Why Do Companies Struggle with Forecasting?

Precedence Research estimates the global software as a service (SaaS) market size to be $358.33B in 2024. The market is large and mature. SaaS Capital says startups with $10M to $20M in revenue spend more than 35% of ARR on S&M, and major players like Salesforce and Hubspot have spent over 40% of their revenue on sales and marketing (S&M). The market is mature, and sales and marketing spending is high. So why do so many companies struggle with forecasting, a task that can make or break their future?

One primary reason SaaS companies need help with forecasting is their time horizon. SaaS companies operate within a “make every month” cadence. In general, sales leaders are worried about this month and next, and almost all of their energy is focused on opportunities that can close within a tight time window. When these leaders are asked to submit forecasts more than 90 days into the future, the numbers submitted are notoriously unreliable. If you ask most SaaS CFOs to evaluate the quality of the 4Q bookings forecast in 2Q, you will hear a high degree of skepticism.

The second reason is that forecasting has become the sole domain of sales leadership. This is a critical mistake. Accurate forecasting beyond the immediate 90 days is a team sport; sales, marketing, finance, and RevOps must all have a position on the team. Each team's contribution is crucial, whether it's marketing delivering a quality top-of-funnel pipeline, finance approving the necessary funds, or RevOps managing and measuring all conversion points. The list goes on. Sales leadership cannot stand alone when predicting bookings on a longer-term horizon.

Assuming these teams are working together, they must also work from a standardized dataset and aligned definitions. They must agree upon which investments best impact funnel performance and have a common framework for reviewing the return on dollars spent. Predictive analytics should be applied, understood, and visualized on a single application or location. Getting individual teams to behave as a cohesive revenue growth team is critical to success.

Let’s face it: If forecasting remains short-term and wholly within Sales, the numbers will always be suspect. But here's the good news: SaaS companies can do better. Considering how much they spend, they have the potential to do better. By shifting the focus from short-term to sustainable forecasting, they can improve efficiency, accuracy, and ultimately, their bottom line.

Here are suggestions on how to move from short-term forecasting to sustainable forecasting.

  1. Track every lead from the earliest possible top-of-funnel entry point to disposition.
  2. Use cohort-based regression analysis to determine how leads move through the sales cycle.
  3. Extrapolate to consider seen pipeline (opportunities) and predict unseen pipeline.
  4. Work to predict bookings on a 12-month timeline at a minimum, without relying heavily on direct seller inputs or roll-ups.

Building solutions like this isn’t easy. It would not be uncommon for an organization approaching $100M in ARR to build multiple Excel workbooks, leverage scripting languages like Python or R, and have multiple analysts working on the predictive model. If possible, organizations should consider using an application to help. Having predictions trapped in spreadsheets is sub-optimal.

When the model is developed correctly, the conversation changes. Instead of deploying inefficient sales and marketing tactics designed to make the next few months, the Executive Leadership Team (ELT) can collaboratively discuss how to close gaps 6+ months in the future. Long-term forecasting is critical to driving efficiencies in a SaaS business model.

I love to discuss forecasting. If you would like to talk, please email me at