The key to remember in making a convincing business case for Master Data Management is that MDM addresses a business/organizational issue more so than a technical one. The nature of the solution yields itself to questions from the potential sponsors as to what core issues it addresses, since at the first sight MDM looks like a big initiative and therefore a major investment.

There are two fundamental approaches to building a business case for MDM. Both approaches are complementary, and in a ideal business case they should be supported in parallel -

1) Cite the problem areas that endanger correct decision making for the business - Hunt down by interviewing end users and potential stakeholder specific instances of data issues that the organization has faced that can be alleviated using MDM. Common issues that can be cited here are conflicting instances of the same data element in multiple data systems raising the question of the ’single version of the truth’, or latency issues in the attribute values in different systems. Other issues might be that parameters are coded in the end-user reports, and not embedded in the data model at all. Another common data-related issue is computational constants are not modelled, and are maintained outside of the system. All these lead to major data quality issues that can be alleviated using the data governance process and the disciplined work flow introduced by MDM.

2) Quantify the solution ROI - Once the list of issues is identified, it will be easier to extend further to quantify the impact of these issues on the organization, and thus justify the investment in MDM. Many of you will agree this is easier said then done. The ROI of MDM is a particularly thorny calculation prone to the assumptions made. However, assuming that enough effort has been made to identify the top five issues in step 1, the battle is more than half won for making the business case. The ROI will be in terms of time saved to enforce/propagate data quality in the system (for example, resources saved by avoiding code migrations that may be required in absence of MDM), or in terms of reduced audit risk due to the robust work flow process enforced by MDM.

Overall, remember to stress that MDM addresses a business problem than a technical one. Do not stress a lot on what tool will be used to implement MDM; the problems faced by the business should be alleviated irrespective of the tool used. Stay focused on listing current issues, and how MDM will alleviate them. Then justify the investment in the solution.

As a last step, be sure to specify the proposed work flow that the MDM solution will need; this need not be overtly detailed, a mere high level overview will support the business case and go some ways in assuring the audience that the solution has been analyzed with the organizational structure and work flow in mind. This will lend support to the MDM business case as well.

Contact me on this article at amol.patil@infonitive.com. More articles on Master Data Management, Business Intelligence and Data Warehousing at www.infonitive.com

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