Master Data Management (MDM) strategy and vision are driven by Enterprise Data Management (EDM) strategy and roadmap. It may also have tactical needs baked into the MDM roadmap. These could include BI, analytics, and such short-term wins geared toward specific business objectives.
MDM is always geared toward process excellence or BI/Analytics. In the former case, MDM will be primarily a cross functional project connecting various functions and related value chain activities; think New Product Introduction (NPI) or Quote-2-Cash (Q2C) flows which are very prominent examples of MDM projects. This is not as easy as it sounds though, and devising the right Master Data Management strategy that incentivizes every function is of utmost importance. One thing I have learnt in my years of practice is that you cannot shove MDM down people’s throats.
When driven by BI/Analytics though, MDM tends to get a little easier. However, for lasting benefits, MDM should not be isolated from broader functional goals set by leadership in Data & Analytics (DA), Chief Data Office (CDO), or functions alike. Among many reasons is the fact that MDM has to work iteratively over time and produce correct results that are in alignment with broader enterprise analytics; e.g. roll-ups.
I have worked extensively with large enterprises and repeatedly solved the above challenges; see some success stories.
We must always use a wider lens, but not waste a lot of time doing this exercise and rely on past MDM collective experience dealing with similar situations over last 2 decades. In short, one must use templated approach to solving for MDM challenges and opportunities.