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Why are your forecast numbers always wrong?

Aryan Trip
Aryan Trip,RevOps Mechanic Clientell
3 mins read
Last updated:
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The most important part of a sales organization is forecast accuracy.

To ensure that your sales engine operates at peak efficiency, it's essential to stay up to date with your team's forecasts, have a good understanding of pipeline health, and gauge varying risk levels with opportunities.

Several negative effects result from missing your projection, of which losing revenue is the primary one.

There are several reasons why companies miss their forecasts, but there are a few major ones, which we will discuss in this blog.

1) Incomplete and Inaccurate CRM Data -

Several factors can cause inaccurate CRM data, but it mainly occurs when data is entered manually, and mistakes are made.

It can also occur when data is imported from external sources and incorrectly formatted or validated. Additionally, CRM data can become inaccurate over time as customers' information changes, such as their contact details or preferences.

Also, because manual entry is a pain and time-consuming, reps generally do it half-heartedly, rendering the data incomplete.

When the data based on which you are supposed to forecast is incomplete and inaccurate, how will your forecasts turn out? It’s a no-brainer, totally unsatisfactory, right?

2) Going with your ‘gut feeling’-

Forecasting cadences without data to bank on generally results in going with what is believed to be correct. The rep may say depending on their prior engagement in a particular deal; they feel a certain way about it converting or not.

But let's take an example of a deal that has been going on for 8 months. Initially, the potential client showed interest, which dwindled but got reignited again, and this cycle continued a couple of times at monthly intervals.

So what kind of feeling would a rep have about this deal? Could this intuition and inclination, although an important factor, be trusted as the only source on to base your forecasting decision?

You know the answer, and that is no.

3) Lack of metrics and insights-

To have an accurate forecast, you need accurate and complete data. But this clean data can only be helpful if used correctly. So how do you use it correctly? Through correct metrics and insights.

You need to know your sales process and what metrics would work for it.

A couple of essential metrics are the Risk Score and Engagement Score. As the name suggests, these tell you the risk associated and the kind and amount of engagement a deal has gone through.

Pipeline coverage and pacing are other metrics that give valuable information and insight. The latter helps you see at what speed a deal is progressing and the former shows you how much pipeline you have, which can give you an idea of how many deals will expectedly convert.

Leveraging your company's and industry's historical data with deals of various kinds(different ticket sizes, geography), you can use these metrics to give you accurate answers about what would happen with your forecast.

4) Having a cadence blueprint-

Most companies that don’t have the features mentioned above in their forecasts also tend to have a haphazard way of conducting them.

This is so primarily because little specific data or anything tangible guides them. This causes them to inspect each deal and ask questions about them.

This is fine until there is time, but when time starts running out, they hurry their cadence.

Instead of doing so, prioritized deals (deals prioritized by data available on them) could be discussed, and others could be segregated into different groups, or maybe some other blueprint could be followed.

There must be a well-laid process to go about the cadence, knowing when and how to discuss various things instead of brute-forcing it. Only then can cadences show effect and forecasting be accurate.

To get effective forecast numbers, consider all these aspects and read this extensive guide to accurate forecasting.

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