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As a sales professional, you know the role of sales forecasting in the success of your business. You might also know how difficult it is to build an accurate sales forecasting model. Several standard sales forecasting methods exist, but there’s no one-size-fits-all model.
For those new to sales forecasting, it’s a process of predicting future sales revenue based on historical sales data, industry trends, and your current sales pipeline. Forecasting sales revenue is essential for business decisions like budget allocation, new hiring, and production planning.
Accurately forecasting sales helps you set realistic business goals. But a study by Korn Ferry shows that fewer than 25% of sales organizations have 75% or more accuracy in forecasting sales. So how do you build an accurate sales forecasting system?
First, we’ll look at how standard methods for sales forecasting fare in predicting sales. Then, we’ll introduce the structure, process, and methodology framework that we use at Cirrus Insight. This sales forecasting model was developed by Sean Picket, our VP of Revenue and Strategic Partnerships.
We hope this method will help you build a unique sales forecasting model for your business.
Here’s what we’ll cover:
Sales Forecasting Methods
Structure, Process, and Methodology (SPM) Framework for Sales Forecasting
Fine-Tune and Enhance Your Sales Forecast Model
Now, let’s have a quick look at these common sales forecasting types. Each has its benefits and drawbacks.
Historical sales data is crucial for forecasting future sales. You take your past sales data and add your year-over-year growth to predict new sales. Forecasting based on past performance is a simple method, and it works well for markets that aren’t prone to changes.
However, it doesn’t yield accurate results if the market has too many fluctuations. If you’re a new business without much historical data, you won’t be able to use this method. Sales forecasting based on past sales data also doesn’t consider your current sales pipeline.
This forecasting method is based on how long a lead takes to convert into a paying customer — that is, the length of your sales cycle. It makes predictions based on how long a lead has been in the sales pipeline.
This method doesn’t give accurate results if you have multiple products with different sales cycles and lead generation methods. It also doesn't consider market fluctuations.
The lead-based forecasting method analyzes each lead in your sales pipeline. Then it calculates the probability of each lead converting into a paying customer. You’ll need detailed information about each of your leads, and the conversion rates of your past leads to use this method.
This method also doesn’t consider market fluctuations. It relies on your past lead conversion rate, which is susceptible to change based on various factors.
This is a basic method used by many businesses to get a rough idea about future sales. Sales reps submit their estimate of the number of deals they’re expecting to close and the timeline for closing.
This method is helpful for business planning if you don't have historical data. However, it’s subjective as it’s based on human intuition. Often, salespeople will be optimistic about future sales, resulting in higher sales predictions.
This sales forecasting method looks at your sales pipeline and shows you the probability of closing deals at each stage of it. Then it forecasts future sales by multiplying this probability by the number of leads in each stage.
For this method, you only need to guess the conversion probability in each stage. But it doesn't consider the opportunity’s age — that’s for how long a lead stays in your sales pipeline.
Businesses seldom use just one type of sales forecasting. Instead, they use a combination of the above sales forecasting methods, using multiple variables, such as:
Multivariable forecasting is accurate as it considers multiple aspects. It often uses forecasting software equipped with artificial intelligence (AI). However, it’s quite complex, especially for small businesses.
As you can see, the standard forecasting techniques have their advantages and disadvantages. They may not work for you as is, so you need to create a custom model for your business. That’s exactly what the structure, process, and methodology (SPM) framework will help you do.
Developing an accurate sales forecasting model isn’t one person’s job. It requires an organization-wide effort, starting from the top decision-makers like the CEO and the board. We’ll see how the SPM method can help you create a model to make accurate sales forecasts.
To start with, SPM isn’t a how-to guide for creating a sales forecasting model. Instead, it’s a guideline that helps you look closer at your organization’s structure and sales process to develop a forecasting methodology.
The SPM framework for sales forecasting involves the following steps:
Does that sound too abstract? While it may take some time to implement the SPM framework, it works once you have all the pieces in place.
At Cirrus Insight, we’ve developed a robust sales forecasting model using the SPM method. As a sales professional, you’ll be able to take some key points from our experience and implement the SPM model as it fits your business.
Now, let’s take a closer look at the SPM method.
To create an effective sales forecasting method, you need to take a closer look at your sales organizations first. In this step, you’ll explore how your business goes to market. For that, you need to create the organizational structure for the following go-to-market organizations:
Map the structure of each of these organizations to their finest granularity, starting from the top executives to sales reps. That will help you understand the following crucial information required for sales forecasting:
For each organization, estimate how many leads are generated and their quality.
For example, you might be getting better leads from marketing or a specific department within it, like social media marketing. But your sales department’s outbound calls may not be resulting in great leads.
In this step, you analyze the structure of your go-to-market organizations and their lead generation capabilities.
In the next step of the SPM framework, you’ll analyze your sales processes. You can start with the following question: “Do we have a well-defined sales process?” If you don’t, you first need to define your sales process.
You might be following industry standards processes like solution selling, strategic selling, or the software-as-service (SaaS) selling process. Whatever your process, you need to map it out step by step.
When you map out your sales process, ask the following questions:
When you map your process and answer these questions, start tracking your historical data. Your past sales data is a great resource to make accurate forecasts.
Next, start looking at the probability of closing sales at each stage of your sales process. For example, only 10% of opportunities at stage one of your sales process will close, 20% of opportunities in stage two, and so on.
Another crucial aspect of the process step is understanding who you sell to. Your forecasting accuracy will significantly improve if you consider:
For example, decision-making happens fast in small businesses, so you’ll have a short sales cycle if you sell to them. But if you sell to big enterprises, your sales cycles might be longer. You need to layer this information in your sales process to get a better forecast.
In the methodology stage, you’ll build a unique sales forecast framework using the insights gathered during the structure and process steps. After the first two steps, you’ll have multiple estimates that’ll help you build a sales forecast model:
The methodology stage is where you put all this information together and make an educated guess about your future sales. Note that this stage happens in cycles, where you repeatedly update your initial sales forecast model.
You might not get it perfect on the first go, so you’ll need to fine-tune your sales forecasting method.
Once you create a sales forecast model, you need to be receptive to changes. You may not get the model right on the first attempt. You need to compare your actual sales to the forecasted sales quarter after quarter and then adjust your sales forecasting model based on your comparison.
Your sales forecasting model might need a lot of tweaking before it can predict sales accurately, especially for new businesses. While adjusting your model, you can also get help from industry standards, third-party resources, and advisors. You’ll also need to schedule quarterly reviews of the methodology and see if it’s been accurate.
Creating a sales forecast model using the SPM method requires collaboration from your entire organization. Essentially, to effectively use the SPM method, an organization should have the following mindset:
“Here's the structure of the organization, here's how we go to market, here's our sales process, here are the steps we take within each of the stages. Let's make sure we keep the CRM system updated so that we can have some accurate forecasting there."
—Sean Piket, Cirrus Insight VP of Revenue and Strategic Partnerships
Once you’ve created a sales forecasting model using the SPM method, you need to enhance it. Sometimes, you might need to look outside your organization for inspiration. Here are some tips for improving your sales forecasting model with external help:
Creating an accurate sales forecasting framework is crucial for your business’s health and success. While there are several methods to forecast sales, there is no one-size-fits-all sales forecasting method.
Structure, Process, Methodology (SPM) is a framework to systematically create a well-rounded sales forecast model. It involves three essential steps:
Creating a sales forecast methodology is a continuous process that needs your entire organization’s collaboration. You also need to research industry standards and consult with specialists and peers to create an effective sales forecast.