For software developers, the agile methodology is not a new concept – it’s been around for decades in one form or another. In 2001, a group of individuals wrote The Agile Manifesto, outlining 12 guiding principles for the agile methodology and cementing the practice in the industry. The agile team has had a huge impact on the software development industry, increasing innovation, productivity, and quality, while decreasing time-to-market for new products.
It’s done so much for the IT industry that agile methods are now spreading to other departments – marketing, sales, customer service – and new industries. There are several key features of working within the agile method. Teams take an iterative approach to work, breaking important tasks down into smaller milestones that can be completed quickly, and using the experience and feedback from these smaller tasks to inform how they approach the next ones. Small, multidisciplinary teams are key, with developers, designers, and product owners working closely together on a project. Organizations that adopt this style place trust in teams and individuals to perform their roles, minimizing the kind of meddling by upper management that slows down innovation and productivity.
Agile + Data Analytics = Success
One essential ingredient to the success of the agile methodology is analytics and business intelligence (ABI). Product owners, team leads, and/or scrum masters need to track, measure, and analyze the results of each incremental product milestone, or sprint. They need to be able to see exactly where each team member is in the completion of their individual tasks. And they need to be able to look retroactively at past sprints to see where things went well and where there’s room for improvement.
Since the benefits of an agile methodology include shorter project cycles and higher productivity, the less time team leads spend analyzing data, the better. Embedded analytics – the integration of analytical solutions and data visualization capabilities into a software application’s user interface to improve data comprehension and usability – can be incredibly impactful here.
Embedding analytics and data visualization in existing internal, day-to-day applications also allows for a seamless user experience and can lead to effective workflow management, improved team performance, optimized prioritization, and faster completion of tasks without compromising quality.
Effective Workflow Management
Embedded analytics makes work more efficient by enabling team leads to track progress using key performance indicators (KPIs) such as team roles, planned versus utilized work hours, and overall task completion rate. A visual analytics dashboard using these metrics helps key decision-makers monitor task statuses and project completion times at a glance. Team leads can identify slow-moving projects and help their teams take the necessary steps to complete the project within the timeline. This improves speed to market of a product, which increases the organization’s potential revenue streams.
Improved Team Effectiveness and Performance
With the help of embedded analytics, team leads and individual team members can track their work performance. For example, a sprint management dashboard lets you track story points, project status, sprint velocity, and scope changes, helping you manage your sprint efficiently. Team leads can recognize individuals who complete high-priority tasks faster as well as those who took more time in previous sprints, assigning tasks considering team members’ strengths and optimizing the team’s performance. Additionally, information about bugs – or defects – such as resolution times can inform the next sprint. This is even more important in remote work, as teams aren’t able to meet face to face to quickly address and resolve issues, which has historically been a key component to agile methodologies.
Better Prioritization
Embedded analytics helps team leads view the importance of tasks completed using KPIs such as tasks by priority, incomplete tasks by project and priority, and bug status by priority. Teams can identify which tasks they should start working on now and which can wait, supporting the completion of high-priority tasks faster. In an agile methodology, accurate and efficient prioritization speeds up project completion time.
Improved Product Quality in Less Time
It’s important, however, to ensure that your organization doesn’t sacrifice quality for speed. Getting a high-quality product to market in less time increases revenue potential and is one of the main reasons an organization chooses to adopt an agile methodology. A release management dashboard, with KPIs such as start date, release date, tasks by priority, completed versus remaining sprints helps to enhance product development. Team leads know how much time it took their team to complete the project, helping them to identify well-performing team members, as well as problem-solve with underperforming team members, improving collaboration, productivity, and ultimately, product quality.
In the digital era, data is essential, and agile teams, in particular, rely on actionable data to work smarter, faster. Embedded analytic solutions allow anyone, regardless of technical knowledge, to incorporate the visualization and analysis of data in their day-to-day roles. Data is actionable, and quicker, allowing organizations to seamlessly maximize the benefits of an agile methodology: approach the market faster, improve product quality, gain more customers, and maintain a competitive advantage.