• by Craig Macdonald , October 17, 2013

In the past decade, an explosion in the volume, variety and velocity of data has overwhelmed almost every industry. Despite an increasing awareness of the opportunities embedded in the growing pool of enterprise data, only a few companies have developed strategies to successfully monetize it for an added revenue stream.

The good news is that a number of forces have been converging lately to create the right setting for more companies to monetize their data. For example, the cost of storing data has been gradually decreasing, and the ability to process and analyze huge volumes of data in real-time is increasing. In addition, companies today can use analytics and business intelligence tools to create monetization opportunities by leveraging their enterprise data.

Companies seeking new data monetization revenue opportunities by leveraging their data with customers should take advantage of this opportunity by understanding the value of enterprise data, how best to maximize its potential through the data value chain, and how to get the data to the market in the most efficient manner.

Assessing the value of enterprise data

Data is the foundation of any data monetization strategy, and determining its value is essential for companies to realize its full potential. Companies that have successfully generated new revenues through data monetization use the following key criteria to assess data value:

• Consumer behavior – The most successful data monetization strategies involve information on consumer behavior such as usage data from consumer devices. 
• Consumer identification – Profiling the consumer while factoring in privacy concerns into the strategy helps to improve and expand the range of personalized customer services.
• Transaction frequency – Information on products or services with high frequency transactions are more valuable than those with few transactions per year.
• Unique data – Unique data existing solely within an enterprise has incremental value.
• Accessible data – While there is plenty of unstructured data available, such as data stored as text, it is of low value unless it is easily accessible.

The data value chain: The path to finding the market opportunity

Once companies asses the value of their data, they must identify the market opportunity by deciding upon the value proposition most relevant to them that would be an asset to potential customers.

A company’s value proposition, or where they can play in the market -- for example, a “data” or “full-service” provider -- can be determined by defining where in the “data value chain” they reside due to the level of data they could leverage with customers. Here are the five stages of the value chain in ascending order of relevance and value to customers: raw data, processed data, data insights, presentation of data insights and data transactions. Once a company discovers their value proposition, they can then develop a business model they want to follow or determine how to move up the value chain if desired.

Commercializing data strategies

As companies begin to shape new data-driven business ventures, they need to determine how to commercialize a particular data strategy. Balancing perception with reality in the following areas is crucial for success:

• Perceived value of the market – For larger market opportunities, a company may want to play at the higher level in the data value chain.      

• Privacy concerns – Companies controlling the go-to-market strategy and interactions with end users tend to have the best opportunity to manage customer privacy.

• Evaluation of core competency – It’s key to understanding the impact of playing at a specific stage in the data value chain.

• Agile organization – Building a data monetization business requires buy-in from many internal teams, and short- and long-term agile business and engineering processes.

• Cross-industry alliances – To operate higher up the value chain, companies will often need alliances to serve customers looking for connected experiences.

The future engine of economic growth

A data monetization business has become more feasible due to Big Data infrastructure and analytic technologies, and the decreasing costs of executing monetization strategies. Therefore, any company gathering data on the use of its goods and services -- particularly consumer data -- has the opportunity to develop new revenue streams from its data-driven business. But time must be invested up front to understand the potential value rooted in enterprise data, and where on the value chain the company wants to position the new data-driven business. Similar to any new business project, there are some risks, but the potential revenue streams from data monetization could be substantial -- they could fuel the next engine of economic growth, reaching across industries and geographic boundaries.