts of ethical issues.

Check out the videos, or subscribe to the podcast, at the TED Blog. I suggest watching the Malcolm Gladwell one first, followed by the Barry Schwartz video.