Data Economics – An essential science for companies to monetize data

By Ganesan Arumugam – Director, Channel Sales, NetApp

An organization’s capacity to access relevant data in a secure, actionable manner is now as important as its cash flow, balance sheet, or market share strategy, and other traditional indicators of business performance. This is because the availability, quality and use of data has become the single biggest source of competitive advantage for organizations whose performance is increasingly defined by their ability to deliver individual and personalized experiences. The latter are fueled by insights and intelligence provided by data spread across the organization (and beyond), so ongoing, real-time access to such data has become a business fundamental.

A firm’s value was traditionally determined by its balance sheet, or the manner in which cash reserves were managed to mitigate risk, leverage market opportunities, and ensure full compliance; the same was true for inventory, talent, capital, and any other form of asset. Today, data is the defining ‘asset’ of our age. A company’s potential and value significantly depend on its mastery over the data available in their organization; from how and where it is stored, to who has access and in what circumstances.

Given the increasing role of data to create, transfer and store value, now is the right time to define a similar set of principles to ensure its optimal use. There’s a lot that can be done with data today. Location-based insights, for instance, are likely to be more temporary than longer term trends such as employment, or marital status. Out of date location data has zero value; in effect, the target has presumably changed location, so any insight or proposed action dependent on the same will be equally invalid.  Conversely, trend data used to develop behavioral profiles or longer-term insights can have a much longer shelf life; in this case, ‘older’ data can retain its relevance – and value – over a far longer period. And there are many permutations in between. So, the value of data would be a function, not only of time, but the precise way in which the data will be stored, managed, and used.

That said, the issue of compliance has become a critical one. Non-compliant and unsecured data actually represents a liability in value terms. To protect their asset, businesses need to consider where and how they store their data, as well as the manner in which it is used. These considerations also extend to the issue of data privacy; the use of inappropriate or unauthorized data can also represent a liability for the organization.

The speed and accuracy with which data can be accessed represents a key factor in determining its value. Speed can be determined by multiple factors: the infrastructure, the location of the data, its nature – is the data ‘owned’ by the company directly or accessed through a third party, for instance?

These above mentioned are a few of the factors that would feature in any ‘equation’ to determine the value of data in an organisation, at any given moment. Given the role of data in determining business value, it can be safely assumed that data economics is emerging as the new science that will help companies derive maximum value from data and monetize it.

250 years ago, Adam Smith codified the role of money creating and transferring value for society, the science of ‘Data Economics’ could fulfill a similar role for data in transforming businesses today. Given its importance and ubiquity, it is just a matter of time before ‘data economist’ becomes as common a position as that of a treasury manager, a financial controller, or a CFO in the boardroom meetings of the future.