Data is not an asset. Not yet.
Thinking formed in practice, published as part of the Bearing & Course Points of View library.
The assumption that data is inherently valuable has become one of the more expensive misunderstandings in modern organisational life. Boards declare it a strategic asset. Strategies are built around it. Investment follows. In too many cases, the data sits largely unused, poorly understood, and quietly costly to maintain.
Possession is not value. That distinction sounds obvious. It is almost universally ignored.
I spent a significant part of my career as a senior executive in the public sector. In that time, I watched the data conversation go through several cycles. Each one arrived with genuine conviction and considerable investment. Each one produced less than was promised. The gap between what was said about data and what actually happened with it was one of the more consistent features of the environments I worked in.
Australia's Data Availability and Transparency Act is a useful case in point. It was introduced on a straightforward assumption: make government data easier to share, and public value will follow. The statutory review tells a different story. Years after introduction, the gap between intent and operation is wide. That is less surprising than it appears, once you understand the incentive structure. Agencies carry the privacy, legal and reputational risks associated with sharing data while receiving little direct benefit from doing so. Refusal is easy, largely consequence-free, and often administratively safer than approval.
Incentives shape behaviour more reliably than policy design.
This is the part of the data conversation that almost never gets discussed seriously. Every strategy I have seen talks about governance, quality, architecture and access. Very few ask the prior question: why does the organisation holding the data have any reason to make it useful? If the answer is unclear, or if the honest answer is that they do not, the rest of the strategy is built on an assumption that will not hold.
The same dynamic appears well beyond government. Financial institutions hold decades of transaction data. Healthcare organisations hold clinical records at extraordinary scale. Logistics businesses hold movement and demand data that could reshape how they operate. In each case, the data exists. In each case, the proportion that is actively used to improve decisions, services or outcomes is smaller than the volume invested in collecting it would suggest.
A mortality data product developed by one government is instructive. Financial institutions have clear obligations to ensure deceased individuals do not remain active in their systems. On paper, current death data should be commercially valuable. In practice, demand was weaker than expected. Institutions already relied on family notification, estate processes and internal controls embedded in their own operations. The data existed. The use case existed. The incentive to change an already functioning system did not.
Useful data begins with a clear audience: who is expected to use it, and for what decision. Purpose shapes everything downstream. Governance matters because someone has to carry the risk, approve access and answer when something goes wrong. Quality matters because data shaped by the assumptions of one system rarely transfers cleanly to another. And incentives matter because none of the other conditions hold if the organisation responsible for the data has no compelling reason to invest in making it useful.
Data becomes an asset when someone uses it to make a better decision. Until then, it is a cost.