The Data Management Challenge–the Real Cost and Value of Data

Since our inception in 1986, we have been involved in a significant number of data management projects. Over that time our consultants found that the majority of clients were seeing data purely as a cost rather than as an enabler. We also found that in many cases the costs were known internally to be very high, but it was not known exactly how high as there was no ability to measure them. During this period the volume and complexity of data requirements grew considerably, and continues to do so.

Firms now face a landscape that is weathered by increasing complexity and huge volume growth. Data is now required for a wider range of asset classes and at a greater frequency, and to satisfy an increasing number of regulatory requirements. The number of data suppliers and their costs are also growing, as is their scrutiny over clients' usage of the data. Given this backdrop, there is a real need to put in place a rigorous data management strategy to ensure consistency and quality of data; and that its usage is managed properly, lineage tracked and costs quantified and allocated accurately throughout the organisation.

In our experience, there is still denial in the industry over the indirect expenses associated with data, so often the best starting point is to understand the total cost of data. The issue isn’t just about the cost of data acquisition, but how it’s enhanced, proliferated and distributed throughout the enterprise. Asset managers should also consider the value of the data to the firm, through robust cost benefit analysis.

In order to measure the cost and value of data, firms must be more rigorous in understanding their true data environment. Whilst many firms (but by no means all), have made significant strides toward understanding their total cost of data acquisition, few have a coherent picture of the data consumers and usage, or the workflows and internal cleansing that is undertaken.

The first challenge for investment firms is pinpointing these costs, as the information is usually lost across processes, jurisdictions and entities. Once a true picture of the data processes and costs is built, you can look to introduce greater efficiencies, rationalise data sources and derive increased benefits from this data.

The first place to start, though, is to work out your true costs of data ownership.