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Agile methodology, a process that breaks larger projects down into smaller phases and focuses on constant improvement, is one of the more collaborative methods of project management. As such, measuring your team’s productivity efficiently is essential. Being able to measure how productive individuals are in each sprint of the project is helpful for employees, managers and the process of effectively completing the overall project.
These metrics for measuring your agile team’s productivity help employees remain focused, offer a clear understanding of expectations and allow your workers to complete jobs efficiently without undue stress.
At its core, agile methodology is an approach to project management that breaks projects down into smaller phases (often referred to as “sprints”) and is focused on continuous improvement.
The four main pillars of the agile methodology are:
In terms of methodologies, there are a variety of different agile framework variations. Some of the most common ones include:
There are many benefits to utilizing agile methodology, from results that yield better customer satisfaction to continuous improvement and greater collaboration among teams. By using agile — and, in turn, creating solid workflow organization — productivity is likely to increase.
This ratio compares the percentage of tasks delivered as per specific guidelines. While customer-centricity emphasizes building the right product at the right time for the right market, knowing how much your teams were able to accomplish successfully against the list of planned tasks gets you accurate insights into both your current resources and their capabilities. Moreover, it gives you an overview of the complexities of the project, casting a shadow over tasks in terms of time, scope and budgeting constraints, thus helping you identify the ones that overran original estimates.
An additional bonus to this ratio is that you can instantly know if your talent management processes need closer inspection. You can then update your skills inventory after identifying if your staff is using irrelevant bodies of knowledge or working with outdated skills. Once you acquire the appropriate hands before a project commences, you’ll avoid overworking existing staff who’re inadequately prepared for the onslaught. What’s more, you’ll take the right skills off the bench and deploy them directly onto the right projects, thereby ensuring that your teams are optimally utilized.
To find the planned-to-done ratio, divide the number of tasks that were planned to be accomplished at the start of a sprint by what was actually accomplished at the end of the sprint.
If your goal is to find and fix bugs before your customers do in the release environment, the escaped defects curve lets you contain 90 percent of the bugs preproduction.
The first step to measuring defects is to consolidate all faults identified. Once you have an accurate count of the bugs, you’ll categorize the extent of risk. For this to happen, your team members should follow protocol to report problem areas as early as possible so that they can be escalated via appropriate channels. Your teams will then spend less time finding and fixing errors when production’s in full swing. They can minimize the chances of errors changing the longevity of the finished product and how it would look or function.
A low escaped defects ratio lets you establish a direct link between their efficiency and customer satisfaction. For example, if nine out of 10 tasks are delivered on time that fulfills client expectations, your success rate is 90 percent.
User stories is the step that documents how many points were gathered during the requirements analysis stage. This is where client briefs are represented digitally to begin task prioritization and sequencing. Teams get clarification on their work packages. The measure itemizes the number of stories committed to in the sprint planning and assesses how many of them are marked as completed.
Your staff can then divide their focus on different aspects of the same user story and work on it in parallel rather than in sequential blocks. For example, if you’re building a flight ticketing system, the development team can create user stories capturing bookings, cancellations, refunds, date changes and points-based mileage. Each member can estimate their efforts by profiling the project on those aspects that are easy to recreate by simply rewriting code where applicable. This move ensures a closer match between the user stories that were committed versus what gets done.
Acceleration is the simplest metric, using data relevance to monitor project health continuously. Measuring team velocity via velocity charts lets you know how different-sized teams are faring in individual sprints.
The first step to accelerating your team’s velocity is to create points that estimate the work in each iteration. Measuring team performances is akin to comparing snowflakes, such as no two are alike because points are conceived based on their line of work. New velocities can be estimated from the initial velocities. For example, a team of developers would measure the time taken to use a new skill while the operations team would factor in the time taken to learn the skill in the form of appropriate training programs.
To calculate the velocity, estimates of all features have to be added up, along with user stories and product backlog items which can be drawn back to the requirements gathered.
Acceleration Formula: (new velocity-initial velocity)/initial velocity
Given the ease of the calculation, you can plan future iterations by adjusting velocities by team size. Lastly, you can monetize performances to estimate cost savings through process improvement. For example, if you’re spending $50,000 per iteration and your acceleration is 5 percent, you save $2,500 per iteration.
As velocity increases, it’s not uncommon for quality to suffer; considering escaped defects (outlined above) while accelerating team velocity is important to mitigating quality loss.
The golden rule of agility is to have your teams work on tasks that fit into iterative sprints. As such, with each iteration lasting no longer than two weeks, your teams can downsize their work packages to fit into this window, regardless of how large a component being worked on is. This gives them optimal work to perform without cramming in tasks that are intrinsically complex and time-consuming.
Having shorter cycles within individual sprints ensures that everyone on the team is aware of short and long-term targets. Subsequently, there’s no lapse in productivity down the chain. With deadlines approaching sooner, a shorter cycle time lets your team get more work done. This is because complacency settles in with extended timelines. Teams forget to prioritize pending tasks and end up underestimating their importance and value. As a result, the wrong things are measured without an overview of the project’s priority log.
Aakash Gupta contributed to this article.