The ROI of Better Software Productivity Measurement (Real Numbers From Real Companies)

“We can’t measure software productivity.” “I don’t believe in Scrum; productivity always decreases.” I’ve heard variations of these statements from C-level executives repeatedly. It’s a common misconception, yet it’s deeply problematic. Measuring software project productivity isn’t just possible; it’s the only way to make the intangible visible. And without this visibility, no meaningful improvement can be made, nor can its impact be genuinely claimed.

The truth is, when you measure the right things, you unlock incredible potential. Let me share some real numbers from companies I’ve coached, demonstrating the tangible return on investment from a smarter approach to software productivity measurement:

Tangible Results from Smart Measurement

Company A (Early Startup): Accelerated Feature Delivery

• Before: An 8-week mean feature delivery time.
• After: A remarkable 2-week mean delivery time – a 75% improvement!
• Key Change: They complemented traditional velocity using story points with a focus on cycle time measurement. This shift allowed them to see and optimise the end-to-end flow of work, not just the output of a single sprint.

Company B (Series A): Drastically Reduced Defects

• Before: Their releases had a Percent Defect Free metric of just 40%.
• After: The PDF metric reached highs of 92% (an improvement of 52 percentual points).
• Key Change: They strategically protected capacity for defect fixing and, crucially, added the lead time for fixes to their core metrics. This created accountability and visibility around quality, making it a first-class citizen in their development process.

Company C (Scale-up): Significant Reduction in Rework

• Before: A disheartening 25% of developer time was spent on rework – essentially redoing work that wasn’t right the first time.
• After: This wasteful rework time dropped to a lean 8% – a 68% reduction!
• Key Change: They implemented comprehensive flow metrics across their teams, providing clear visibility into where work was getting stuck, handed off inefficiently, or returned for corrections.

The common thread across these successes? They stopped measuring mere activity and started measuring meaningful outcomes. They understood that project-level metrics alone tell only part of the story, so they complemented them with other metrics that provided visibility into the entire system. This approach is at the heart of how I help organisations achieve continuous improvement and sustainable productivity increases.

Why Most Measurement Efforts Fail (And How to Avoid It)

There’s ample empirical evidence that many measurement efforts in software development unfortunately fail. By “failed,” the literature often means that the measurement effort changes frequently, or that historical data quickly becomes irrelevant. Among the primary causes of this are:

• Changing Business Needs: Businesses are dynamic, and their needs evolve. Consequently, the information required from engineering teams must also adapt. Rigid measurement systems struggle to keep pace.
• Measuring for Measuring’s Sake: Simply collecting data without a clear connection to strategic decisions is a recipe for wasted effort and eventual abandonment.
• Gaming the Metrics: When people optimise for the metric itself rather than the desired outcome, the data becomes corrupted and misleading. This happens when metrics are used for individual/team performance reviews rather than systemic improvement.
• Analysis Paralysis: Too many metrics, not enough action. Overwhelm from a deluge of data without clear insights can be just as detrimental as having no data at all.

Keeping It Simple: The 4-Metric Rule for Project Control

Assuming that measurement goals will change and evolve with the business, the key for me is to keep it simple. The goal is to make measuring as cheap and unobtrusive as possible, ensuring it consistently delivers value to the business by enabling smarter decisions.

I often advocate for a “4-metric rule” to initially manage any software project effectively:

1. Scope: What exactly are we building? (Clear definition of what “done” looks like, and the unit with which we will be measuring it).
2. Time: When, or for how long, are we building this scope? (Delivery timelines and progress.)
3. Cost: How much will we need to invest in building this scope during the period? (Resource allocation and expenditure.)
4. Quality: Is the product fit for purpose? (Meeting requirements, low defect rate, usability.)

If we can consistently measure and manage these four fundamental elements, our projects can become significantly more predictable and “under control.” This visibility empowers us to make informed decisions about the project’s trajectory and even design various scenarios about the interaction between these crucial variables.

Making the System Visible: Adding Context-Specific Metrics

Once you have the project basics covered, you can then add the minimum set of additional metrics to visualise your specific organisational needs:

• For CTOs: Focus on delivery predictability (can we hit our deadlines consistently?), quality trends (are we getting better or worse at preventing defects?), and technical debt impact (how is past technical debt affecting current delivery speed and quality?).
• For Scrum Masters: Track flow efficiency (how much time is spent actively working vs. waiting?), establish and monitor Work-in-Progress (WIP) limits (to prevent bottlenecks and maintain focus), and consider introducing team health indicators (like psychological safety and knowledge sharing).

Parting Thoughts

Measuring in software is undoubtedly hard, and measuring productivity is particularly challenging. In the age of increasingly complex tools and distributed teams, the problem has, in some ways, worsened. Yet, we need some indication of what and how we are building software. In mid- to large-sized organisations, we need measures that are stable enough to allow for meaningful comparisons across different products, teams, or periods.

The companies that succeed in measuring software productivity effectively don’t just deliver faster – they deliver more predictably, with consistently higher quality, and with happier, more engaged teams. It’s about empowering your teams with the right information to continuously improve, leading to sustainable productivity increases that genuinely impact the bottom line.

What’s your biggest challenge with measuring software productivity? Are you tracking activities or outcomes?