How accurate is your CAFR data?
It's pretty amazing—all the places information needed for financial and budget reporting comes from.
For city, county, and state governments, the list of agencies providing information for CAFR and budget reports can get lengthy. Unfortunately, it usually falls on a small team or even a single individual to gather and aggregate all the data. Hours are spent manually copying and pasting numbers from emails and spreadsheets into homegrown data systems or more spreadsheets.
The shortest distance between data scattered across multiple government agencies and efficiency is, not surprisingly, collaboration. But the tools commonly used for building financial and budget reports simply don't support true collaboration. Data comes from multiple places in multiple formats and has to be manually compiled in a way that allows for analysis and distribution. Without technology built specifically to support the process, it quickly becomes a lot of work.
The keyword to take notice of here is manual—and manual can equal errors.
Each time data is added to charts, tables, and even written reports, someone must enter that data by hand—not to mention track down and verify the accuracy and source.
Over the past few years, accuracy issues have plagued the market from public companies and large banking institutions to government agencies. Everyone is familiar with JP Morgan's London Whale, but let's not forget a few other debacles where a misstep in desktop software was blamed.
In 2012, a U.S. state miscalculated and understated the number of students who would enroll in its public schools—resulting in a $25 million budget shortfall and costing two of their top finance officials their jobs. This error was attributed to a "faulty reference in a spreadsheet."
City, county, and state governments need to take notice of these costly mistakes, and each needs to ask, "Just how accurate is my data?"
When taking into account that the first version of financial and budget information usually needs to be amended, the number of hours put into aggregating all the data adds up to a significant amount overtime—the exact opposite of efficiency.
The first step in becoming more efficient is to understand exactly how and where you spend your time. Analyzing and reporting financial data presents similar problems whether for government agencies or private companies. Everyone pulls data from multiple channels, and everyone has to deal with unexpected updates to that data.
This infographic shows how much time is spent on tasks throughout the reporting process. How does your process compare?