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December 23, 2016.

It’s late.

Dave Apthorp’s family is expecting him home. His young children want him to help finish decorating the tree.

Unfortunately, Apthorp is still in the office.

That’s because it’s year-end and a third of the pipeline opportunities forecast to close in December have slipped.

Yet one week ago, the sales forecast for the year looked good.

Apthorp told his boss, Mike McCluskey, that his team will exceed quota. Now he’s working on his excuses.

Not for the first time.

He calls McCluskey:

“I’ll come in next week and see if we can get some of the deals over the line after all”, Dave tells him.

McCluskey points out that very few customers will be at work next week.

“Dave, it’s the same every quarter. We need to get this sorted out in 2017.

“I read this blog post on sales forecast accuracy last week”, continues McCluskey. “It’s by a guy called Gary Smith. He’s published a lot on the topic of salesforce dashboard best practices.

“Let’s get him into the office in January and see if he can help improve our sales forecast accuracy”.


Sales Forecast Accuracy

In the ideal world, sales managers are confident that every opportunity will close when expected. Imagine if your close dates were always reliable and your sales forecast always accurate?

If only.

Sadly, things aren’t that simple. It’s life that deals slip.

But what can sales managers do about it? How can they avoid getting caught out by nasty surprises at the end of the month? How can they avoid sales forecasts that disappear overnight?

Experience shows it’s often right to be sceptical about sales forecasts. However, knowing which deals have a high probability of slipping means we can take action.

We can double-down on doubtful deals, find new opportunities, work to bring future deals forward.

It also means we can manage expectations by adjusting the sales forecast well ahead of time.

Nevertheless, to scrutinise deals effectively, we need some pointers to highlight riskier opportunities. These pointers help us decide which opportunities to question. They help us identify the deals about which we should be sceptical.

So how do we do this?

These three pipeline quality metrics give us these pointers. They will help you improve sales forecast accuracy and save you from many unforeseen late nights in the office.


Introducing the three killer pipeline quality metrics

The problem is clear:

We need to identify deals that have a higher than average chance of slipping. We can do this using three pipeline quality metrics that can lead to sales forecast accuracy.

Here are the three metrics:

  1.    Number of Close Date Month Extensions.
  2.    Number of Days since the last Stage Change.
  3.    Number of Days the Opportunity has been open.

No single pipeline quality metric dominates the others. Use the metrics in conjunction with each other to get the full picture.

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Here’s how it works – the pipeline analytics process

Create a table that displays all the deals that are due to close this month. Include the three pipeline quality metrics in this table.

Salesforce dashboard chart that show pipeline quality metrics such as the number of close date extensions.

Let’s say your average sales deal takes three months to complete. However, you have one deal that has already been open for more than 200 days. The Close Date has slipped from one month to another, four times. It’s been in the same Opportunity Stage for 60 days.

You’re probably right to question whether this deal will close successfully this month. Based on the metrics, there’s good chance it will slip again. In other words, the three pipeline quality metrics are an excellent way to gauge sales forecast accuracy for the period.

Sales managers reviewing these metrics can ask questions about these deals. But the same questions can also be asked by salespeople – the reps who own the Opportunities – to scrutinize and self-manage their own sales forecast.


Pipeline quality metric #1 – number of close date month extensions

Here’s a statistically robust way to forecast tomorrow’s weather.

Whatever is happening today, predict that’s what the weather will be like tomorrow.

You will be right more often then you are wrong.

It’s the same with opportunities. If a deal slipped last month, there’s an increased chance it will slip this month.

The Number of Close Date Month Extensions gives us this data. This pipeline quality metric counts the number of times the Close Date has slipped from one month to another.

Close Date changes within a month don’t matter. Nor do changes that make the Close Date earlier. This metric counts the number of times the Close Date has extended from one month to another.


Pipeline quality metric #2 – days since last stage change

This pipeline quality metric counts the number of days since the Opportunity Stage was last updated.

Life is not linear. Opportunity Stages don’t change at regular, pre-determined intervals. But a lengthy period without a change – in the context of your average sales cycle – is a sign of a dormant deal.

Let’s say the Opportunity Stage hasn’t changed for a significant period. The deal has slipped from one month to another –  several times. Then you are right to question the close date of this month.


Pipeline quality metric #3 – number of days open

This pipeline quality metric counts the number of days that the opportunity has been open. The clock stops ticking when the deal changes to Closed (Won or Lost).

This pipeline quality metric is valuable in its own right. But the primary purpose is to put context into the other quality metrics.

Deals that have had a significantly longer than average sales cycle have a lower chance of closing successfully this month, particularly if the opportunity has already slipped from one month to the next several times. And especially if the Stage has not been updated for quite a while.

To repeat:

Sales forecast accuracy is not about one single pipeline quality metric. It’s about understanding the context. Scrutinize your pipeline with these three pipeline quality metrics to unlock the insight you need to question your deals and find the ones that have a high chance of ruining your sales forecast.


4.30 PM, Friday December 22, 2017

Dave Apthorp now uses these pipeline quality metrics to proactively manage his sales forecasts.

He’s gained a reputation for sales forecast accuracy. And he’s spending a lot less time working late in the office. 

If Dave can do it, so can you.

Apthorp calls his wife.

“Honey, tell the kids I’m on my way”.

Dave Apthorp has left the building.


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