No Sales VP would ever willingly admit it, but it’s time to face facts – most sales forecasts are guesses, stabs in the dark that rely on incomplete information. The typical sales forecasting methods used by most organizations are, as Jason Jordan articulates in this blog post for HubSpot, comprised of arbitrary guesses in several key sales metrics:

• The size of an opportunity

• The estimated close date of an opportunity

• The sales funnel stage that an opportunity is in

• The likelihood of closing this opportunity

The first three “guesses” all ultimately feed into the last erroneous guess. As they say about life, “You get what you put in.” Well, what do you think you will get when you put incorrect and inaccurate information into a sales forecast?

Enough is enough! Stop guessing, and start adopting sales forecasting methods that produce actually accurate sales forecasts!

Historical data jumps to the forefront

As Jason mentions in his post, eliminating the guesswork requires using history as a guide, or more specifically your historical sales metrics. This means diving into your Salesforce.com CRM to pull that data, export it to Excel and start a deep-dive analysis. Essentially, what you’re trying to answer in your analysis is this:

• Historically, how have various variables – such as opportunity age, size and stage – affected whether that opportunity was Closed-Won or Closed-Lost?

Once you have a large enough sample size of how opportunities react to the aforementioned variables, you can then reasonably extrapolate that number to future opportunities, thereby giving you that more-accurate sales forecast that you need for better visibility and to drive better business decisions. For instance, if opportunities above a certain value – say $10,000 – have historically closed at a much lower rate than the rest of your opportunities, that should give you the grain of salt you need when analyzing and forecasting future large opportunities.

The problem is that exporting Salesforce reports to Excel for analysis is an arduous and time-consuming process. That difficulty in analysis was one of the primary driving forces behind the creation of our InsightSquared software. We believe that CEOs and Sales VPs should be able to look into their historical sales metrics and conversion rates with just a few simple clicks. Our FREE Sales Funnel report on the Salesforce AppExchange provides this simple access to the historical conversion rates you need.

Help me forecast more easily and more accurately!»

Think about the buyer, not the seller

Another common “guess” cited by Jason Jordan that often sinks sales forecasts is what stage your buyers are in. This is because of a serious fundamental issue – your sales process is aligned to the selling process, when it should be aligned to the buyer’s process.

Think about it: you should know where your sales reps are, and what they’re thinking, at each step of their own process. Unless you’re trying to get into the mindset of your buyers at each specific step of their progress from the top of the funnel all the way to the bottom, you’re not likely to enter the correct and accurate info into your CRM, thus diluting the quality of your CRM data and ultimately jeopardizing your sales forecast.

Rectify this problem by re-defining your sales funnel stages to reflect thinking like a buyer, rather than thinking like a sales rep.

Watch out for those landmines!

Even after analyzing your historical data to provide reasonable comparisons, re-defining your stages to sync up to the buyer’s process and eliminating as much of the guesswork from your forecasts as possible, there are still precarious landmines on the landscape for you to avoid:

Forecast killers.

Unless they are properly accounted for, these killers can sink the accuracy of any sales forecast, even one that has removed all guesses. These killers need to be identified and taken with a grain of salt, with their associated opportunities flagged as at risk. Some of the most common forecast killers include:

• Slippage – opportunities that have changed close dates or value many times.

• Timing – opportunities that have languished in certain stages for too long. A win/loss analysis by sales cycle will help you identify what “too long” means.

• Lead source – some lead sources generate riskier opportunities than others.

When running your sales forecasting meeting with your closing reps, make sure that they point out potential forecast killers in reviewing each of their closing opportunities.

The right sales metrics – with the proper historical perspective and careful analysis – can help eliminate the guesswork that is inherent with a sales forecast. Let InsightSquared help you get your sales forecasts right, without having to break your own back to do so.