Beyond Velocity: Why Your Project Tracking Dashboard Misleads You

Your project tracking dashboard might hide the real story. It shows speed, not true progress. While you focus on sprint numbers and closed tickets, the most important work on your team goes unseen.

At Exceeds AI, we study data from tools like GitHub and Jira across many engineering teams. We found a big issue. Key efforts like fixing deep code issues, strong code reviews, and guiding new developers don’t show up on typical project tracking dashboards. This means companies often overlook their best workers and reward those who just close tickets fast.

This isn’t a small problem. It costs companies a lot by misusing talent and missing chances to improve.

Why Your Dashboard Can’t Keep Up with Today’s Work

Modern work has changed, but many dashboards haven’t. New ways like microservices and remote teams make work complex. Yet, old metrics can’t track this new reality, as noted in this study.

Think about today’s projects. One feature may need talks across teams, changes in many places, updates to guides, and lots of reviews. But your dashboard just counts a few tickets. An engineer who helps a new teammate solve a tough problem gets no extra credit compared to someone doing easy tasks.

These tools only look at past results, like tickets done. They miss future benefits, such as less tech debt or better team skills. Research from DX shows that focusing only on speed can lead to lots of work with little real value.

What Your Dashboard Misses: Key Work Stays Hidden

Much of the best work happens outside tickets. Fixing complex code to avoid future problems doesn’t boost speed numbers. Deep code reviews that find bugs or teach skills aren’t shown in charts. An engineer who designs a plan saving months looks idle in old metrics.

Data from Multitudes shows key work often missed:

• Planning designs: Stops costly redo work.

• Fixing crashes: Keeps systems running.

• Writing guides: Speeds up future tasks.

• Team teamwork: Breaks down barriers.

• Guiding others: Builds team strength.

Companies like Netflix saw a 40% rise in team happiness when they looked at code review quality, not just tickets. They also promoted high-impact workers faster by spotting hidden efforts.

This affects team culture. Engineers learn that only countable work gets praise. So, they split tasks into tiny pieces or skip hard fixes to look productive.

Shift to Understanding People, Not Just Projects

The next step isn’t a new dashboard. It’s about focusing on people, not just tasks. Project data shows what’s done. People data shows how it’s done and who helps the team grow.

AI can help here. It looks at code changes, discussions, and reports to see the real value of someone’s work. Studies show AI tools can measure things like clear feedback or teamwork, which were hard to track before.

For example, AI can spot who asks smart questions in reviews to stop bugs. It can also check guides to find those who explain things well. These details help make fair reviews possible.

Real Impact: Lessons from 100+ Engineering Teams

Our research on over 100 teams shows hidden patterns. Engineers who write clear guides or give detailed feedback prevent big problems three times more often. Yet, old dashboards miss this.

One client found their "worst" engineer by ticket count was their most vital. This person spent 60% of their time reviewing code and teaching. Their feedback stopped issues worth $2 million, but old metrics marked them as low-performing.

Another client learned their fastest workers added tech debt. By checking code quality, they saw rushing caused weeks of extra fixes per release.

This approach saves time too. One client cut 90% of review prep time and saved over $100,000 yearly by using automated data tools.

An engineering leader said, "Exceeds gave us clear insights on team work. We now see who truly helps, not just who closes tickets."

Learn how Exceeds AI reveals your team's real impact. Request a Demo.

How This Changes More Than Just Reviews

Understanding people’s work helps beyond reviews. It improves big decisions with real data.

You can allocate resources smarter. Instead of hiring more coders, you might train on writing guides if it cuts onboarding by 40%. Promote based on teamwork skills, not just ticket counts.

It helps keep talent too. Data shows engineers stay 60% longer if their hidden work is valued. Recognizing all efforts stops top workers from leaving.

Keep using tools like Jira for daily tasks. Platforms like Exceeds AI add deeper insights for reviews and team planning.

Combine your current tools with AI insights. Use one for tasks, the other for growing your people.

What’s Next for Engineering Leaders: A Unified View

In 3-5 years, top teams will use systems blending project data with AI people insights. These will show team health and skill gaps instantly.

Imagine spotting burnout risks early or having solid proof for promotions. Picture feedback happening as work unfolds, not just yearly.

Some leaders already do this. They use AI for coaching tips and plan teams based on data.

Teams adopting this will stand out. They’ll keep talent, build stronger groups, and create a culture valuing all kinds of impact.

Focus on people, not just tasks. The future of leading teams is here with deeper insight.

See a new way to measure team impact—Request your Exceeds AI demo today.

Frequently Asked Questions

How Do People Insights Differ from Project Tools?

Project tools like Jira track tasks and timelines. People insights look at how work happens and who adds real value. Project tools count tickets. People tools use AI to review code and teamwork for a fuller picture.

What Work Do Dashboards Often Miss?

Dashboards skip key efforts like fixing deep code issues, giving helpful reviews, planning designs, handling crashes, writing guides, teamwork across groups, and teaching new engineers. These don’t show in ticket counts but matter a lot.

How Does AI Check Quality of Work?

AI reviews data like code talks and guides to find value. It spots smart feedback in reviews, clear writers, or teamwork patterns. This helps measure skills that were hard to see before.

Can These Tools Work with Current Systems?

Yes, people insight tools connect with systems like GitHub or Jira. They add value without changing your workflow. You keep using what works, with extra data on top.

What Benefits Come from People Insights?

Teams gain fairer reviews, better talent retention, smarter hiring plans, less time on review prep, clear promotion paths, and stronger teamwork. It values all contributions, not just visible ones.

Sources

1. How to Measure Engineering Team Performance - Multitudes

2. Engineering KPIs: Aligning Team Performance Metrics - Teamhood

3. Measuring Engineering Team Performance - Steady Space

4. The engineering metrics used by top dev teams - DX

5. Software Engineering Dashboard Essentials for Better Team Efficiency