Organizations are different from one another. Projects and business strategies differ from one another. Make sure your development approach matches your organization and project. Many project managers are moving away from conventional predictive Software Development Life Cycle (SDLC) methodologies toward adaptive SDLC methodologies.
Should you?
To determine this, you should have a clear understanding of predictive vs. adaptive SDLC approaches and identify the best methodology for your organization and your project.
As the name suggests, predictive SDLC assumes you can predict the complete workflow. It involves fully understanding the final product and determining the process for delivering it. In this form of project life cycle, you determine the cost, scope, and timeline in the early phases of the project.
One of the most common predictive models is the waterfall model. It assumes various phases in the SDLC that can occur sequentially, which implies that one phase leads into the next phase. In simple words, in waterfall model, all the phases take place one at a time and do not overlap one another.
While the waterfall model is quite simple and easy to use and understand, it also entails a few drawbacks that could drastically impact your project.
Since the waterfall model follows a sequential approach, once an application is in the testing phase, it becomes difficult to go back and debug it in the development stage.
The main concern of a predictive SDLC approach is to develop and maintain the specifications of the final product. This makes it ideal for projects where all the requirements are defined and well understood with a clear vision of the final product.
In predictive SDLC, there are minimal expected changes as the work is already predictive and well-known. The team has a clear idea of exactly where the project is heading and how to follow the sequence.
On the other hand, a predictive approach can be extremely rigid, requiring developers to maintain strict and rigorous standards throughout the life cycle. Since the sequence of the work is already predetermined, any subsequent changes can be very costly and time-consuming.
Adaptive SDLC approaches have a mix of incremental and iterative development. It involves adding features incrementally and making changes and refinements according to feedback. In other words, the work can easily adapt to the changing requirements based on new feedback received from the client.
Agile and other iterative methodologies fall under the umbrella of adaptive SDLC. A key element of adaptive SDLC methodologies is that while it defines certain milestones throughout the SDLC, it also allows flexibility to achieve them.
Adaptive SDLC, such as Agile, focuses on achieving the desired end goal by quickly adapting the dynamic business requirements. It puts more focus on the present requirement and leaves room for future scope of the project.
Adaptive SDLC approaches are best for projects that have the potential for significant changes in scope or that there is uncertainty in what is desired. You may need to adapt to the changing demands of the client for these projects.
The adaptive SDLC methodology is typically faster than predictive SDLC approaches. This is primarily due to the fact that few projects are sufficiently understood to really use a predictive SDLC methodology. When requirements are not sufficiently understood, issues are identified late in the lifecycle and this leads to expensive re-work.
Since each approach has its uses for specific types of projects, there is no clear-cut decision as to which of them is better. The choice depends largely on the project type, your strategies, and organizational needs.
It’s best if you carefully analyze predictive SDLC and adaptive SDLC and weigh the pros and cons for each project rather than relying on a uniform approach for all projects.
As you can see, both predictive and adaptive SDLC approaches have unique benefits so it would be a huge mistake to use only one of them for all your projects. Carefully assess each project demands and specifications to see which approach you should take.
Got any questions about predictive vs. adaptive SDLC? Let us know in the comments.
Previously published at https://www.cypressdatadefense.com/blog/predictive-vs-adaptive-sldc/