There are a number of System implementation methodologies that are used by implementation teams across the world. An implementation methodology is a structured approach to planning, designing, developing, testing, and deploying information systems. Such methodologies guide implementation and business teams through the project that they are working on and the complexities associated with implementing new systems.
Selecting the appropriate methodology depends on various factors, including project size, project complexity, generic and specific requirements, along with the team’s experience and expertise. A thorough understanding of each methodology’s strengths and weaknesses is crucial for successful system implementation.
Implementation methodologies include the Waterfall Approach (a linear and sequential approach where each phase must be completed before the next phase begins), the Agile Methodology (which is an iterative and incremental approach that is based on flexibility and customer input and satisfaction), the Verification and Validation model (an extension of the Waterfall model with testing at each development stage), the RAD (Rapid Application Development) approach (which focuses on quick development and the iteration of prototypes) and the Incremental model (where the system is built in increments and where functionality is added piece by piece), to name just a few approaches.
Going-Live and the date of Go-Live. There are a a number of considerations to take into account when going-live with the New System, including: the size and nature of the Company or Group, organizational readiness. the complexity of the system, budget constraints, risk tolerance, reporting deadlines, other changes happening in the organisation, resources availability and the importance of the changes being made. The below highlights a few Go-Live Approaches.
Big Bang (Direct Cutover) Approach:
A date is set for the cut-over and the new system replaces the old system at the set date. With a multi-faceted group this may also refer to all companies going live on the new system at the same time. This approach like all others exhibits both pros and cons. The pros of this implementation methodology revolve around a quick implementation time with no parallel systems to maintain in the background. There are however significant risks with adopting this approach and the abruptness of the change, including how such change may create operational and financial disruption if issues arise.
Phased Rollout
With this implementation methodology the new system gradually replaces the old system, either module-by-module or business-by-business over a planned period of time. Feedback from the early users of the system which is being rolled out in stages enables improvements to be made prior to full roll-out of the system. A gradual (phased) rollout of the new system means that it is easier to manage and monitor the impact of changes created by the implementation of the system whilst reducing the risk of widespread disruption from the implementation and any changes in process and procedure associated with the implementation.
Parallel Adoption
This implementation strategy entails the running of both old and new systems in parallel for a defined period of time. Over this time the results from the two systems are compared and where differences are encountered, need to be investigated and resolved, prior to cutting over permanently from the old system to the new system. This approach allows the testing of specific functionality in smaller bite-sized chunks, whilst providing a safety net (i.e. switch back to the old system during the parallel period) for critical functions. Implementations via this approach tend to be longer in timeframe, may lead to additional costs being incurred and potentially data inconsistencies.
Hybrid
As the name states this is a hybrid of the above three approaches, plus others not mentioned above (e.g. rolling deployment, pilot implementation and Canary deployment. The use of a Sandbox (test system) to put through and test / validate changes prior to go-live in the production environment reduces risk associated with making changes in real-time on the production environment.
