What’s the difference?

When it comes to software development, choosing the best software model is just as important as choosing the best vendor. Why is the model so important? A wise man once said that if you fail to plan, you plan to fail, and the Systems Development Life Cycle (SDLC) model is an important component in planning a project. The SLDC is a conceptual framework that describes all the actions in software development — in other words, it’s the key planning tool that will guide your developers step by step throughout the project. You require a model that can keep all the business requirements, assure every feature is designed and built accurately, and ensure the project works as it should. 

The various SDLC models fall into two primary groups: predictive and adaptive. Both methods are equally valid, and it’s the project type that should drive the model selection. The choice will depend on the evaluation of all the pros and cons of each model in the context of the particular project’s goals and limitations. 

Predictive Development

Predictive, or Incremental, development is a process of software development where the model is designed, implemented, and tested incrementally until the product is completed — or until all the requirements have been satisfied. This model connects the elements of the waterfall model with the iterative conception of prototyping. In this model, each module passes through the requirements, design, implementation, and testing stages. 

As this model involves delivering system components as they’re completed, it allows for partial utilization of product meaning completed features can be used before the full project is finished — and avoids a long development time. That means this model helps reduce the traumatic effect of adding a completely new system all at once. 

Pros: 

  • The predictive model makes a working software product faster than the adaptive model. 
  • It’s more comfortable to manage uncertainty with this model because possible obstacles are identified and handled during their first iterations. 
  • It is easier to test and debug during iterations of smaller pieces than on the full product. 
  • This model allows for more flexibility, as changes to scope and requirements may be made to every increment. 

Cons: 

  • This model needs good planning and design. If tasks aren’t done correctly in each phase, the complete project can be impacted. 
  • A clear and complete description of the whole system is needed before it can be broken down and developed incrementally. 
  • Additional efforts are required to integrate each component of the system. 

When to use the predictive model: 

  • When the requirements are clear and can be completed in logical phases, even though some details may evolve with time. 
  • When there are some high-risk features and goals or when the product requests for new technology. 
  • When the customer needs clarity on and strict adherence to the target delivery/end date based on the agreed-upon scope. 

Adaptive Development

Adaptive life cycles like SCRUM or Kanban (also known as agile or change-driven) are designed to repeat quickly on projects that are a little more innovative or less certain. They’re dependent on ongoing stakeholder contributions, and they react quickly to the changes in project scope and system demands. This procedure is sometimes referred to as freeform software design as it offers an incredibly flexible design model, promoting adaptive planning and evolutionary development when the end goal is not quite as concrete. 

Short sprints with many product demo sessions allow flexibility and prompt adjustments to a product increment, decreasing the risk of wasted costs, even when we’re moving fast. Daily scrum meetings are intended to track growth and proactively react to changing conditions. Product owners are closely involved in the development process, eventually becoming a part of a team to allow real collaboration between our developers and our clients. 

Pros: 

  • This model permits evolving requirements so change can be implemented very smoothly given the shorter planning cycles.
  • This model promotes customer satisfaction through fast and continuous delivery. 
  • Adaptive development promotes active involvement and interaction from key project stakeholders, which allows for product build based on priority and accuracy. 

Cons: 

  • Planning can be questionable. 
  • Team members must be highly skilled and cross-skilled as core teams are small. 
  • The project can simply get thrown off track if the customer is not clear on the desired outcome. 

When to use the adaptive model: 

  • When the end goals of projects are not clearly explained. 
  • When the implementation process must start faster.
  • When the project calls for experimental software design. 

When it comes down to it, neither the predictive nor adaptive model is significantly better than the other. Both methods have their uses, and there is not a right or wrong selection. Incremental development tends to be best for static projects where the conditions aren’t likely to change throughout the development process. In contrast, adaptive models tend to be a better option for projects in which changes are likely.