1. Moving beyond research: building an enterprise data service from a research foundation San Cannon IASSIST 2014
The views expressed are those of the author and do not indicate concurrence by other members of the staff or the Board of Governors.

2. Once upon a time…. There was decentralized data management
Division level decision making and procurement
Division or unit level management (or not)
Only occasional cross division data sharing
And the people were (mostly) happy
The data lived close to them
They made all the decisions
They took care of “their data”

3. In the research world
There were two professional data management groups – one focused on time series (macro) data and one focused on detailed financial (micro) data.
They provided operational data management and subject matter support for the research community.
Other business lines handled things less formally and with fewer dedicated resources

4. Financial crisis (and cleanup)
More people needed access to more data more often and more quickly.
No formal policies or guidelines meant that even the well intentioned may not be “doing the right thing”.
Little coordination meant individualized data management approaches lead to inconsistency, incomparability, and frustration for users.

5. Research adapts
Data management groups are reformed with the split being between data and applications
More data means and more sharing means research data folks increasingly serve as an enterprise service
Resources are strained and competing priorities between business lines add more challenges

6. Strategic planning process begins
Data pain is felt across the Board and data governance identified as one of 6 strategic themes for the Board
Consultants run around for several months interviewing everyone who thinks about data (including focus groups of users, officers and managers with data responsibilities, etc)
Multiple discussions with, and input received from, the highest levels.

7. What did they find? Few consistent policies.
Limited formal coordination between divisions on data.
Highly variable data management.
Constrained data environment.
Long standing silos with subject matter experts maintaining “their” data will not scale to handle the new data landscape.

8. What did we do?
Hire the first Chief Data officer, Micheline Casey who started in May 2013.
Reconstitute the Board Data Council (BDC) as a governance body.
Data management groups from the research area are moved into the OCDO to formally become enterprise service providers.
Begin to develop the service portfolio.

9. OCDO Service Portfolio
Governance
Standards
Data quality
Risk management
Clearance & intake process
Architecture
Information architecture
Business Analysis and Modeling
Inventory, Metadata and Taxonomy
Data Management
Acquisition and Integration
Distribution
Lifecycle management
Program Management
Project management
Change management
Communications
Training and education
Advisory Services
Content expertise
Help desk
Best practices
Board of Governors Data Strategy

10. How will we do this?
Hire lots of new people into new roles (information architects, business analysts, data governance analysts) – 18 net new
Revisit and reengineer current business processes to improve our ability to provide service across the enterprise – 2 major consulting engagements underway
Communicate, communicate, communicate – major outreach initiatives on going and planned

11. How are things going so far?
Three positions filled, four more currently advertised, others to come
Communication plan drafted, engagement model under development
First enterprise project sponsored by the BDC underway
Still working to make sure people know what we can do for them, not what we will do to them.

12. Last slide Questions? Thanks for listening! San Cannon
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