How to Forecast Revenue Accurately

Why accurate revenue forecasting matters

Creating a revenue forecast allows companies to plan for future projects, increase hiring, budget for purchasing commercial property, introduce new products, manage future cash expenses, and more. Companies that can forecast accurately tend to have a notable advantage over their competition.

In fact, research from Aberdeen Group shows that there’s a direct connection between more accurate revenue and sales forecasts and higher-performing businesses.

Typical sales forecasting relied on sales professionals to provide the information to create sales forecasts. But this simply doesn’t work unless they’re using a data-driven approach. What’s most likely is that they’re using ‘best case scenario’ evaluations of what their sales numbers will be.

Barriers to accurate sales forecasting

There are a few things that consistently interfere with acquiring those much-needed accurate forecasts:

  • Data Problems: Either not enough data, the wrong data, or data based on potential deals that may or may not close
  • Excessive Positivity: Everyone wants to give a good report, and the tendency is to focus on the most positive possible numbers and receivable increases—even when those numbers are the least likely
  • Disconnect Between Forecasts and Reality: Companies that consistently use sales professionals’ forecasts without going back at the end of the term to review how accurate those forecasts really were may encourage reporting without accountability
  • Evaluating Sales vs Costs: A full picture of sales forecasting must include the data on the cost of sales. Without this, managers and teams don’t have an accurate understanding of the forecast. Of course, depreciation of current assets can also impact the total amount of the cost of goods.

Underreporting revenue projections and missing things like cash payments may cause a company to take an overly conservative approach to its budgeting. They may delay expansion, curtail investing activities, avoid large credit sales, fail to hire enough staff, and miss opportunities for future growth. When revenue is higher than these projections, businesses may have already increased their current liabilities unnecessarily. They may even be hit with an unexpected income tax bill.

The opposite happens when overreporting revenue projections. Companies may commit to unrealistic expansions, onboard too many new hires, rely too heavily on cash flow from operating activities (or have negative cash flow), and fail to respond to changing market conditions in a timely manner.

revenue forecasting

The foundation of revenue forecasting

Revenue Forecasting: The process of predicting the revenue generated in your business over a specific accounting period (monthly, quarterly, or annually).

Two of the most basic reports of a revenue forecast are whether the business will grow or contract, and how much it will do so. While the term ‘forecast’ indicates that this is not exact, companies (and those who analyze companies) are expected to provide fairly accurate revenue forecasts.

We want to avoid Judgment Forecasting and focusing on Quantitative Forecasting. As its title suggests, judgment forecasting is mainly intuitive, uses subjective data, and leans heavily on experience and anecdotes.

Quantitative Forecasting uses current, objective metrics along with specific past information (records, sales figures, and past forecasting). Of course, if your company has only used Judgment Forecasting in the past, those forecasting numbers won’t be very useful. But consistent discrepancies between forecasts and actual numbers may be the motivation to switch to a more reliable method.

Before we get into specifics, we must acknowledge the place that unexpected and unpredictable events have on forecasts. The coronavirus pandemic influenced massive discrepancies in forecasts—far better performances for some, and far worse for others. Companies are working to build resilience into their business plans, but there will always be an element of the unknown.

Simple forecasting method

There are a variety of revenue forecasting methods. If your company has relatively stable revenue and a consistent growth rate, you can use the simple direct method of forecasting. This method takes the product of the last quarter’s revenue and growth rate to determine the next quarter’s revenue as well as average revenue growth. Here’s what it looks like:

  • Q1 Revenue: $500,000 Q1 Growth rate: 2.1%
  • Q2 Revenue: $515,000 Q2 Growth rate: 2.9%
  • Q3 Revenue: $525,000 Q3 Growth rate: 1.9%
  • Q4 Growth rate forecast: (2.1 + 2.9 + 1.9)/3 = 2.3%
  • Q4 Revenue forecast: 2.3% growth x $525,000 = $537,075

Using an average of the previous three quarters of growth rates, Q4 revenue is expected to be $537,075. The straight-line method works well when growth is consistent and should correlate to the balance sheet for that quarter or period of time. For companies with more volatile growth or expenses (or both), this method won’t work.

Timelines and expenses

These are the easier parts of a revenue forecast to get right. The timeline (the period of time that the forecast includes) you choose is based on the nature of your business. Since forecasts use resources, smaller companies may choose quarterly, or even annual forecasts. Seasonality and businesses with revenue that fluctuates throughout the year may use longer timelines or compare the same quarter year-over-year.

Or, you may base your timeline on your average sales cycle (often directed by cash flow from operations). Whatever you choose, it’s best to stick to it so that you can make valuable comparisons between forecasts.

In general, your expenses are also fairly predictable data points. Fixed expenses just need to be transferred to your forecast as is. Variable costs will require some guesswork. Looking at past timelines and comparing the changes in variable costs may help, but you’ll have to take into account fluctuations in the business (and economy) that impacted your variable expenses.

Sales forecasts

Here’s where many companies get a little overwhelmed. The best way to create accurate sales forecasts is with accurate data. Ideally, each sales professional will have accurate numbers on each of their clients, the total revenue generated from each client (the timeline can vary, as long as it’s the same for each client), and the total cost of the sale. With this, you can determine the average revenue each sales professional is generating per client.

Couple this with data on leads vs clients (how many leads convert to clients), and you’ll be able to determine with some accuracy how much of a sales professionals’ pipeline will convert to real revenue and positive cash flow.

There are some great online tools to help your sales professionals track their sales pipeline, lead generation metrics, average close rates, lead-to-client conversion rates, and average revenue per client. This information can become a powerful forecasting tool for sales professionals to streamline their approach and focus on the clients most likely to convert and produce the most future revenue. And it's rewarding to see how income statements reiterate the forecasts when they're based on accurate sales information.

As we mentioned at the start, relying on gut projections or best-case scenarios will not give useful data. However, there is an element of intuition that can contribute to a sales forecast. Experienced sales professionals often have helpful predictions about the market. They’re aware of new competitors, competitors that may be closing their doors, and changes in market dynamics. All of these aren’t data-driven, but they’re important to consider.

Addressing the challenges of accounts receivable and accounts payable

All the forecasts in the world don’t help when you’re facing unpredictable payments. For many small and medium businesses (SMBs), extending net terms is a crucial part of closing sales deals and pursuing larger contracts. But those net terms can leave a challenging cash flow situation that may impact your revenue forecasts while reducing the total amount of cash payments you receive. The past year has created substantially more challenges for cash inflows. Some customers—even ones with longstanding reputations for always paying on time—have simply not made their payments. This has impacted financing activities, short-term cash flow, and even created new liabilities when the ability to meet financial demands simply isn't there.

The solution to accessing working capital while ensuring positive cash flow includes a service called digital net terms. Resolve Pay works with businesses to run discreet credit checks on potential clients, determine the ideal net terms for each situation, and then advance pay up to 90% of invoices from approved customers within one day. With your repayment and cash flow challenges resolved, you can accurately report net income, use your receivables as a source of cash, meet your accounts payable needs, reduce liabilities, and negotiate better terms with your suppliers.

Taking this approach empowers your team when creating the next revenue forecast by eliminating the unknown of future payments and revealing the creditworthiness of customers.

Project-level reports and revenue forecasting

Another group of metrics you can put together to assist with more accurate revenue forecasting are project-level reports. These will look at all the historical data involved in a project (both successful projects and those that cost your money): hidden expenses, inside costs, overhead, and of course, income. They can be very helpful when your business has various revenue streams.

Looking at project profitability will give insight into the expected revenue of upcoming projects. If you already have project-level reports, you can use them as a starting point to compare profitability between different clients and projects. And creating a system to track them going forward will give you useful data for revenue forecasting.

Businessman studying data

The more data you have, the more you know

New businesses and startups will have more of a challenge with revenue forecasting than businesses that have data going back for years. Time will help. The more data you gain, the more you’ll know. And comparing the effectiveness of revenue forecasts against actual results is the only way to truly determine how accurate your forecasts are.

The longer you’re in business, the more you’ll see the impact of trends, liabilities, changes, growth, depreciation expenses, and constriction in your business—provided you’re consistently using equivalent data for your comparisons. To some extent, you should be able to use other company’s forecasts that are similar to yours to get an idea of what kind of growth to expect.

At the same time, it’s important to leave some room for error and the unexpected in your forecasts. Look at how you’ll handle unexpected growth as well as unexpected losses. If the pandemic has taught us anything, it’s to prepare for the unexpected!

Internal revenue forecasting vs analyst’s revenue forecasting

We’ve only discussed the revenue forecasting that companies and business owners do internally and use to direct their budgeting, revenue projections, and plans for expansion or cutbacks.

But another area of forecasting is security analysis done by stock analysts on publicly traded companies. These are used by investors and shareholders to determine future decisions. While being a publicly-traded company isn’t necessarily at the top of a small business owner’s list of priorities, it’s helpful to know that the basic tenets of revenue forecasting and following good accounting principles will guide the business as it grows.

Stock analysts use data from the company, industry data (things like how the industry as a whole is performing) and even consumer information to guide their results. You can use this information as a small business. Look into the analysis of companies in your industry. Learn about potential market size, competitors, and current market shares. It’s also helpful to follow reports from relevant industry groups.

Analysts also look at the financial statements of companies. Balance sheets give good information about a company’s current inventory level and how their inventory is changing between reports. Shipments and predicted unit sales are also important.

You can certainly apply the information gained from these large evaluations to your own forecasts. If seasonal sales are projected to be higher than average, and your business is primarily seasonal sales, you can prepare (and make a marketing plan) to take advantage of those higher sales.

The limitations of forecasting

Using the same forecasting method each quarter is important for generating an accurate forecast. Continuously changing your forecasting method can get complex and doesn’t allow you to improve your technique. And, things like net cash flow, liquidity, and irregular debits for companies that primarily rely on cash sales will have an impact.

Also, know that forecasts aren’t crystal balls. Sure, you can get a good idea of what revenues will be for the next quarter, and maybe the next year. But, going out five and ten years is an exercise in futility. In general, the further out in time for your forecast, the more likely it is to be incorrect.

Focusing on good operational controls will help with generating consistent revenues, which, in turn, can help improve forecasting. These controls include being able to get accurate data from people on the front lines of the business, such as salespeople. Over time, they will align with statements of cash flows, and balance sheets while directing operating activities that promote growth.

Big shocks will certainly throw off a forecast. If 25% of the company is laid off, that’s a very large fluctuation and will likely have a substantial impact on your forecast. It will come through in revenues, but your forecasting may not be able to accurately predict it. The next few quarters will allow the company to reset and the forecast to come back in line.

Good forecasts are always dependent on good data. And the more timelines you have with good data, the better your forecasts will be. Start with the data you have and build on that to create a solid history of usable and relevant data.

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