And what to do about them.
Vendors and conventional wisdom can be misleading.
You need 3x pipeline coverage. Fuhgeddaboudit. We've measured it. Coverage is weakly related to actual sales. Large deals make it highly volatile. And you only have a few observations of previous quarters to use for determining your ideal ratio. It's hard to make conclusions based on such limited data. Also, coverage ignores new deals. Finally, if you try to manage to a coverage ratio, the metric will be gamed. You might as well look at sunspots or any other random data to predict what you will need. Better off ignoring it. You already know you need more pipeline. (We explore this comparison in more depth here.)
You can repeatedly get 2% accurate forecasts. That’s wildly unrealistic—even under idealized conditions that don’t reflect your business. Aim for within 10% – 20% for each forecast you make (provided you have enough transaction volume—typically a hundred deals or more that you are working to close each quarter). If you only have a handful of deals, your business is not forecastable. And if something changes: the economy, your competitive position, your behavior, your customers' behaviors... that forecast needs to be recalibrated. Keep in mind that your sales team's job is to change things to make that forecast wrong. They should be using the forecasts to show them what needs attention, thereby making the early-in-the-quarter forecasts wrong.
Win rate is a simple ratio: wins/(wins + losses) or wins/(wins + losses + open deals). These two common formulas are both fraught with problems. Win rate is a function of time. For any group of deals, wait longer and you will (cumulatively) sell more. Any simple ratio that ignores time (as both formulas above do) is an oversimplification. Read our review of the flaws in the common methods and what to do instead.
You need AI to get better forecasts. You might improve your forecasts with AI. But you should first get the most out of the simplest models—that you can understand. Then consider further optimization. Also, AI is a black box. You can’t see inside to understand what is driving the numbers. AI can create useful signals that feed traditional models. This is not an AI model but rather an AI signal. This can help—if you have reliable data available for all your current and historic opportunities. But look to this AFTER you have the basics covered.
You need a third-party application to do forecast rollups outside of Salesforce. Nonsense. Salesforce Collaborative Forecasting has multi-level rollups, manager overrides, spreadsheet entry. You’re already paying for it.
More metrics help you understand what is going on. The right metrics are critical. But more metrics create more confusion. Metrics should be things that you can control, and that are directly related to things you care about. Before you add a metric, measure it to see if it's correlated to sales.
So what to do? No one knows what the future holds with certainty. Adjust your expectations. Focus on what's reasonable to expect, and which basic factors have the biggest effects on sales.
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