Well, this is similar to the question: “How long is a piece of string?” It all depends on how you look at it. The cost of data can be measured by how much it cost to acquire, store, quality control and communicate with it. But the “value” of the data resides in the use of it to improve the business. The cost and value are two extremes of the same axis, as shown in this figure.
Data acquisition is a necessary first step on the road to achieving value. Thereafter, we have to take three further steps before our data can yield value – data quality control, data communication and data storage. Most IT vendors operate in those areas with their commodity products. That’s the easy part – a part that usually adds costs to the data, but doesn’t produce much value.
As in any other business investment, the management of data needs to be seen from a ROI perspective. The amount of money corporations are prepared to spend on data acquisition, storage, communication and quality control, is proportional to the value they believe they are getting from it. If the perceived value is not there, then anything spent on it will probably be considered a “high cost” expense. This makes it essential for corporations to understand that the actual value comes from how to retrieve and use the data as a Business Intelligence (BI) tool.
It is not always simple to measure the value added to the business as there are other variables which, along with the data, improve business performance. The issue is the “perceived” value which users place on data regardless of the underlying data management technology used. For example, a manager would not care less if the data is stored in Oracle or MS SQL Server database, or how often the back-up is done, etc. Users want readily available, reliable data, which keeps them informed on how the business is going based on data perspective (KPIs). That’s where the data’s value is realised. The rest is just “cost”.