Managing cash flow is important when making financing decisions, choosing price points, designing credit rules and executing many other business tasks. And using data instead of hunches—and analysis rather than guesswork—to model cash flow can help improve efficiency in business.
An income forecast projects accounting earnings into the future. But it may not be the best way to tell whether a company will have cash available to pay the bills, notes Bryan Lapidus, director of FPA practice for the Association for Financial Professionals. (AFP is a society for treasurers, chief financial officers and other corporate finance specialists based in Bethesda, Maryland.)
For instance, if a product line is expected to generate $10 million in revenue and $9 million in expenses in the next 12 months, the income forecast is a straightforward $1 million.
“But what happens if there is high volatility around collecting sales revenue from customers, but tight terms around payables?" Lapidus asks. “You may run out of cash while still producing income."
—Bryan Lapidus, director of FPA practice, Association for Financial Professionals
In this case, a business owner could start examining their history to get a better idea of what terms to ask for from suppliers and customers.
“Look at the data around past collections," says Lapidus. “What is the time lag for payments? What is the standard deviation? This is the crux of using historical data to project future cash flows."
A Cash-Flow Modeling Process
Naturally cash flows are different in different businesses. However, Lapidus says, “All good analyses start with a good question. What do you want to know? What decisions do you want to make?"
The next step to improve efficiency in business by modeling cash flow? Identify the data needed to answer the question. It may be sales or expenses by day, week or month, by store, region or country or many other variables.
“What are the independent variables that may impact your study?" Lapidus asks. “Get the data and make sure it is clean."
After that comes modeling and analyzing the data. Many businesses use spreadsheets for this task.
“There are other stand-alone tools, and many accounting software packages and planning systems have really increased their sophistication lately," Lapidus says. “Explore the embedded functionality in your toolkit."
Finally, see if the results make sense and seem likely to actually improve efficiency in business.
“Don't blindly follow the outputs or conclusions—there are many reasons why they may be incorrect—but think about what they say about your original question, how to interpret it and what outcomes it may lead to," Lapidus suggests.
Forecasting to Improve Efficiency in Business
Minneapolis-based job search site College Recruiter uses the company's experience to assign projected closing dates for sales contracts.
“That tends to be an educated guess based upon our experience with the customer, item and quantity being purchased, or both," founder Steven Rothberg says.
Each contract also gets a projected value based on the dollar number they think the customer will buy.
“Our proposal might be for $20,000, but if we think that they're likely to buy $12,000, if they buy at all, then the projected value is $12,000," he says.
Another percentage estimates the likelihood the sale will close.
“This is another educated guess based upon the customer, item being purchased and how far along in discussions we are," Rothberg says.
The estimated close percentage might be 10 percent to start and rise to 90 percent by the time the customer gives a verbal commitment.
All this data based on historical experience gives Rothberg a way to improve business efficiency.
“If the projected close date is 30 days from now, the projected value is $12,000 and the percentage likely to close win is 90 percent, that means that we can estimate for cash-flow purchases that we will receive a sale worth $10,800 ($12,000 x 90 percent) in 30 days," he explains.
Because it uses yesterday's data to predict tomorrow's results, cash-flow modeling is not a perfectly foolproof way to improve efficiency in business.
“The biggest challenge to using historical data to project forward is that the future may not look like the past," Lapidus says. “This is especially true of smaller companies that do not have a long track record, or may change their product set or customer interactions quickly that it renders the historical data incomplete. When you try new things, then comparisons to history lose their relevance."
Data accuracy is another issue. Numbers generated by the accounting system may be accurate. However, other departments may use different systems and formats.
“The interaction of finance and operational data can shed a light on cost efficiencies, but are the data sets compatible?" Lapidus asks.
The digitalization of business means more data is available than ever before. And, Lapidus says, as a general rule businesses are getting smarter about using data to improve business efficiency.
“The software is getting better at making the tools available, which leads people to use it more often and more successfully," he says.
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