Remember how in elementary school the teachers frequently talked about kids in the class having different learning styles? Multiple studies show that more than 60% of the population are visual learners… and common sense tells us that very few people easily consume endless lines of numbers in a table. The numbers blend together. They are often shown in unfamiliar units (i.e. in thousands or in millions). Yet finance and accounting professionals frequently produce endless tables of numbers and expect them to “tell a story.”
Below I’ve included Nike’s Income Statement from their most recent 10k (yes it’s really that small).
An unedited Income Statement for Nike. Pulled directly from the company’s 10k.
Let’s compare the Income Statement above to a "Visual Financial Statement,” I created. The expenses are shown in light blue and are “costs to the business” (for example Total Revenue minus Cost of Revenue equals Gross Profit). Is the Visual Financial Statement perfect? No. Does it need to be supplemented with more detailed financial data for those who want to go deep in the weeds? Yes. But for the large majority of people, this tells a story that they can’t get from the table above. Trends are easier to identify, comparisons are easier, and the true nature of how money flows from Revenue to Net Income is more clear.
A “Visual Financial Statement” for Nike. Light blue bars are expenses.
I’m arguing that many finance professionals need to do better. My clients get Visual Financial Statements regularly. Not just to understand their Profit & Loss but also for Cash Flows, and other key metrics.
I’ll make my final point by stepping out of the world of finance and into the work of statistics. The following four datasets (know as Anscombe's quartet) have the same descriptive statistics (things like the mean, median, and variance). If we looked at summary statistics of the datasets we would be misled (because those metrics would imply that these datasets are the same). So, let’s use a visual representation of the data instead (if you imagine these datasets are financial metrics of a company, it’s easy to see how important the visuals become).