Since the popularity of our Information Value Management® solution has grown so has the question “how does this compare to or compliment metadata management?” There are distinct differences between the two based on the unique challenges we have observed and tackled in the collective 300+ man-years of data governance experience we have within DATUM LLC. The purpose of this blog is not to question the value of metadata management. There is a very real need to discover and document attributes that describe the context of data, but the needs for the IT organization are distinctly different from the needs of the Business in that regard. This gives rise to a different approach through Information Value Management® (IVM). Before we can discuss a new approach, we must understand the current position of metadata in an organization.
What is Metadata Management?
The simplest definition of metadata is: data about data. The management of metadata is positioned by major analyst firms as a key IT discipline but still as a support function to a support function. Many analyst firms direct IT buyers toward metadata management tools as a back-end discovery and architecture function for their more technical team members. In fact, metadata management is not a part-time hobby and requires skilled senior IT personnel to capture inputs and manage the central repository of content. The discipline is so rigidly guarded that metadata management rarely achieves business exposure because the systems don’t easily publish findings for review or consumption by business users. Moreover, they are shaped in the hands of their keepers as an IT-centric view of enterprise data.
The Relationship Between Data Governance & MetaData Management
Metadata management doesn’t have a natural fit in the growing trend of business data ownership because it’s an IT owned toolset and discipline attached to analytics. The expression of information value the CDO, CPO, CFO and others seek needs to feel more like a strategy map that provides natural navigation from the target business object, business process or business metric to the value statement and organizational contribution of data. The growing trend in data governance is solving operational business challenges in parallel with analytical integrity. This makes for a business-centric, lean approach that metadata management has a hard time keeping pace with. Metadata Management makes part-time participation from business users difficult because of training, but most data stewardship, data ownership and data management roles are part-time overlays embedded within the business. The primary challenge today is efficiently discovering and documenting from the people that know it best the definition of which data is most important (and why) in addition to the definition of what “Clean or Trustworthy” is.
The approach to defining information value needs to feel more like crowdsourcing (with approvals) to maintain direct contact and efficiency with the source of knowledge. Estimating the number of interviews, workshops and meetings necessary to stage attendance of a metadata team (IT) documenting the context, value and ownership of data creates a cost-prohibitive endeavor. The most time-consuming problem in the data governance cycle is defining ownership which often leads to prolonged challenges in dual hierarchies, peer relationships and joint custody that aren’t adapted easily into the inflexible hierarchy of metadata management tools that begin with top-down definition.
So…How Does IVM Compliment Metadata Management?
What IVM® does is crowdsource and package up the context of data and value to feed the decision-cycle and approvals of the data governance board and data governance council. This helps achieve:
- Agile integration/collaboration of Business and IT teams to deliver people and process definition
- Reduced review and rework of data analytics and data automation solutions
- Faster time-to-value for Information Management and Data Governance solutions
- A sustainable, program based view of data and analytics projects
Giving the business the freedom to navigate a strategy and programmatic solution cycle with the freedom to address both the top-down strategy and bottom-up sourcing of inputs makes for a very powerful and efficient path to success for our customers. In fact, our customers see an average of 40% time savings on delivering functional specifications and around 50% reduced rework and meeting time when delivering a data automation solution. Moreover, the transparency and ease of navigation achieved through IVM® give the governance and analytics teams a broader knowledge base that is more sustainable through business transition, scale and even divestiture because the organization is more broadly and deeply engaged in the dialogue of realizing data value.