Intangible assets are nothing new.

Companies work with patents, computer software, even trade secrets on a regular basis. In fact, historical research by the Centre for Economics and Business Research showed that the value of intangible assets in the U.S. and the UK nearly doubled between 2001 and 2011.

Now, companies might also have to figure out how to add data as a valued asset on corporate balance sheets.

A 2014 Wall Street Journal article explored this idea, and included a sizeable figure from

Leonard Nakamura, an economist at the Federal Reserve Bank of Philadelphia, which said that corporate holdings of data and other intangible assets could be worth more than $8 trillion.

“It’s flummoxing that companies have better accounting for their office furniture than their information assets,” said Douglas Laney, an analyst at technology research and consulting firm Gartner Inc. in the same article, “You can’t manage what you don’t measure.”

So if you’re a CEO, a CFO or a CIO and you see potential changes in accounting standards coming, how do you apply sensible accounting practices to this data? Here are 4 ways to do that.

1. Data valuation

Companies today are deriving competitive advantage, intellectual property gains and even data monetization from their data. For those companies that are actively monetizing their data by reselling it to others, there is likely a very tangible way of measuring profits from the effort.

For the majority of companies that use data for competitive or marketing advantage, there’s one way to calculate if the use of big data is what’s responsible for a certain profit number, whether that number comes from an increase in sales or market capture. They have to compare the results of their data-driven campaigns to campaigns that did not use this data.

This is a non-exact science at best, and it gets even murkier. For example, it can be difficult for firms to assess the intellectual property value of the very algorithms it uses to deal with all its data.

2. Operational expense

If data is to be considered as an asset on a balance sheet, there must be a corresponding cost for acquiring or building this asset. Organizations have to value the hours spent on collecting, refining, and enriching their data, as well as the personnel recruiting costs, storage and computing costs, facility costs, and any other cost factors that go into data asset development. In some cases, organizations are already doing this with their return on investment (ROI) formulas where they track the costs going into data development and put it against the cost of acquiring the data as an asset–but this practice is largely done on a per project and not on a corporate-wide basis. This is where CXOs need to get to work.

3. Data depreciation

As data ages, it loses its relevance and its value. Formulas will need be devised to depreciate data over the period of time that it ages (e.g., depreciation taken over three years, five years, etc.). To determine the correct depreciation cycles, regulators and CFOs will need to work together with CIOs to determine what normal lifespans for data are–and then factor in a viable depreciation formula against these lifespans.

4. Data wastelands

Enterprises have pockets of useless data. It might be data that dates back over ten years that is no longer relevant to what the corporation does, or data that has been routinely stored or backed up, that is temporary or that no one understands. There is an ongoing cost to maintaining these data wastelands, and there will be time when the best practice is to purge them. If they are sitting on corporate balance sheets, they will also have to be expensed. The best move here for CXOs is to only admit data that has proven worth to the corporate balance sheet so that charge offs can be minimized.

Is data on the balance sheet like to become a reality in the near term?

No, it isn’t. But CXOs need to put data valuation on their planning roadmaps now so they can begin the process of educating their boards and positioning their balance sheets for the change.