An IT mindset has dominated the way organizations view and manage their data.  Even as issues of quality and consistency raise their ugly head, the solution has often been to turn to the tool and approach data governance in a project oriented manner.  Sustainability has been a challenge, relegated often to IT managing and updating data management tools (MDM, data quality, metadata management, information lifecycle management, and security).  Forrester research has shown that less than 15% of organizations have business lead data governance that is linked to business initiatives, objectives and outcomes.  But, this is changing.  More and more organizations are looking toward data governance as a strategic enterprise competence as they adopt a data driven culture.

This shift from project to strategic program requires more than basic workflow, collaboration, and data profiling capabilities to institutionalize data governance policies and rules.  The conversation can't start with data management technology (MDM, data quality, information lifecycle management, security, and metadata management) that will apply the policies and rules.  It has to begin with what is the organization trying to achieve with their data; this is a strategy discussion and process.  The implication – governing data requires a rethink of your operating model.  New roles, responsibilities, and processes emerge. 

To date, data management technology has attempted to address these new roles, responsibilities and processes by focusing on the intersection of subject matter experts for data policies in the business and how to implement these in an automated and scalable fashion.  That is table stakes and not enough.  Managing data is like managing another aspect of your business.  Marketing and Sales have CRM applications.  Finance and Operations have ERP applications.  Product management, Engineering, and Manufacturing have product lifecycle management application.  Data Governance requires its own application because the processes, tasks, coordination and oversight require the same type of discipline, consistency and sustainability as other operations.

Vendors are beginning to wake up to this new reality of what Forrester sees as Data Governance 2.0 – business ownership, business strategy, and emphasis on business outcomes.  New capabilities are being introduced, and some new vendors are stepping in.  While early, along with my colleague Henry Peyret, we conducted research on what tools and solutions are available that support the administrative and strategic aspects of data governance. The result –  The Forrester Wave, Data Governance Tools Q2 2014 is out.

Here are some key take-aways from the research:

  • vendors are still married to the legacy of data management owning and running with data governance focusing capabilities toward tactical data governance 
  • no single data governance tool manages across all five data governance pillars (MDM, data quality, ILM, metadata, security) – although some vendors (IBM, Informatica, SAP) can with significant integration between products.
  • Only two vendors (Trillium Software, SAP) provided data governance metrics that linked data conditions with actual business outcomes (regulatory risk, total cost of ownership, etc.)
  • Only one vendor (Collibra) has an in market tool that provides a data governance 2.0 environment specifically for strategic data stewardship and operations
  • Significant product innovation is coming (from more application like tools to better user interfaces and reporting)  that will lift data governance management out of IT and into the hands of the business.  While IBM, Informatic and Collibra lead in strategy, others such as Information Builders, SAP, SAS, and Trillium Software are introducing specialize capabilities that will make them stand out (industry and regulatory specific, better reporting and audits, improved buisness support, etc).

This is an emerging market; we expect the data governance tool landscape to shift sharply in the coming year with those in the Leader category potentially facing stiff competition, and the potential to see consolidation, acquisition, and new companies emerge.  What you should know when considering data governance tools?

  • There is no single solution, but data quality, MDM and metadata management often are tightly connected to govern across
  • Identify tools that enforce best practices for the administrative aspects of data governance – keep in mind the end user is the business and may not be a "data geek".
  • Look carefully at what it takes to connect data conditions and processes to business outcomes as this effort may be a BI on Data project.
  • Understand the vendor roadmap – choose those that have solid strategies and prototypes/early releases geared toward the strategy, process, and administrative aspects of governance, not just data management and data processing.

Come hear more about the data governance vendors and market landscape in our July 9, 2014 Forrester Webinar highlighting the results of our Forrester Wave Data Governance research.