Estimates
ProBeya's Estimates page provides a spreadsheet-like batch editor for entering three-point duration estimates (optimistic, most likely, pessimistic) on WBS tasks. These estimates feed directly into Monte Carlo simulations, enabling probabilistic schedule forecasting that accounts for uncertainty rather than relying on single-point guesses.
This feature is designed for project managers and planners who need to capture estimation data efficiently across many tasks and visualize the statistical distribution of each estimate before running simulations.
Overview
Traditional project scheduling assigns a single duration to each task, creating a false sense of precision. In reality, every task has a range of possible durations: the best case, the expected case, and the worst case. Ignoring this range leads to systematically optimistic schedules.
Three-point estimating solves this by capturing the full uncertainty range for each task:
- Optimistic (O) -- The best-case duration if everything goes right
- Most Likely (M) -- The expected duration under normal conditions
- Pessimistic (P) -- The worst-case duration if significant problems occur
ProBeya's Estimates page makes it efficient to enter these values across all project tasks in a single session, preview the resulting probability distributions, and feed the data into the Monte Carlo simulation engine.
Getting Started
- Navigate to a project and select Estimates from the sidebar.
- The page loads all WBS tasks for the project in a batch editor table.
- For each task, enter the Optimistic, Most Likely, and Pessimistic duration values.
- Select a distribution type for each task (PERT-Beta, Triangular, or Normal).
- Review the distribution preview to verify the estimate shape looks reasonable.
- Click Save to persist all estimates.
- Navigate to the Monte Carlo simulation page to run a simulation using the saved estimates.
Key Concepts
| Term | Definition |
|---|---|
| Three-Point Estimate | A set of three values (Optimistic, Most Likely, Pessimistic) that define the range of possible task durations. |
| Optimistic (O) | The minimum realistic duration. Everything goes according to plan with no issues. |
| Most Likely (M) | The expected duration under typical conditions. The mode of the distribution. |
| Pessimistic (P) | The maximum realistic duration. Significant problems occur but the task is still completable. |
| Distribution Type | The statistical model used to generate random samples: PERT-Beta (default), Triangular, or Normal. |
| PERT-Beta Distribution | A weighted distribution where the most likely value carries 4x the weight of the extremes. Mean = (O + 4M + P) / 6. This is the industry standard for schedule risk analysis. |
| Triangular Distribution | A simpler distribution defined by the three points without additional weighting. Mean = (O + M + P) / 3. |
| Normal Distribution | A symmetric bell curve. Requires a standard deviation override since the three-point values define the range, not the shape. |
| Monte Carlo Simulation | A statistical technique that runs thousands of random trials using the estimated distributions to produce a probability distribution of project outcomes. |
How It Works
Batch Estimate Editor
The BatchEstimateEditor component presents a table-style interface optimized for rapid data entry:
- Each row represents one WBS task
- Columns: Task Name, Optimistic, Most Likely, Pessimistic, Distribution Type, Standard Deviation Override (for Normal distribution)
- Tab/Enter navigation for efficient keyboard-driven entry
- Inline validation ensures O ≤ M ≤ P (the fundamental three-point constraint)
Distribution Preview
Each estimate row includes a visual preview of the resulting probability distribution. This small sparkline-style chart helps estimators verify that the distribution shape matches their intuition about the task's uncertainty profile.
For example:
- A task with O=5, M=7, P=20 produces a right-skewed distribution (long tail of delay risk)
- A task with O=8, M=10, P=12 produces a nearly symmetric distribution (well-understood task)
Validation Rules
The editor enforces statistical validity:
| Rule | Description |
|---|---|
| O ≤ M ≤ P | Optimistic cannot exceed Most Likely; Most Likely cannot exceed Pessimistic. |
| All values positive | Duration estimates must be greater than zero. |
| Distribution consistency | Normal distribution requires a standard deviation override if the three-point range is very wide. |
Data Flow to Monte Carlo
Saved estimates are stored as part of the project's Monte Carlo simulation configuration. When a simulation is executed:
- The engine reads each task's three-point estimate and distribution type
- For each trial (typically 10,000), it generates random duration samples from the specified distributions
- Task durations are aggregated through the project's dependency network to compute total project duration
- The result is a probability distribution of project completion dates
WBS Integration
Estimates are linked to WBS (Work Breakdown Structure) elements. The page fetches WBS tasks via the Monte Carlo tRPC routes and presents them in hierarchical order matching the project's work breakdown.
Configuration
| Setting | Description |
|---|---|
| Default Distribution | PERT-Beta is the default distribution type for new estimates. Can be changed per task. |
| Simulation Count | The number of Monte Carlo trials (configured on the simulation page, not the estimates page). |
| Standard Deviation Override | Only applicable for Normal distribution. Overrides the computed standard deviation with a custom value. |
Permissions
| Role | Capabilities |
|---|---|
| Project Viewer | View estimates for project tasks |
| Project Member | Enter and edit three-point estimates |
| Project Manager | All member capabilities plus save batch estimates and configure distribution types |
| Organization Admin | Full access across all projects |
The estimates page resolves the project from workspace and project slugs using the server-side tRPC caller, ensuring URL-based access control. If the project does not exist or the user lacks access, a 404 is returned.
Tips & Best Practices
Three-point estimates benefit from diverse perspectives. Have the task owner, a peer, and a technical lead each provide independent estimates, then discuss and converge. This reduces anchoring bias.
If a task involves new technology, unfamiliar processes, or external dependencies, widen the optimistic-pessimistic range. Narrow ranges on uncertain tasks produce overconfident simulations.
The PERT-Beta distribution is the industry standard for schedule risk analysis because it weights the most likely value appropriately. Switch to Triangular only if you have a specific reason to give equal weight to all three points.
Estimates should be updated as uncertainty resolves. A task estimated at O=5, M=10, P=30 days before design review might become O=8, M=12, P=15 after requirements are finalized.
If the preview shows a shape that does not match your intuition, adjust the values. A nearly flat distribution suggests the team has no idea how long the task will take -- that is a risk signal worth investigating.
Troubleshooting
| Issue | Resolution |
|---|---|
| No tasks displayed | Verify the project has WBS elements or Monte Carlo simulations configured. The estimates page requires WBS task data to display. |
| Save button not responding | Check for validation errors. The batch editor validates all rows before allowing a save. Red-highlighted cells indicate invalid values. |
| Optimistic exceeds Most Likely | The three-point constraint requires O ≤ M ≤ P. Adjust the values so the optimistic estimate is less than or equal to the most likely estimate. |
| Distribution preview not rendering | The preview requires all three estimates (O, M, P) to be valid positive numbers. Empty or zero values suppress the preview. |
| Estimates not affecting simulation | After saving estimates, navigate to the Monte Carlo simulation page and run a new simulation. Saved estimates are consumed at simulation time, not in real-time. |
Related Features
- Monte Carlo Simulation -- The primary consumer of three-point estimates. Runs probabilistic schedule analysis using the saved data.
- Dependencies -- The dependency graph determines how individual task durations aggregate into project duration. Critical path items have the most impact on simulation results.
- PPM Projects -- Estimates are project-scoped and linked to the project's WBS structure.
- Gantt / Timeline -- The timeline view can display estimated duration ranges alongside the baseline schedule.
- Governance Framework -- Estimation quality metrics can be tracked as governance health indicators.