Thursday 1st March ... I have just completed delivering a presentation on Data Governance at Ovum London conference http://governance-planning.ovumevents.com/
I'll add a link to the slides here shortly.
I'm sure that we all know that data is growing at a vast rate, however there's been an even bigger problem concering uncontrolled growth that I have recently read about ...
... 12 Grey Rabbits were brought to Autralia in the 19th Century for sport. After 2 years there were in excess of 2million per year were being shot & still the population wasnt dented. A few years later the population was over 400million. So, even the Data explosion highlighted by the 2011 IDC Digital Universe study hasn't yet reached these proportions.
IT Governance:
From several of the well established frameworks (eg ITIL), the common key components of an IT Governance framework seem to be:
1) Strategic Alignment:
Within their service cycle, IT services in their entirety bring a benefit in respect of the corporate strategy and generate added value for the enterprise.
3) Resource Management:
Efficient management of resources such as applications, information, infrastructure and people, as well as optimization of the investment.
4) Risk Management:
Identification and analysis of the risks in order to avoid unpleasant surprises and to gain a clear understanding of the company’s risk preference.
5) Performance Management:
Monitoring and control of all performances in terms of their orientation towards the corporate strategy.
Looking now at Data Governance, some of the key areas that need to be considered, certainly to folks more used to IT Governance are:
1) There are usually 3 main drivers for Data Governance:
Pre-emptive: Where organisations are facing a major change or threats. Designed to ward off significant issues that could affect success of the company.
Reactive: Where efforts are designed to respond to current pains
Pro-active: Where Governance efforts designed to improve capabilities to resolve risk and data issues. This builds on reactive governance to create an ever-increasing body of validated rules, standards, and tested processes.
2) Data Governance can be implemented in 3 ways, often these may overlap (Tactical, Operational, Strategic).
3) There is certainly no "one size fits all" approach to Data Governance. Need to have a flexible approach to Data Governance that delivers maximum business value from its data asset.
Data Governance can drive massive benefit, however to accomplish this there needs at least to be reuse of data, common models, consistent understanding, data quality, and shared master and reference data.
Organisationally, different parts of the business have different needs, and different criteria for their data. A matrix approach is needed do these different parts of the organisation and data types are driven from different directions.
However, no matter how federated the organisation may be there will be some degree of central organization required. This is to drive Data Governance adoption, implement corporate repositories and establish corporate standards
The IPL Business Consulting practice have a flexible DG framework that can be tailored to help.
4) Communication & stakeholder engagement is key. No matter how brilliant the framework is, or how great your polices or DG council are, if you dont adequately engage and communicate with the stakeholders, the DG initiative will go nowhere.
5) Finally, all of this is only important if Information REALLY is a key corporate asset for your organisation ..... so ask yourself, is it?
So IT Governance vs. Data Governance?
In summary, Data Governance is a vital frequently overlooked component of an overall IT Governance approach. Remember the 5 commmon components of an IT Governance approach? Well, lets apply these in a Data Governance context and we see ...
1) Strategic Alignment:
Delivering information to the requisite quality, time, completeness and accuracy levels and optionally monetising the value of information.
3) Resource Management:
Ensuring people, and technology resources are optimised to ensure definition, ownership, and delivery of information resources meet business needs.
4) Risk Management:
Information security, backup & retention and delivery are balanced against regulatory and accessibility needs as befits the company’s risk preference.
5) Performance Management:
Monitoring and control of Data Governance roles, responsibilities and workflows such that they meet the demands of the corporate strategy.
I'll add a link to the slides here shortly.
I'm sure that we all know that data is growing at a vast rate, however there's been an even bigger problem concering uncontrolled growth that I have recently read about ...
... 12 Grey Rabbits were brought to Autralia in the 19th Century for sport. After 2 years there were in excess of 2million per year were being shot & still the population wasnt dented. A few years later the population was over 400million. So, even the Data explosion highlighted by the 2011 IDC Digital Universe study hasn't yet reached these proportions.
IT Governance:
From several of the well established frameworks (eg ITIL), the common key components of an IT Governance framework seem to be:
1) Strategic Alignment:
Alignment of the business and IT strategy with regard to the definition as well as the review of and improvement in IT’s contribution to value.
2) Value Delivery:Within their service cycle, IT services in their entirety bring a benefit in respect of the corporate strategy and generate added value for the enterprise.
3) Resource Management:
Efficient management of resources such as applications, information, infrastructure and people, as well as optimization of the investment.
4) Risk Management:
Identification and analysis of the risks in order to avoid unpleasant surprises and to gain a clear understanding of the company’s risk preference.
5) Performance Management:
Monitoring and control of all performances in terms of their orientation towards the corporate strategy.
Looking now at Data Governance, some of the key areas that need to be considered, certainly to folks more used to IT Governance are:
1) There are usually 3 main drivers for Data Governance:
Pre-emptive: Where organisations are facing a major change or threats. Designed to ward off significant issues that could affect success of the company.
Reactive: Where efforts are designed to respond to current pains
Pro-active: Where Governance efforts designed to improve capabilities to resolve risk and data issues. This builds on reactive governance to create an ever-increasing body of validated rules, standards, and tested processes.
2) Data Governance can be implemented in 3 ways, often these may overlap (Tactical, Operational, Strategic).
3) There is certainly no "one size fits all" approach to Data Governance. Need to have a flexible approach to Data Governance that delivers maximum business value from its data asset.
Data Governance can drive massive benefit, however to accomplish this there needs at least to be reuse of data, common models, consistent understanding, data quality, and shared master and reference data.
Organisationally, different parts of the business have different needs, and different criteria for their data. A matrix approach is needed do these different parts of the organisation and data types are driven from different directions.
However, no matter how federated the organisation may be there will be some degree of central organization required. This is to drive Data Governance adoption, implement corporate repositories and establish corporate standards
The IPL Business Consulting practice have a flexible DG framework that can be tailored to help.
4) Communication & stakeholder engagement is key. No matter how brilliant the framework is, or how great your polices or DG council are, if you dont adequately engage and communicate with the stakeholders, the DG initiative will go nowhere.
5) Finally, all of this is only important if Information REALLY is a key corporate asset for your organisation ..... so ask yourself, is it?
So IT Governance vs. Data Governance?
In summary, Data Governance is a vital frequently overlooked component of an overall IT Governance approach. Remember the 5 commmon components of an IT Governance approach? Well, lets apply these in a Data Governance context and we see ...
1) Strategic Alignment:
Alignment of the business information needs and the IT methods and processes for delivering information that is fit for purpose.
2) Value Delivery:Delivering information to the requisite quality, time, completeness and accuracy levels and optionally monetising the value of information.
3) Resource Management:
Ensuring people, and technology resources are optimised to ensure definition, ownership, and delivery of information resources meet business needs.
4) Risk Management:
Information security, backup & retention and delivery are balanced against regulatory and accessibility needs as befits the company’s risk preference.
5) Performance Management:
Monitoring and control of Data Governance roles, responsibilities and workflows such that they meet the demands of the corporate strategy.
