Test Estimation Models: Comparing Popular Methods
Which estimation model should you use—WBS, Three-Point, PERT, story points, analogous, or Monte Carlo? This guide compares the most common approaches side-by-side with formulas, examples, and when to apply each.
Different estimation models answer different questions. Some are great for visibility and stakeholder alignment (WBS), others capture uncertainty (Three-Point/PERT), while a few provide probabilistic confidence (Monte Carlo). This guide helps you choose the right model—or hybrid—for your testing project.
If you want a broader walkthrough of estimation steps and templates first, start with Test Estimation Techniques: Complete Guide (With Examples & Tools) .
The Models at a Glance
| Model | Best For | Strengths | Limitations |
|---|---|---|---|
| WBS | Visibility & accountability; large or complex work | Transparent, negotiable scope; reusable patterns | Can be time-consuming; misses variance without ranges |
| Three-Point | Capturing task-level uncertainty | Simple inputs (O/M/P); quick to teach | Needs discipline on assumptions; still a single mean |
| PERT | Weighted averages; better central tendency | Reduces effect of extremes via 4×M weighting | Confidence levels still implicit unless you add variance |
| Analogous | Early estimates; similar past projects | Fast; uses historical reality | Requires good actuals; risks false similarity |
| Story points | Agile teams with stable velocity | Team-relative sizing; works across roles | Translation to hours/budget can be fuzzy |
| Monte Carlo | Risk communication; P50/P80/P90 timing | Probabilistic dates & effort; scenario testing | Needs ranges/variance; perceived as “mathy” |
How to Choose (Quick Decision Guide)
If you need…
- Stakeholder clarity: Start with WBS.
- Ranges for uncertain tasks: Add Three-Point or PERT.
- Confidence levels (P50/P80/P90): Run Monte Carlo.
- Early portfolio number: Use Analogous or Story points.
Recommended hybrid
WBS → Three-Point/PERT → Monte Carlo for critical releases; swap in Analogous or Story points when discovery is still unfolding.
For a complete walkthrough of the hybrid process, see Test Estimation Techniques: Complete Guide (With Examples & Tools) .
WBS (Work Breakdown Structure)
Break the testing effort into clear, countable tasks: strategy, design, env/data, execution (UI/API), non-functional, triage, regression, reporting. Estimate at 4–16h granularity for accuracy without micromanagement.
- Pros: Visible scope; easy to negotiate tradeoffs; reusable templates.
- Cons: Doesn’t encode uncertainty by itself; can be heavy if over-granular.
Three-Point Estimation
Use three inputs per task: Optimistic (O), Most Likely (M), Pessimistic (P). Two common formulas:
Triangular
Mean = (O + M + P) / 3PERT-weighted
Mean = (O + 4M + P) / 6Use when: tasks have meaningful variance but you want a lightweight range method.
PERT (Program Evaluation and Review Technique)
PERT assumes the task duration follows a distribution and weights the most likely value (M). It pairs perfectly with Three-Point inputs and sets you up for Monte Carlo confidence outputs.
- Why QA teams like it: Dampens extremes; plays nicely with WBS.
- Be mindful: Garbage in (O/M/P) → garbage out; capture assumptions.
Analogous / Historical Estimation
Base your estimate on similar past projects (normalized for complexity, platforms, and risk). Works well during discovery or for portfolio planning.
Example: Prior 20-screen mobile app took 400 QA hours ⇒ estimate 30 screens ~ 600 hours (then refine with WBS/PERT).
Agile Story Points & Velocity
Story points are a relative sizing system. Convert to calendar using historical velocity, then infer QA capacity from typical QA:Dev split or explicit QA tasks.
- Good for: Mature teams, incremental planning.
- Watch-outs: Velocity drift, unclear mapping to budget.
Monte Carlo Simulation
Run thousands of trials using your O/M/P (or PERT mean + variance) to produce probabilistic timelines (P50/P80/P90). This is the cleanest way to communicate schedule risk.
For inputs and setup patterns, see the complete estimation guide .
Hybrid Models That Work Well in QA
- WBS + PERT: Most common for release planning—transparent scope + uncertainty handling.
- Analogous → WBS: Early number to align execs, then detail with WBS.
- Story points → PERT: Use points for backlog, PERT for critical non-negotiable work (perf, security, compliance).
- WBS + PERT → Monte Carlo: When commitments require confidence levels.
Worked Examples
Example 1: Web Release (WBS + PERT)
| Task | O | M | P | PERT (h) |
|---|---|---|---|---|
| Test design & data | 24 | 36 | 60 | (24+4×36+60)/6 = 38 |
| Functional execution | 60 | 90 | 135 | 92.5 |
| Non-functional baseline | 10 | 18 | 30 | 18.7 |
| Triage & verification | 20 | 30 | 45 | 30.8 |
| Regression & sign-off | 16 | 24 | 36 | 24.7 |
| Total | ~204.7 h | |||
Calendar: 3 testers × 30 focus h/wk = 90 h/wk → ~2.3 weeks (P50). For P80, add contingency or run Monte Carlo.
Example 2: Analogous → WBS (Mobile)
Historical feature family: 150 hours. New scope is 25% larger with more devices → 150 × 1.25 = 188 h. Build a WBS to validate and distribute effort across env/data, execution, and regression.
Example 3: Story Points → Budget
Team velocity 45 pts/sprint. Historical QA share ≈ 40% of effort. If 2-sprint increment is planned at 90 pts, QA ≈ 36 “points worth” of work. Convert using avg hours/point from your actuals (e.g., 3.2 h/pt ⇒ ~115 hrs).
Common Pitfalls & Anti-Patterns
- Single-number promises: Always provide ranges or confidence levels.
- Invisible work: Environments, data, triage, reporting—make these explicit lines.
- Copy-paste analogous numbers: Normalize for platforms, risk, and device/browser matrix.
- Ignoring non-functional: Performance, security, and accessibility require time and tooling.
- No re-estimation triggers: Re-estimate when scope or risk changes materially.
FAQ
What’s the simplest model for a quick estimate?
Analogous if you have good historicals; otherwise a lightweight WBS + Three-Point for top tasks.
How do I communicate confidence without overwhelming execs?
Show P50/P80 dates as two options and the top two risks that move you from one to the other.
Where do I start if I’m new to all of this?
Read the overview and grab templates from Test Estimation Techniques: Complete Guide (With Examples & Tools) , then try WBS + Three-Point on your next sprint.
Conclusion & Next Steps
- Draft a WBS to make all QA work visible.
- Add Three-Point/PERT to encode uncertainty at task level.
- Run Monte Carlo for P50/P80/P90 when commitments matter.
- Use Analogous or Story points for early/portfolio planning; replace with detailed models later.
For step-by-step templates and more examples, revisit Test Estimation Techniques: Complete Guide (With Examples & Tools) .