Want better forecasts? Try creating universal opportunity definitions and benchmarks for your team.
I’ve seen many Salesforce admins and business analysts struggling with defining salesforce opportunity stages and the associated probability values. Why is it important?
Well, one of the core purposes of a CRM system is forecasting. This means the company needs to understand as accurate as possible how much money they are going to make and thus how much money they can afford to spend. This is called "revenue forecasting". Other forms of forecasting are "post sales resources forecasting" (e.g. how many deployment specialist are we going to need) or "supply chain forecasting". Here are two two simple measures to get to a significantly better forecast accuracy, without even having to use the newer and much more complex forecasting feature.
Salesforce Forecasting Basics
The opportunity object has four important fields related to forecasting: Amount, Probability (controlled by the field Stage) and Expected Revenue. If Amount and Stage are populated, the Expected Revenue automatically evaluates to Amount x Probability.
This makes sense since let’s say you have a $5000 deal in the pipeline which will be closing with a 50% probability, the CFO can expect $2,500 revenue from that deal at this point in time - thus the value of Expected Revenue is what you are forecasting.
This example illustrates the importance of (a) assigning the right percentage value to each sales stage and (b) making sure users pick the right value at the right moment.
Note that the field Probability is controlled by the field Stage. Every pick list value of that field has a specific percentage defined. These pick list values are supposed to reflect the stages/milestones in your sales process.
When you assign percentages to the individual pick list values you must not pick random percent values. Instead, for every stage you should look at past opportunities and for each sales stage ask yourself the question "what’s the percentage of of deals that closed after they reached this stage?".
You might come up with a table like this
- Discovery: 14%
- Product Demo: 21%
- Trial: 63%
- Contract Negotiations: 92%
- Closed - Won: 100%
- Closed - Lost: 0%
For example only 21% of all opportunities that reached the stage Product Demo eventually closed. The remaining 79% dropped out.
At first you might find these "unround" numbers odd, but you will be surprised how this leads to a realistic Expected Revenue number without any extra effort for your users.
Salesforce Opportunity Stages
It is important that all sales reps have the same understanding when to pick which sales stage. Ambiguity must be avoided. One typical source of ambiguity is when it is unclear whether a stage describes a "completed milestone" or a "task in progress". For example if you have a stage called "Product Demo" does that mean "a product demo has been scheduled" or does it mean "we gave them a product demo and now we are working on the next milestone (e.g. product trial)”.
I prefer the "tasks in progress" paradigm where a sales stage is defined by a number of individual tasks that are supposed to be completed without any particular order. For example the stage Product Demo could be defined by the tasks "schedule demo", "prepare the demo", "conduct the demo", and "analyse feedback". I have seen companies that have checklists for each sales stage in order to make sure all required steps have been completed before the opportunity can go to the next sales stage. Point is to make sure everybody is on the same page what is included in each sales stage.
The sales stages in the example above also seem to have a huge gaps between Product Demo: 21%, Trial: 63% and Contract Negotiations: 92%. This means a lot of vagueness in your Expected Revenue. Ideally you are able to find sales stages in between these. For example can the stage “Product Demo” be split into two stages and a percentage value can be assigned to each, following the rule above?
What does that Mean in Practice?
If your company is selling different types of good/services that all have in fact the same sales stages but the percentage values are different, you will have to create more than one sales process with the specific percentage values. Salesforce won’t let you create the same Stage Name twice so you have to come up with a minor difference in the stage name.
As your business changes, the percentage values will change over time too. So you will have to adjust them from time to time.
We have described how you can get to a significant better revenue forecast accuracy by avoiding ambiguity on the meaning of your sales stages and by using empirical values as percentage values. This comes with no extra effort for your users.