What does it mean to treat data as an asset?
When considering this concept, we must define what data is and how it can be considered an asset. Data can easily be defined as a collection of stored truths that are open to interpretation and manipulation. Expanding on this definition, data can be viewed as a set of captured facts, measurements, and ideas used to make decisions.
Furthermore, InvestorsWords.com defines asset as any item of economic value owned by an individual or corporation. Now let’s apply this definition of asset to our definition of data, and ask the following question. Can facts, measurements and ideas be items that are of economic value owned by an individual or corporation? The obvious answer is yes; data can be bought and sold like commodities or analyzed to make smarter business decisions.
We can look at the economic value of data in one of two ways. First, data can be sold as a commodity that can take the form of goods like eBooks, Training, Music, Movies, and so on. Customers are willing to pay to gain access to this data for their consumption. This directly implies that there is an economic value for data in the form of a commodity because customers see a value in obtaining it.
Secondly data can be used in making smarter business decisions that allow for companies to become more profitable and/or reduce their potential for risk in regards to how they operate. In the past I have worked at companies where we had to analyze previous sales activities in conjunction with current activities to determine how the company was preforming for the quarter. In addition trends can be formulated based on existing data that allow companies to forecast data so that they can make strategic business decisions based sound forecasted data.
Companies that truly value their data are constantly trying to grow and upgrade their data and supporting applications because it is the life blood of a company. If we look at an eBook retailer for example, imagine if they lost all of their data. They would be in essence forced out of business because they would have nothing to sell. In turn, if we look at a company that was using data to facilitate better decision making processes and they lost all of their data then they could be losing potential revenue and/ or increasing the company’s losses by making important business decisions virtually in the dark compared to when they were made on solid data.
