Developer Productivity: The Secret Sauce to Building Great Dev Teams

Software development costs an estimated 63% of a project’s budget, making developers and their work performances a centre point of executive discussions. Initially, organizations resorted to a more mechanical approach of locating the work done by their devs- through average lines of code written or bugs fixed per day. However, the metrics don't convey the full picture of software development lifecycle. 

Teams with high productivity and process efficiency have taken a more provocative approach by focusing on the ‘how’ of development- the developer behavior, collaboration patterns, code reviews, and team dynamics. Identifying and eliminating bottlenecks helps the team work on their core competencies and be more productive.

What is Developer Productivity?

It is difficult to visualize developer productivity in isolation. In the most broader terms, it is the amount of quality and reliable software developed efficiently by an engineering team. Most teams track it via assessing different metrics that indicate how well a team of developers performs against predetermined goals. These include time-to-completion, bug rate, developer experience, code coverage, and team collaboration.

Development processes can be evaluated based on those outcomes; however, they do not help manage developer productivity. Forsgren et. al’s SPACE framework, or Objectives and Key Results (OKRs) provides a practical and multidimensional viewpoint into developer productivity and proposes a new approach to defining, measuring and predicting it. The focus of all these approaches is developing and releasing software quickly while reducing the time to value and increasing return on investment.

The Metrics of High Developer Productivity

Global Code Time Report shows that only 10% of developers code for 2 hours per day, while 40% of them may spend around an hour per day coding. It is a clear indicator that managers cannot accurately calculate developer productivity based on the lines of code written in a day.

DevProd shouldn't be limited to outdated performance metrics. Instead, it is a holistic approach that factors work quality, customer feedback, collaboration, and flexibility. The aim is to identify and eliminate bottlenecks in the development process to boost developer performance. A Microsoft survey results show that developers report 49.4% output on good days. They can make significant progress on their coding tasks when working uninterrupted. A holistic approach would be to minimize interruptions for the engineering teams.

Additionally, a single metric cannot ensure the reliability and quality of the output. Therefore, it is essential to observe multiple indicators and focus on outcomes when assessing the productivity of engineering teams. The below productivity metrics will help you build an effective DevOps Maturity Model and avoid dev burnouts:

• Deployment frequency- The frequency of successful product releases made by an organization. Deployment frequency is the simplest DORA metrics that helps deliver high customer value while reducing Time-to-Market.
• Lead time- The amount of time it takes from receiving a project request until the time it is released. It ensures planning accuracy through the project’s development, testing, and release phases.
• Cycle time- Cycle time is the duration of each project stage. Gauging how long your team takes to go from the request to deployment helps avoid missed goals and limits dev burnouts. 
• Team well-being- Maintaining a work distribution equilibrium across engineering teams 
• Velocity- An agile metric for project planning, Velocity or Sprint helps deliver the desired quantity of work within the specified timeline.
• Change failure rate- A DORA indicator for customer satisfaction that measures how often a change causes an unexpected problem. It focuses on reducing the number of incidents in a deployment.
• Time to restore service- Aimed at decreasing the number of outages, this DORA metric measures system restoration time after each failure.
• Developer satisfaction- Surveying developers about their experience with products and services helps improve developer engagement by making informed development decisions.
  
  

How Teams With High Productivity Look Like? 

Collecting measurements of current processes, performances, and outcomes is essential to growing a business. However, it is equally vital for engineering teams to understand their performance. Research shows 89.2% of developers say productivity can be measured using good metrics, and 92.1% wish to know how productive they have been.

Great developer teams bring in cognitive psychology and behavioral economics to maintain high productivity. Google’s Tech Lead Manager of Engineer Productivity Research, Ciera Jaspen, says measuring metrics is expensive yet important. They have designed the Goals/Signals/Metrics (GSM) framework to assess desirable attributes when calculating the productivity of engineering teams. Common attributes found across highly productive teams are: 

• Low cycle time: Cycle time is the time taken from the initiation of a task to its completion. Efficient teams maintain low cycle times by making decisions quickly and delivering tasks on time. 
• Distributed workload: A team consists of people with different skills and capabilities. Teams distribute workload to ensure the right job is assigned to the right person. As a result, all tasks are efficiently completed while preventing dev burnouts.
• Lower change failure rate: The change failure rate is the percentage of changes that do not produce the desired results. Elite engineering teams use analytics and predictive modeling techniques to identify potential points of failure proactively.
• Faster lead time: Lead time is the total time taken to complete a task from initiation until final delivery. Implementing cycle times helps teams ensure tasks are completed efficiently and on time.
• Clear sprint planning: Sprint planning is the practice of setting up tasks for a specific period. Elite teams use the agile project management approach to break down tasks and assign them to the right people. It ensures that each task has a clearly defined timeline and that resources are allocated appropriately.
• Async tasks- 41.1% of developers say “waiting for other people to do stuff” impacts their productivity on a typical work day. Asynchronous development among engineering teams eliminates the need for team members to be in constant communication with each other during the entire development process. Instead, the approach allows developers to concentrate on their own tasks and then coordinate during integration.
• Deep work- Elite teams facilitate deep work by allowing developers to focus on coding for uninterrupted hours. The team distributes and structures creative tasks in specific blocks of time. Staying free from distractions, such as email notifications, unplanned meetings, and phone calls, allows developers to get into a state of flow and achieve meaningful progress in less time.
• Robust generative culture- High-performing teams create and nurture an environment of finding innovative solutions to complex problems. They prioritize exploring unconventional ways of tackling tasks. All voices are heard and respected by creating a safe space for experimentation.
• Low burnout- The best engineering teams focus on preventing burnout. They recognize the warning signs early on and take proactive steps to reduce developer stress levels. Setting realistic goals and prioritizing tasks makes their workload manageable while reducing overwhelming feelings of exhaustion, anxiety, and demotivation.

Taking Developer Productivity to the Next Level

Building a highly productive engineering team involves the right mix of skills, tasks, culture, and timelines. Creating a collaborative environment that values stress-free deadlines, encourages innovation, and rewards performance helps improve developer productivity.

An engineering analytics platform can provide visibility into the engineering metrics, workflow milestones, to evaluate and assess project progress. It can also be used to boost team productivity through insights on bottlenecks and efficiency drivers.