Data Analytics for Finance and Accounting
When I’m trying to convince a team of potential clients why they should make analytics part of their overall management strategy, I usually start by walking them through data analytics for finance and accounting because financial performance is a top-of-mind concern for almost every manager I’ve ever met, and most of them are already familiar with about half a dozen basic financial statements and reports – which are the foundation for any successful analytics initiative.
The Foundation: An Accounting System and a Few Basic Reports
When I start an analytics engagement, I usually show up with checklists of reports most companies are probably already running – and that I ll want to access because the data that goes into them will be useful in later stages of the process. Because the practice of accounting itself is governed in the U.S. and in other countries by a formalized standards boards, and we’ve been measuring financial performance for so long, most companies and government bodies are already in pretty good shape.
For finance and accounting analytics projects I usually look for these reports and financial statements first:
- Balance sheet.
- Profit-and-loss statement.
- Budget vs. actuals report; revenue and expenses.
- Aging accounts receivable.
- Vendor-payment history.
- Inventory turn.
Most accounting systems will create these reports for you – including lower cost systems like Quickbooks and Freshbooks – and if you have them and they re accurate, you re probably capturing enough data to move forward with a few more advanced projects.
Adding Value to Financial Metrics with Advanced Analytics
But accurate reporting is just the beginning. Once you’ve got a good set of measurements in place, a good analytics practitioner can help you understand what is really going on with your company s finances: what s truly driving financial performance, and where you might find hidden revenue and cost savings opportunities.
As I’ve written before. data analytics practitioners have several tricks up their sleeves to help you understand what your company s data is really trying to tell you and to add value to your existing financial reports .
Here are a few examples:
Providing Explanatory Analysis – “No, really. Why?”
Using a few basic statistical methods, a good analytics practitioner can help you dive deep into your financial data and understand what other factors are truly influencing factors such as profit.
A few basic questions I usually tackle are:
- Are all of our customers and products equally profitable?
- What really drives our revenues and costs?
- Are all of our project managers, territories and lines of business holding to budgets?
Spotting Trends Early with Good Leading Indicators
I also try to find patterns that aren’t easy to spot, and use leading indicators to alert managers before things get out of hand.
- Are there any trends in our revenue or expenses that need immediate attention?
- Which things do we buy frequently enough that we could take advantage of bulk-purchase discounts?
- Are any of our payments atypical? Could they be duplicates?
Predicting the Future
And of course, when possible, we want to know what’s next, so we look for answers to questions such as:
- When will we run out of money?
- Can we predict revenue for next year based on other forecasts about the economy?
- What happens to our costs if X, Y or Z happens?
- When are our customers likely to pay us?
If you’d like to learn more about data analytics for finance and accounting, or how data analytics can help other aspects of your business, download our new guide:
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.