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As a finance team, you are the keepers of your organizations report card. You are the ones best prepared to provide an informed view of how the company is performing at any given time.
With volatile economic conditions making the future harder to predict, finance teams need to become more proactive and agile in their decision making. This leaves no room for ambiguity in your reporting—CFOs need to get crystal clear on the metrics theyre tracking and make that data easily accessible to their team.
In the years I've spent working closely with CFOs through the DBP Institute to provide recommendations on their data and analytics, I've found that there are 12 reports I'm consistently recommending to businesses no matter their size or industry.
In this blog, I'll break down each of these reports along with their business impact. I'll also explore three things finance leaders can do to build a reporting function that produces not just numbers, but insights.
Financial reporting at its most basic level is concerned with analyzing historical data—how much money did you bring in last quarter? How much did you spend? Did that spending differ from the plan? And so on.
The more advanced you get in your financial reporting, the more concerned you get with the future—analyzing correlations and making predictions.
But just like you cant expect to play tennis like Roger Federer if youve never even held a racket, you shouldnt set your sights on predictive analytics if you have difficulty reliably creating the most basic financial reports.
Thats why I find it helpful to think of financial performance measurement as a continuum that finance teams can progress along as they get more mature in their reporting.
What can make it difficult for companies to move along that continuum, however, are fundamental issues such as:
I'll dig into how you can address these problems later on in the blog. First, let's get into the 12 financial reports I most frequently recommend to finance leaders, listed from most basic to most advanced. These reports can all be created in Excel or Power BI.
One of the first financial reports I'll typically work with CFOs on is an exploratory analysis. Exploratory analysis as a data analysis technique involves looking for patterns in a specific data set to get an initial sense of what the data is telling you and to detect any anomalies or outliers. It's one of the first steps FP&A teams should take when doing modeling and forecasting.
In this initial investigation of the data (which might be your sales volume, revenue, expenses, capital expenditures, for instance), you'll want to look at centrality and variation. Centrality metrics such as mean, median and mode help you understand your data set by identifying where most of your data points are clustered (the center of distribution). Variance looks at how spread out your data points are relative to the mean.
Association analysis is a data analysis technique focused on finding interesting relationships between items in a large data set. For example, retail companies can use association analysis to identify purchases that customers frequently make together and use those insights to fuel demand planning.
Tracking how the company's actual spend compares to its original budget lets your finance team know whether your planning assumptions were effective. You'll do this through variance analysis with a Budget vs. Actual report.
When you find variances between budgeted and actual figures, it's important to follow up with budget owners to get context on the reason for the discrepancy and apply those learnings for future decision making. For any areas where you performed better than planned, how can you replicate those successes in the future? For any areas where you performed worse than planned, how can you react appropriately (be it, due to market conditions or error during the budget process)?
Profitability analysis involves looking at a company's revenue in relation to its expenses to evaluate whether specific projects are profitable. While many companies focus solely on net income, profitability analysis should go much deeper and take into account ratio analysis, return on assets, capital and equity.
You can also gain a deeper understanding of your operational efficiency by segmenting your profitability analysis by customer. Large customers that bring you more revenue might require more investment from your marketing, sales, distribution and customer support efforts, which could mean you're losing money on that account—an insight that a straightforward profitability analysis wouldnt show you.
A horizontal analysis—also called a trend analysis—is a method of tracking your company's performance by comparing financial data from specific accounting periods (a previous period and the current period).
This helps you spot trends in your financial data that can point to specific strengths or weaknesses. Horizontal analysis can also help with identifying seasonal trends.
A vertical analysis, in contrast, looks at just one reporting period within a particular financial statement. The goal of a vertical analysis is to determine what a value looks like in proportion to the whole. For instance, you might analyze a specific line item on your balance sheet as a percentage of total assets or liabilities.
This method is especially useful for setting threshold limits, comparing your company's performance against industry trends and comparing values of vastly different sizes (such as financial data from two very different size companies).
A price volume mix analysis examines how specific factors (such as price, sales volume and product mix) impact your revenue. This type of report allows you to dig deeper into your business's performance than youd be able to if looking at revenue without these additional dimensions.
Any changes in your product pricing, the volume of products you sell and the unique combination of the products you sell at a given time will have a downstream impact on your revenue.
Generating a price volume mix analysis can help you zero in on areas to optimize. Im a big believer in the power of one—what would just a 1% increase in price mean for business? What would a 1% reduction in cost mean? Exploring these incremental changes is a good place to start.
Like the name suggests, a break-even analysis aims to determine the point at which your company breaks even—when your total costs (considering both fixed and variable costs) are equal to your total revenue.
This helps your finance team understand how much revenue the business needs to generate in order to cover its costs (the point at which the company has neither profit nor loss). A break-even analysis is especially useful when layered with sensitivity analysis (more on this later).
Predictive analysis involves using historical financial data and financial modeling to forecast future outcomes. The two areas of predictive analysis I tend to focus on with CFOs are revenue and cash flow forecasting.
A revenue forecast aims to estimate your company's future revenue based on historical performance and the existing state of your business. Similarly, a cash flow forecast will do this, but for cash inflows and outflows.
Running frequent forecasts (and making sure theyre accurate and reliable) is essential for carrying out your business planning and making sure you dont run into cash shortages. A rolling forecast is a great way to help your business react to dynamic market conditions and mitigate risk.
Prescriptive analysis—also called optimization analysis—is a level up from predictive analysis. It goes beyond just predicting possible outcomes to provide recommendations on the best plan of action for your business.
Prescriptive analysis involves looking at past performance, current performance, available resources and likelihood of future scenarios to suggest a course of action based on those insights. A data analytics tool equipped with artificial intelligence (such as Power BI) is a great resource for this, given its ability to process high volumes of data.
Scenario and sensitivity analysis have similar aims and can both be used to evaluate the level of risk in a set of potential future outcomes. Scenario analysis, however, explores a variety of scenarios from best case to worst case, whereas sensitivity analysis looks at how changes in one specific variable can lead to different outcomes. You might also know sensitivity analysis as what-if analysis.
Scenario and sensitivity analysis can be especially powerful when used together. For example, you could run a scenario analysis to gauge what might happen if your business were to launch a new product, then use sensitivity analysis to dig deeper into one of those scenarios. Both scenario analysis and sensitivity analysis can be done in Excel.
Although risk analysis is ordered last in this list, it can—and should—be performed at any stage in your company's reporting maturity.
Risk management is a function thats already inherent in FP&A, as the business unit responsible for carefully monitoring and carrying out the company's financial plan. Several of the reports I've listed above will integrate risk analysis to some degree (especially predictive analysis, prescriptive analysis, scenario analysis and sensitivity analysis), as they're tools intended to help your finance team evaluate risk and make decisions in the interest of mitigating that risk.
The data your finance team generates is only as good as your ability to turn those raw numbers into insights.
When organizations stop seeing their finance teams as number crunchers and start seeing them as value creators, this paves the way for more strategic decision making. CFOs play a massive role in initiating this shift and enabling their team to step into the role of strategic business partner.
Here are three things I believe every CFO should do if they want to build a reporting function that delivers insights the company can readily put into action.
If you dont start with trustworthy data, all the flashy emerging technologies in the world such as AI wont matter. The quality of your analysis and the output of all the reports I covered in this blog are only as good as your input.
When I begin working with finance leaders, I'll first work with them on identifying data sources for all the KPIs they want to track and evaluating the reliability of the data they already have.
Some data sources will be straightforward as they'll come from your financial statements, whereas others will be harder to pin down and might come not just from your ERP, but your CRM system and even static Excel spreadsheets. Consolidating all these data sources into one source of truth through a complete planning platform is a great step toward eliminating data integrity issues.
As a CFO, you're working with raw numbers someone else originated—whether thats your sales team, procurement team or members of your own finance team—and are tasked with turning them into insights.
Thats why, to be able to produce insights that will be immediately useful to the business, you need to be a great collaborator. Because as a finance leader you may be one degree removed from the numbers, forming close connections with the individuals responsible for capturing and aggregating that data will be extremely valuable. These partnerships can give you a more nuanced understanding of the data—and help you become more data centric in general.
Believe it or not, I've encountered many companies where the majority of people make decisions based on intuition. This is not a bad thing in itself, but I believe there should always be a combination of intuition and hard data involved in decision making.
If theres no established culture of data-driven decision making at your organization, however, then the likelihood of qualitative and quantitative analysis happening together is very low. Some of the most successful companies I've consulted for have had a data-centric CFO with an affinity for numbers at their helm.
Finance leaders can look to expand their department's sphere of influence within their organization and foster a data-centric culture across the company by becoming better business partners. Vena's 2022 benchmark report, The State of Strategic Finance, found that the biggest benefits of finance business partnering were to costs and margins (reported by 50% of survey respondents) and revenue growth (reported by 34%).
Getting your financial performance reporting where you want it to be can feel like a daunting prospect. But, its important to remember that you can't build a world-class reporting function overnight.
Start by defining the core KPIs that will help you assess your business's performance and then make sure you have reliable data to measure them. Next, build the reports that will deliver the most immediate value (usually focused on historical performance) and work your way up to more complex reports (usually focused on future performance).
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