Learning to Use Financial Accounting Numbers Strategically
Catherine Schrand, a professor of accounting at the Wharton School of the University of Pennsylvania, gets what you really think of her. “I know the reputation of accounting,” she told a group of high school students visiting Wharton’s campus during our summer Cross-program lecture series. “I know that we are seen as a boring group of people.”
Dr. Schrand fights that stereotype. Accounting is her life’s work and her research interest. Accounting, she said, is like financial forensics; it requires deep investigation into how companies operate and is about uncovering the hidden stories behind the numbers. “Accounting is the preparation and generation of information and the aggregation of that information in a way that’s useful in decision-making,” noted Schrand. “People think accountants are all about preparing accounting information, but I focus on actually using that accounting information to make decisions.”
Here are 4 ways Professor Schrand talks about using financial accounting information (see sidebar below) as a strategic tool for understanding a company’s true financial health and potential:
💰 Equity valuation. What is the fair value of a public company’s stock? Investors are hungry for this information as they figure out where to put their money. Investors use accounting data, particularly earnings, to forecast future cash flows and use discounted cash flow valuation models. Small changes in earnings persistence (the continuity of earnings from one period to the next) can dramatically impact a company’s valuation. “It is true based on research, that earnings, current period earnings, are a better predictor of future period cash flows than current period cash flows,” noted Schrand.
💰 Disaggregation techniques. An income statement aggregates accounting information, meaning it combines financial data from different sources into a consolidated view. It’s important to analyze disaggregated components like Research and Development (R&D) expenses, income taxes, and interest expenses to understand a business and to get at why, for example, certain earnings are likely to persist. “Financial statements are highly aggregated,” said Schrand. “But the standard setters do require certain items to be disaggregated, and they’re meant to be helpful to people who are trying to forecast future cash flows.”
💰 Analyzing managers’ decisions. Company managers can influence reported earnings in different ways, in particular structuring transactions for accounting benefits. What are the numbers telling you that might obscure or distort the true economic position of a firm? One example is reporting of research and development, an important innovation arm of a company. “There’s a lot of evidence out there that managers, if they want to show higher earnings, reduce their R&D,” observed Schrand. “Every dollar of R&D that you save increases your earnings by $1. Is that a good business decision to reduce R&D? How are you going to grow in the future if you’re not developing new things? But it makes your earnings that year look better.”
💰 Knowing the risks. Accurate risk assessment for analysts and investors depends a lot on understanding how accounting works – not just reading the surface numbers, but also interpreting what they represent. For example, Dr. Schrand, whose research focuses on earnings quality, said that not all earnings are equal in terms of persistence. Earnings that come from unusual or non-recurring events (like a legal settlement) are less reliable predictors of future performance. Higher-quality earnings translate to lower risk.
Concluded professor Schrand: “You need to understand the business model of a firm in order to be able to interpret its income statement. But on top of that, you need to understand how the accounting represents their business activities.”
I found it interesting that earnings are usually a better measure of future cash flows than cash flows themselves. I was surprised at first, but then the idea of earnings persistence makes so much sense. If a company has consistent earnings for a long time, it gives investors somewhat of a reasonable basis to rely on those earnings and project into the future. This is also part of the reason why, in some cases, even very tiny changes in earnings can have such large impacts on the value of a stock. I wonder what happens with companies where earnings are known to be unpredictable, such as startups, tech companies, etc. Do earnings have more value in those situations, too?
For startups and tech firms, earnings aren’t that useful. Amazon went over 20 years without consistent profits and still gained massive value. Same with Uber. Constant losses, huge valuation. Investors focus more on growth, market potential, and user data than earnings.
DCF can still apply, but it relies on projected revenue, not historical performance. So no, earnings do not carry the same weight. It is not about persistence. It is about potential.
It’s crazy how much managers can shape the story behind the numbers especially with things like R&D cuts just to boost short-term earnings. That’s a red flag for real growth and long-term value. Accounting isn’t just about numbers on paper it’s about understanding the real business beneath them. If more people dug into this investors wouldn’t get played by flashy but hollow earnings.
Accounting gets a bad rap. Mention it in public, and you might get the same reaction as if you’d just declared a love for watching paint dry – especially if that paint is on spreadsheets. But Professor Catherine Schrand is on a mission to rescue accounting from its “boring” reputation, and trust me, she makes a compelling case. Under her guidance, accounting isn’t dry number-crunching; it’s financial forensics. Think Sherlock Holmes, but with spreadsheets and income statements. She’s not just teaching math; she’s teaching how to decode the hidden stories companies tell through their financials.
Professor Schrand offers four sharp strategies to turn financial accounting data into something truly useful, like making smart decisions instead of expensive mistakes. Take equity valuation: she shows how looking beyond today’s stock price and into a company’s current earnings can reveal tomorrow’s cash flows. That’s not just a prediction, it’s like a superpower!
Then there’s disaggregation, which is basically ripping the mask off those neat consolidated reports to figure out what’s really driving performance. R&D spending? Market dynamics? You’ll find out. Furthermore, she sheds light on analyzing managers’ decisions, showing how accounting choices can sometimes obscure a firm’s true economic health. Finally, she tackles risk, not the kind you take when you assume your phone is charging because you “definitely plugged it in,” but the kind that significantly impacts earnings quality and long-term business health.
Ultimately, what Professor Schrand proves is this: accounting isn’t about adding things up; it’s about pulling things apart. It’s the crucial difference between looking at a company’s numbers and understanding them. It’s for people who want to know what’s really going on behind the data and make smarter financial choices because of it. So no, accounting isn’t boring. Not when it’s taught like this. It’s detective work with a calculator.
I loved this article! I’m a student in the CFA Investment Foundations program and I am studying about investing in stocks. I like Professor Schrand’s concept that accounting teaches us about money by discovering what the numbers actually say. I do something similar with NeuroEd, where I observe data to determine how engaged students are and how fatigued they become.
I enjoyed the concept of decomposing numbers. Similar to Schrand’s recommendation that R&D and tax expenses be separated, I break down user activity data, such as test scores and task duration, to enhance NeuroEd’s customized learning sequences. The in-depth data, such as identifying stocks that yield consistent returns rather than quick profits, assist investors like myself and educators in comprehending actual performance.
I consider risk and earnings quality while thinking about stocks. I review normal profits and unusual gains. I do this so that I may know when users are dropping off. I ensure NeuroEd’s AI does not mistake genuine disengagement with random behavior.
Thanks for the reminder that various kinds of numbers—such as financial statements and app usage information—tell a larger story. I will keep this in mind when I study for my CFA, make investment decisions, and develop NeuroEd.