Every time I post a business dashboard that makes use of dial gauges, I get lots of feedback from data visualization experts about why the gauges don’t add much value to the dashboard. OK, my infoviz specialists, try my latest thinking on for size:

So, if a particular dial gauge only adds a little value to a business intelligence dashboard, just add a ton of them to get lots of value!

Ha ha!! What do you think of my approach to dial gauges? Here’s an example. Check out this stock market dashboard. It features the use of a dial or two. Click on the dashboard screenshot to enlarge the image. On the actual dashboard, the dials can be drilled down to reveal historic data. Try out the stock market dashboard dials for yourself.

Stock Market Dashboard with a Couple of Dial Gauges

Actually, I was thinking about the above dashboard because I wanted to grab a snapshot of some financial market metrics at this historical time. Of course, the stock market is on everyone’s mind because of today’s 777 point decline. Here’s a memento of what happens when a $700billion rescue plan gets voted down.

Did anyone read the recent article in Computerworld/infoworld titled:

How BI could have provided early warning to financial market meltdown: Various analytic tools could have provided banks an early warning of the risks to their loans and securities, some observers say.

The premise is that analytics and business intelligence ought to have provided some visibility into the emergence of this financial mess (after all, they ARE called dashboards!)

Click on the following link to read an excerpt from the article:

In the coming weeks the feds and the surviving financial services institutions will have the daunting task of unraveling all the securitized loans and other instruments that are hiding the toxic investments. But does the technology exist to do that? And if so, could it have been used to prevent the bad debt from hitting the fan in the first place?

The fact is that despite government regulations like Sarbanes-Oxley, there is little visibility mandated by current regulations into the origination of loans and how they are broken up, resold, and resold again.

To cite the classic example of how we got into this mess, consumers were given 100-percent-plus variable mortgages without any security. Not only could those mortgages be sold to other banks, but they could be divided into five, ten, or twenty tranches — financialese for slices — and resold to five to ten different organizations, making it difficult to track who was involved and who ended up taking the risk.

Theoretically, the financial service providers were clear on the risks of each type of loan and had a way to gauge whether they had enough liquidity — cash and other easily sold assets — available if the riskier loans went south. But a New York Times report indicates that in fact many financial institutions gamed their analytics to favor positive scenarios over negative ones in order to justify keeping less money in reserves should the risky loan blow up. “A large number of buyers of these kinds of instruments really didn’t care about the value. They just wanted to flip it. A lot of people just didn’t want to know,” concurs says Josh Greenbaum, principal at Enterprise Applications Consulting.

Analytics and CEP tools could have helped

Had these financial services companies and banks established business intelligence metrics as to the ratios of what kind of debt they were holding versus the cash reserves they held, their analytics systems might have driven alerts earlier in the process, says Michael Corcoran, a product manager at the BI provider Information Builders. But as anyone in business already knows, consolidating that kind of data to get those answers more often than not is a slow process that typically ends up being done manually in an Excel spreadsheet well after the fact.

Tags: Stock Market Dashboards, Financial Markets KPIs, Dial Gauges, Digital Dashboard Design