5 Sales Forecasting Methods | The Good, The Bad, and The Fired

5 Sales Forecasting Methods | The Good, The Bad, and The Fired

Depending on who you speak with, nearly every sales manager has her or his own unique sales forecasting method.

Forecasting techniques range from in-depth analysis of historical data, to whatever the sales reps say, to whatever the manager feels, to whatever the CEO wants to hear. In enterprise sales, depending on sales cycle length and complexity, each company’s sales process will be slightly different. This is why there are many things that can impact a company’s sales forecast, such as:

  • Cyclical or Seasonal fluctuations in sales.
  • Sales cycles can be impacted by economic conditions.
  • Conversion rates can fluctuate due to competition.
  • New products can create unpredictable results.
  • Sales targets and long-term goals can change throughout the year.

But, this doesn’t mean that methods of forecasting vary so widely. In this article, we’ve boiled down some of the most complex sales forecasting techniques into five methods and given our two cents on the effectiveness of each one.

1. Forecasting By Opportunity Stage

This is most commonly known as the “weighted pipeline” approach.

When your forecasting by opportunity stage, each of the opportunities in your sales pipeline is set to a stage in the sales process by your sales rep, and each of the steps in your sales process is assigned a probability of win/loss. For example, you might have a step in the process associated with a proposal being sent, and you might know that once a proposal goes out, on average, deals have a 50% chance of being won.

The advantages of this approach is its simplicity.

Your salesperson tells you where they are in the process. You then know the probability of the deal being won. When you average this over a large number of deals, you stand a good chance of having an accurate sales forecast.

The disadvantage is that while this might work over a large number of deals. Regression analysis shows that the correlation between stages and probability can be quite low for an individual deal. It also prevents the salesperson from ever thinking seriously about their sales forecast. So they feel no responsibility for it.

2. Forecasting With Historical Data

Sales data can be used in various ways to create a sales forecasting model.

Historical sales data, pipeline numbers, and win rate percentages for a given period can provide a benchmark for how your sales reps will perform in future quarters. If you know how productive an average sales rep can be, you can extrapolate across a large team. Likewise, if you know how much pipeline it takes to generate $1M in revenue, you can calculate how much sales growth you will see from your current pipeline if it contains a lot of early-stage deals. And if you know the average amount of revenue that can generate an average lead, you can start forecasting sales based on the recent results of your marketing team.

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All these statistical methods have one characteristic – they take the human element out of forecasting.

This can be very appealing to a Finance team, or a Sales Operations team with a Finance background, but it is of relatively low use to your sales leadership. By de-coupling your sales forecast from the salespeople’s perspective and the deals they are working on, you are not providing any actionable data to your managers and executives that they can use to run the team.

3. Forecasting Using Industry Benchmarks

Many early-stage companies that lack both a sales pipeline of opportunities and any relevant historical data end up forecasting using industry benchmarks. They make an estimate for their average selling price, their average sales cycle and forecast sales based on an idealistic view of the world.

When it comes to building a sales forecast for your team, don’t pay too much respect to people who are not intimately familiar with your business. Make a rudimentary forecast as quickly as possible, set expectations that you need some real data before it becomes accurate, and get cracking building pipeline, working through sales cycles, and figuring out who exactly needs your product or service and what they are willing to pay for it!

4. Forecasting With Engagement Data

Forward-thinking companies are starting to use more real-time data when it comes to determining the health of opportunities. Tools like Datahug can help you measure the health of deals in your pipeline using CRM data alongside additional insights gathered from email, calendar, and phone.

Certain signals such as the responsiveness of the prospect, the existence of future meetings, and the number and seniority of people actively engaged at an account can be combined with CRM data to create leading indicators of deal health.

This is more effective than forecasting by opportunity stage because it introduces an objective source of data to go alongside the sales rep’s gut feel. It also unearths insights that can be used for sales rep coaching, so that alongside more accurate forecasts, you also get better rep performance.

5. Forecasting By Sales Rep Submissions

The most effective way to build a sales forecast is to have sales reps submit individual forecasts on a weekly basis – either for the current month or current quarter. This forces the sales rep to assess the health of their pipeline regularly and be honest with themselves. Tools like Datahug enable the submission of the forecast on a deal-by-deal level and the tracking of historical forecasts. They also allow managers to override their reps’ forecasts and alert reps when forecasted deals are not showing true signs of health.

Tell your sales team that the number they submit will be very close to the number submitted to the CEO and board and it will empower them to take forecasting more seriously. Hold them accountable to forecast accuracy over time, and they will take pride in learning more about the process and improving their forecasting skills.

It is a lot harder for your salespeople to commit to a number than it is to update a number of deals and not think about the consequences. But holding your salespeople accountable to the forecast helps them develop as professionals, keep better track for their deals, and reduces the burden on your managers so they can spend more time coaching their teams.