Data governance (DG) is vital to the success of master data management (MDM) projects. Unfortunately, the DG market remains fragmented and unfocused on the requirements of large MDM initiatives.
Contemporary solutions are essentially “reactive DG” due to their approach as “data steward consoles” of downstream data quality issues. The much anticipated solution would be “active DG” wherein both upstream and downstream lifecycle processes are integrated end-to-end via workflow such that evergreening of the DG rules is a continuous process improvement cycle benefitting the enterprise. Sadly, many of the currently marketed DG solutions consist primarily of white papers and demo-ware, or “passive aggressive DG”; that is they purport to deliver a certain capability, yet provide otherwise.
Enterprise-level DG that includes entire master data lifecycle (creation, promotion, archiving, …) is extremely difficult to execute for a number of reasons – organizationally and technically. Yet increasingly this is being mandated as a core deliverable of large-scale MDM projects.
Through 2009-10, both major systems integrators and MDM boutique consultancies will focus on productizing their DG frameworks/methodologies while MDM software providers struggle to link upstream DG processes with downstream MDM hubs.
By 2011-12, all mega vendor MDM solutions will evolve from “passive aggressive DG” mode to “active DG” wherein they provide the capabilities to capture business rules which in turn are propagated into an MDM.
By 2012, both corporate and line-of-business data stewards will be a common position as Global 5000 enterprises formalize this function amidst increasing de facto and de jeure recognition of information as a corporate asset.; moreover, governmental compliance mandates will require that financial services organizations provide “proof of data governance” as a proactive measure.
In 2H2009, the MDM Institute conducted a multi-client survey of early adopters and evaluators of DG initiatives across a broad range of MDM projects. Based on an increasing dictate for process rigor regarding governance of customer data, and increasing recognition of the necessity to treat DG as a prerequisite for large scale or enterprise MDM programs, clearly Global 5000 enterprises are now recognizing the opportunity to take a more strategic view of DG.
This “best practices” session will provide insight into these key issues:
• What are the business drivers for enterprise-strength DG?
• What are the technology challenges in implementing DG for enterprise magnitude business problems?
• Why is “active” DG superior to “passive” or “passive-aggressive” DG?
• How are large enterprises justifying and catalyzing their DG processes?
• Which are the “desirable” vs. “essential” DG solution criteria – e.g. GUI sizzle for hierarchy management vs. end-to-end team-based governance for the data steward function
• How does an organization organize and execute through the four stages of DG maturity: anarchy (basic), IT feudalism (foundational), business monarchy (advanced), and federalism (acme)