Diving into accounting analytics marks the beginning of an exciting journey filled with opportunities for professional development and career advancement. The ability to generate and interpret analytics can significantly enhance the value accountants bring to their roles and organizations. Regardless of the technology at your disposal, the following three items will help you get started in your upskilling journey in accounting analytics:
- Map out how accounting data is inputted to the ledger
- Exception-based analytics can go a long way
- Understanding sample methodology
Map out how accounting data is inputted to the ledger
Accounting data is non normal: Dozens of individuals in a company typically record and approve journal entries, and most companies don’t have consistent policies on journal line aggregation (e.g. posting ten $1 transactions or one $10 transaction). It is difficult to identify outliers and trends with variability in how data gets inputted to the ledger. The first step in accounting data analytics is to understand your data. Pull down all the transactions for a ledger account and try to answer the following:
- How many sources are there?
- How many different people or departments are recording entries?
- Is the data at the most granular level or are transactions aggregated?
Mapping out these aspects will assist in building out respectable trend analyses and analytics. The basis of data analytics is to map out and understand the data, so don’t skip this step!
Exception-based analytics can go a long way
Exception-based analytics involve identifying and investigating transactions that significantly deviate from expectations. Payments to unapproved vendors, revenue transactions that far exceed reasonable amounts or unusual debit/credit combinations are all examples of exception-based analytic use cases.
Accountants are uniquely positioned to thrive in the realm of exception-based analytics, thanks to their specialized training in researching and understanding unusual transactions. Start in your area of expertise and create a list of what you would consider exceptions. Look at your journal entries to see if anything pops out and continue to fine tune your list depending on what you uncover.
Understanding sample methodology
Reducing financial statement risk is crucial in accounting. How can accountants minimize risk with the least amount of effort? Chances are good that your organization samples transactions. Without understanding sample methodology, a lot of wasted hours and effort can happen if selecting transactions haphazardly. Review what your organization is sampling:
- Are there subgroups of transactions that should be stratified first and then sampled?
- If you audit transactions, do they each carry the same level of risk?
Reviewing historic sample results may indicate if your audit procedures or control sampling is working or if it needs a tune-up.
Wrap-up
Start your analytics journey by focusing on one of the outlined areas. As you become more comfortable, you’ll find that these foundational practices not only enhance your current procedures but also pave the way for advanced analytical exploration.