I've been researching the practical implications of the SEC's proposed XBRL rules, in which publicly listed companies would need to "tag" data in their financial statements by 2009 - 2011 (depending on the size of the company).

I intend to write about the topic in the September issue of Business Finance magazine, and I expect to include an account of a company that's currently using XBRL on a voluntary basis. Specially, I'm interested in finding out how much heavy lifting is required (probably not too much), how much XBRL-enablement will cost (not much at all, actually) and whether most companies are hiring XBRL experts (no).

So far, these interviews and discussion have yielded interesting insights, including the following:

In theory, most companies already know how to do this. Getting disparate finance and accounting systems to "talk" to business performance management (BPM) and business intelligence applications is similar to implementing XBRL capabilities. That said, most companies will need software.

This won't be too expensive. Buying the software and, in some cases, related services will be affordable -- probably much more cost-effective than hiring an XBRL expert to create an in-house solution. This is not Section 404, not by a long shot. One vendor says the whole process takes less than 10 hours and costs less that the amount a company invests to file a quarterly statement.

In fact, some companies will gain a healthy ROI. A relatively small portion of the thousands of U.S. public companies receive regular, in-depth coverage from financial analysts. In theory, XBRL will enable smaller companies heretofore ignored by analysts, to get their stories out more effectively. XBRL long-term investment: small companies that want analyst coverage.

Track records will help you differentiate among vendors. Some vendors already sell XBRL-tagged information to financial services companies. In fact, your company may already have been tagged. For my money, I would strongly consider selecting with a software firm that's already been hammered by the Type-A quants at hedge funds whose billion-dollar decisions depend on getting the data-tags correct.