Engineering teams — specifically software engineers — are powerful assets of any technology company. After all, the products and tools they produce directly impact revenue generation, customer satisfaction, and profitability.

In a slower economy, maximizing the efficiency of your engineering teams can eliminate unnecessary labor hours, reducing budgetary bloat. This becomes even more important when you consider that engineering and development teams typically comprise some of the most highly paid employees in an organization. Every labor hour saved here can translate to exponential savings.

Unfortunately, engineering labor costs are notoriously difficult to estimate — meaning that it’s equally challenging to measure whether or not you’re actually being efficient. Unexpected defects and support issues, architectural and infrastructure flaws, library issues, communication overhead, and even the skill level of various team members can add untold hours to work estimates. Adding to the issue, many organizations rely on development teams to provide estimates themselves. Team members hoping to please executives will often agree to workloads and timelines that are overly aggressive or unrealistic.

This tension between customer-facing teams, executives, and software developers will be familiar to almost anyone who has worked in technology. Engineers are extremely intelligent, capable, and creative individuals who take pride in their work. However, at times their laser-focus on the products they create can undermine or clash with business goals. Developers who seek to meet impossibly high standards of design often fall victim to letting the perfect be the enemy of the good.

When economic futures are uncertain, it’s all the more important that all team members are aligned and working together to meet shared goals. Internal confusion or disagreement over deadlines and priorities wastes precious time, negatively impacts customer satisfaction, and generally lowers your ability to do more with less.

Being able to precisely forecast project time can help engineers and management come to a common understanding of what is realistic and achievable. Tracking labor and other metrics also allows you to set quantifiable goals and measure your team’s ability to meet them. Here are some of the most important numbers to track.


Estimate to Actual Ratio

This metric assesses your ability to create accurate work-hour estimates. Simply put, it’s the difference between the time you estimated for a certain project and how long it actually took. 

Not only does this measurement shed light on the accuracy of your estimates (and where there may be room for improvement), but it can also be a crucial indicator of where to invest in the future. Estimated engineering hours and time to market should play a huge role in your decision-making as you weigh the potential Return on Investment (ROI) of various product directions.


Velocity and Rate of Change

Velocity — also known as throughput rate — measures the speed of engineering’s output, while the rate of change tracks the increase and decrease of that metric over time. 

Defining what is “good” in regard to these various metrics depends on your organization and where you are now, but the overall goal is continuous improvement. Clear and regular measurement of performance keeps velocity at the forefront of everyone’s mind and helps you see how you are doing over time.


Build-to-production Defect Ratio

It’s impossible to write code without generating some bugs. That’s why Quality Assurance (QA) teams exist. While tracking the raw number of defects can help you assess code quality, the additional context of where in the workflow bugs tend to occur — and where they’re resolved — is crucial. Defects are much cheaper to fix and less likely to frustrate customers when they’re identified upstream. 

Tracking a ratio of where in the build-release cycle defects are found can help your quality assurance team (and engineers) focus their efforts on solving bugs before product releases go to market.


Code Coverage

Code coverage metrics tell you how many lines of code are executed during automated testing and are typically measured as a percentage of executed versus total lines of code. 

More thorough code coverage can help you automate bug detection and ease the burden on your QA team — and measuring coverage can help you understand how successful you are at this. It’s important not to rely too heavily on automated testing, however, as high coverage does not always correlate to fewer bugs and/or less time spent testing and resolving defects.


Labor Hours by Task Type

The ability to break out engineering work hours by task type can help you analyze how much time team members are spending on value-added work. For example, comparing the amount of labor spent on support work versus work outlined on your roadmap can provide insight into product quality, performance, and where bottlenecks exist in your workflow, among other things. 


 

We’ve found that richly featured time tracking software can significantly ease the burden of tracking and reporting on labor hours so you can come up with granular metrics like these.

Obtaining these KPIs requires the cooperation of the engineering team. You will need to implement project time tracking in order to create accurate measurements and get buy-in from each employee. At Journyx, we’ve built our time tracking software with ease of use in mind. Our tools allow you to enable precision metric tracking without adding to the administrative burden of your team. You can track labor, billable hours, expenses, and resource capacity by project, task type, team, and employee.

Ideally, time tracking will help your team focus on improvements to velocity, efficiency, and work quality so you can maximize the value they can deliver to the company overall. And that may prove invaluable as you work to streamline business processes and stretch your budget while you prepare for markets to bounce back.