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All organizations need to know where their money comes from and where it goes. Accounting systems typically include a standard set of reports and analytics tools that help organizations monitor the basics, and controllers and CPAs typically make sure that businesses roll out the most important ones. If you want to find ways to earn more revenue or cut costs, the way to start is by diving into the metrics your accounting system tracks for you – and then digging deeper with data analytics.
Profit and Loss Statements
A Profit and Loss Report
The number one thing most businesses need to know is if they are actually making money – and if not, where are they falling short.
The good news is that almost all accounting packages ship with a “profit and loss” statement, along with other more complicated mechanisms for understanding where money is entering and leaving an organization. If you have an accountant, you almost certainly have a profit and loss statement, and the ability to dive down into company divisions and product lines to determine which are winners and which are losers.
Know When and Where Profits are Down with Data Analytics
P & L Report with Data Analytics: Where are Profits Down?
The trouble with most profit and loss statements – and other measures of financial gain – is that they are long, complicated documents. Readers must pore through pages and pages of text, or scroll through screens and screens of data, to find what they’re looking for. Typically what they want to see is if there have been any sudden and unexpected changes in profitability in one or more parts of the business.
With data analytics, businesses can build smart profit and loss statements that predict what mangers should expect to see for the next quarter based on the last few quarters’ metrics, and highlight those areas where something strange may be happening.
Aging Receivables Reports
Aging Receivables Report: A List of Clients That Owe Us Money
Businesses need to know where their money is coming from – and when they aren’t getting paid on time. Most accounting packages ship with an “aging receivables” report that will show them which clients owe money — usually broken down by receivables 30-, 60- and 90-days overdue.
Predict Which Clients Won’t Pay You with Data Analytics
Receivables with Data Analytics: Clients That Owe Us Money and are Likely to Not Pay
As useful as lists of clients that owe you money might be, what’s even more helpful is a list of which are unlikely to pay you at all.
By using data analytics to review a history of which clients eventually pay and which don’t, companies can predict where they should focus their collection efforts, and who they should avoid doing business with in the future. (Banks and credit rating agencies do this all the time.)
Top Vendors Payment Report
Top Vendor Payments Report: A List of the Vendors We Pay Most
Businesses also need to know where their money is going – and when there might be an opportunity to negotiate a discount on what they buy.
As with receivables, most accounting packages ship with a “top vendor” report in their “accounts payable” module, that will show the vendors that receive the greatest portion of their expense budgets. In some cases, the reports will also show the number of checks that have been written to those vendors, which will allow a manager to get a sense of how frequently those vendors are paid and if there’s an opportunity to negotiate better payment terms with that vendor.
Reduce Vendor Overpayment with Data Analytics
Reduce Vendor Overpayment with Data Analytics
Unfortunately, organizations that make high volumes of vendor payments occasionally make mistakes and these mistakes aren’t always fraudulent. For any number of reasons, a vendor might issue the same invoice twice, and your accounts payable staff might pay both of them unintentionally.
Fortunately, there are ways to spot invoices that have probably already been paid through data analytics.
DataClear is a Baton Rouge-based data analytics consulting firm. Contact Us for a free 30-minute consultation and discover how your company can profit from data-driven decision making using tools that won’t break your budget.