The 3 metrics below are part of the "we have always done it that way" culture. However, when you actually dig deeper into how they're calculated they're absolutely meaningless. People who ask you for these 3 metrics likely mean well, but have not dug into the calculations themselves to really understand their meaning.
Below I explain why these are arbitrary and meaningless metrics and propose alternatives to getting to what the person asking the question is really trying to understand.
1. What percentage of Sales Reps hit their Quota?
When people ask this they are trying to understand "if you hire a new sales rep, is there a high likelihood they will succeed". If that is the case you have created a repeatable sales motion that you can hire sales reps into and revenue will come out. The intention of this question is good, but the metric that is used is misleading.
If Company A says 80% of my reps hit quota, but Company B says 40% hit quota you immediately assume Company A has a more efficient sales cycle, more revenue coming in, etc. The problem is Quota is arbitrary. It is a number used for finance for compensation plans and that reps want to hit to get to their accelerators. Company A might have a $500k quota and Company B might have a $2M quota. Quota should be used as a way to incentivize sales and for finance to budget. It should not be used as a metric used to evaluate company performance.
The real metric to use here is Productive Capacity per Rep. This answers how much ARR will a ramped rep close in a given year. This is the number you can use for modeling out how much a new rep hired once ramped will contribute to sales. That is a number you can compare across companies, as it removes the arbitrary nature of the metric.
2. What is your pipeline coverage? Do you have 4x pipeline coverage?
This is one of the most arbitrary and generic sayings in the SaaS world. It is meaningless. The question is saying whatever pipeline you have, that 25% of that will turn into ARR (regardless of how far along the pipeline is or when that will actually turn to ARR). The question is coming from the right place - - trying to predict your ARR in the next 1,2,3,4 quarters. However the metric being used is one of the reasons companies fail to be able to forecast correctly. It fails to take into account Likelihood of Win and Timing of that Win.
In the B2B SaaS world, where sales cycles can be 1 year, every pipeline dollar can be early in that cycle or late in that cycle. The probability of winning early stage pipeline is significantly lower than winning late stage pipeline. On top of that the late stage pipeline will turn to ARR sooner than the early stage pipeline. 4x pipeline coverage assumes all pipeline has a 25% conversion rate to ARR and doesn't care WHEN you will win that ARR, making this have zero meaning.
The real question should be "What is the Expected Value of your Pipeline in X months"? Using Win Rates Over Time you can predict the value of your existing pipeline by quarter.
3. What is your Win Rate?
Most companies look at the number of "Closed Won Opportunities"/("Closed Won Opportunities" + "Closed Lost Opportunities"). Two major issues with this that cause companies to inflate their win rate which leads to poor forecasting. The first is reps often fail to "Close Lose" opportunities that are truly lost for numerous reasons. That means many open opportunities are really "lost" which would lower the win rate calculation. Second, is there is not a time component when people ask for Win Rates. The calculation above essentially assumes will you ever win that opportunity even if it happens 2 years down the road. The real way to answer this question is to look at Win Rates Over Time. An example would be "What is your 52 Week Win Rate"? This would look at all opportunities Open, Won, or Lost that were created at least 52 weeks ago. Then, of those, how many were won within 52 weeks of it being opened. If it was won in week 60 then it would not be counted as a "win" in this calculation. You then divide Wins by Week 52/Total Opps Open at least 52 weeks. You would create this for week 1, 2, 3....week n and apply that to your existing pipeline to get an accurate view of the value of your existing pipeline.