Craving a delicious – and deliciously accurate – sales forecast? Well, you’re in luck! We’ve unearthed our tried-and-true recipe, perfected over generations of detailed sales analysis, and are now ready to share this secret recipe with the world of Sales VPs.
So clear out the kitchen on your sales floor. Acquire all the ingredients you need (as listed below) and check out our easy-to-follow, step-by-step recipe to cooking up an accurate, tasty sales forecast.
Ingredients
– 1 ounce Opportunity Stages
– 1 cup company averages, broken down by: 4 tablespoons Average Sales Cycle (winning), 4 tablespoons Average Loss Cycle, 4 tablespoons Average Deal Size, 4 tablespoons Average Conversion rate from each Sales Funnel Stage
– 1 pound open pipeline opportunities
– 6 teaspoons essential Sales Pipeline Metrics
– 2 pounds meetings
– 1 pound pipeline review
– 1 pound sales forecasting
– 365 (or more – 365 is our minimum suggested size) servings of historical conversion rates
– a pinch of rep intuition
Directions
1. Split up your meetings. Set aside the pipeline review for another time – it is critical that you NEVER combine your pipeline review and sales forecasting meetings. Use the sales forecasting meeting once a week, ideally on a Monday, to inspect and review later-stage opportunities. The pipeline review meeting can be used once every two weeks, with a focus more on early-stage opportunities.
2. Standardize your 1 ounce of Opportunity Stages. Don’t settle for a lesser brand, such as forecasting stages like commit or upside – these are notoriously subjective inputs that depend too much on your reps’ judgment. Make sure that the opportunity stages used in your forecast match the buyer’s process. Your sales team should properly qualify each opportunity before moving it to the next opportunity stage.
3. Dive into your servings of historical conversion rates, from the first funnel stage all the way to closed-won. This will inform you on how your sales team has traditionally done in the past, shaping the accuracy of your current forecast. We suggest having at least 365 servings of historical data – or a year’s worth – but the more historical data you have, the better.
4. Prepare a marinade mixture using each of the company’s 4 averages: average sales cycle (on winning opportunities), average loss cycle, average deal size and average conversion rate from each stage to Closed-Won. These are the benchmarks that each of your open opportunities should be measured against.
5. Take stock of the opportunities in your pipeline for this forecasting period, looking at them through the lens of your 6 teaspoons of essential sales pipeline metrics. These are:
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Stage – which stage is the opportunity is currently in? Opportunities in very early stages should not be included in this sales forecast.
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Age – how long has this opportunity been in this stage? Opportunities that have languished in particular stages for more than 2x or 3x your typical sales cycle should be considered “at-risk.”
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Size – how valuable is this opportunity? Opportunities that are worth 3x or more of your typical average deal size should be considered “at-risk.”
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Engagement – how much engagement has the rep had on this opportunity in the past 10 business days? If there is little to no activity, it should not be forecasted to close in this period.
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Effort – how much overall effort has been expended on this opportunity? This should be measured by tracking activities logged in your CRM. You don’t want to spend a lot of effort on opportunities that are not likely to close.
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Slippage – how many times has this close date changed or been pushed back? Slippage is a key indicator that of an opportunity stalling.
6. Sprinkle a pinch – but just a pinch – of your rep’s intuition on top of your data-driven forecast. You want to start your recipe with the data-based ingredients, and then decide how much of the rep’s intuition you should add as a garnish. Sometimes, reps just have ‘happy ears’ and think all of their opportunities will close indiscriminately. However, other times they might have inside information – based on a private conversation with the prospect, for example – that might lead them to believe something other than what the data is showing.
7. Your data-driven sales forecast is now ready to serve to your CEO or Board of Directors!
