The Situation

A leading international Asset Management company with offices across 32 geographic locations accumulated several “master data” sources independently maintained by different business domains. This resulted in a large overhead on maintenance either manually or through multiple development teams. Any changes to the data in these “master data” sources required 48 hours to make, review, amend and approve due to the time differences across the geographic locations. The manual maintenance of data also created a risk of generating errors, inaccuracies, inconsistency, and lack of confidence in the data.

 

The Task

Deliver a sustainable, scalable and a centralised single source master data management solution that provides high confidence in  data quality, accuracy and timeliness using Agile methodologies.

Act as SCRUM Master during Agile Development process.

The solution must satisfy the following criteria:

  • Deliver cost-effectively,
  • Decrease operational cost
  • Reduce operational and regulatory risk.

The Action / Approach

  • Developed an Agile Proof-of-Concept (PoC) approach to identify a key impact/benefit area which could be used as a PoC mitigating risk of delivery.
  • Facilitated evaluation and selection of supplier and product based on functionality and price
  • Negotiated commercial agreements with client and 3rd party supplier
  • Wrote the Statement-of-Works (SoW) with the client and 3rd party supplier
  • Supported Product Owner and Development Team with SCRUM processes and coached the team in the Agile framework.
  • Led the implementation of Data Governance Framework and Data Management Process

 

The Result

  • £5M reduction in operational and capital cost.
  • Reduced data management maintenance cycle from 48 hours+ to approximately 12 hours by better accommodating time zones in the approval process.
  • Increased process efficiency by 40%.
  • Increased reliability and enhanced data quality through implementation of Data Governance framework and Data Management processes to achieve at least 90% data accuracy

Relevant Business Perspectives

Relevant Industries