If you were to ask a typical salesperson how much of a given product they believe should be on hand at all times, they’re likely to respond with a number so high that the company’s bottom line couldn’t bear it. After all, it’s a salesperson’s job to move product, and you can’t sell what isn’t there. At the same time, however, reality dictates that today’s businesses must attempt to run just-in-time supply chain operations just to stay competitive. That means from a logistics perspective, the ideal answer to the same question is as close to zero as is possible without disappointing customers.
In practice, most of the time these two competing desires must meet somewhere in the middle for sustainable operations. To make that happen, salespeople and their departments have to have realistic discussions so they can create reliable sales forecasts to aid in their company’s sales and operations plans (S&OP).
The good news is that it’s not necessary to have a background in supply chain management to participate in the process, from a sales point of view. All that’s needed is some real-world sales data (if available), and the right forecasting process to come up with an accurate result. To help, here are a few different sales forecasting methodologies, and when they should be used.
Lead Analysis Forecasting
If the sales you’re trying to predict revolve around building relationships to convert qualified leads into sales, you can use your lead data to make a sales forecast. Here’s what information you’ll need:
- An average number of leads acquired in previous months
- A breakdown of where those leads came from
- A conversion rate per lead source
- Average sales revenue per lead (broken down by source)
If you have this data available for at least three previous months, it should allow you to work out how many sales should come in via each lead generation method in use. It should also provide hard numbers as to the number of products sold that can form the basis of a future projection. As a side benefit, this method also provides insight into how well your conversion processes are working, and which ones might need some work.
Opportunity Stage Forecasting
Sometimes, lengthy sales processes make it difficult to isolate a reporting period to use as a basis of a projection. For example, a salesperson may work with a customer for months to close a large sale or end up losing the sale just before the finish line. Other customers might move swiftly through the pipeline and close in mere days. To make a prediction on a process like that, you must look at your historical data to calculate the odds that a sale will close based on how far along it is in the process. This is best accomplished using a CRM solution like Pipeliner CRM or a similar product.
For example, you may discover that in the earliest stages (like leads coming in from a web form), there’s a chance of conversion of 10% or less. For leads that go further, such as in-person meetings or product demonstrations, the rate is closer to 80% or more. To make a prediction using this information, analyze the data for as many months as you have and categorize where each potential sale was within the period. Then use the odds you’ve established to estimate how many sales should have closed within the period. You should end up with a nice rolling sales average that may be used for a future projection.
If the business hasn’t been in operation for very long, or if there isn’t enough hard sales data to make a reliable prediction, there’s really only one alternative: getting a prediction from each individual salesperson. This method, of course, is only for startups and the like who have little choice but to start somewhere – and even then is only advisable if the salespeople involved have plenty of experience to draw on.
As a forecasting method, it couldn’t be simpler. Just ask each salesperson to provide a report on what they believe their sales output will be each month. Let them know they won’t score any points by talking up their potential results or offering too-rosy estimates of their ability. With luck, they’ll be able to come up with figures that are at least somewhat reliable. In this scenario, though, it’s critical to simultaneously make plans to start collecting the types of data that will allow for a different methodology for future projections.
The Bottom Line
It’s important for salespeople and their departments to realize that there’s a real business imperative to keep costs low by only producing or purchasing enough inventory to cover expected sales. The better their analysis and the more honest their estimations are, the more the company will benefit. The company’s supply chain operations will become more efficient, too – and that will help to guarantee that there’s always product available to sell and that every customer is served on time, every time.
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