Our goal is to provide support to our clients during the whole lifecycle of large transformation projects with specific expertises.
Project and Roll Out strategy
Spoon management team involvement in successful projects gives us the maturity and methodology to support our clients in defining appropriate project strategies, namely:
- Roll out strategy (scope, organization, big bang vs phased approach, pilot site),
- Back office strategy (front office vs back office, site vs remote activities, organisation, tools and processes),
- Go live strategy (data migration strategy, cut to live strategy, on site support, post go live support),
- Sustain phase strategy (hand over from project organisation, call to resolution process, front line,level 1, level 2 and 3 processes, release management)
A key success factor for large transformation projects is the linkage between strategy and operational schemes. Detailed and robust architecture designs should create and maintain this linkage throughout all phases of an implementation project. We have developed within Spoon skills and cross boundaries ways of thinking to tackle and deliver architecture design works.
Testing is always time consuming and if not properly managed creates quality issues or even delays go live. Remote back offices create constraints but can also be considered as a unique opportunity to implement efficient and added value testing processes. Spoon has developed its own processes to support various tests cycles using state of the art testing tools.
Development for large ERP or Bespoke Oracle systems
Our technical teams receive specific training to be efficient in an ERP environment with a thorough understanding of the business context of each process. We also developed very strict guidelines to identify the less intrusive solution for a given requirement with an on going concern for future maintenance.
Migration and Data Loading
Our tools for data loading cover most objects within E business suite with a comprehensive and structured process which secure the overall process and manage the various situations to be faced during data loading poor quality data, complex transformation rules, large volumes, …)