Financial forecasting is a high priority for CFOs, and doing it more efficiently and accurately is an admirable goal. Yet so much has been written about forecast accuracy that it is has become one of the myths of modern finance. When managers chase accuracy, the mere act of forecasting often causes them to alter their action plans, which alters their ability to track forecast accuracy.
Steve Player, APQC’s senior finance fellow, recommends tracking forecast reliability instead. In tracking reliability, you measure to see if a forecast is free from bias.
An unbiased forecast is one critical cog in the continuously rolling wheel of financial planning for any organization, but if a team is spending too much time on forecasting, it’s not spending those hours on other, high-value priorities.
For this month’s metric, we focus on the cycle time in days to prepare the financial forecast, as reported to APQC’s Planning and Management Accounting Open Standards Benchmarking survey by 1,416 business entities.
For the purpose of this metric, APQC refers to forecasting in general, regardless of time period. The data reflect all of the activities involved in preparing a financial forecast, including creating estimates of the projected income and expenses, as well as developing projections of profit-and-loss statements, balance sheets, and cash flow. This may include updates and revisions to the rolling forecast.
The fastest 25% of organizations can prepare a financial forecast in eight days or fewer, while the slowest take 16 days or longer. At the median are the organizations that need 12 days to prepare a financial forecast.
Let’s assume we’re talking about a quarterly forecast process, including updating the rolling profit-and-loss forecast. Over the course of one year, the slower group needs more than one additional month of FTE time to complete the same work as the fastest group. That’s a whole month of effort that those finance teams could be applying to other strategic priorities.
Whether an organization creates a comprehensive forecast every month or on a quarterly basis, the forecast needs to be reliable and fast. Business unit managers and executive leadership need that projected trend data, in which operational information is converted into expected revenues, costs, and operating profits. With it, they can adjust the sails of the organizational ship as needed. If it takes too long to produce a forecast, it may be too late to turn back before sailing into a storm, or the winds may have already shifted and blown the organization further off course.
If it takes a finance team 16 or more days to create a forecast, that time could be better spent performing analysis that could help the organization navigate into calmer waters. Chances are, organizations in that bottom quartile have a forecasting process that’s heavily dependent on manual work.
Time delays are also often the result of a lot of guesswork involved in forecasting, based on subjective input from a lot of different people. In addition to taking a lot more time, this kind of judgmental forecasting tends to be less accurate, because it’s easy for key drivers of performance to get overlooked.
Many organizations are stuck just doing simple judgmental forecasts. They just ask their sales personnel how much business they think they will close this month. But sometimes, salespeople, wanting to look good to their bosses, will tend to underestimate so they can under-promise and over-deliver.
If sales repeatedly does that, either finance or operations will begin to inflate their forecasts to avoid the period-end fire drills they have to do to meet the extra units that sales has left out of the forecasts. A guessing game is created that lacks transparency and leaves lots of potential on the table for the competition to grab.
Smarter companies track what’s happening in the sales pipeline based on contacts made and relationship maturity. They track how marketing efforts are enticing sales prospects at various steps on the journey to becoming customers. They have studied their sales process and know how long it takes to move prospects through the sales funnel — from interested prospects to qualified buyers who are asking for a demo — and can predict how current activity will drive results.
It may take weeks to develop the business algorithm that creates a financial forecast. But doing so helps the CFO get to know the business better. Start tracking what’s happening in sales, marketing, and all other areas of the business. Figure out what causes a sale to close and what’s driving the sales lead engine. Understand those drivers earlier in the process, so buying behavior can be tracked and sales predicted with more lead time.
Forecasting well and forecasting quickly are often linked. Those who can do it quickly are most likely capitalizing on available technology and are able to produce mini-forecasts on demand. They are tracking key drivers and have established algorithms that allow them to pull a forecast at any time. They’re also tracking leading predictive indicators.
All of that may sound even more time-consuming, but once the organization is tracking the right indicators and collecting the right data, the power of analytics, enabled by automation, makes it easy. When, as CFO, you start drilling down into the data and asking questions, the answers help refine your questions and nail down the predictive information you really need. Then, it’s a simple matter to pull daily snapshots, play with the outcomes of different scenarios, and quickly prepare detailed financial forecasts, so that the organization can pull the right levers.
Perry D. Wiggins, CPA, is CFO, secretary, and treasurer for APQC, a nonprofit benchmarking and best practices research organization based in Houston, Texas.