How to Determine the Right Agile Development Methodology

2 min read

Not all Agile methods are alike. If someone tells you that they practice Agile software development, you have only heard the start of their story. That’s because today’s Agile teams use a wide range of methodologies.

So, how can you determine the right Agile methodology for your team? It starts with knowing the most common ones used by today’s top software development teams. The most popular Agile methodologies used by today’s practitioners are:

One exception to this list is Kanban. While Kanban is not considered an Agile development method, it is commonly used in conjunction with Agile methods to increase efficiency.

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Now that you know the types of methodologies in use, it’s time to determine which one is best for your team. When it comes to comparing and choosing which method is best for a team, the idiom “different horses for different courses” comes to mind.

The most popular Agile methods are Scrum and XP, which are very much aligned in their practices. That said, there are some notable differences between the two:

1. Scrum team iterations, which are called sprints, tend to be two weeks to one month in duration. XP teams work in iterations that are one to two weeks long. 2. Scrum teams do not allow changes into their sprints, whereas XP teams are much more open to making changes within their iterations. 3. XP teams work in a strict priority order as determined by who is serving in the “customer” role, whereas a product owner prioritizes the backlog items for a sprint. However, the team has the freedom to determine the sequence in which they are developed. 4. Scrum is much more focused on management practices and less defined when it comes to engineering practices.;

 

Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.