Text Analytics in Practice: Identifying Dated and Redundant Government Regulations


Ok, we acknowledge from the get-go that government regulation isn’t the sexiest topic on the planet. But what if we told you there is a tool/technique that can help us reduce or at least streamline the amount of government regulations we have on the books? Good idea? We think so.  The technique is text analytics and the tools could be software like QDA Miner and WordStat.

A team of analysts and data scientists at Deloitte has written the following article “Using Advanced Analytics to Drive Regulatory Reform.” The analysis was done on The Code of Federal Regulations (CFR). Using their own techniques, the team analyzed, 217,714 sections of the 2017 CFR to identify regulations that are candidates for reform. Reasons for reform might relate to redundancy across departments, changes in business practices or changes in technology. One candidate would be a regulation governing log drives on a northern U.S. river where there hasn’t been a log drive since 1937.

Fortunately, we have the modern technology of text analytics that enables us to search these extremely large volumes of documents and make the huge task of regulatory reform possible.