Working to an agreed budget and plan, GREYFLY were commissioned to create a projects prediction proof of concept [PoC]. The PoC was to review existing projects systems and data with the purpose of creating a prediction tool based on pin-pointing learnings from historical project data sources.
The client is a successful IT services business which has a good track record in delivering high profile relatively standardized projects whilst being under acute costs controls.
The assessment was commissioned by the UK Head of PMO who was responsible for supporting project delivery and driving standards and efficiency.
GREYFLY deployed experienced capable consultants and in due course technical specialists who initially investigated existing project systems to identify the maturity of existing data and identify gaps that could enable the AI in PM prediction journey.
Findings and recommendations were presented within a report to key stakeholders. Project data sources were reviewed to identify existing data entities and data maturity quality. This was compared to the Greyfly data model to ascertain the ability of the client to build a prediction proof of concept.
The resultant data comparison was used to inform the ETL [Extract, Transform, Load] stage of ingest. Once data was deemed acceptable priority was given to identify the definition of project success and failure.
Results showed as well as current capability strengths and weaknesses and specific areas that should be targeted for transformation and/or automation, along with an ability to create a prediction proof of concept.
Following on time delivery of the maturity and AI readiness assessment report, recommendations were fully accepted ahead of Executive presentation.
Specific recommendations lead to an on-going implementation phase where GREYFLY consultants were engaged to build a prediction Proof of Concept, move forward with top priority automation opportunities and transform priority projects process re-engineering opportunities.
