Lack of clear accountability. Continuous Improvement requests (enhancements, production tickets) handled by resources based on availability of bandwidth instead of capabilities and skills.
Siloed approach to managing Continuous Improvement requests â€“ each department tracked metrics from the time the request landed on their queue.
Average time taken to fixing production bugs and deploying to production was 6-7 weeks
Exafluence conducted a thorough gap analysis of the client's current state including Processes, People & Tools. Inherent issues were identified and documented. The solution comprised Roadmap definition and an approach towards building a Factory Model for all data analytics and reporting needs across the identified Corporate functions along with Key Outcomes
Exafluence recommended, designed and implemented an SLA driven Analytics COE.
Key Objectives of the ACOE:
Set-up a centralized organization that funnels all analytics requests and delivers per SLAs
Deliver BI and Data requests in much shorter time frames as opposed to the inordinately long marathon runs, while upkeeping First Time Quality
Provide BI Services on Demand, through a Services Catalog based delivery with built in estimation models.
Better collaboration with Business and other teams - Platform, Development, Support
Results to the Customer:
Value-led metrics, ready to use templates and checklists were created
Service Catalogue based model enabled users to pick up and chose from the itemized reports and analytics with upfront transparency on the associated price and timelines
Optimized triaging mechanism led to reduction in ageing of the tickets by up to 80%
Validations and source to target reconciliations for migration workstreams ensured data sanctity