Bob Schneider is a Partner in 
Wilson So is the Director of Hitachi Consulting Corporation XBRL: An Interview with Chie Mitsui
Chie Mitsui is a Data Analyst at Nomura Research Institute, where she is helping design NRI’s new XBRL-enhanced services. She previously worked as system designer for information service products at Jiji Press, a Japanese financial news and data distribution company. Ms. Mitsui holds a masters in physics from the Tokyo University of Science and is pursuing her MBA.
1. In February you conducted a well attended workshop at the Tokyo Stock Exchange that was sponsored by XBRL Japan. Could you tell us its purpose and who signed up for it?
XBRL has been implemented at both the Tokyo Stock Exchange’s TDnet and the Financial Services Agency’s EDINET. Naturally, interest in using XBRL for investment analysis has increased; analysts and investors want to know “What can XBRL do for me?” These end-users represent the final and key link in the financial reporting supply chain, yet their views on XBRLized disclosures haven’t been given great weight in the implementation process.
Given that TDnet’s mission is to deliver timely financial information to the investment community, there was a strong sense that such workshops are essential for helping end-users utilize the system’s XBRLized data. The attendees were (primarily) analysts, data intermediaries, and representatives of securities firms.
2. Were they receptive to the need for XBRLized data?
I think many end-users are not satisfied with their current choices for retrieving financial data, namely, using the services of a data vendor or inputting the data themselves from a PDF into, say, Excel. But that doesn’t necessarily mean they are completely convinced of the need for XBRLized data.
Let me give you an example from our workshop. The XBRL tool we used has dialogs to choose elements on the calculation sheets and provides easy viewing for beginners. Once you construct an initial sheet with an opened XBRL file, you can use the same sheet for other files. When attendees made the calculations for the target company we selected, some users felt it would indeed be easier to simply stick with copying data from a PDF.
But what I emphasized to these users was that, while that might be true for a single company’s data, it’s not the case when you want to compare all companies in the same industry. That’s when XBRL really shows its colors.
We used XBRLized data for 3Q 2008 to calculate the ratio of accounts receivable to sales for both the target and a broad group of companies; this would help identify the risk in reported profits and potential cash flow problems. When we compared the results, the target company’s ratio was a little higher than average. The attendees did realize the usefulness of XBRL in this situation. Nevertheless, we did have some hurdles to overcome.
3. Which were?
For the first company we selected, the actual element was notes and accounts receivable-trade, and for most of the companies we selected this was the right choice. But for one company the element was just accounts receivable-trade, which didn’t treat notes receivable, and its inclusion generated an error message. The experience highlighted for attendees the special nature of using XBRL data.
When analysts and analysts use data from data intermediaries, the data is normalized so that items are combined for better comparability. Having the original data allows for more specificity and better analysis, but it also raises issues like the one I just cited. If you want to compare a financial ratio for dozens of companies, you do not have time to check each instance for errors. You need to choose the right element to verify your hypothesis.
4. So in your view using TDnet’s XBRL data for comparing financial ratios of many Japanese companies simultaneously can prove difficult?
Well, it’s not a problem of the XBRL – it’s the nature of Japanese financial reporting. The taxonomies used in the US reflect US GAAP accounting and have much more structure. The software enables users to identify the parent element, and they can use tree-like navigation to select the elements they need. Japanese taxonomies, in contrast, are relatively flat, and it is more difficult to know the relationships between elements. That is the real issue: how to make taxonomies.
There are other significant differences in US and Japanese taxonomies. For example, attendees were surprised that US GAAP taxonomies had contexts that identify the specific time period. In contrast, Japanese taxonomies have contexts like CurrentYearConsolidatedDuration. That doesn’t mean you’re likely to confuse 2007 and 2008 data for Japanese companies — the taxonomy provides for that distinction. But it does require that you adjust your software settings accordingly.
5. So you see consequences for international comparisons as well?
I do. Of course, institutional investors, as well as some individual investors, trade equities on an international basis. Differing accounting standards among nations naturally result in differing taxonomies. But beyond the dissimilarities that result from accounting standards, the nature of XBRL taxonomies, the naming of elements, and so forth can vary among countries in important ways. So for now, sector analysts who want to analyze their industries on a worldwide basis will encounter comparability issues directly related to the XBRL.
At the same time, I see opportunities for improved financial reporting through XBRL. Items that have been traditionally combined for paper-based reporting – such as notes and accounts receivable – can be disaggregated and reported separately with XBRL. More granularity will mean more accurate reporting.
6. What was the main conclusion you drew from the workshop?
The most important thing I came away with is the need for end-users to be part of the XBRL conversation. After all, all of the work of XBRL implementation is ultimately aimed at them. This meeting was a good opportunity for their voices to be heard, and I hope there will be more of them in the future.