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PMO & Delivery Ops

Heather Hazell
  • Updated

This guide is for PMO and Delivery Operations leaders who need a clear, repeatable way to understand predictability, cross-team flow, and portfolio risk. It highlights the LinearB views that connect plans → actuals → delivery constraints, so you can run better planning cycles, reduce surprises, and support executive decisions with evidence.

Time required: 10–15 minutes to orient, 30–45 minutes to define a recurring cadence
Difficulty: Easy

TL;DR – What to use first

  • Teams → Iterations (Current + Completed) to see planned vs. delivered, carryover, and unplanned work by team.
  • Metrics → Delivery to understand where flow is slowing (coding, pickup, review, merge) and how that affects predictability.
  • Project Delivery Trackers to track initiative / project health across teams and spot schedule risk early.
  • Resource Allocation / Investment Strategy to confirm where FTE time is actually going vs. your portfolio plan.
  • AI summaries & reports to turn trends into concise, repeatable updates for planning and business reviews.

Overview

Your job is to make sure the organization is building the right things, in a predictable way, with clear visibility from initiative down to iteration. LinearB helps by connecting:

  • Project / initiative plans from your project management tool
  • Git and PR activity from your repos
  • Iteration patterns and flow metrics across teams

This guide helps you:

  • See how plans, execution, and bottlenecks line up across teams.
  • Identify where unplanned work and scope churn are eroding predictability.
  • Track initiative-level progress and risk in one place.
  • Validate whether allocation and investment match priorities (where enabled).
  • Run a simple operating rhythm that feeds planning, QBRs, and roadmap updates.

What you likely care about

  • Are we delivering what we committed to this sprint / iteration / increment?
  • Which initiatives or projects are off track, and why?
  • How much unplanned work is consuming capacity and putting roadmaps at risk?
  • Where does the flow actually slow down (coding, review, merge)?
  • Are we investing effort where the business expects (by product, initiative, or category)?
  • How do we create a repeatable, evidence-based planning loop instead of anecdotal debates?

Where to spend time in LinearB

1. Teams → Iterations (Current & Completed)

Why: This is your planning quality and predictability view.

  • Current Iteration
    • See what was planned vs. what is actually moving.
    • Spot scope creep, unplanned work, and likely carryover early.
    • Use this in planning / standup forums with EMs and PMs to make explicit tradeoffs.
  • Completed Iterations
    • Review planned vs. delivered, unplanned work, and carryover trends.
    • Identify teams consistently over-committing or overloaded.
    • Use patterns to adjust capacity assumptions and iteration / PI planning rules.

If AI Iteration Summary is enabled, use it to:

  • Get a fast narrative of each iteration (wins, risks, patterns).
  • Anchor retros and planning discussions on data plus summary, not memory alone.

2. Metrics → Delivery

Why: This is your flow and bottleneck view across teams.

  • See Cycle Time broken down into stages (Coding, Pickup, Review, Deploy / Merge).
  • Identify systemic bottlenecks (for example, review consistently slow across multiple teams).
  • Compare teams and time periods to see where changes in flow are driving schedule risk.
  • Use this to explain why commitments slipped (review queues, oversized PRs, long deploy times) and where to focus improvement.

3. Project Delivery Trackers

Why: This is your initiative / project-level health view.

  • Track progress, scope, and risk for key projects and initiatives.
  • See how much work is done, in progress, and at risk across contributing teams.
  • Use status plus underlying metrics to prepare portfolio and steering-committee reviews:
    • What changed since last review?
    • Where is risk increasing?
    • Which teams or stages are the constraint?

Pair this with Iterations and Delivery to answer: 
“Is this project off track because of scope, capacity, or flow?”

4. Resource Allocation & Investment Strategy

Why: These views connect capacity and investment decisions to actual work.

  • Resource Allocation
    • See where FTE time is actually going (projects, epics, initiatives, categories).
    • Check whether actual effort matches your portfolio priorities.
    • Spot over-investment or under-investment in specific streams.
  • Investment Strategy Report
    • See category-level breakdown (for example, new feature vs. maintenance vs. infrastructure).
    • Track strategic balance over time and align with finance / planning.

Use these views before and after planning cycles to validate that allocation decisions stuck, and where you need to rebalance.

5. DORA & reliability metrics (if configured)

Why: DORA metrics provide stability and reliability context for your portfolio.

  • Use Deployment Frequency and Lead Time to see how quickly work reaches users.
  • Use Change Failure Rate (CFR) and MTTR to ensure speed is not undermining reliability.
  • Combine these signals with iteration and project views to explain why roadmap dates are safe or fragile.

Quick-start checklist – PMO / Delivery Ops

Your starter signal set:

  • 1–2 key initiatives or programs you are responsible for.
  • 2–4 teams that are critical to those initiatives.
  • A recent timeframe (for example, last 2–3 iterations or last 30–60 days).
  1. Open Teams → Iterations (Completed) for the selected teams.
    Note patterns in planned vs. delivered, carryover, and unplanned work.
  2. Switch to Teams → Iterations (Current).
    Identify early risk signals: rising unplanned work, scope creep, or likely carryover this cycle.
  3. Open Metrics → Delivery for the same timeframe.
    Identify 1–2 common bottleneck stages across those teams (for example, review, pickup).
  4. If Project Delivery Trackers are enabled, open the trackers for your top initiatives.
    Check status vs. plan, and see which teams or stages are driving risk.
  5. If Resource Allocation / Investment Strategy is enabled, confirm whether FTE time distribution matches what you expect for these initiatives.
  6. Capture a one-slide summary:
    • 1–2 key risks (for example, unplanned work, review bottleneck, misaligned allocation).
    • 1 small improvement you will pilot next cycle (for example, commit rule, WIP limit, review focus).

This becomes the basis for your planning and portfolio conversations.

Metrics to prioritize

Focus on a small, durable set:

  • Planned vs. delivered work per iteration (per team).
  • Unplanned work and carryover trends (as surfaced in Iterations).
  • Cycle Time with stage context (especially review and pickup).
  • Work in progress and large-batch patterns that drive variability.
  • FTE allocation by initiative / category (where enabled).
  • DORA metrics (where configured) as stability and risk indicators.

Recommended PMO / Delivery Ops operating rhythm

Weekly / per iteration

  • Review Teams → Iterations (Current) with EMs / PMs for critical teams:
    • Flag scope creep, unplanned work, and likely carryover.
    • Agree on mid-iteration tradeoffs to protect priorities.
  • Check Metrics → Delivery for notable stage bottlenecks affecting current work.

End of sprint / iteration

  • Use Teams → Iterations (Completed):
    • Compare planned vs. delivered.
    • Look at carryover and unplanned work sources.
  • If AI Iteration Summary is enabled, use it to accelerate retro prep and document 1–2 system-level learnings per team.

Monthly

  • Review Project Delivery Trackers for key initiatives:
    • Adjust status, risk, and expectations based on actuals.
  • Review Resource Allocation / Investment Strategy :
    • Validate that effort is aligned with your portfolio.
  • Use Metrics → Delivery to check whether recent process changes are improving flow.

Quarterly / per planning cycle

  • Use Iterations, Delivery, and Allocation to:
    • Inform capacity assumptions and load per team.
    • Align initiative scope and dates with reality.
    • Identify where platform or process investments are needed to support the next cycle.

Common pitfalls

  • Treating LinearB as only an engineering dashboard instead of a planning feedback loop.
  • Looking at one iteration in isolation instead of trends across cycles.
  • Focusing only on “on time / late” labels without understanding flow bottlenecks.
  • Ignoring unplanned work and intake discipline, then being surprised by missed commitments.
  • Running planning and QBRs without closing the loop on actual allocation and flow.

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