The value of data governance in 2024

According to InfoGov.com, the principles of Information Governance (InfoGov) empower us to refine the quality of our data, shield sensitive information from prying eyes, and foster an environment of transparency and trust.

Gartner defines data governance as the specification of decision rights and an accountability framework to ensure the appropriate behaviour in the valuation, creation, consumption and control of data and analytics.

Gartner also posits that data governance best practices comprise setting the right governance foundation, building an effective governance structure, designing and deploying governance policies and standards, evaluating and improving performance, and establishing a process of iteration and learning.

The recently concluded AI for Business Leaders Summit in Kuala Lumpur and Singapore highlighted the importance of data governance in the digital era, and even more importantly, towards the continuing development and adoption of artificial intelligence.

Importance of data governance in 2024

Kelvin Looi, VP of Data, AI & Automation Technology Group, IBM APAC, noted that data governance has always been important. In 2024, the deployment of generative AI will be influencing more attention to data governance in 2024.

“As we know, Gen-AI is powered by data in its foundation models. Data in a Large Language Model is an example. Gen-AI applications do not differ from any other IT applications that use data. Garbage-in-garbage-out; one needs to secure the data, protect the privacy of customers, and comply with privacy and other government regulations.,” he stressed.

Echoing the sentiment, David Chan, managing director at AdNovum Singapore, opined that in 2024, amidst the evolving data landscape, organisations must prioritise data governance as it is essential for navigating complex data management challenges in a rapidly changing business environment.

Aligning IT with business outcomes is one of the key challenges identified by 22% of Asia Pacific decision-makers, according to Forrester. He posits that a clear data governance framework is, therefore, necessary to address concerns like data sprawl and ensuring integrity from end to end.

“Such governance guarantees standardised approaches, transparency, and accountability, transforming data use cases into tangible business value. With the recent boom in generative AI, a structured data governance program is crucial to handle the copious amounts of data being generated, contributing to analytics and machine learning,” he commented.

Struggles in the data governance journey

Make no mistake, organisations will struggle to implement, execute and sustain governance processes, as noted during dialogues with finance and technologies attending the AI for Business Leaders Summit.

According to Looi, one of the top reasons is the lack of senior leadership support. Companies where data governance is active in the CEO’s agenda do well. “Without senior leadership support, you won’t get the resources and commitment,” he opined.

Clear data ownership and accountability is a factor, he added. “You need clear sight on who is responsible for which data and make them accountable. To get them committed and sustain the process, they need to understand the values this data generates for the company,” he elaborated.

“Having a robust and comprehensive data governance framework with the right technology tools to make the process more efficient and effective will help too. There are many other factors, but one more to point out is the lack of communication and collaboration across the company on the importance of data quality and governance.”

Kevin Looi

For his part, Adnovum’s Chan attributes the hurdles to a misalignment between IT and business outcomes. He points to the absence of a standardised approach to data governance as further complicating matters.

According to Gartner, 55% of decision-makers acknowledge their struggles with translating data use cases into tangible business value. Transparency and accountability issues, such as unclear data collection processes and ownership, also further complicate effective governance.

“To overcome this, addressing data ownership, defining roles, and outlining processes for collection, curation, and qualification is crucial towards unlocking data's full potential in business operations,” suggested Chan.

Lasting regulatory influence

Asked which government-led data governance activity in Asia will have a lasting (and significant) impact in 2024 and beyond, Chan cited Singapore's "Data.gov.sg" platform, which provides access to open data, and holds potential for regional impact.

He explained that its expansion to other countries could potentially broaden transparency and spur innovation across Asia. Additionally, collaborative efforts like the ASEAN and APEC Data Governance Frameworks that aim to harmonise regional data practices are also good indicators of collaborative efforts.

“Ultimately, Government-led data governance's lasting impact hinges on effective enforcement, public-private collaboration for resource leverage, and ethical considerations like balancing data accessibility with privacy to build trust and ensure sustainability,” he continued.

In February 2024, ministers from Japan and ASEAN held a session on the Future of data governance in Asia and the operationalization of “Data Free Flow with Trust (DFFT)” in Singapore.

They discussed the sustainable and inclusive development of data governance in Asia. The ministers shared their data privacy and protection regulations in their respective countries. They also discussed future collaborative models for cross-border data sharing.

Looi says that’s leadership from the top and will have a lasting impact on data governance collaboration and DFFT across these countries, to support the ever-growing digital economies that are intertwined.

Data governance’s boss

It is understood that the chief data officer (CDO) has overall responsibility for data-related functions including data management, ensuring data quality, and creating data strategy.

However, not every organisation in Asia has the luxury of having a CDO. Looi posits that it depends on the size and structure of an organization. He opines that the CDO can have a data governance leader who handles the day-to-day data governance operation with support from data stewards.

“In a big organisation with many business units, you can form cross-business or cross-functional data governance committee chaired by the CDO with data stewards supporting their respective business or functions,” he continued.

A 2023 Harvard Business Review article, however, points to research suggesting is ineffective because the CDO role is poorly understood, and incumbents of the job have often met with diffuse expectations and short tenures.

Gartner says the most successful companies establish cross-functional teams for their data and analytics governance initiatives. Chan concurs adding that effective data governance requires collaboration among various stakeholders in an organisation.

“C-Suite leaders provide strategic vision and allocate resources for a robust framework, emphasising a data-driven culture,” he added. “Data Governance or IT teams develop and implement policies, ensuring consistency and quality. Employees adhere to governance policies, provide feedback, and ensure ethical data use.”

“Each stakeholder plays a critical role at different stages, necessitating a collective effort for successful implementation, execution, and long-term maintenance of data governance practices within the organisation.”

David Chan

Lasting data governance

Given the evolving nature of technology, practices and regulation, is it possible to achieve lasting lasting data governance? And if yes, what needs to happen?

Chan believes that for an enterprise to achieve lasting data governance, it is crucial to establish a transparent and accountable data governance framework tailored to the organisation's specific business needs and objectives on their use of data.

“By contextualising data challenges within the broader business goals and outcomes, organisations can determine the relevance of data in everyday activities,” he outlined. “Additionally, ensuring data integrity, implementing data quality metrics, and adhering to regulations are essential components, to not only safeguard the data but also enable the organisation to unlock the full potential of insights and business value across diverse use cases,” he remarked.

For his part, Looi says for an enterprise to achieve lasting data governance, name one thing that needs to happen. Having leadership commitment and a robust framework are important to achieving sustainable data governance.

“The framework needs to be adaptable to business changes and have clear policies, procedures, roles, and responsibilities with supporting tools. These steps will ensure the allocation of resources, and removal of obstacles to embed data governance throughout an enterprise’s operations,” concluded Looi.