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Kelle O'Neal

Thanks for joining our data conversation! This blog is an opportunity to share the real life challenges, opportunities and approaches to improving the quality and value of data in your organization. We will write about everything data related from translating "data" speak into "business" speak, to governance models, to the real differences among the myriad software tools available. But there's one catch: we all have to agree to toss out the fluff. That's right, no 30,000 foot, theoretical strategies that leave you wondering how to execute and actually improve performance. Visit regularly to learn from peers and partners on how they are managing and improving data, and we hope you'll also share your views and experiences.

About the author >

As Founder and Managing Partner of First San Francisco Partners, Kelle O’Neal manages specialist data governance and data management consulting services to complex organizations that deliver faster time to results. Kelle can be reached at kelle@firstsanfranciscopartners.com or through the First San Francisco Partners website.

Follow First San Francisco Partners on Twitter at @1stSanFrancsico.

Editor's Note: Find more articles and resources in Kelle's BeyeNETWORK Expert Channel. Be sure to visit today!



The Framework for Data Governance

Whether it stems from a desire to understand customers at any time from any channel, a need to balance old mainframe systems with new technologies, a requirement to comply with numerous and emerging regulations or some other initiative...we all want to connect data to business value.

Amidst these and other data challenges, successful and sustainable Data Governance (DG) is becoming a top priority for organizations that want to ensure the right people are involved in determining standards, usage and integration of data across projects, subject areas and lines of business (LOBs).

A critical step in DG design is identifying the best-fit operating model for your organization. The operating model is a framework articulating the roles, responsibilities and decision making process for governance. 

It ensures the right people are represented and it helps to create accountability. It also facilitates communication and provides a process to resolve issues. While it does help form the basis for the DG organizational structure, it is NOT an org chart. 

Here's a high level overview of the pros and cons of the Centralized, Decentralized, Hybrid and Federated model types to aid in assessing your own organization.

Centralized Operating Model

Similar to a project model with an executive sponsor, here everything is owned by the DG Lead, and those involved in governing and managing data report directly to this person.

A rule of thumb to determine the best sponsor is to identify where there is political leverage beyond a title (such as CFO or COO) because cross-functional involvement and support are fundamental to success in this role.

Pros
  • Establishes a formal DG executive position
  • DG Steering Committee reports directly to executive
  • Data Czar/Lead means there is one person at the top; easier decision making
  • A one-stop shop
  • Easier to manage by data type
Cons
  • When implementing, there is generally a large organizational impact
  • New roles will most likely require Human Resources approval
  • Formal separation of business and technical architectural roles
centralized-model.jpg

Decentralized Operating Model

The antithesis to the Centralized model, here everything is committee-based so there is no single DG owner. This is how most data governance programs start and is a very grassroots structure.

Pros
  • Relatively flat structure
  • Informal Data Governance bodies
  • Relatively quick to establish and implement
Cons
  • Consensus discussions tend to take longer than centralized edicts
  • Many participants compromise governance bodies (making it potentially unruly)
  • May be difficult to sustain over time because of its informality
  • Provides least value since it tends to be the least productive
  • Difficult coordination
  • Business as usual
  • Issues around co-owners of data and accountability
decentralized-model.jpg

Hybrid Operating Model

Like its name implies, this encompasses benefits of both models - here there is a centralized DG office with a decentralized (virtual) working group. The Steering Committee is centralized in that there is only one for the whole company, and it represents all the key lines of business or business units.

Pros
  • Centralized structure for establishing appropriate direction and tone at the top
  • Formal DG Lead role serving as a single point of contact and accountability
  • DG Lead position is a full-time, dedicated role so DG gets the attention it deserves
  • Working groups have broad membership for facilitating collaboration and consensus building
  • Potentially an easier model to implement initially and sustain over time
  • Pushes down decision making
  • Provides ability to focus on specific data entities
  • Issues resolution without pulling in the whole team
Cons
  • DG Lead position is a full-time, dedicated role (therefore may require new headcount)
  • Working group dynamics may require prioritization of conflicting business requirements
  • Too many layers
hybrid-model.jpg

Federated Operating Model

Very closely related to the Hybrid Model, this model provides for additional layers of centralization/decentralization as is often required in large global enterprises. 

Pros
  • Centralized Enterprise strategy with decentralized execution and implementation
  • Enterprise DG Lead role serving as a single point of contact and accountability
  • "Federated" DG practices per LOB to empower divisions with differing requirements
  • Potentially an easier model to implement initially and sustain over time
  • Pushes down decision making
  • Provides ability to focus on specific data entities, divisional challenges or regional priorities
  • Issues resolution without pulling in the whole team
Cons
  • Too many layers
  • Autonomy at the LOB level can be challenging to coordinate across the enterprise
  • Difficult to find balance between LOB priorities and Enterprise priorities
federated-model.jpg
The Key to Successful Data Governance

Whichever model you choose; remember that simplicity and usability are essential for acceptance. When you ensure the operating model fits the culture of your company, you're embedding Data Governance into your operations and aligning your strategy for long-term sustainability.

Posted July 27, 2015 4:39 PM
Permalink | 1 Comment |

1 Comment

Great article Kelle providing an outline of a new data governance function and capabilities.
Other supporting questions with each of the above options are Business Change backing and Executive Sponsorship (ideally CEO) and the funding approach that fits with the Business culture & TOM.
Once the model is chosen, how each of the chosen models above, become part of the organisations operating DNA to ensure sustainability.

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