“Virtually everything in business today is an undifferentiated commodity, except how a company manages its information. How you manage information determines whether you win or lose.” – Bill Gates
An organisation’s business decisions and data lifecycles are independent and also inter-related and inter-dependent at the same time. As your organisation’s data and information matures and improves during its lifecycle, so should the business decisions based on this data.
For this progression to successfully mature and improve there must be an organisational data governance program in place. The purpose of the program is to establish and maintain a sustainable data and information framework providing clarity of purpose, data management processes, and a clear definition of roles and responsibilities.
The more time and cost your organisation spends on looking for and/or manipulating data for decision making, the more the real value of your business decisions is eroded.
Independent global research and numerous surveys are telling us “people across many industries, are spending up to 50% of their time looking for required data, ensuring it is correct and manipulating its format to enable its use across the organisation in the decision making and planning processes”1. This circumstance is far from ideal. It indicates acquired data is being used almost immediately for a particular purpose, then discarded with no consideration for the future.
Many organisations don’t realise the value of data and information as an organisational asset and so will never fully exploit its true value. Generally organisations have four core assets; financial, human, physical and data and information. Often, only the first three of the four are represented as a full member of an organisation’s executive management team and accountable to the Chief Executive Officer.
So why, more often than not, is data and information not a full member of the executive management team? Why does it lag behind the other three in importance? Why does it have a line of accountability either at a lower level or is never clearly defined?
Is it because the real value of data only comes to the forefront when business decisions require trust and confidence in the organisation’s data and information assets? Or is it because the value of data as an organisational asset is taken for granted or just not understood?
Consider the following from Data Driven by Thomas C. Redman, 2008;
“No other asset offers the potential to align an organisation on common tasks, be created for reuse, or is built into many different products and services. The properties of data as an organisational asset, has no counterpart in any other of an organisation’s assets”.
As the statement by Redman implies, data is an immensely valuable organisational asset. However if this is true, why does it become the most neglected and poorly maintained of an organisation’s the four core assets?
When asked “If your organisation managed its financial assets the same way it manages your data and information assets, what could your organisation look like?” as part of a global survey of data management practices2, a leading Australian Oil and Gas Executive answered, “We’d be broke in a week.”
It is apparent many organisations don’t comprehend data as an organisational asset, or why data governance is important to its health and quality. However, whole industries and organisations are being forced more and more into a disruptive and rapidly evolving digital world, which demands the use of accurate data and timely dissemination of information.
To make informed and timely decisions in accordance with organisational business objectives, business leaders want access to trusted, clean data, but often have misguided concepts on how to get it, how to manage it and, ultimately, how to value it as an asset. They don’t understand why they need data governance to successfully ensure they get trusted data when and where the organisation needs it.
So what is data governance? Just like financial governance, data governance is the practice of organising and implementing a framework of policies, procedures and standards to effectively manage the quality and usage of data and information.
Data governance is one of the ‘pillars’ of data management. It should always be considered hand-in-hand with data stewardship (the implementation of data management processes in accordance with governance policies, principles, and standards) in order to attain a sustainable data quality capability across your organisation.
Initiatives to implement data governance are often seen as either bureaucratic organisational or technology efforts, driven from a corporate level with a top-down emphasis. While well intentioned, this approach is often met with resistance and suspicion from information users within the organisation. As a result, it falls short of expectations when implementing and sustaining a strong data governance program which will deliver trusted, high-quality and clean data to the operational business.
Data governance is not meant to solve all business or IT/IM problems in your organisation. The main goals and objectives of data governance are to:
- Define, approve and communicate data strategies, policies, standards, architecture, procedures and metrics
- Track and enforce conformance to data policies, standards, architecture and procedures
- Sponsor, track and oversee the delivery of data management projects and services
- Manage and resolve data related issues
- Understand and promote the value of an organisation’s data assets
A data governance program should not create bureaucracy. It should establish a way for the information users to work with data and information to make your organisation’s operational business successful and create sustainable value. The way forward should be based on four core strategies:
- Create (or elevate) the role of CIO as a full member of the executive management team
- Create an enterprise data management board
- Establish an enterprise wide data management program and strategy
- Reduce costs associated with poor data quality and data repair by investing in quality at the data creation point or source
Data Governance Success: organisational commitment
Data governance success demands not only operational business attention, but also high-level organisational commitment. Data governance policies and processes are not just a ‘tick-in-the-box’ on a corporate charter; they are business as usual fundamentals (just like HR and Finance policies) which everyone in your organisation must sign up for to create long-term sustainable business value and ensure a competitive advantage.
Data governance must include clear descriptions of accountabilities, tasks and activities which an organisation must perform to achieve and maintain a known level of data quality. These include:
- A framework of principles, policies, standards, roles and responsibilities and processes to enable effective management of strategic data and information assets
- Definitions of data governance accountabilities, tasks and activities which are described and documented with assigned roles and responsibilities (e.g. executive and senior management, data stewards, data quality analysts, data governance and/or stewardship leaders and team members, information users etc.)
- Reference to people and organisational capability, processes and controls, and technology and architecture
- Allowing the business to take proper and responsible ownership of its data and information assets where people clearly understand their role and the data and information they are responsible for
- Definitions of the tasks and activities that the business must perform to achieve and maintain a mandated level and standard of data quality and performance
Organisational commitment to data governance, as an operational business issue, must come from the Executive and Senior Management level and be ‘championed’ by the information users within your organisation. It is the information users who have the deepest understanding of the operating business, its events and vocabulary, and the data hierarchies and associated business rules.
Most importantly effective data governance does not come together all at once. It must be given the proper support and commitment to develop and mature over time, to become a core business process with improvement objectives which are continually revised to reflect changing business objectives, and to be used as criteria in managing data improvement.
Ultimately, good data governance will be successful within your organisation when the correct balance between people and organisational capability, processes and controls, technology and architecture and accountability between data producers and consumers is achieved.
- Redman, T. (2008). Data driven. Boston, Mass.: Harvard Business Press.
- Experience Matters (2015), The barriers to and the benefits of managing data, information and knowledge as a business asset. Available from: http://iaidq.org/publications/webinars/price-2015-09-23/