To Centralise or Not To Centralise, That is the Question...

Which Data Governance model is right for me?

There’s still much debate about whether Data Governance should be centralised or not. 

Thinking back to the Data Quality AsiaPacific event in March, Nonna Milmeister at Telstra made the point that as far as she’s concerned, there’s little interest in the “where does it sit” discussion, and I broadly agree with Nonna’s point of view that the hierarchical placing of the team may be a bit of a red-herring with respect to the core Data Governance function, which exists to facilitate the overall process of information flow within the organisation. (see also my post “What Do The Simple Folk Do”…)

However, when it comes to the overall organisational operating models for Data Governance, the question is somewhat different. It’s not so much about the hierarchical situation of the core team; it’s more to do with the overall approach to bringing the various governance groups together in a cross-functional, enterprise-wide approach. I suggest that rather than being a hierarchical or functional issue, it will be the social and cultural characteristics of an organisation that will be the deciding factors in determining which approach to adopt.

Each organisation will of course have its own dynamics, cultural constraints and behavioural norms that influence the way the business runs; these are often not formally recognised or dealt with, even in organisations that have well-documented Mission or Value Statements. However, I have identified three broad categories of organisational cultural models that I think have an overarching influence on the approach to establishing an Data Governance environment:

1. Centralised IM Governance

Each business unit may operate separately, but there is significant commonality across the whole business lifecycle. Customers, product lines and service channels are inter-related and cross-business effectiveness is enhanced by close co-operation.

Approaches & processes for Information Management and Data Governance need to be held in common.

One set of controls and policies is put in place for Information Management throughout the organisation.

GOOD FOR: Hierarchical organisations where there needs to be a significant amount of information sharing between departments and business units. This is typical in organisations where information sharing and re-use is required at the detailed level.

EXAMPLES: Banking, Telecoms, Retailing

2. Federated IM Governance

Each unit operates autonomously and may have very different approaches & processes. However, each executes the same overall functionality & responsibilities as the others. There are shared guiding principles & objectives for Information Management.

GOOD FOR: Geographically diverse organisations with a loose hierarchy. Information sharing is appropriate at a high level (themes, approaches, learning). This would suit organisations where significant differences in the operational environment exist, but where the overall high-level objectives are held in common.

EXAMPLES: Universities, Healthcare authorities, Social Welfare programmes.

3. Distributed IM Governance

In the distributed model, there is little or no commonality within business units, customer base and product lines, with each operating fully autonomously.

GOOD FOR: Organisations that are operationally diverse and functionality independent, with little or no need for sharing information between silos.

EXAMPLES: Fast-Moving Consumer Goods businesses operating widely differing product markets (e.g. Cosmetics, Foodstuffs and Cleaning products); government departments with diverse portfolios.

Clearly these are very generalised models, but in my experience, any organisation will fall into one of these categories of cultural behaviour. It then becomes part of the Data Governance function’s role to identify the most suitable model and match any initiatives to fit within the cultural norms that apply. (Beware trying to enforce one approach on an organisation that has another social structure!)

Does your organisation fit into one of these three cultural orders? Will mapping these behavioural norms help you to identify the best approach to rolling out Data Governance capability within your company? Or are there other types of environment that would require a different approach? Please let me know your views.

(See also Share the Love... of Data Quality for some thoughts on a distributed approach to more operational aspects of data governance & data quality management.)