ICAEW.com works better with JavaScript enabled.

Customer data - Buried treasure


Published: 10 Jan 2017 Updated: 01 Nov 2022 Update History

Exclusive content
Access to our exclusive resources is for specific groups of students and members.

While it may not be the most obvious asset, data can be worth a staggering amount.

In 2015, Caesars Entertainment Operating Co, which owns the famous Caesars Palace casino brand in the US, filed for bankruptcy protection over $18bn of debt. Last summer, it tried to block creditors who had sought to sue its private-equity backed parent company. While Caesars Entertainment offered $4bn to save the casinos, the creditors argued its worth was $12bn. One of the areas where high value had been placed? The data of 45 million customers held in the Total Rewards Loyalty Program, which Information Age reported to be worth $1bn – more than any of the Caesars’ Las Vegas real estate.

Information Age’s assertion that “data is now one of the primary assets companies are after in an M&A, in some cases more so than the people, intellectual property or real estate” is amply demonstrated in the above example. It’s a message that is filtering down to businesses of all sizes and in all sectors – the value of your data matters (and not just during a potential crisis situation).

David Lyford-Smith, the technical manager for IT and the profession at ICAEW, last year attended an event hosted by the Royal Academy of Engineers, where the challenges of valuing the UK’s data economy were discussed by “key thinkers from the fields of engineering, technology, government, accounting practice, and academia”. The Academy concluded that data assets are an essential element of the value of UK companies, and only likely to become more so. Lyford-Smith noted in a Chartech article: “Currently these assets are not readily recognisable in corporate reporting, nor are they considered in government statistics around GDP. Valuation of these assets in internal management accounting is also rare.”

This view is one that is also shared by Douglas Laney of analysts Gartner, who said: “We are in the midst of the information age yet information is still considered a non-entity by antiquated accounting standards.” Gartner stated that its research along with studies by KPMG and others had “shown how significantly investors and financial analysts favour information-savvy and info-centric companies”, but despite this, information was not recognisable as a balance sheet asset even though it would likely meet the criteria.

Lyford-Smith said the Academy believed this state of affairs “undersells UK productivity, doesn’t appropriately encourage the use of open and structured datasets, and under-promotes the need for security around data”. By bringing data valuation techniques to the fore, the Academy argued, the economy and society could benefit.

Raw data had low value. The value was greatest once that information was then applied to reality, and knowledge about the business, its customers or its suppliers was gained as a result

Business & Management Magazine, January 2017

Measure for measure

Lyford-Smith reported that the engineering event participants felt “raw data had low value (especially if it was unstructured)”, but that if analysed into understandable information, the value would become clearer. “The value was greatest once that information was then applied to reality, and knowledge about the business, its customers or its suppliers was gained as a result.”

Naturally, analysts have been thinking about how to approach this problem, and have come up with a variety of methods. Gartner, for example, has developed its own information valuation method, which begins by “inventorying and measuring information assets”. This can be done by “using well-honed and established methods for valuing other kinds of assets” or – if the business is not ready to financially value its information – “consider metrics that assess the information’s quality characteristics, business relevance or impact on non-financial performance indicators”.

It developed six formal valuation models in conjunction with valuation experts, accountants and economists, which can be seen in the diagram below, but in essence cover the following areas:

Foundational measures:

  • Intrinsic value of information: how correct, complete and exclusive is this data?
  • Business value of information: how good and relevant is this data for specific purposes?
  • Performance value of information: how does this data affect key business drivers?

Financial measures:

  • Cost value of information: what would it cost us if we lost this data?
  • Market value of information: what good could we get from selling or trading this data?
  • Economic value of information: how does this data contribute to our bottom line?

Gartner suggested that these measures could be used to change business culture, “make information-related decisions, and apply well-established asset management principles and practices to managing their newly anointed information assets”, and that this should be done under the leadership of a chief data officer (CDO), as well as other executives.

Figure 1: Selecting an information valuation method

Keeping scores

Another analyst recommending involvement of a CDO is Data Clairvoyance. Its valuation method begins with setting up an office of data, adopting responsibility for “data governance, metadata management, data quality and data architecture”. The CDO would “serve the strategic role as the ‘broker’ of data between creators and users”, according to Data Clairvoyance CEO and founder Reuben Vandeventer. He advocates businesses creating a comprehensive inventory of business data elements, acquiring metadata about how the information is made and used. After arranging for ‘data stewards’ to monitor quality of set chunks of data, the critical next step, says Vandeventer, “is to develop a standard method for quantifying how the data elements exist” within the organisation.

He adds: “This metric must include the ‘tribal knowledge’ (people-based metadata), the frequency of use/demand on the data element, and the overall quality of the data element.

“We call this metric the data certification score, which is a holistic indicator that measures how the data is used based on both quantitative and qualitative inputs.”

These scores can be monitored and recalculated over time, perhaps even on a weekly basis. “Once data certification scores are calculated, you can use statistical methods to correlate them with the key operational or financial KPIs/metrics of the organisation,” Vandeventer adds.

Data Clairvoyance also recommends using quantitative measurements derived from metadata to instigate a process of multivariate regression, allowing businesses to “analyse independent variables about specific data elements”.

This method, the analyst believes, “means that for the first time, an organisation can bring a level of accounting rigor to its data valuation processes that operates at the level of GAAP accounting”.

Part of the difficulty in valuing data is that the costs of performing this refinement process – and the value of the knowledge ultimately attained – was largely unknown until the work had been undertaken

Business & Management Magazine, January 2017

Unanswered questions

However, there are questions to be answered around rigour and processes as Lyford-Smith’s article raises: “Part of the difficulty in valuing data is that the costs of performing this refinement process – and the value of the knowledge ultimately attained – was largely unknown until the work had been undertaken.”

Discussion at the Academy event around valuation methods found that “current accounting practice around intangibles is quite limited”, with existing rules “allowing for recognition on a transactional basis – ie, if the data could be valued against an external market, or as an element of goodwill on a business combination”.

Lyford-Smith recognised that accounting rules have to lead to results that external stakeholders can rely on to make their financial decisions, “and the value of data and similar internally generated intangible assets can be overstated if rules aren’t clear and conservative”. He concluded, though, that ignoring the value of data assets wasn’t tenable in the long term.

This is a position shared elsewhere, and that has given rise to thoughts of what may come next. A Capgemini and EMC survey – reported in Big & Fast Data: The Rise of Insight-Driven Business – found 63% of respondents believed the monetisation of data could become as valuable to businesses as existing products and services. It varied across sectors, from 55% in healthcare to 83% in telecommunications, but all sectors saw it as relevant.

As data valuation methods continue to be refined and applied, there is no telling how quickly businesses will be able to not only give themselves a boost in terms of the total value of their organisation, but also identify ways in which that data could be sold on to further increase its value. It might just be worth keeping an eye on where the customer data ends up in the Caesars Entertainment case.

Further reading

Download pdf article

Related resources

The ICAEW Library & Information Service provides full text access to leading business, finance and management journals. Further reading on the value of data is available through the resources below.
Terms of use

You are permitted to access articles subject to the terms of use set by our suppliers and any restrictions imposed by individual publishers. Please see individual supplier pages for full terms of use.

More support on business

Read our articles, eBooks, reports and guides on Financial management

Financial management hubFinancial management eBooks
Can't find what you're looking for?

The ICAEW Library can give you the right information from trustworthy, professional sources that aren't freely available online. Contact us for expert help with your enquiries and research.

Changelog Anchor
  • Update History
    10 Jan 2017 (12: 00 AM GMT)
    First published.
    01 Nov 2022 (12: 00 AM GMT)
    Page updated with Related resources section, adding further reading on the value of data. These new articles provide fresh insights, case studies and perspectives on this topic. Please note that the original article from 2017 has not undergone any review or updates.