Return on data assets: A new way for leaders to think about data and the balance sheet

Return on data assets:

A new way for leaders to think about data and the balance sheet

In today's digital society, one could easily argue that data is the most valuable asset for any organisation. Companies like Uber and Netflix consume billions of data points to constantly improve their understanding of customer trends and behaviour, while simultaneously improving the overall user experience. Without data, there would be no ride-sharing option, and creating content that captivates specific audiences or geographies would be impossible. The irony, however, is that despite its apparent intrinsic value, data assets are still not captured on the balance sheet of any organisation. The reason? It turns out that it's incredibly difficult to quantify the monetary value of data accurately. In order to do so, business leaders are required to think outside of the box.

While technically, data meets the minimum acceptable criteria for a balance sheet asset, current accounting practices still prohibit organisations from capitalising data as an asset. There are two main reasons for this: first, current practices introduce certain practical inefficiencies, and second, a lack of ability to establish a direct link between data and measured business outcomes. The latter of the two leads to priceless data assets being either under-utilised or disregarded altogether in the organisation's strategy to build new or alternative revenue streams. The first step towards avoiding this trap is for organisations to create a culture of visibility and access to data that can supplement and improve the thought processes of everyone. Data must become the secret sauce that inspires and empowers people to drive revenues and enhance profitability. Data cannot be added to the balance sheet unless it underpins the value-creation process across the entire organisation.

The question becomes how to measure this movement. Wall Street analysts use a metric called Return on Assets (or ROA) to help assess how efficiently a company uses its assets to generate profit. A high value for ROA means that a

company is more efficient at leveraging its assets to produce positive returns. ROA provides a crucial benchmark for CxOs and forces them to consider the strategic implications of operations on profitability. However, since data is not reflected on the balance sheet, current metrics still fail to capture the returns from investing in data practices.

Proposing a new financial metric: Return on Data Assets

Considering the shortcomings of existing metrics like ROA, it is clear that an alternative approach is required for companies to quantify the returns generated from using their data. One possible alternative is to consider the Return on Data Assets (or RODA). The foundation of RODA is to look at the income driven by data assets (both direct and indirect) and compare that with the costs of creating and curating the data assets.

In this scenario, we can classify a "data asset" as any object that provides information (e.g., a dataset containing customer records) or a service that augments information to deliver insights (e.g., a model used for risk assessment). Having complete visibility of how data is used across the organisation becomes essential to construct a clear framework for comparing project outcomes. The basic formula for RODA is as follows:

RODA =(Yield from Data Assets)/(Cost of Data Assets)

Taking this formula, companies can quantify their ability to monetise data assets cost-effectively and efficiently. The principles of RODA require that CDOs optimise both the yield from data assets and the cost of those assets. On the income side, CDOs must focus on use cases where data can be leveraged to drive the maximum business value (direct or indirect). Looking at the cost, CDOs must work to construct a data strategy for the most cost-effective way to create, maintain and secure data assets. Existing data assets must either be monetised or decommissioned and replaced to create an ecosystem of high-productive data assets.

At the micro level, RODA can help CDOs and business leaders prioritise projects and use cases. At the macro level, it can help CFOs allocate capital more effectively and help CTOs make better decisions on which technologies to implement. Simply put, if RODA is greater than the cost of capital, a project or use case creates positive economic value. Conversely, if the cost of capital is greater, a project or use case erodes the bottom line and is not worth pursuing.

Conclusion: Understanding how data is driving the business

Adding data to the balance sheet as an asset means completely rethinking the organisation's approach to evaluating and quantifying the value derived from its data, whether direct or indirect. Companies like Uber likely didn't have to undergo significant transformation to quantify its data asset value, but that's because data was already embedded as a value driver at the core of the corporate strategy. Most organisations, however, still struggle to understand how data is powering the business, let alone capturing it as a tangible asset on the balance sheet.

It's vital for any organisation serious about building a data asset strategy to prioritise establishing a simple yet clear financial metric to quantify the tangible value of its data assets. Whether it's fundamental or financial, data has always been and always will be the core driver of value to the organisation's bottom line. It's time to move data to its rightful place: as an asset on the balance sheet.

Eon Retief, Technical Director, Financial Services, Databricks

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