This article is a complete guide to using Expected Revenue in sales.

Why is this topic critical for sales managers?

It’s vital because Expected Revenue delivers a reliable revenue forecast that stands up to scrutiny when used correctly. It’s the sort of sales forecast you can defend in front of the board.

Expected Revenue also lets you know whether the funnel is big enough to hit your current sales quota.

Nevertheless, some people dismiss Expected Revenue as irrelevant.

That’s a pity. After all, inaccurate revenue forecasts and poor target visibility are the banes of many sales managers’ lives.

In this detailed guide, I explain:

• The formula for calculating Expected Revenue.
• How it’s different from the Weighted Pipeline.
• Why you should use this powerful tool for sales forecasts.
• How the metric predicts target performance.
• Where to get a free Expected Revenue report for Salesforce.

With that, let’s start.

The Expected Revenue Formula

You calculate the Expected Revenue of an opportunity by multiplying the deal’s value with the probability of a successful outcome.

This calculation gives you a dollar value for each opportunity. Sum these numbers to get the total Expected Revenue for all deals.

For example, let’s say you have an opportunity with a June close date. If the deal is worth $50,000 and the probability is 25%, the Expected Revenue is $12,500.

Increase the probability to 30%, and your Expected Revenue is $15,000.

And adding up these dollars for all your deals closing in June gives you the total Expected Revenue for that month.

Naturally, you can sum the Expected Revenue in the same way for each month, quarter or year.

Expected Revenue versus Weighted Pipeline

You might be thinking:

The Expected Revenue formula sounds like the math for the Weighted Pipeline. What’s the difference?

It’s this:

The Weighted Pipeline refers only to open deals. In other words, you only have opportunities that are in the funnel in your Weighted Pipeline report.

In contrast, Expected Revenue includes your pipeline deals AND opportunities you have won.

Of course, the probability of winning a deal that is already in the bag is 100%. Consequently, your Expected Revenue report includes these deals at their total value, plus the weighted amount for each pipeline opportunity.

Let’s take our earlier example.

We have a pipeline opportunity in June with an Expected Revenue of $12,500.

However, let’s say we have already signed a deal in that month for $15,000. That means our total Expected Revenue for June is $27,500.

Calculating Expected Revenue in Salesforce

Fortunately, you don’t need to open Excel or reach for pen and paper, to calculate the Expected Revenue in Salesforce and most other CRM tools.

The system does it for you.

In Salesforce, the field on the opportunity is, you guessed it, Expected Revenue.

Nevertheless, there’s an odd quirk in Salesforce. When you get started, Salesforce hides the field from all users.

Make the field visible by updating the field-level security.

Doing this will also make it available for reports and charts.

Why Some Executives Dismiss Expected Revenue

Here’s the view some sales managers take:

Opportunities are binary. You either win the deal, or you don’t.

For example, let’s say you have a pipeline opportunity for $10,000. If you win the deal, it’s worth $10,000. On the other hand, it’s worth zero if you lose it.

These managers say Expected Revenue is irrelevant because it doesn’t reflect this binary outcome. Rather, the report shows a figure for this opportunity of between $1 and $10,000, depending on the probability.

Instead, they say, the report should show $0 or $10,000 based on whether or not you are forecasting a win.

But wait a moment.

Why Expected Revenue Makes Sense

Let’s say your team has 50 deals due to close this quarter.

You know you will win some and lose some.

But here’s the unfortunate problem:

You can’t be sure which you will win and which you will lose. As we all know, it’s pretty darn tricky to predict the outcome of sales deals confidently.

Of course, if you know in advance which deals you will win, your sales forecast will include these deals at 100% of their value. And you wouldn’t bother chasing deals you know will be lost.

However, life isn’t like that, unfortunately. No matter how good your qualification process is, we all know it’s hard to predict the outcome of a sales deal.

Nevertheless, we are still under pressure to produce reliable sales forecasts despite the uncertainty.

That’s why Expected Revenue is a powerful tool. Taking the weighted value of each deal reflects the uncertainty we all face and produces a sales forecast we can explain and justify. It reflects the probability of winning each deal rather than taking each opportunity at 100%.

Of course, like all good things, there’s a catch.

Video: How And Why To Calculate Expected Revenue For Sales

Expected Revenue and Opportunity Probability

Here’s the catch:

A reliable Expected Revenue report depends on having realistic probabilities for each pipeline opportunity. (We don’t need to worry about won deals, we can take their value at 100%).

However, the probability isn’t always as dependable as it can be. That’s because, in most cases, the figure relates directly and only to the Opportunity Stage.

In other words, if the Stage moves forward, the probability auto-increases. That happens even if your chance of winning the deal hasn’t changed.

What does this mean? You can significantly improve the reliability of your Expected Revenue reports by taking a few simple steps.

Manually Adjust The Opportunity Probability

Most salespeople believe the probability is for each Stage is fixed.

However, that’s not the case. You can change the percentage yourself on each deal, and all you have to do is type the new value into the box.

When should you do this? Well, for example, let’s say you are working with a long-time, regular customer. Usually, the chance of winning the deal is higher compared to selling the same products and services to a new prospect.

Pro-tip: Fine-tune the probability of each opportunity based on real-world factors and the salesperson’s intimate knowledge of the deal.

I recommend you assess the percentages on each deal in your pipeline reviews. Focus on the more significant opportunities, and check the probability reflects your judgment on the chances of winning the contract.

These simple steps have a high impact on the reliability of Expected Revenue reports.

Expected Revenue And Target Tracking

When measuring sales versus quota, you need to know two vital things.

First, did we hit our target in previous months and quarters? And second, will we achieve the quota in the current period?

Let’s think about that second question.

Whether you will achieve the target depends on how much business you have won in the current period, plus your weighted pipeline.

And guess what? That’s the formula for Expected Revenue.

That’s precisely how our popular GSP Target Tracker works. Let’s take an example.

Let’s assume we are currently in February 2022. Here’s the target record for Dave Apthorp for the month.

You can see that Dave’s target is $50,000 and that so far this month, he’s won $20,000. That’s a good start.

But will Dave hit his number?

His total pipeline for this month is $60,000. That sounds great. But hang on. The weighted value of that pipeline is only $25,000.

That means Dave’s total Expected Revenue is $45,000 (that’s $20,000 won plus $25,000 of a weighted pipeline).

Therefore, we are forecasting a $5,000 shortfall for Dave this month. You can see that in the chart on the right-hand side.

In other words, we are using Expected Revenue to make a reliable forecast on whether a salesperson will achieve their quota.

In this case, it looks like Dave has some work to do.

Follow the link below to learn more about the GSP Target Tracker app, including demo videos, screenshots, and a free trial.

Auto-Adjust The Opportunity Probability

Your business can improve the accuracy of Expected Revenue by automatically updating opportunity probabilities.

You do this based on historical deal data.

In other words, rather than the salesperson fine-tuning the probability on current deals, you adjust in the background based on what you know has happened in the past.

I’ll explain how you can do this easily using a workflow rule or Flow.

Historical Opportunity Conversion Rates

When you make a personal investment, there’s often a warning that past performance is not an indicator of future returns.

However, with sales teams, it’s different. Past performance is an excellent indicator of future ratios, and we can use that to our benefit.

In other words, knowing the win rates from similar deals in the past means it’s possible to forecast future conversion ratios. As a result, we can predict the Expected Revenue with even more confidence.

Let’s take an example.

Comparing Win Rates

Look at the dashboard chart below. These compare the win rates between new and existing customers.

We can see that we won 45% of all opportunities with existing customers. However, only 30% of new customer deals closed successfully.

Remember, these are the overall conversion rates. However, it shows that the win rate for existing customers is almost 50% higher than for new customers.

As a result, we don’t need to stick with the pre-defined probability for each Stage. Instead, we can update the percentage based on whether the deal is for a new or existing customer.

For example, say the default probability on the Proposal Made Stage is 30%. We can auto-update this to 35% on existing customer deals and reduce it to 25% on new customer opportunities.

Let’s take another scenario. There’s a wide variation in win rates between salespeople or territory in some businesses.

Here’s the report showing the territory conversion rates for one company.

Again, remember these are the overall win rates. However, now that we know this information, we can auto-update the probability based on the territory.

For example, in Proposal Made, we might set the probability to 40% in the United States and 30% in Europe.

In short, automatically adjusting opportunity probabilities based on historical data improves the accuracy and reliability of your Expected Revenue reports.

Get An Expected Revenue Report For Salesforce

To create an Expected Revenue report in Salesforce, follow these detailed steps.

1. From the reports tab, click New Report.
2. Select and Opportunities Report.
3. Include the Expected Revenue field in the report.
4. Double-click on this field and select Sum.
5. Optionally, deselect the Sum on other fields.
6. Save your report.

I show you how to take these steps in my video about Expected Revenue.

Alternatively, you can install our free GSP Sales Dashboard. This dashboard includes the core set of reports and charts you need for proactive pipeline management in Salesforce.

What To Do Next

Here are five things you can do next.

1. If you haven’t already, watch my video on Expected Revenue.
2. Take a look at the GSP Target Tracker app. It makes excellent use of Expected Revenue to measure pipeline coverage versus quota.
3. Install the free GSP Sales Dashboard. Use this as a template for creating your ideal pipeline management dashboard.
4. Get salespeople to fine-tune the opportunity probability on their deals. Review these numbers in your upcoming funnel review.
5. Ask yourself whether you need to auto-update the Stage percentages in your business.

And of course, if you have questions or want to talk about any of the content in this article, you can get in touch with us.

Many sales managers struggle to create reliable sales forecasts.

In fact, many forecasts are wildly inaccurate.

Even (or especially) when the sales team is using a CRM system such as salesforce.

The trouble is gut feel just won’t cut it.

Nor will simply applying a top-down win rate to all opportunities.

Instead, what’s needed is a sales forecast that is robust and can stand up to scrutiny.

That’s because often the sales forecast is shared with the company leadership, finance, peers and back-office colleagues. Other people depend upon a reliable revenue projection to do their own jobs properly.

Being wrong, month after month, doesn’t help anyone.

That said, sales forecasts don’t need to be perfect. But in many businesses, they need – and can – be a heck of a lot more reliable than they are at the moment.

About This Guide To Sales Forecasts

This guide is the most comprehensive online resource to creating reliable sales forecasts.

In this expert-written guide you’ll learn:

• Section 1: Why sales forecasts are often unreliable.
• Section 2: How to create a sales forecast report in salesforce.
• Section 3: How to improve forecasting accuracy using three key reports.
• Section 4: Which three opportunity metrics help identify the deals most likely to slip from your sales forecast.
• Section 5: Where to get the sales forecast template, reports, dashboard charts and metrics highlighted in this guide, all for free.

So, if you’re looking to improve the sales forecasting process in your company, you’ll love this guide.

By the way:

You don’t have to be using salesforce to get tremendous value from this guide. We are experts in salesforce so naturally, that’s what I’ve used to create the examples. However, you can apply the exact same sales forecasting methods to the CRM system in your business.

We recently hosted a webinar on the same topic. There’s a recording of that webinar just below.

1.     Why Sales Forecasts Are Inaccurate

A sales forecast is an informed prediction of the revenue a sales team will achieve in a given period (e.g. the current month or quarter). It reflects the deals already won in the period plus an estimate of the sales pipeline that will close successfully in the time remaining.

But why do we go to all the trouble of creating sales forecasts in the first place?

It’s because reliable sales forecasts:

• Provide the executive team with advance information on the health of the business.
• Tell sales managers whether they have enough pipeline to meet quota.
• Help fulfilment, order processing, manufacturing and other teams to plan and operate efficiently.
• Enable finance executives to project capital requirements and cash flow with confidence.

Doubtless there are many other reasons, specific to your company.

However, in many businesses the revenue forecast is taken with a pinch of salt by the leadership team.

Often even the VP of Sales doesn’t believe them (although she wishes she could). And embarrassingly, she struggles to explain why they are so inaccurate.

Why many sales forecasts are unreliable

Here are the three most common reasons I’ve found that explain why many sales forecasts are unreliable.

• Deals slip from the forecast. Often this happens at the last minute. Sometimes the same deal has slipped at the last minute more than once.

Sometimes this occurs because salespeople are optimists. Deals they thought would happen, don’t.

Furthermore, in many businesses, salespeople are under pressure to maintain the size of the pipeline. Setting deals to Lost or removing them from the funnel, contradicts this pressure. Consequently, deals that no longer have legs stay in the pipeline but slip to the next month.

Unfortunately, sales forecasts are usually submitted before the month end. This means the forecast often contains many unreliable deals that end up slipping after the forecast is created.

• Deals appear out of nowhere. Sometimes this saves our bacon. Other times it simply makes the sales leader look silly.

In other words, sandbagging. Salespeople go out of their way to avoid management pressure on deals. For example, by keeping an important deal under the radar for as long as possible.

However, these deals simply don’t figure when creating the forecast.

• There’s no crystal ball that tells us which deals we’ll win and which we won’t. Or indeed when we’ll win them. After all is said and done, customer decision making is out of our hands.

If we knew in advance which deals we will win and which deals we will lose, then we’d save ourselves a lot of trouble. Unfortunately, no matter how hard we try we’re still left with customer-driven uncertainty.

Sometimes we attempt to mask these uncertainties by asking salespeople to ‘Commit’ to deals. However, that’s like asking a soccer centre forward to commit to scoring a goal. We all know he’s trying. But there’s still a chance he’ll miss (a pretty good chance if he’s the centre forward on the team I support!).

If we want reliable sales forecasts we have to address these sources of unreliability in other ways. That’s what we’ll cover in Sections 3 and 4.

Before that, let’s examine how best to create a sales forecast in CRM systems such as salesforce.

2.     How To Create A Sales Forecast In Salesforce

What’s the best way to create a sales forecast in salesforce?

Answer:

Use an Expected Revenue Sales Forecast report.

An Expected Revenue Sales Forecast report combines the revenue from Won deals with the weighted sales value from pipeline opportunities.

Sometimes the report includes filters that exclude certain deals (for example, those at a very early stage).

How the Expected Revenue Sales Forecast reports works

The report combines Won and Pipeline Opportunities.

For Won deals, 100% of the revenue contributes to the sales forecast.

For pipeline deals, however, the sales value of each opportunity is multiplied by the Opportunity Probability.

For example, a deal for $10,000 at 40% will have an Expected Revenue of $4,000. A Won opportunity for $20,000 will have an Opportunity Probability of 100% and an Expected Revenue of $20,000.

In other words, the Expected Revenue of any specific deal is the weighted value of the opportunity.

Incidentally, in some businesses the sales forecast does not reflect the total, gross value of the sales deal. That’s because the revenue from the deal spreads over time. The sales forecast is therefore the amount of scheduled revenue that will be achieved in the period.

If this is the case, then you need the GSP Scheduled Revenue app. However, the principles of Expected Revenue apply equally to sales forecasts based on scheduled revenue.

Why include Won deals in the forecast

Most sales forecasts relate to the current period; for example, this month or this quarter.

As such, the sales revenue we can expect is a combination of deals we’ve already won during the period; plus deals we expect to win.

That means we need to include won opportunities in the forecast.

Why use the Expected Revenue of pipeline opportunities

Some salespeople don’t like the idea of the Expected Revenue (or weighted revenue) of pipeline deals.

They argue opportunities are binary. We’ll either win it or we won’t. Take 100% of the sales value or zero dollars.

However, here’s the thing:

In any given period, you don’t categorically know which deals the sales team will win and which deals they will lose.

Let’s face it, if you knew which deals you were going to lose, you wouldn’t bother with them in the first place.

So it’s logical to take the weighted value of pipeline opportunities. That way we get a reliable total value of forecast sales.

Providing of course, the opportunity probability is reliable.

Entering reliable Opportunity probabilities

In salesforce, as with most other CRM systems, there’s a default Probability associated with each Opportunity Stage.

In other words, the probability is set automatically when the Stage is set.

Manually adjust opportunity probabilities

However, here’s something not everyone realises:

The Opportunity Probability can be manually adjusted. This is as true in salesforce as it is in all other CRM systems.

This means the salesperson can override the default probability for the Stage.

For example, the default Probability for Proposal Made might be 35%. Salesforce will automatically set this value for ALL opportunities at this Stage.

However, in reality the probability for a new customer might be lower. The probability for an existing, long-term strategic customer may be higher. So, we can manually adjust the probability when the default value isn’t appropriate.

Use workflow to adjust opportunity probabilities

Here’s another option.

Automatically adjust opportunity probabilities using pre-defined rules.

For example, use workflow rules to set the opportunity probability for strategic customers to 40% at the Proposal Made stage.

Naturally, you’re assuming the probabilities you pre-define in this way will be more accurate than those set by the sales team.

That may well be true for an inexperienced team. Or if you’re not confident salespeople will adjust the probability where appropriate.

Use the GSP Probability App

We’ve figured out how to get historic opportunity probability and velocity data out of salesforce.

In other words, we can retrospectively analyse all opportunities and calculate two things:

1. How long each opportunity spent at each stage. In other words, stage-by-stage pipeline velocity.
2. The percentage of all deals won or lost once they reached a given stage.

This is valuable information.

For example, at one manufacturing client we discovered that 23% of deals in Investigation were closed successfully for new customers. Yet for existing customers it was 33%.

Furthermore, we identified that these figures varied by +/- 6% across territories and individual salespeople.

The outcome is that in this company, opportunity probabilities are defined tightly now based on accurate, reliable historical statistical data.

This improvement led to a step-change in the reliability of sales forecasts.

If you want to measure pipeline velocity or analyse historical probability data in your company then get in touch.

How to get the Expected Revenue Sales Forecast report

You might be wondering:

Is there a simple way to get the Expected Revenue Sales Forecast report?

The easiest way is to install the GSP Sales Dashboard.

This free package includes all of the reports and sales metrics highlighted in our Sales Forecasting Guide.

3.     Improve Sales Forecasting Accuracy

Three reports significantly improve the process of sales forecasting because they give robust visibility of the pipeline.

So use the information contained in these reports to achieve a step-change in forecasting reliability.

(We’ll talk about additional metrics in Section 4).

However, before we start there’s a critical prerequisite of robust pipeline visibility: unambiguous Opportunity Stages.

Opportunity Pipeline Stages

High-quality visibility of the sales pipeline leads to vastly improved sales forecasts.

However, in turn funnel visibility depends upon everyone understanding, and agreeing, on the meaning of the Opportunity Stages.
Unfortunately, very often that’s not the case.

In salesforce it doesn’t help that the default Opportunity Stages aren’t well understood. Nor particularly useful in many businesses.

So do two things:

First: change the Opportunity Stage picklist to values that have meaning in your business. This blog post will help you define the right values.

Second: make sure everyone understands and agrees on the meaning of each Opportunity Stage.

Those two items are critical to using the most important pipeline review chart.

Report 1: Pipeline by Stage and Close Date

This simple report and chart is the starting point in reviewing and analyzing a sales forecast.

That’s because what the chart and underlying report often reveal, is that any sales forecast based on the opportunities in salesforce is immediately going to be way off base.

However, get the underlying information right and you’re well on your way to a reliable forecast.

Let’s take an example.

Based on this example, here are the primary areas to investigate that improve our chances of getting a reliable sales forecast.

Deals with Close Dates in the past

This is a common problem.

So much so, in fact, I’ve published a blog post specifically on the steps you should take when you’re funnel looks full of out-of-date opportunities.

In this case, it’s not too bad.

What are those deals doing in previous months? Are they still open? If so, will they close in the current month? Or are they deals that are no longer viable and should be removed from the pipeline?

Addressing this is the first step to getting a reliable sales forecast for the current month or quarter.

Pro Tip

Drill down to the underlying report.

Here’s a great feature of Lightning reports in salesforce.

Click on the number within the report that you want to investigate. Now we can see the specific deals that make up the number.

Right click on the Opportunity Name to open it in a separate tab.

Update the Opportunity by changing the Close Date and / or Stage.

Repeat this step until you no longer have Opportunities with old Close Dates.

Deals with unrealistic Opportunity Stages

Let’s look at the current month (I’m assuming it’s May 2019 for the purposes of this demonstration).

Many B2B companies have a sales cycle of three to four months. Some much longer.

So how realistic is it that deals with an Opportunity Stage of Prospecting or Investigation will close this month?

In fact if we are mid-month (which is often when we are producing sales forecasts), then even many deals in Proposal Made may not close successfully this month.

So here’s what you do.

Same as before, look at the underlying detail.

Review the early stage opportunities. There’s three possible scenarios for each one:

1. The Close Date and Stage are accurate.

Perhaps it’s an existing customer with a strong purchasing track record that has told us he’ll definitely be ordering this month.

2. There’s a reliable Close Date but the Stage is wrong.

In other words, the Opportunity is more advanced in the sales cycle. Assuming you’re confident in the Close Date, update the Stage.

3. There’s a reliable Stage but the Close Date is wrong.

Perhaps this deal was originally anticipated to close this month. But now it’s not. Move the Close Date so that your forecast for this month is more robust.

Of course, there’s also the possibility that both the Stage and the Stage need updating.

So go through the funnel opportunities in your sales forecast and make sure you are happy with the Close Date and Stage in every case.

Pro Tip

Managers with large sales teams and / or lots of opportunities can’t go through every deal this way. One technique to avoid this is to manage by exception, using the metrics explained in Section 4.

Create a version of the Close Date by Stage report to run on My Team. Have sales leaders to go through the same pipeline validation process with their team members.

And then go a step further. Providing the Role Hierarchy is correct, when individual salespeople run the My Team report, they will see only their own deals. Train and educate each salesperson on using the report to check and validate their personal pipeline.

Unlikely funnel spikes

In many businesses there’s a determined sales drive at certain times of the year. In particular, to close deals in the last month of the financial year or quarter.

Here’s the Funnel by Close Date and Stage chart I saw recently.

Can you guess when their financial year ends?

You’re right. December. And of course that means there’s an additional quarter-end in March, June and September.

So why the spikes?

The reason is that in this business, salespeople are under top-down pressure to meet revenue expectations from internal and external company stakeholders.

Consequently, hopeful Close Dates are assigned to many opportunities. These are based not on the customer buying process, but on the desire to assuage other pressures. “It’s bound to close sometime this year, I’ll put in the year-end”.

In reality, how many deals do you know that close on December 31?

The same thing happens with the quarter-end.

The result?

The sales forecasts reflect funnels containing artificial peaks in the number and value of opportunities that will be won. Consequently, these sales forecasts are almost always unreliable.

So, review your longer-term pipeline. Validate that peaks in the value of deals to be closed accurately reflect sales effort and marketplace conditions rather than the need to satisfy non-customer stakeholders.

Otherwise?

You’re simply kidding yourself.

Pipeline by Created Date

Reviewing the pipeline by created date is another way to validate funnel quality.

This chart shows deals due to close this month (and therefore in our current sales forecast) by created date.

Does your sales forecast contain many deals with a longer-then-average sales cycle?

It looks like it here.

Potentially, these are deals that consistently move along in order to maintain the size of the pipeline. If you’re reliant upon these deals to meet your sales quota, you may be on wafer-thin ice.

Same steps as before.

Drill down to the underlying deals.

Assess the viability of these deals. Do this to gauge reliability of your sales forecast.

Conversion Rate Report

You might be wondering:

How does a report that shows opportunity win rates (conversion rates) help us assess the reliability of a sales forecast?

Well, take a look to check that historic opportunity conversion rates are realistic.

First example.

Let’s assume that in your business, instinct and experience tell you the opportunity conversion rate should be around 30%.

So, how do we explain a conversion rate report in salesforce that shows the win rate is 70%?

Two possible reasons.

Opportunity sandbagging

Not all deals enter the pipeline immediately. In other words, only when the salesperson is confident of a successful outcome is it entered in salesforce. It’s called sandbagging.

On the one hand, this means your sales forecast might be pessimistic. This is because there are deals out there being worked on, some of which may come to fruition. It’s simply that you don’t have visibility of them.

If this genuinely is the case, your revenue forecast is still going to be pretty inaccurate. Only this time the forecast will be too low.

And as the VP of Sales it doesn’t exactly give the impression you’re on top of what’s going on.

Deals in the pipeline too long

Deals that no longer have legs are not moved out of the pipeline.

The result?

The funnel contains many deals that are unlikely to close successfully any time soon (if ever).

Some of these deals may be in your current sales forecast. Consequently, the forecast probably overstates revenue. In any event, it’s not built on solid foundations.

Which explanation applies in your business if the conversion rate is artificially high? Sandbagging or dormant deals? Or both?

Well, instinct and anecdotal evidence might be enough.

But to be sure, take a second look at the Pipeline by Created Date chart.

If there’s a significant number of deals open much longer than seems reasonable then it’s probably the second explanation. Dormant deals aren’t removed from the funnel.

Take a good look at these deals. Weed out those that undermine your sales forecast.

4.     Pipeline Quality Metrics

The reports and dashboard charts we’ve looked at so far are an excellent way of validating the sales forecast top down.

But you might be thinking:

How do I manage by exception? What are the metrics identifying specific deals that potentially should not be included in the sales forecast?

There are three deal metrics we can use to surface deals that have an increased chance of slipping from the forecast. Deals that will potentially leave egg on our face.

Here they are:

1. Number of Close Date Month Extensions. This is the number of times the Close Date on the Opportunity has moved from one month to another.

2. Number of Days since the Last Stage Change. This tracks how long it is since the Opportunity Stage was last updated.

3. Age of the Opportunity. This is the number of days the Opportunity has been open.

Use these metrics to manage by exception.

In other words, they help sales managers quickly and easily identify high-risks deals.

You can do this using a dashboard table.

The table shows deals due to close this month. So they’re all potentially in your sales forecast.
But can you rely upon them?

Well, the Oxted Manufacturing Opportunity has been open over 200 days. It’s 100 days since the Opportunity Stage was last updated. And the Close Date has moved from one month to another 4 times already.

Not exactly a banker, I’d say.

Perhaps this deal WILL finally close this month.

But you get the idea.

These sales metrics and the accompany dashboard help rapidly identify deals we must investigate further.

5.     Get Free Salesforecasting Resources

Here are free resources that will radically improve the sales forecasting method and technique in your company.
• GSP Sales Forecast Template.
• 30 minute web meeting with me.

GSP Sales Forecast Template

This free dashboard has been installed over 1,000 times. You can find it on the AppExchange here.

The package contains:
• All the reports described in this sales forecasting guide.
• A comprehensive dashboard with drill-down to all reports.
• The three deal quality metrics and dashboard table that help you manage by exception.

There’s even a configuration guide that explains how to adapt the sales forecast template to the specific needs of your business.

Apply for the 30 minute web meeting

Each week I hold four free one-to-one meetings lasting 30 minutes.

The discussion is private and specific to your company. You decide the specific topic to discuss so that you get maximum benefit from the discussion.

It doesn’t have to be about sales forecasting. Here some recent examples of other topics I’ve covered recently. How do I:
• Adapt salesforce to the specific needs and processes of my business?
• Embed robust forecasting and pipeline management techniques across my sales team?
• Track revenue versus quota and know whether there is sufficient pipeline to meet target?
• Increase salesforce benefits and the investment ROI?
• Manage framework agreements and other non-standard opportunities?

Good luck and happy forecasting!