Time was, we made value in factories. In the industrial age, businesses created wealth through the output of newly-invented machinery. But we’re now in the information age – one where value is created via information and computerization rather than at the lathe or loom. Data can be used to improve decision making, refine processes, develop better products and services, or sold to create value for the company. But we’re terrible at calculating its value.
Most businesses agree that the information they hold has immense value to their organization, but modern accounting practices haven’t yet llearnedhow to assign proper value to that information.
This causes a host of problems, such as knowing how best to insure these information assets and also when pricing a business for sale. Business accounting standards simply haven’t yet caught up with the digital age.
Accounting practices can more easily account for financial, human, and material assets than they can data assets. It’s not easy to assess the value of data, which takes many forms. Its valuation will vary according to how complete, consistent and accurate it is, and how recently it was gathered. Sensible valuation would probably also take into account how that data is stored – even the most useful or rare data would be less valuable if it’s stored on wax cylinders.
Calculating the value of data
Humans have never been at their best when faced with an absence of information. When we’re unable to correctly assess worth, a common fallacy is to overinvest in an asset, which can drive it beyond any accurate reflection of its real value to anyone. These market bubbles inevitably burst, leaving economic turmoil behind them.
Humans have done this before with assets from tulip bulbs to dotcom companies. Lack of information has always led to poor decision-making.
Real market bubbles are fortunately rare, but incorrectly assigning value to assets causes market turmoil whether it’s a bubble or not. One common outcome is that companies are incorrectly valued at point of sale. This can have the effect of disappointing the buyer when they discover they overpaid for the business. Equally frustratingly, the sale may not happen at all if parties cannot agree on the value of the business.
When high profile companies are sold, it’s common for the sale value to be hotly debated in the press. It’s hard to really understand why Microsoft recently paid $26 billion for LinkedIn when the company was valued at just over $3 bn. The argument that Microsoft investors no doubt made was that the true value wasn’t captured using conventional accounting methods, which are unable to categorize the data assets LinkedIn possessed.
But this puts us on shaky ground. Although Microsoft clearly worked out their own way to account for the value of their acquisition, they evidently had to depart from standard accounting practices to do so. Many commentators would argue that they overpaid for the business.
Investors that need to defend their decisions may struggle to convince shareholders why paying 10x more than the paper value of a company makes sense. If accounting practices can’t capture all the value in a business, it’s hard to prove them to anyone. Data businesses are probably more likely to be underpriced than overvalued because they can’t prove their own value to anyone.
If a company such as LinkedIn can transform themselves from a $3bn valuation to a $26bn valuation merely by finding a way to capture their own worth, it’s clearly in their interest to find a method of doing so.
If we aren’t representing a company’s real value, we’re going to miss opportunities to realize that value. If data is a true commodity then the market needs to be able to assign a value to it, or we’ll miss opportunities to trade it and hence for use to be made of it.
Better decision making
Assigning value to information assets also helps companies make better decisions about their governance. If an organization understands how valuable their data is, they can assign it the resources it needs to help realize that value. This could be via investments in technologies to get the most from this valuable asset, or investment in security to properly protect it.
Assessing the economic value of information is such a hot topic that it’s coined its own discipline – christened ‘infonomics’. This field of study is likely to cover the measuring, managing, and monetising of those precious data assets.
The first studies in this area probably need to find ways to value information that everyone can agree on. After all, measures of worth can’t be compared if everyone doing the measuring uses a different measuring tool.
Many of the most talked about problems of the modern age reflect the fact that technology is romping ahead of all our social systems, including accounting practices. The challenge of properly assessing information value is just another instance of this. Eventually, we’ll catch up but in the meantime, many companies are going to be wrongly valuing one of their more precious assets.