What does an ideal sales pipeline look like?
Monday, July 27, 2009 at 8:00AM One of our clients asked us recently: “What does an ideal sales pipeline look like for our business?” They were looking for reliable standards that sales managers could use to evaluate future business from each of their sales professionals.
As we’ve discussed previously in this blog, the old rule of thumb for pipeline coverage — a 3-to-1 ratio of total value of all opportunities in the entire pipeline to the sales goal — doesn’t hold up very well anymore. While the old 3-to-1 pipeline coverage ratio worked well during the extended cycle of worldwide growth throughout the 1990’s, it has become outdated today.
Evaluating only the pipeline’s total un-weighted value relative to a sales goal doesn’t tell us very much about what the pipeline contains. Consider this: if you win only 10% of your sales opportunities, then you better have a 10-to-1 pipeline value to goal ratio. If your win rate is 50%, a 2-to-1 ratio will do the job. If all of your opportunities are in the early stages of your sales process, then you will need many more opportunities than if they are all in the final stage of your sales process (…assuming that you have a defined sales process, of course).
If aggregate evaluations of pipelines produce distorted views of sales potential, then what criteria should sales professionals use to determine the health of their business development? After working with hundreds of clients, we’ve found an approach to defining an “ideal” pipeline that incorporates the following key elements:
- Sales Cycle Complexity (Quality)
- Days in Stage (Speed)
- Yield Probability (Volume)
By understanding each of these elements, salespeople can determine what their optimum pipeline should look like, and then adjust their selling behavior relative to how well their pipeline conforms to this standard.
Understanding Sales Cycle Complexity
In general, the more complex the sales process, the longer it will take to develop and close business. Strategic products and services that deliver high value to customers, are mission-critical to customer operations, and which require multiple evaluators and decision-makers in the buying process almost always have longer average sales cycles than products and services that are simple point solutions and which require only a single decision-maker. Understanding how your customers buy is therefore the first step in defining your ideal pipeline, as this indicates how many stages buyers must complete before coming to a buying decision. Each stage represents a milestone in their decision process, the completion of which can be determined by identifying an appropriate verifiable outcome - a customer-exhibited behavior that tells sellers if they are in alignment with the buyer - for each stage.
For example, your buyers might go through five stages in their decision process, in general:
- Develop Business Strategy
- Determine Needs
- Evaluate Alternatives
- Select Solution / Evaluate Risk
- Resolve Issues / Finalize Contract
Your sales process should align with each of the stages in your customers’ buying process. So, using the above buying process as a guide, your corresponding selling stages might be:
- Create Opportunity
- Qualify Sponsor
- Develop Power Sponsor
- Prove Capabilities
- Negotiate and Close
Of course, your sales process could have more or fewer steps, depending on how your customers prefer to buy. And you could have different variants of sales process, depending on your portfolio of solutions and the kinds of customers you serve. However, settling on a standard process that conforms with the majority of your typical sales opportunities will help define the ideal shape of your pipeline.
Understanding Days in Stage
Once you’ve established a buyer-aligned sales process, you can then determine the average time in cycle that your typical prospects take to move through each stage. For example, if your average sales cycle is about four months, and if you generally engage with customers in the Qualify stage, then your average time in selling for each stage might be:
- Create Opportunity - complete
- Qualify Sponsor: 15 days
- Develop Power Sponsor: 25 days
- Prove Capabilities: 45 days
- Negotiate and Close: 35 days
Total number of days in a typical sales cycle: 120 days
The number of sales process stages and each of their average durations tells us the length of the total pipeline, and a general level of effort required at each stage.
Understanding Yield Probability
As opportunities move through each stage of your sales process, they get closer to a buying decision, and therefore, have a higher probability of closure. We can therefore assign a yield probability to opportunities that complete each stage of the pipeline, to represent the likelihood of winning. (This assumes that you are qualifying opportunities at each stage of the sales process, and that unqualified opportunities are being filtered out.)
Your yield percentages for your sales process might look like this:
- Create Opportunity: 0%
- Qualify Sponsor: 25%
- Develop Power Sponsor: 50%
- Prove Capabilities: 75%
- Negotiate and Close: 100%
Ideal Pipeline Volumes
With a well-designed buyer-aligned sales process, you can develop standards for the ideal volume of opportunities flowing through the pipeline that take quality, speed and volume into account. The following formula determines the ideal amount of opportunity potential that should be in each stage of the pipeline:
(Goal x (Average Sales Cycle / Time Remaining to Goal) x (Average Days in Stage / Total Days in Average Cycle)) / %Yield in Stage = Ideal Amount for Stage
Sounds simple enough — but don’t worry, a well-designed CRM system should be able to calculate this for you!
Using our example sales process and yield percentages above, the ideal amount of value that should be in our pipeline for the Qualify Stage, assuming that it is January 1st and our goal for the year is $1.8 million, would be:
($1.8 million x (4 months / 12 months) x (15 days / 120 days)) / .25 yield = $300,000 Ideal Amount for Qualify Stage
Using these assumptions and applying the formula to all remaining stages results in an ideal pipeline of:
- Create Opportunity: n/a
- Qualify Sponsor: $300,000
- Develop Power Sponsor: $250,000
- Prove Capabilities: $300,000
- Negotiate and Close: $175,000
Total pipeline: $1,025,000
Note that the total pipeline in this example does not equal the desired goal - isn’t that a problem? No, because this formula takes into account the average sales cycle length and the amount of time left to attain the goal. In the above example, this total amount of unwieghted pipeline value is less than the annual goal because there are at least three sales cycles remaining before the goal deadline (4 months average sales cycle / 12 months remaining until goal = 3 sales cycles). When the probability of winning for each stage is also taken into account, the total projected revenue on this idealized pipeline is equal to the desired goal amount.
This formula is most useful for determining an ideal pipeline for a rolling period forward — in our example above, a rolling 12-months forward. If you choose to look at pipeline management for a shorter period, then you will find that the formula will recommend increasingly large total pipeline volumes as you get closer to the goal deadline. That is because it is including volumes from stages that cannot be won before the goal deadline - as a result, you should discount any pipeline volume for stages that are outside of the time remaining.
This perspective on pipeline management replaces the old “3-to-1” coverage rule that once served managers well. This approach assumes that your sales process is aligned with how your customers want to buy, and that you are qualifying opportunities rigorously throughout the sales cycle. As you can see, you can have total pipeline volume to goal ratios of less than 1, and still achieve your goal.
Good luck and good selling!





Reader Comments (5)
I do not really understand the explanation of why in the example you used above, the total ideal pipeline is less than the desired goal. As per my understanding, by applying the probability of closure, the amounts of yield from each stage will actually be lower than the value currently in the pipeline, right?
Would be great if you could explain.
The formula for calculating the ideal pipeline takes into account the average sales cycle length and the amount of time left to attain your sales goal. In the example used in the post, the total amount of un-wieghted pipeline value is less than the annual goal because there are at least three sales cycles remaining before the goal deadline (4 months average sales cycle / 12 months remaining until goal = 3 sales cycles).
Think of your pipeline as a farm, with multiple growing seasons. If you have three seasons each year, you can expect to cultivate a certain amount in each season - you don't need to cultivate your entire year's goal in one season. As a result, the amount growing on your farm doesn't have to be a "bumper crop" all the time.
Of course, this assumes that you have some consistency in growing seasons, and that you can expect each crop to be about the same - it doesn't take into consideration any kind of unforseen disasters. Just as a farmer can't predict a tornado's effect on their fields, so too can salespeople be affected by unknown threats to their sales pipeline. So if you can cultivate a "bumper crop" every once in a while, that is certainly a good thing, but not required if everything else remains consistent.
Great article...I've been working on something similar for my team and you hit the nail on the head. I have a question on how you calculated the % Yield in Stage? In your example you used 25%. Did you simply calculate the number of total opportunities and divide by the number of closed deals? Thanks in advance for your reply.
Great article.
I continue to tell my team that all of the pipeline metrics mean nothing if you put garbage in the pipeline or are not honest about the sales stage. I help this in my sales process by considering all of the opportunities in the first stage as non metric opportunities. This is a bit of a psychological crutch as sales reps feel good about posting something on the board, but not compelled to explain it away to management when it goes away when the sales rep has really done a better job of qualification and has had some peer review.
Keeping the pipeline metrics as a historical reference is also of great value, particularly from a coaching perspective. Of course, you need to have a really well thought out sales process, founded in a deep understanding of your business and your market.
Calculating the % Yield in Stage isn't usually as simple as counting the number of total opportunities and dividing by the number of closed deals, unfortunately. We've found that many of our clients' opportunity management systems -- whether they be manual, spreadsheet-driven, or fully automated CRM applications -- are a little loose when it comes to when opportunities should be entered and updated and closed as either a win or a loss. Without strict and consistent policies, using such systems to calculate yield statisically is suspect, since the volatility of the dataset can be quite high.
This becomes a lot easier, however, if you can establish consistent verifiable outcomes at the end of each of your stages. A verifiable outcome is an observable behavior of the customer that confirms that the seller is in alignment. Too many sales processes are internally focused -- we gave them a proposal, a demo, a price quote, etc. These may indeed be useful sales activities, but the important thing is how the customer reacts to these actions -- did they approve the content of the proposal, confirm the product fit after the demo, or express how their potential value compares to the price? These customer reactions tell us if we are making progress towards a close.
With clear verifiable outcomes, you have an easier time establishing the probability of winning at the end of each stage, because they are based on more objective, observable data. Verifiable outcomes also provide managers with specific inspection points for oversight and coaching.
After working with hundreds of clients with B2B sales, we have discovered that a good starting place for yield percentages, if no other data is available, is as follows:
- Initial contact established with potential buyer: 10%
- Sponsor admits pain and agrees to diagnosis in Sponsor Letter: 25%
- Power Sponsor agrees to explore and approves Evaluation Plan: 50%
- Verbal approval received from Power Sponsor: 75%
- Contract negotiation scheduled or in progress: 90%
- Contract signed: 100%
Your yields might vary, depending on the number of stages in your sales process. However, for typical B2B sales situations, we have found that the above starting values are a good place to begin -- most clients only need to tweak these yield values by no more than 5%, after they've had some experience with several opportunities, to get very accurate predictions of future revenue streams.
By the way, we cover a lot of the details of pipeline mapping and analysis in chapter 14 of our book, The Solution Selling Fieldbook, which you can order here: http://bit.ly/xF1zN
Hope this helps -- good luck and good selling!