How to Value Data as an Asset
How to Value Data as an Asset
Current GAAP accounting Practices don’t allow for valuation of intangible assets (Data) on a Balance sheet, so how does an organisation Measure or Place value on their data?
Drucker’s famous Phrase comes to mind here “you can’t manage what you can’t measure.”
This brings the line of reasoning that for Data and by inference all processes & people involved with managing it to be properly valued in an organisation it should be listed as an asset and there be recognised guidelines on how that valuation was arrived at.
It’s not entirely true if it’s not measured you can’t place value on it, it often just becomes implicit value rather than explicit – take a look at the value of Facebooks shares vs virtually any company that has more tangible assets like a car manufacturer
Gartner Predicts that by 2022 organisations will be valued on their information Portfolios – Although we constantly reference the information age, we are yet to explicitly list the value of organisations based on information.
There are 3 key areas to address in order to consider the value of Data
- It must be definable & Identifiable
- It must Promise some economic Benefit to either your organisation or others
- You must be in charge of it (much like the average homeowner doesn’t have the mineral rights to what’s under their property, Organisations must have those rights for the purposes it intends to value the data for.)
These are the basic principles’ from which to start;
The second criteria is possibly the most interesting because there is the most room for creativity and acumen, some businesses already take public data freely available to all and turn it into something of economic benefit, showing that almost all data will have some value if you only have the imagination and skills to make it so.
How to Value Data, there are 8 Key Elements that Drive value
These are not ranked as different types of data and use cases will give different weighting to elements
- the uniqueness of the Data Set – Can this dataset be easily recreated?
- Ease of Use
- volume, the size or number of records
- gaps in the data
- the ability of users to combine data sets together.
- restrictions on the use of Data or risk deriving from it
- accuracy of the data
- durability, how long is this data accurate and relevant for?
The Income approach to valuing Data has distinct limits. As Data assets are becoming better curated both new and legacy data can hit many of the criteria above but may not have their value accurately reflected in an income-based valuation method.
The Market approach to valuing data is based on observing other sales and making comparisons, Volume is the key to this working well.
Markets need to be transparent and assets need to be comparable in order to properly compare X with Y, accurately classifying data assets, and then having the volume of trades to identify value will be the goals.
The Property market has similar issues and REITs (Retail Investment Trusts) are a way of trading what would normally be difficult to compare asset classes and are now a recognised asset class a potential goal for Data as an Asset, however, REITs had a rocky beginning and there are many minefields to avoid.
The Prudent Value method of valuing data developed by Dell CTO Bill Schmarzo which essentially values data based on how efficiently or effectively it is used for decision making.
Given that only 0.5 of Data created is made use of and in the average FTSE 250 Company a 10% increase in Data accessibility results in £50 million increased revenue – This indicates that Data is very inefficiently used at present, any valuation based around this is also likely underestimating the value the data.
Bottom line – data is an asset and should be treated as one. The more an organisation focuses on managing data as an Asset the better the likely return. In order to do that Data Ownership in organisations should be centralized like any other major asset class would and form a central part of the Strategic viewpoint.