Data: Why Your Most Valuable Asset Needs a Rulebook

In the modern enterprise, data holds a precarious position: as both the most valuable asset and the most significant source of risk.

Left unmanaged, data can quickly become inconsistent and insecure. Data governance is vital for organisations to build trust in their data and make informed decisions, particularly in the context of AI and ML.

The long-standing metaphor declaring “data is the new oil” is beginning to show its age. While the phrase successfully captured data’s immense value, the comparison is flawed.

While oil is a finite resource with inherent value and its risks, while significant, are primarily physical, data is different. An infinitely reusable commodity, its value is contextual – but its risks can be existential as, when ungoverned, data turns from an asset into a liability.

With AI booming and ever-tightening privacy regulations like GDPR and the CCPA at play, leaving arguably a business’ most critical digital resource without a rulebook is out of the question.

But, the real value of data comes not from its raw existence, but from the trust that is forged through a robust, intentional system of data governance.

The data shift

Historically, data has been treated as a by-product of business. Now that narrative is shifting, with data less of the exhaust to the powerful machine but the fuel.

Using ungoverned, low-quality fuel in a high-performance engine – especially when it comes to AI – is an invitation for disaster. Governance can be viewed as a way of refining that fuel, ensuring the information powering the most critical decisions is understood, consistent, secure and trusted.

“We live in a mobile-first and cloud-first world,” Microsoft’s CEO Satya Nadella said recently.

“Computing is ubiquitous and experiences span devices and exhibit ambient intelligence. Billions of sensors, screens and devices – in conference rooms, living rooms, cities, cars, phones, PCs – are forming a vast network and streams of data that simply disappear into the background of our lives.

This computing power will digitise nearly everything around us and will derive insights from all of the data being generated by interactions among people and between people and machines. 

“We are moving from a world where computing power was scarce to a place where it now is almost limitless, and where the true scarce commodity is increasingly human attention," Satya says.

His vision is one that epitomises how data governance is no longer just about controlling access or compliance – it’s about stewarding an unprecedented volume of data to maximise value while safeguarding privacy and security.

The data governance cultural shift

Achieving the high level of trust needed requires a profound cultural shift and a collective agreement to treat information as a primary corporate asset. 

Maria C. Villar, Managing Partner at Business Data Leadership, who served as Global Vice President of Data and Analytics at SAP until last year, says this requires deep commitment. 

“Good data governance is not a project, it’s a programme," she says in The Chief Data Officer’s Playbook by Caroline Carruthers and Peter Jackson. “It requires a change in culture and mindset, where data is treated as a strategic asset across the entire organisation. When you manage data as an asset, the value you can derive from it multiplies.”

Speaking about her own book, 'Managing Your Business Data: From Chaos to Confidence', and the importance of data governance, she reiterates: “Good data governance is like water. It’s the pipe. It’s the electricity that runs every part of the company.

"So the more confidence you have in the underlined foundational data that you have, the faster you can make decisions and the faster you can really go after your customers with more information about them. 

“But governance is really more than just technology. I think that’s an important point.”

Both she and Satya acknowledge the importance of humans in this equation, and the human element of governance where the real work begins.

As Maria emphasises, a successful data governance programme distributes responsibility away from a central IT function and embeds it within the business itself, establishing a network of people who understand and are accountable for the data in their domain.

From a digital swamp to curated library

Without a human-led approach to governance, the corporate data landscape can become fragmented and inaccessible, with pockets of valuable information trapped in siloed systems. Different departments can also use conflicting metrics, leading those in the boardroom away from decisive action. 

Analysts and data scientists, who should be uncovering breakthrough insights, spend up to 80% of their time simply trying to find and clean the data they need, a CrowdFlower Data Science Report finds.

Data scientists spend about 60% of their time cleaning and organising data and 19% collecting data sets – showing that, without effective data governance, organisations face disorganised, inconsistent and poor-quality data, making preparation for analysis time-consuming.

From the perspective of Randy Bean, BCG Senior Advisor, author and data speaker, humans are at the heart of whether data governance succeeds – technology is necessary, but people, culture and communication ultimately determine the value organisations get from their data.

“The real challenge in becoming data-driven is cultural change, not technology,” he shares.

“Data is something that’s a primary asset of the organisation. It’s not a project. It’s not a little thing within some part of the organisation, it should be one of the things that’s most central, just like you think of the finances of an organisation.

“It’s that shift in thinking to think that data is something that matters to all of us, as opposed to data is something that’s relegated to some group that we all only call upon when we need them.”

Having the boardroom on board

Ultimately, the most compelling case for data governance is a strategic one. In the AI era, the quality of governance will directly determine the capacity to compete. Biased or inaccurate data leads to biased and inaccurate AI-driven outcomes, exposing a company to reputational damage and legal jeopardy. This makes governance a top-tier boardroom concern. 

As Arvind Krishna, CEO of IBM, emphasised recently, the future of AI hinges on this very issue. He states that AI “has to be built on a foundation of trust and transparency.”

That foundation is data governance. It provides the auditable trail of where data came from, how it has been transformed and who has accessed it. It’s the licence to operate that gives leaders the confidence to deploy powerful AI tools responsibly. 

For a modern leader, advocating for investment in governance is as fundamental as advocating for investment in new technology – because one cannot succeed without the other.