Managing MDM Projects — Preparation

  • A common sense based approach
  • Constructed uniquely to meet challenges in MDM Projects
  • Applies principles of RUP, Waterfall, and Agile project management models
  1. Discovery and Assessment
  2. Scope and Approach
  3. Analysis and Design
  4. Development and QA
  5. Deployment

The Preparation

Discovery & Assessment

  • Client only has a business issue and is looking for a solution within the available tools in the organization
  • Client has a business issue, realizes that the issue cannot be resolved with the available tools in the organization and willing to explore further
  • Client has a business problem, knows that MDM is a solution but not sure about the next steps
  • Client has a road map, high level MDM architecture in place, and wants a validation of architecture and further collaboration during implementation

A clear business case:

  • The true nature of the issue is not always clear at the beginning due to various environmental factors in an organization. Through constant inquiries, we identify all the issues faced, categorize them, prioritize them, and see if MDM is the right solution. At the end of our inquiries, if the discovery is that the client does not need an MDM solution, it is our duty to inform this to the client as well.
  • Once the client decides on implementing an MDM solution, we continue our discovery by understanding the client’s business goals, current systems in place, and overall data vision of the organization.
  • A strong business case for MDM is built with this understanding, and we help the primary sponsors of the project in selling the MDM vision to rest of the sponsors and stakeholders.

Program Roadmap:

  • As part of the roadmap, we identify key master data entities (Customer, Product, Supplier, Account and so on), identify the different sources to be integrated, decide on features of MDM to be implemented, and prioritize each one of them
  • A comprehensive data quality assessment is also done in order to plan for quality fixes well in time for requirements. In the next section below titled “Source Data Quality”, I have elaborated on the ways to do data quality analysis
  • A phased approach to a multi-year roadmap is taken targeting key business deliveries at the end of each phase
  • For a long term MDM investment, it is important to build the entire vision and roadmap at the beginning. This would help us anticipate and plan upcoming changes in the client’s technology and business landscape and phase our implementation accordingly
  • Once the roadmap is in place, the implementation should be in baby steps such that the sponsors start seeing tangible benefits of the implementation as early as possible through small victories that cumulatively meets the MDM vision over the years

Source Data Quality:

  1. We will be ready for the first phase and when we sit for data mapping, there will be sufficient clarity and minimal rework
  2. Once we get a grip on quality of data, along with what will be accepted by MDM, a parallel team can start working on analyzing the remaining source systems, ready in time for subsequent phases

Scope & Approach

  • Determine priority of each of the master entities in the organization, and decide on which entity to implement first
  • Identify source systems, analyze them, and come up with an integration plan of source systems
  • As applicable, plan for building all necessary support architecture to handle real-time, near real-time and batch load data. For clients that already have these in place, evaluate and ensure readiness for MDM implementation
  • In alignment with the client business and IT teams, come up with tangible deliverables for each phase that business can use, or see value in
  • Come up with high level requirements document that forms the basis of detailed functional requirements and data mapping that should be created in subsequent phases

The Non-’iterative’ preparation:

Developer and Designer

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Abhikhya Ashi

Abhikhya Ashi

Developer and Designer

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