Three-Case Modeling

A single-point forecast is a bet. A three-case model is a strategy. Base case represents the most likely outcome given current trajectories. Upside case represents what happens if key assumptions break favorably — higher win rates, larger deals, faster expansion. Downside case represents what happens if assumptions degrade — longer sales cycles, higher churn, compressed deal sizes. The goal is not to predict which case materializes. The goal is to make decisions that are sound across all three.

                    Downside    Base      Upside
────────────────────────────────────────────────────
New ARR              $3.2M      $4.8M      $6.1M
Expansion ARR        $1.1M      $1.6M      $2.2M
Churned ARR         ($1.4M)    ($1.0M)    ($0.7M)
────────────────────────────────────────────────────
Net New ARR          $2.9M      $5.4M      $7.6M
Ending ARR          $22.9M     $25.4M     $27.6M
YoY Growth            14.5%      27.0%      38.0%

Key Variance Drivers:
  Win rate:    18% / 24% / 30%
  Avg deal:   $38K / $44K / $52K
  Churn rate:  8% / 5.2% / 3.5%

1. Define the Variance Drivers Not every assumption needs three cases. Identify the 3-5 assumptions with the highest impact and the lowest confidence. These are your variance drivers. Win rate, average deal size, churn rate, and sales cycle length are typically the highest-leverage variables in a SaaS revenue model.
2. Quantify the Range Use trailing data to set realistic ranges. If your win rate has been 20-28% over the past four quarters, your downside is 18% (slight degradation), base is 24% (trailing average), and upside is 30% (best quarter plus modest improvement). The range should be plausible, not aspirational.
3. Stress Test the Downside The downside case is the one that matters most — it determines your survival constraints. Can you make payroll in the downside case? Can you maintain minimum R&D investment? Does the business remain viable? If the downside case breaks the business, your base case better be extremely well-supported.