How to Build a Product-Engineering Dashboard

“How’s that feature going?” “On track.” “When will it ship?” “Soon.”

Neither side has numbers. Both sides leave uncertain whether they’re aligned. This conversation repeats weekly, same script, same ambiguity, same lack of shared data.

Engineering has dashboards full of velocity charts, burndown graphs, and cycle time metrics. Product has roadmap views, prioritization scores, and stakeholder updates. These dashboards serve their respective teams but do nothing to create shared understanding between them. The cost of this fragmentation is $450 billion annually lost to context switching globally, much of it from people toggling between systems trying to piece together a complete picture.

A product-engineering dashboard is different from a PM dashboard or an engineering dashboard. It shows the metrics that matter for alignment: whether product priorities are being executed, whether engineering capacity matches product ambition, and whether the work being done connects to the outcomes being sought.

This guide covers how to build a dashboard that both teams trust and actually use.

Why separate dashboards create problems

Product and engineering teams typically maintain separate views of their work. This separation creates alignment gaps.

Different tools, different views

Product roadmaps live in PM tools like Productboard, Asana, or Monday. Engineering work lives in Jira. These tools have their own dashboards optimized for their own use cases, and even Jira’s efficiency features don’t address the cross-tool visibility problem.

The PM dashboard shows roadmap items, prioritization rationale, and stakeholder commitments. It does not show sprint progress, story completion rates, or technical blockers. The engineering dashboard shows velocity, burndown, and cycle time. It does not show strategic priorities, customer impact, or roadmap alignment.

Neither dashboard answers the question both teams need answered: are we building the right things at the right pace?

Metrics without context

Engineering metrics without product context can be misleading. A team with perfect velocity might be building the wrong things. High cycle time might be acceptable if the work is high complexity. Sprint completion rates do not indicate whether the completed work moved the product forward.

Similarly, product metrics without engineering reality can be unrealistic. A roadmap showing four major features this quarter means nothing if engineering capacity supports two. Prioritization scores are theoretical until engineering estimates ground them.

Manual reconciliation

Without a shared dashboard, someone has to manually reconcile the views. Usually that falls to the PM, who checks Jira progress and updates the roadmap, or creates summary reports that combine data from multiple sources.

This manual work is time-consuming and error-prone. The reconciliation happens periodically (weekly, monthly), which means the shared view is always somewhat stale. And the work of creating it takes time away from more valuable activities.

What a product-engineering dashboard should show

A good shared dashboard answers the questions both teams care about without drowning either in irrelevant detail.

Roadmap-to-execution status

The most important view: what roadmap items are in progress, and what is their actual status?

For each current roadmap item, show:

• Roadmap priority and timeline: What was promised to stakeholders? This grounds the discussion in commitments.
• Linked engineering work: Which epics and stories implement this item? The connection should be explicit and visible.
• Engineering progress: What percentage of the linked work is complete? Is it on track based on current velocity?
• Risk indicators: Are there blockers? Has scope changed? Is the original timeline still achievable?

This view lets anyone see whether roadmap commitments are being met without digging into individual tickets or asking for status updates.

Capacity and commitment balance

Engineering has finite capacity. Product has potentially infinite ideas. The dashboard should show whether these are in balance.

• Current sprint commitment: How much work is in the current sprint relative to typical velocity?
• Backlog depth: How many sprints of work are groomed and ready? A shallow backlog (less than one to two sprints ready) indicates a grooming problem. A deep backlog (more than four to six sprints) may indicate prioritization ambiguity.
• Resource allocation by roadmap item: What percentage of engineering capacity is going to each major initiative? This reveals whether actual work matches stated priorities.
• Unplanned work ratio: What percentage of sprint capacity goes to bugs, tech debt, or other unplanned work? High ratios reduce available capacity for roadmap items.

Delivery performance over time

Trends matter more than snapshots. The dashboard should show how delivery performance changes over time.

• Velocity trend: Is the team delivering more or less than in previous periods? Significant changes warrant investigation.
• Cycle time trend: How long does it take from work starting to work shipping? Increasing cycle time often indicates process problems or increasing complexity.
• Prediction accuracy: How often do items ship when originally planned? Poor prediction accuracy undermines stakeholder trust and planning reliability.
• Scope change frequency: How often do requirements change after work begins? Frequent scope changes indicate either premature commitment or poor requirements definition.

Quality and technical health

Shipping fast means nothing if quality suffers. Include quality indicators that engineering cares about.

• Bug rate: How many bugs are filed against recent releases? Rising bug rates indicate quality problems.
• Tech debt ratio: What percentage of capacity goes to paying down technical debt? Too little and debt accumulates. Too much and features do not ship.
• Escaped defects: How many bugs are found by customers versus caught in QA? Escaped defects indicate testing gaps.
• Deployment frequency and success rate: How often does the team deploy, and how often do deployments succeed? These are proxies for engineering health and confidence.

Building the product-engineering dashboard

Implementation depends on your tools and technical resources. Here are the common approaches.

Using your PM tool

If your PM tool supports robust dashboards (Asana, Monday, Notion with good integrations), you may be able to build the shared dashboard there.

Advantages: PM is already comfortable with the tool. Easy to link roadmap items to dashboard views.

Challenges: Getting Jira data into the PM tool requires integration. Native integrations often provide limited data. Engineering may not adopt a tool they do not already use.

Using Jira

Jira has dashboard capabilities that can show both engineering metrics and, with some work, product priorities.

Advantages: Engineering is already there. Rich engineering metrics are available natively.

Challenges: PMs may find Jira dashboards clunky. Roadmap context is not native to Jira. Building product-relevant views requires JQL expertise.

Using dashboarding tools

Tools like Looker, Tableau, or even Google Data Studio can pull data from multiple sources and create unified views.

Advantages: Complete flexibility in what you display. Can combine data from any source. Professional visualization capabilities.

Challenges: Requires data engineering to set up and maintain. Additional tool in the stack. Someone has to build and maintain the dashboards.

Use software integrations

Some integration platforms include dashboard capabilities that leverage the connections they maintain between your tools.

Advantages: Dashboard is built on real-time synced data. Changes in either system are immediately reflected.

Challenges: Dashboard capabilities vary by platform. May be less flexible than dedicated BI tools.

Regardless of where your dashboard lives, you need data flowing from both product and engineering tools.

For basic visibility, you need:

• Roadmap items with their priority and timeline
• Jira epics and stories linked to those roadmap items
• Current status of engineering work
• Velocity and capacity data from Jira

Two-way sync platforms sync data between PM tools and Jira at the field level. This means your roadmap priority appears on the linked Jira epic, and Jira progress appears on your roadmap item. When the data is synchronized, building a dashboard on either side reflects the complete picture.

Metrics that matter for product-engineering alignment

Not all metrics deserve dashboard real estate. Focus on metrics that drive alignment and action.

Good metrics for shared dashboards

• Roadmap item completion rate: What percentage of planned roadmap items shipped as intended? This is the ultimate measure of alignment between product ambition and engineering delivery.
• Time from prioritization to delivery: How long from when an item is prioritized to when it ships? This reveals the whole-system efficiency, not just engineering speed.
• Priority alignment: What percentage of engineering capacity goes to the top-priority roadmap items? If priority one items get less capacity than priority three items, something is wrong.
• Stakeholder satisfaction with predictability: Do stakeholders trust the dates product commits to? This is subjective but critical. Survey or ask directly.

Metrics to avoid on shared dashboards

• Story points delivered: Story points are an internal engineering measure. They do not mean anything to product or stakeholders. Show features delivered, not abstract points.
• Individual contributor metrics: Tracking individual developer performance creates wrong incentives and does not serve alignment goals.
• Lagging vanity metrics: Page views, user counts, and revenue are important but do not belong on a product-engineering alignment dashboard. They measure outcomes, not the process that creates outcomes.
• Metrics nobody acts on: If a metric is just informational and never triggers action, it is clutter. Every metric should have a response when it moves outside acceptable range.

Making the dashboard useful

A dashboard that nobody looks at is worthless. Driving adoption requires intentional effort.

Single source of truth

The dashboard must be the authoritative source for alignment questions. If people still ask for status updates verbally or via email, the dashboard is not doing its job.

Make the dashboard the first place anyone goes for status. Reference it in meetings. Link to it in status communications. When someone asks a question the dashboard answers, direct them to the dashboard.

Accessible to both teams

The dashboard should be equally accessible to product and engineering. If it lives in a tool one team does not use, that team will not look at it.

Consider where to place the dashboard for maximum visibility. Slack or Teams integration to show key metrics. TV display in common area. Homepage of commonly-used tool.

Regular review cadence

Build dashboard review into existing meetings. Start sprint planning by looking at the dashboard. Begin stakeholder updates with dashboard screenshots. Make the dashboard a natural part of how work is discussed.

Weekly review at minimum. Daily glances are better. The more frequently people look at the dashboard, the more likely they are to notice changes and act on them.

Clear ownership

Someone owns the dashboard. They are responsible for keeping it accurate, adding new metrics when needed, and removing metrics that are not useful.

Ownership does not mean doing all the work. It means ensuring the dashboard serves its purpose and evolving it as needs change.

Action-oriented design

Each section of the dashboard should suggest action when metrics are concerning.

Red indicators should have clear next steps. If velocity is trending down, the next action might be “investigate in retrospective.” If a roadmap item is at risk, the next action might be “PM and engineering lead sync to discuss scope.”

A dashboard that shows problems but does not guide action creates anxiety without resolution.

Improving your dashboard over time

Your first dashboard will not be perfect. Expect to iterate.

Start simple

Launch with a minimal dashboard: roadmap items, their engineering status, and one or two key metrics. Add complexity only when the simple version is working and people want more.

Simple dashboards get used. Complex dashboards get ignored while people ask for simpler views.

Add metrics based on pain

When alignment problems emerge, ask whether a metric would have caught them earlier. If the problem was a priority mismatch, add a priority alignment view. If the problem was scope creep, add a scope change tracker.

Metrics should address real problems, not theoretical ones. Let your experience guide what to measure.

Remove what isn’t used

If nobody has looked at a section of the dashboard in a month, remove it. Dashboard real estate is valuable. Metrics that do not earn attention do not deserve space.

Review dashboard usage periodically. Ask both teams what they find valuable and what they ignore.

Calibrate thresholds

Alert thresholds need tuning. Too sensitive and everything is always red, causing alert fatigue. Too loose and problems are not caught until they are crises.

Watch how people respond to indicators. If red indicators are routinely ignored, the threshold is wrong. Adjust until indicators accurately reflect when attention is needed.

The goal of a product-engineering dashboard

A product-engineering dashboard is not about surveillance or accountability theater. It is about creating shared reality. When both teams see the same information, they can have informed conversations about tradeoffs, risks, and priorities.

The best outcome is that the dashboard makes status meetings unnecessary. Everyone already knows the status. Meetings focus on problem-solving, not information gathering.

When product and engineering share a view of their work, alignment becomes easier. Disagreements surface early when they are cheap to resolve. Trust builds because both sides see the same truth.

If you are ready to build a unified view of your product and engineering work, see how Unito helps product and engineering teams stay aligned.

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