Blog post

Setting R2R Benchmarks Improves Velocity of Financial Reporting and Data Quality

Build a Framework for Continuous Improvement in R2RSetting Record-to-Report Benchmarks

By carefully designing internal benchmarks it is possible to provide a framework, which brings about continuous improvements in the performance of the Record-to-Report process.  Normally the most pressing concerns relate to productivity (we have already mentioned man-days per entity as a measure of this), speed of financial reporting and data quality.  Ideally, corporate finance executives should be striving for improvements in all three areas.

Data capture from ERP and other operational systems marks the commencement of the process and logically, this is where initial efforts should be directed. In fact the method and conduct of data capture can have a profound bearing on productivity, data quality and speed. So early attention focused in this area should be well rewarded, and contrary to popular opinion speed and data quality do not necessarily pull in opposite directions. With careful design it is possible to improve the velocity of financial reporting and data quality.

Benchmarks for Data Quality

The desire to improve data quality should start at the very beginning of the Record-to-Report cycle, i.e. with data capture from subsidiaries and other kinds of reporting entities.  The scope for error can vary significantly depending on the nature of the organization and the method of data capture employed.  For example, in the case of a reporting entity in which the corporate head office has a minority interest or an entity representing a joint venture, it may be difficult to impose the group reporting pack, data entry standards and timescales for submission.  So setting management expectations up front (ideally contractually) is very worthwhile.

The second challenge is the nature of the interface between the system of data capture and the underlying trial balance in the ERP or financial system in the case of financial data or other source system in the case of non-financial information, such as statistics or environmental data.  Whether the information is collected via spread sheet, automatic interface or web-based front end, each requires a different approach.

This is my third blog on Benchmarking as it relates to the Record-to-Report process. Next week, look for my post on “Benchmarks for Managing Interfaces” where we will explore the potential “hidden ‘bear trap’ for the unwary.”