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Data as an Asset in Balance Sheets: The way forward

How it began?

I was a data cynic until I met the Group CEO of a UK based- one of the largest personal injury law firms. It was a usual business meeting during early days of my career, where my idea was to understand competitive landscape for law firms. As a Research & Management Consulting organisation, I wanted to instigate a study on industry’s best practices. As expected, I was anticipating the names of some other law firms, but the conclusion from that discussion came as a shock to me. So it started like-

Me: So who do you think is your biggest competitor today?

Answer: Tesco

Me: What? Did I hear Tesco?

Answer: Yes. You heard it right.

Me: Could you please explain?

Answer: Yes, Tesco. Because the way it leverages its data to understand the behavior of its customers- they can change the shape of any business they enter into.

Tesco collaborated with Dunnhumby to leverage predictive analytics to gain deeper insights about their customers’ behavior. Their insights now help Tesco stock the right products, optimize prices, run relevant promotions and communicate personalized offers for customers across all contact channels. This alliance to make strategic decisions based on customer behavior has provided more value and loyalty-building experiences for Tesco.

This entire conversation encouraged me to initiate a comprehensive research on the Value & Valuation of Data and this virtual asset, if been part of companies’ balance sheets, may change the game completely going forward.

Data is the next Oil

In this era of omnipresent networks, proliferation of sensors and devices, and increasingly information-intensive applications the amount of global data more than doubles every two years[i]. With waves of data rushing over virtually all sectors of the economy, corporations need a new game-plan to create value from data. Today, the data has great potential to turn tables in business. It can empower citizens, change how government works, and improve the delivery of public services. It may also generate significant economic value. According to a recent report by McKinsey, going forward, data can help unlock $3 trillion to $5 trillion in economic value annually across various sectors of the global economy including education, transportation, consumer products, electricity, oil & gas, health care, and consumer finance.


Data is now widely being acknowledged to create value in various ways.











Some companies have started realizing the significance of data and have instigated reaping benefits from the same. Here’s a look at few of them:-










If Value- Why not Valuation

Now I started wondering, if the data is so important in today’s information savvy world, why should it not be a part of our balance sheets? Of course there would be some challenges for data to find a shelter for itself in balance sheets, the same way goodwill or any other intangible item would have found at the first place.  However, reaching to a value of data seems equally, if not more prudent than that of many other intangible assets like goodwill, patents etc.

As per Gartner[i], although data meets the formal, established criteria of a balance-sheet asset, archaic accounting practices disallow the capitalization of information assets on financial statements. As a result of this omission, many organizations are either neglecting or at best, struggling with the valuation of data- and probably resulting in the missed opportunity to boost companies’ assets & valuation and hence stock prices from it.

The ownership of the components of financial reports is largely demarcated. Elements of balance sheet generally attract the ownership and accountability, as they are visible to the outer world and investors take cues from them, for their investments in the company- directly or indirectly. For example, the cash balance is always being scrutinized by CFO and inventory is under purchasing manager’s consideration. This has helped these line items evolve with time.

Let’s explore how intangible assets are valued. Conventionally, intangible assets are valued through following accounting practices:

  1. Cost-based: Value is determined based on how much the asset cost to create. This method may be imprecise for data, because data is often created as an intermediate product of other business processes. Cost could be assessed based on cost of storage and other data infrastructure, but this would not arrest the full worth of the data nor reveal the differences in value between vastly different data sources.
  2. Market-based: Value is defined based on the market price of comparable goods in the market. In most cases, comparable data sources are non-existent. A market would necessitate a reliable & consistent concept of what makes data more or less valuable. Moreover, even if there were a well-formed data market, data sources rarely have the same content or quality.
  3. Income-based: Value is defined based on an estimation of future cash flows to be derived from the asset. This methodology may be suitable for valuing data. Income-based evaluation is the only type of method that makes sense for data. However, its unique characteristics may make its execution slightly challenging.

Challenges for “Data as balance sheet item”

Several features of data may make them difficult to value within a traditional balance-sheet accounting framework.

  • The data chain shown below helps identify some of the reasons why valuing data is so tricky.








Data’s value increases as it moves through the data valuation chain and to value it precisely, it is important to judge appropriately that where exactly the data lies in the chain. Also, the data is non-subtractable, meaning that its use does not prevent other additional uses, which means that, many different data valuation chains can be completed with the same original raw data.

  1. Further, in economics, traditional goods are transparent because the buyer knows what they are getting before agreeing to purchase but the valuation chain, on the other hand, could be completed only to result in no value at all.
  2. Datasets are heterogeneous, meaning market valuation is not always appropriate.
  3. Estimations of the return on investment in data (the income derived when firms invest in data and use them in their business) can be highly ambiguous.
  4. Data does not have a physical existence and hence may be considered to have an inestimable life when equated alongside tangible assets. However, data can depreciate rapidly if it is readily outdated (e.g. unstructured social media and financial trading data).
  5. Some data has additive value, that is, the value of the original data increases exponentially and not just incremental, as more data is accrued (e.g. clinical, DNA and climate data).

Potential Valuation Techniques

Today there’s a performance gap between the realized and the potential value of information but CIOs can help­ to close that gap and generate more value out of their information assets by applying infonomics practices to corporate data. Going forward, one of the following practices or possibly a technique altogether different from the below mentioned ones, may be used to value the data available within an organisation. The researchers are still working and trying to dig out innovative ways for the same and its time that the accounting gurus should sit together and brainstorm to lay out a plan for the valuation of data in an organisation.

Possible promising ways of valuing data:

Cost value of information. This model may measure the cost of acquiring or replacing lost information. This is the way valuation experts value most intangible assets that don’t have a discernible market value.

Intrinsic value of information: This model may quantify data quality by breaking it into characteristics such as accuracy, accessibility and completeness. Each characteristic may then be rated and tallied for a final score, which inturn may be assigned a financial value.

Economic value of information: This model measures how an information asset contributes to the revenue of an organization.

Market value of information: This model may measure revenue generated by selling, renting or bartering corporate data, one of the best ways to value an information asset.



Today, most business leaders and IT executives increasingly vouch about how their company’s information is one of their most important assets. In order for an organization to become information-savvy, it must initiate by internally recognizing information as an actual asset. The old adage goes, “You can’t manage what you don’t measure,” and corporations need to start inventorying and measuring their information assets.

As humungous amount of data is created and companies potentially making commercial use of it, it does make a lot of sense now to give it its due place in balance sheets and before the same happens, a need has arisen today for a proper and feasible method to value the data. With IoT gaining pace and a huge amount of data waiting at sidelines & ready to cuddle us in near term, it calls for a strong case to indulge ourselves in the valuation of data, before it is too late!









Going by the words of W. Edwards Deming, statistician, professor, author, lecturer, and consultant- “In God we trust. All others must bring data.





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