A sales pipeline is a structured visual representation of the sales process, indicating the current value of opportunities at each stage in the pipeline. Forecasting leverages this pipeline data and historical trends to estimate the value of deals expected to close in a future period.
Sales pipeline forecasting is the cornerstone of business strategy. It provides the top management with a clear picture of expected cash flows. It enables data-backed decisions for capacity expansion, allocating marketing spending, and securing finance. However, The 2021 State of Sales Forecasting report by Insightsquared reveals that 68% of B2B businesses missed their forecasts by more than 10%. Pipeline forecasts must be automated and streamlined using a structured approach to ensure accuracy.
Methods for Sales Pipeline Forecasting
The two most commonly used methods for assigning probability weights are listed below.
1. Opportunity stage method
This method assigns a probability value to a deal based on the stage at which it is in the sales pipeline. The further a deal is along the sales pipeline, the likelier it is to close successfully. The probability value assigned to each stage is per historical data analysis. In the absence of historical data, this method is vulnerable to subjectivity in setting the probability values.
This method is straightforward to implement with most tools. However, it does not account for the age of the deal. A deal stuck in the pipeline for months is treated the same as a deal that has progressed rapidly.
2. Length of sales cycle method
This method sets a probability value for a deal based on the time it has already spent in the sales pipeline compared to the average sales cycle length. The probability of successful deal closure increases as it nears the average sales cycle length. You can calculate the average sales cycle length from historical data. It is the average number of days it takes for a lead to travel through the sales pipeline.
This method is also straightforward to implement and is less subjective. However, it requires accurate historical deal data and timely updating of the sales pipeline.
Steps in sales forecasting
While there are several statistical sales forecasting methods, the following note focuses primarily on pipeline-based methods. The steps described below are prerequisites for forecasting sales.
1. Document the sales process
A well-documented B2B sales process understood by all sales reps and teams is the first step toward defining a sales pipeline and using it to forecast sales. It must list all tasks and workflows comprising the sales process and clearly define target-setting mechanisms for the sales reps.
2. Define the sales pipeline stages
The next step is to create a sales pipeline. Based on the sales process, you can define stages or milestones that denote the completion of key activities of the sales process. For example, qualifying leads, sending proposals, and providing live demos can be defined as intermediate sales pipeline stages. It is also crucial to have a complete consensus among all teams on the definition of each stage.
3. Gather historical sales data
It is necessary to gather historical deal data to ascertain the critical parameters required for forecasting. You need data regarding the number of opportunities generated, deals closed, deal sizes, and the time taken to win deals over the last year or more.
4. Update sales pipeline values
The next step is to update the sales pipeline with the latest deal data. It should show the total number and monetary values of deals at each pipeline stage. Sales reps should regularly update the sales pipeline to reflect the most current data.
5. Select a pipeline forecasting method
Pipeline-based forecasting methods assign a probability value associated with each opportunity to calculate a weighted value. For example, if the actual value of a deal is $2 million and it has an 80% probability of conversion, its weighted value is $1.6 million. The total of the weighted values of all opportunities in the pipeline gives the forecasted sales value. The probability values must be assigned using a suitable forecasting method.
Sales Forecasting Benefits
Accurate sales pipeline forecasting is a competitive advantage for B2B businesses. It results in the following benefits:
Helps grow sales and achieve targets: According to Aberdeen Group’s research, companies accurately forecasting sales are 10% more likely to increase their revenue year-on-year and 7% more likely to hit their targets. Forecasting helps identify warning signs and take corrective action early.
Predicts cash flows: Sales forecasting enables businesses to predict incoming cash flows to plan accordingly for securing short-term and long-term financing and managing payments.
Improves sales and marketing budget allocation: Sales pipeline forecasting enables enterprises to understand the most effective marketing channels for generating high-quality leads. It also helps allocate budgets for the sales activities that boost the sales pipeline velocity.
Optimizes inventory management: For B2B product companies, sales forecasts form the basis for inventory management. It helps avoid excessive inventory that ties up capital and also avoids stockouts.
Sales forecasting tools
Digital sales pipeline forecasting tools can help enhance the accuracy of your sales forecasts. They integrate seamlessly with campaign and CRM tools to collate the current and historical data. You can configure business specific sales pipeline stages, and intelligent analytic algorithms can automatically calculate the sales forecasts for a given period. These forecasts are made available as real-time visual dashboards for the top management to enable strategic decisions.
