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What is your data worth? Insights for CPAs

Data value is driven by its context. This article identifies key considerations in assessing the value of data and its role in value creation.

This article is part of our Mastering Data series. This series examines the digitization underway in Canada's economy, why it's important, the data governance issues it creates, and how to address them. It also looks at the role you can play as a CPA in guiding your organization through the transition.

Read this article to learn:

  • perspectives to consider when assessing the value of data
  • the relevant characteristics of valuable data
  • the dynamic nature of data
  • additional concepts for valuing data
  • the roles of CPAs in valuing data

Data is central to implementing the digitization strategies that drive value for many businesses today. Increasingly, decision makers need to make investments to support the data collection, storage, acquisition and tools needed to enable digital value creation. Yet there is no simple answer to the question "What is data worth?" to guide leaders in their investment decisions.

Value is in the eye of the beholder

In fact, "it depends" is often the best initial answer to questions about data's value. This is because there are numerous perspectives from which data's value can be determined. Key examples include the following:

Value creation decision-making perspective: Data can be used to optimize existing products/services by using data-driven insights to improve performance. Data can also be a product that directly enables transactions that could not occur in the absence of the data.

Buying, selling or licensing data perspective: What are others willing to pay to have access to the data or its derived insights?

Valuation perspective: Is there a market for the data or is it solely for internal purposes? If there is a market, are there specific valuation methods that are preferred for different scenarios?

Taxation perspective: What factors should be considered in assessing the value of data from a tax perspective under different time horizons?

Financial reporting perspective: Like other intangibles, data that meets certain criteria can be disclosed at cost. CPAs should consider whether their organization could benefit from voluntarily providing broader disclosure about their data portfolios, how they are being managed, and the role of data in value creation for the organization.

Risk and risk management perspective: Data that is not managed properly can be a potential liability, rather than an enabler of future value streams. In such circumstances, mismanagement of data can destroy value instead of creating it.

Public policy perspective: Around the world, many governments are reassessing how to encourage innovation through digitization of existing records while ensuring that data is regulated to protect citizens and to ensure it is taxed appropriately.

Characteristics of higher value data

Within the accounting paradigm, data is a specific category of intangibles. Two key considerations are relevant to assessing the value of data, and intangibles in general:

Tradability: Can the data be separated from the organization and sold or licensed to another organization? Tradable data can be sold or licensed, otherwise the data only has relevance to its owner.

Multiple simultaneous value streams: Can the data be used for multiple purposes within and outside the organization, or at the other extreme, is it limited to a single use within the organization?

While data has characteristics in common with other tradable intangibles, it also has unique characteristics, as summarized below.

Characteristics of data that are common to other intangibles:

  • high initial creation cost but low replication cost (although infinite reproduction may diminish commercial value in the long-run)
  • little inherent value — value potential depends on ability to enable other value streams
  • value creation potential depends on complementary business assets and context
  • potential ability to enable multiple simultaneous value streams in multiple contexts

Characteristics of data that are unique relative to other tradable intangibles:

  • growing exponentially faster than any other category of intangibles
  • for many organizations, value creation potential depends on emergence of relevant data value chains (see below)
  • legal protections and obligations are not as mature as other intangibles assets; some types of data are easy for competitors to emulate
  • risks related to privacy and protection of personal data
  • given the dynamic nature of data, potential value may be time limited if not continuously refreshed
  • cyber security and regulatory consequence are significant

Other factors to consider that will influence value potential include:

Cost to produce: How much does it cost to produce the data or analysis, including all direct, indirect and overhead costs? Hardware and software costs should be considered.

Exclusivity (vs broadly available): Are there competitors who provide the same or similar data/insights? Will this transaction be exclusive, or will the data/insight be sold to others?

Relevant life (measured in time): How long until the data/insights are no longer or less relevant? Longer relevance increases the value of the data/insights.

Ultimate commercial impact: How significant is the impact of the data/insights expected to be to the purchaser? Is the use of the data/insights expected to create little or significant value for the purchaser?

The dynamic nature of data

Increasingly, value creation from data takes place along a data value chain  that involves third parties, rather than within the boundaries of a single organization. This is due in part to the emergence of specialist firms involved in data collection, analytics and brokerage.

Graphic of the big data value chain, showing data collection and data access as upstream components and data analytics as the downstream component.

Data portfolios created within these value-chains are highly dynamic. They are continually evolving as new data is created, stored and analyzed. Further, data is typically a flow asset, which depletes over time, rather than a stock asset, which maintains its value over time. Portfolios that are not continually refreshed quickly become stale-dated and lose relevance.

The dynamic nature of data is reinforced by the following factors:

Technological changes that make it easier to create, store and analyze data to derive insights

Regulatory developments affecting the ability to use certain types of data for various purposes. This is particularly true for personal data, regulations for which may be different or change across different jurisdictions and over time. There is currently a patchwork of jurisdictional issues nationally and internationally that is unlikely to change in the near term.

Competitive and security threats that require constant vigilance to safeguard the data.

Attempts to model value streams from data must ensure that the model fully reflects the dynamic nature of the underlying data.

Potential CPA roles in valuing data

Whether you work in the private, not-for-profit or public sectors, you are probably looking at new ways to harness data – including how to value it. CPAs must use their foundational proficiencies in business expertise, judgment, skepticism, analysis and systems to help answer the question: what is data worth?

Professional judgment is central to valuing data. CPAs need to consider not just their self-interest and obligations to their employer, but also their obligations to the public good to ensure that the value assigned to the data is fair.

Building on this publication, we will continue to support CPAs who are involved with exploring issues around data, its value in relevant contexts, and its role in creating value for their organization. Stay tuned for future publications arising from our Data Governance and Value Creation workstreams. 

Mastering Data series

More information is available on the critical role CPAs can play in mastering data, including the following articles: