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Data governance a central strategic resource
There needs to be concerted efforts to create and enhance the level of awareness about the importance of data as a business asset, especially for organisations that hold huge volumes of operational and customer data.
“This is required across the organisation right from the board level to the operational level,” said Mr Mark Jansen, Partner, Data & Analytics Leader at PwC Singapore.
Citing an earlier PwC study that polled some 2,100 C-suite leaders, business unit heads and senior vice presidents, Mr Jansen said senior management want to be more data-driven but acknowledge there is more to do.
About two-thirds (61%) of respondents say their own companies’ decision-making is only somewhat or rarely data-driven.
Data has become a central strategic resource for all organisations in the digital era.
With fast-moving developments in analytics, how successfully and efficiently companies harness their mass stores of data can determine whether they succeed or fail in the disruptive market place.
What is data governance?
Data governance is the overall management of the availability, usability, integrity and security of data within organisations.
According to PwC, a sound data governance programme could include:
- a set of standards, policies, and processes that manage the quality, consistency, usability, security, and availability of information across the enterprise;
- a governing body or council that oversees the execution of these policies and procedures; and
- an interaction model that defines when, where, and how the organisation’s leader responsible for data engages with various business and IT groups.
“Given this scope, employees from every grade of the organisation has a role to play in data governance,” said Mr Jansen.
Who owns data governance?
Industry executives say sound data governance is not the sole responsibility of people at the top, although they could help to set the right tone.
“First and foremost, there must be senior management sponsorship of effective data governance, much like compliance, in order to dedicate the resources required to run such a function,” said Kelvin Tan, Head of FinTech & Data, Singapore Exchange.
“Next, the technology systems, tools and data architecture must be put in place such that the data can be efficiently managed.
“Finally, there must a cultural shift among all employees to ensure that data governance is adhered to and even commended,” said Mr Tan.
PwC said there is no one answer to the question of identifying roles and responsibilities.
While the top management sets the tone, operational management has significant responsibilities in day-to-day data management.
“From our experience, there is no one model that fits all companies,” said Mr Jansen.
He said broadly speaking, the responsibility rests within the remit of Chief Operating Officer (COO) and Chief Data Officer (CDO).
Depending on the part of the organisation that is leveraging data and analytics, the CDO or COO takes the lead as the case may be.
The COO is typically responsible where operational improvement is the main objective of a data governance programme, said Mr Jansen.
How can organisations improve data governance?
To improve data governance, experts say policies need to be complemented with effective tools that make it easy and convenient for the end user to adhere to such policies.
These include tools such as data dictionaries, business glossaries and data models that define the data transformation.
“For data governance to ultimately be effective, it must be addressed by a data-driven organisation culture, or else it will be a never-ending game of ‘cops and robbers’ that will lead to a deterioration of productivity, the very opposite of what data governance strives to achieve,” said Mr Tan.
He suggests that data should also be centralised into a data warehouse to help the data management team better govern.
PwC names three key things that organisations can do to improve data governance:
- Cultivating a data-driven culture where there is an increase in the level of decision-making based on data.
- Making data a day-to-day business issue, adopting this as a problem for the organisation overall and not just the technology unit.
- Building the mindset that data governance is not a one-off project and devoting more efforts to monitor the operational aspects of data governance as well as keeping the policies or procedures up-to-date and relevant.
Observers say good data governance could also be linked to the organisation’s cybersecurity strategy.
The risks of data breaches have escalated tremendously as businesses and consumers become more connected through digital platforms.
This has also multiplied the costs for companies that fall victim to situations where their data is compromised or exploited.
“Companies can put more effort to protect the areas they deem as high risk that will cause a great impact to the business when breached,” said John Lee, President of ISACA Singapore Chapter, which represents information systems governance professionals.
“But it is impossible to implement the same level of protection for all the assets,” he said.
“A cyber security strategy aligned with the business strategy will ensure that the critical areas and information assets are prioritised and appropriate protection measures put in place,” said Mr Lee.
- This series is brought to you by CPA Australia to share knowledge on topical issues relevant to business, finance and accounting.
Effective data governance
An effective data governance programme requires an appropriate balance of people, process and tools.
• To start with, breaking the data governance journey into small phases with clear tangible objectives is helpful to keep the momentum on.
• Engaging with the business from the early stages of the initiative is another important factor for successful implementation. Initial resistance from business users could be overcome by explaining the business case and rationale well in advance of starting the programme.
• Organisations should always be clear on the return on investment from data initiatives. There is always a risk of analysis paralysis. A start should be a clear assessment of what data is critical. Beyond this is what data is available that might further enhance the organisation’s capabilities that perhaps is not captured today but can now be captured via new data technologies such as natural language processing, and behavioural and sentiment analytics.
• Organisations should leverage appropriate tools for accomplishing data governance objectives. Implementation of a tool alone is not going to resolve the issue. It needs to be accompanied by appropriate management support and policies and procedures.
• The framework and tools selected for data governance should support scalability and flexibility as the function evolves and enhances its coverage.
• Similar to any transformation journeys, data governance needs to have a strong change management programme embedded into it to prepare, empower and support all users who are impacted by and have a role to play in data governance.