With that in mind, sales reps are often hesitant to commit to anything, preferring to under-commit and over-deliver.
While playing it safe is understandable, it makes sales forecasting unpredictable and difficult to manage.
All too often, managers and sales reps are left guessing which potential buyers will make it through to close, and when it’ll happen.
What impact does this have?
According to this article on Entrepreneur.com, 54 percent of deals forecasted by reps never close.
To help correct this problem, we’ve outlined four best practices that will strengthen and improve the accuracy of your sales forecasts.
1. Your pipeline begins in marketing and ends in finance
When organizations talk about their pipeline, they’re often just referring to their list of opportunities.
In reality, it’s much more than that.
Your pipeline actually starts in marketing with lead generation, funneling into how many leads have been nurtured, qualified and closed.
Even then, your forecasting pipeline doesn’t end when an opportunity closes. It continues through finance and ERP systems to ensure order capture, demand planning, billing and invoicing.
If teams base their forecasts on just a percentage of their pipeline, they’ll be wildly inaccurate.
Consider more than just your list of opportunities.
Take an in-depth look at the entire process from start to finish to capture a true revenue forecast.
2. Forecast based on your business model
No two companies forecast the same way.
Even separate departments within the same organization may forecast differently.
Some forecast based on revenue and profit, while others may focus on margin and product.
An organization’s forecasting must match its business model.
If you define your forecasting process to behave one way, there will be hurdles for those who aren’t used to operating that way.
Without alignment with the business, organizations are unable to change the way they forecast.
With that in mind, as a manager, you must come up with a forecasting solution that is flexible and adapts to the business model(s) of your organization.
3. Create views for different groups of users
Different groups of users have different data needs.
For example, territory-based forecasts might work for your organization’s sales teams, but your product teams, industry business units and other groups will need to cut deals along different dimensions.
An effective forecast allows you to “pivot” so deals can be aggregated by account, product, geography, vertical and more.
It’s important that each forecast you create is able to deliver role-specific views, adapt to organizational changes, and use past, present and predictive data.
4. Adhere to a repeatable cadence
Every organization needs a forecasting cadence.
Having a repeatable cadence not only gives managers a chance to frequently forecast, but also constantly monitor quota, judge accuracy, and report on the entire execution.
A typical schedule might look something like this:
Adhering to a regular cadence can also be useful in helping a business determine where it might be trailing.
This gives the team time to adjust and make up numbers elsewhere by finding deals on the cusp and bringing them in.
Finally, having a regular cadence is essential in helping businesses manage expectations for the quarter.
Stay tuned for predictive forecasting
These four steps are a solid starting point for organizations looking to clean up their sales forecasts.
But it doesn’t stop there.
According to Thomson Reuters, 40 percent of S&P 500 companies typically miss sales estimates in a given quarter.
Next time, we’ll discuss the benefits of data science and predictive analytics, and how they mesh with sales forecasting to further improve accuracy.
Until then, you can learn how to become a predictive sales organization by downloading the free ebook below.
Free eBook:Becoming a Predictive Sales Organization
Discover how data science can help you improve your sales forecasts and increase revenue.
Image credit: Christophe Verdier