Britehouse MDM Best Practices overview
28 June 2010
- Get business sponsorship.
- Choose the first Master Data issue that is definable - and that can be solved within a short period of time - and then build the designed MDM Solution on that foundation.
- Investigate and propose a scalable, flexible solution that will allow the company’s MDM programme to mature, as the business understanding and acceptance matures and incorporates future Roadmap Projects.
- Invest time documenting data related processes and how each Master Data element, is governed for each Data Process; this involves a process of Creating, Validating, Authorizing, Maintaining, Monitoring and Deleteing.
- Build a strong Master Data Management business foundation early, where the business can be supported and Data Business Rules can be enforced.
- Build relationships within the business and IT, and constantly promote the need for Master Data consistency. Drive the need to be aware and included in business and IT Projects to assess the Data need, and plan for the required data processes, data consistency and business rules that will need to be enforced.
- There is significant value in building on existing practices and identifying areas of data inconsistency before trying to implement a new MDM software, such as SAP MDM.
- Timing of data updates and fixes must never be underestimated. Once a data process is known and the investigation on how to adjust or fix data is documented with business owners for each step, the key is to highlight the timings of when the fix can take place and the impacts of that change on the Supply Chain Process.
- Expect resistance to MDM Projects and plan for delays in rolling each Roadmap Project out.
- Explain to all role players that an MDM Programme is not about quickly fixing a data field. Every MDM action has consequences, will need to be repeated and will require a monitoring and evaluation process. When presented with budgets, business cases or requests for additional resources, company management suggest….‘a small project with some resources temporarily assigned to clean-up the data’. Experience shows that high volatility Master Data fields will deteriorate or become inconsistent within hours of fixing, due to multiple user access, regionalized data, or conflicting field requirements - by various business projects or divisions.