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Feature - Forecasting

LinearB’s Forecasting section brings two views together to help teams plan and deliver confidently: Project Forecast — a probability-based completion forecast using Monte Carlo simulation, and Progre…

heather.hazell
Updated by heather.hazell

LinearB’s Forecasting section brings two views together to help teams plan and deliver confidently: Project Forecast — a probability-based completion forecast using Monte Carlo simulation, and Progress Over Time — a timeline view showing how scope and completed work evolve. Both views use real issue data from your PM tool to give you a realistic sense of when work will finish and how it is progressing.

TL;DR

  • Project Forecast predicts when a project is likely to complete based on historical throughput.
  • Progress Over Time shows how scope, statuses, and completion change period-over-period.
  • Both require a defined project scope using filters (Epics, Initiatives, Features, Tags, etc.).
  • Best used for scoped initiatives—not for continuous or unbounded workstreams.

Overview

Forecasting is available under the Projects → Forecasting tab in LinearB. It uses only your connected PM tool (Jira or Azure Boards) — no Git data is required for these views.

Forecasting includes two complementary tools:

  • Project Forecast — uses Monte Carlo simulation on completed issues to estimate completion windows.
  • Progress Over Time — shows how work moves through statuses over time and whether scope is stable, growing, or completing as planned.

Both use the same project definition (filters). Once a project is scoped, both forecast and trend analysis update automatically.

Before You Begin

  • Access: Any user with visibility into the Projects tab.
  • Integrations: Jira or Azure Boards connected.
  • Requirement for Forecast: At least 30 completed issues and 5 weeks of completion history inside the selected project scope.
  • Project filters: Required to define what work belongs to the initiative you're forecasting or tracking.

Where to Find Forecasting

Open Forecast and Progress Over Time
  1. Navigate to Projects in the LinearB web app.
  2. Click Forecasting.
  3. Choose between:
    • Forecast — completion probability model
    • Progress Over Time — delivery trend timeline

Project Forecast

1. Define your project scope

Project Forecast relies on a clearly defined scope using filters such as:

  • Jira: Epics, Initiatives, Projects, Labels, Boards, Versions
  • Azure Boards: Features, Epics, Projects, Tags, Fields

To configure:

  1. Open Projects → Forecasting → Forecast.
  2. If no scope is defined, click Add Filter.
  3. Select the PM fields that represent the project.
  4. Save your filters as a reusable project definition.
2. Minimum data required
  • At least 30 completed issues in the selected scope.
  • At least 5 weeks of completion history.
  • A defined end state — fixed-scope projects forecast best.

If these conditions are not met, LinearB will display guidance instead of a forecast.

3. How Monte Carlo simulation works

LinearB runs thousands of simulations based on historical delivery throughput to produce probability-based completion dates.

  • Every simulation represents one possible completion path.
  • Completion probabilities are grouped by week.
  • The output is a distribution — not a single deterministic date.
4. Reading the forecast visuals

Weekly Probability Chart

  • Shows the likelihood of completing in each upcoming week.
  • Color-coded:
    • Red: ≤ 50% likelihood
    • Yellow: 51–74%
    • Green: ≥ 95%

Distribution Graph

  • Histogram showing the concentration of “most likely” finish weeks.
  • Switch using the Y-axis selector: Distribution.

Calendar View

  • Color-shaded calendar showing confidence levels by week.
  • A quick way to visualize delivery windows on a timeline.
5. When forecast is unavailable
  • Too few completed issues.
  • Insufficient historical throughput.
  • Completion probability is extremely low (e.g., < 3% in next 15 weeks).
  • Project appears to already be complete (> 95% Done).

Progress Over Time

1. Access the Progress Over Time view
  1. Go to Projects → Forecasting.
  2. Select Progress Over Time.
  3. Adjust the time frame using the date picker.
2. Configure filters

Uses the same filter logic as Project Forecast.

Jira filters include:

  • Project
  • Initiative
  • Epic
  • Board
  • Label
  • Fields / Custom Fields
  • Fix Version

Azure Boards filters include:

  • Project
  • Feature
  • Epic
  • Tag
  • Field
3. Understanding the Progress graph
  • Stable graph height → stable scope.
  • Increasing height → scope creep.
  • Growing “Done” segment → steady progress.
  • Flat “Done” segment → stalled progress.
4. Customize your view
  • Toggle between Story Points and Issues.
  • Toggle workflow statuses on/off in the legend.
  • See average velocity at the top of the chart.
5. Insights panel

The Insights panel highlights delivery risks such as:

  • Issues stalled in a status
  • Issues In Progress with no Git activity
  • Unassigned work
  • Issues missing estimates (if your team estimates)
  • Developers overloaded across epics

You can customize which insights appear using the gear icon.

6. Initiative / Epic / Issue lists

The table below the graph shows work items within the selected scope. Views include:

  • Issues — granular breakdown
  • Epics / Initiatives — aggregated progress

Troubleshooting

No forecast available
  • Not enough completed issues.
  • Not enough historical throughput data.
  • Project scope may be too large or too small.
Progress Over Time looks empty
  • Time range may not include activity.
  • Filters may not match actual issues.
  • PM integration may be disconnected.
Velocity seems incorrect
  • Check if you're viewing Issues or Story Points.
  • Ensure issues transition to Done consistently.
  • Check if the date range is too narrow.

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