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.
5 comments:
Curt
Thanks for the post - made me think and I blogged a response to it (and some other posts) here
JT
James Taylor
The Smart (Enough) Systems blog
My ebizQ blog
Author of Smart (Enough) Systems
Some years ago, I spent a few years working for Cognos, helping customers deploy reporting and OLAP tools, often to large numbers of mid-level employees. While I have nothing against these tools in themselves, I came to suspect that many of the people receiving these tools were not qualified to use them, and wondered what the business implications might be.
As an example, at one company (which is no longer in business), I discovered that a previous installation of the report-writing tool had been configured with incorrect joins (of source tables on the database). This company had been relying on the output of this tool for 3 years, yet no-one was aware that it was generating potentially erroneous results!
Further, I wonder if the average corporate worker has the statistical sophistication to fully understand the output of such tools. As I like to say, when an employee comes to a meeting claiming that "2 out of 3 of our customers also use brand X", do they mean "67% of thousands of customers", or do they literally mean "2 out of 3 customers"?
-Will Dwinnell
Data Mining in MATLAB
@James - oops, looks like you've confused me with Curt Monash (BI consultant and industry commentator). This is the Monash University BI blog (Monash is a large Australian university in Melbourne).
Was bound to happen, I guess!
Cheers,
Rob.
@Will - happens more often than you'd like to think, unfortunately. I came across a similar situation involving a consultant friend of mine on a DW/BI project. In building the new reporting system, they discovered a bug in the original reporting tool that had never been noticed.
Management absolutely trusted the old reporting system, so they replicated the bug with the pilot project of the new system so the numbers would match up. Six months later they switched off the bug and silently moved to the correct calculations.
It really went against the grain for this guy, but it had to be done to establish confidence in the new system (the client IT manager pushed for it).
I couldn't agree more with this post. It is a shame the consultants pitch such a wonderful world outlook when in fact the truth would enable much better results. BI is great, but it takes tons of work from knowledgeable people both from operations and IT working together for quite some time to get a system that can actually help improve the business. We have seen this time and again in our six sigma training programs.
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