Here at InsightSquared, we’ve talked to a lot of sales managers about their analytics and reporting. Every single one of those conversations inevitably finds its way to the topic of forecasting. It is the one report virtually every sales leader thinks about every single day. Regardless of sales model or approach, even the most nascent sales organization spends time building and maintaining forecasts.

Before we go too much further on various sales forecasting methods, we should set a common understanding of what a forecast is. A sales forecast is a projection of what your performance as a sales organization will be at the end of a measurement period (most often either monthly or quarterly). It is the expected value of your bookings at the end of the measurement period, i.e. how much business you think you will close.

If you’re just getting started with forecasting, here’s a run down on basic sales forecasting techniques and their strengths and weaknesses:

Opportunity Stages Forecasting

In CRM system such as Salesforce.com, your opportunities each have a status or Opportunity Stage. Each stage represents a milestone as you work towards taking a validated sales opportunity across the finish line and closing the deal. As an example, in the software world, these stages might be steps like “Completing an assessment call”, “Providing a demo”, “Enrolling in a trial”, “Submitting Quote” and “Closed – Won”.

Each of these stages will have a “probability of closing” associated to them. So an opportunity in an early stage might have a probability of closing of 10%, whereas a later stage (like “Submitting Quote”) might have a 90% probability of closing.

Using this method, sales leaders create a basic forecast by multiplying the amount associated to each opportunity by each opportunity’s probability of closing, for those opportunities expected to close this period (i.e. those with a close date set in the CRM to this period).

Here’s a quick example:

There are some advantages and disadvantages to this (and any) approach. Lets run them down:

Pros:

• The math here is easily understood.
• The method is highly objective. The emotional element is largely taken out of the equation. If it is in an early stage, the probability of closing is low, no matter how good the sales rep feels about the opportunity.

Cons:

• The probabilities associated to different stages are rarely tested nor rigorously derived.
• Further analysis is needed. A conventional pipeline forecast will not account for opportunities that will close in that period but have not yet entered the pipeline. Furthermore, the shorter your sales cycle, the bigger this issue becomes.
• This approach is reliant upon accurate close dates in your CRM. Sales leaders are often hounding their reps to update their close dates with this method.
• Sales cycle length is not taken into account. An “ancient” opportunity that is 2 years old but set to have a close date of this month is counted the same as the “typical” opportunity that is only weeks old and also due to close soon.

Forecast Stages

To combat some of the flaws of the previous approach, other sales organizations use Forecast Stages to generate their forecast. Independent of the milestone hit by the opportunities, sales reps and managers are asked to make an assessment of their opportunity. Common forecast assessments might be “Commit” (i.e. I am committing to bring this in), “Strong Upside” (i.e. if a few things go our way, this could come in), “Upside” (if more things go our way, this could come in) and so forth.

Sales managers use these assessments to build out different scenarios for the consumers of their forecasts (CEOs, CFOs). The “worst case” scenario would be just closing the Committed opportunities. The “Strong Upside” scenario assumes more deals closing. The Upside scenario is more optimistic and assumes even more deals closing.

Pros:

• Companies can calculate a forecast well in advance of many opportunities reaching later stages in their progression. A sales rep can say “this deal is early, but I’m putting it in ‘Commit’”. This is more commonly followed by sales teams with longer sales cycle times and external, field sales teams.

Cons:

• Its much more qualitative and subjective. People, especially on the tails of a good meeting or a strong demo reaction, will be optimistic about their deal. They will have “happy ears” and lead to overly optimistic forecasting.

Length of sales cycle and other methods

More advanced methods can of course be used. One such advanced method would use the length of the sales cycle to adjust the expected value. By evaluating the age of each of your opportunities and comparing it to the typical length of your sales cycle, you can judge algorithmically the likelihood the opportunity will close in the period you’re forecasting as opposed to a later one.

The math in an approach such as these can get complex, quickly. Which is why more advanced reporting and analytics solutions are useful. You, as a sales manager, can focus on your strengths and leave the fancy math to the MIT PhDs behind the scenes.

Let’s get creative

Sales leaders are a creative bunch. More than one has said to me that forecasting is “half-art, half-science”.

The methods I outline here are relatively basic. If you’ve built a forecast, you’ve probably modified, tweaked and improved your own methods.  Certain types of customers might have a track record of closing more frequently than others. Or certain geographies might haggle for lower prices with greater regularity.

Have you set up a Sales Forecast? How has it worked for you?

Interesting in reading more about how to build a sales forecast? Download the eBook: