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5 Essential Steps Toward Monetizing Your Data

November 19, 2014   |   1:37 PM
Teradata Articles

Data monetization can be about selling data. Most of the time, monetization is less direct: making a process run more efficiently, incentivizing certain types of behavior, or revealing the true value of an asset.

Every company will approach data monetization differently, but gathering a variety of ideas from academia, tech analysts, and leading practitioners, I have identified five steps that can move you toward data monetization.

1. Start with Questions

Too often companies start out staring at the data. Instead, try asking your staff which questions, answered at the right level of detail in the right timeframe, would most impact performance. Use those questions to help you assess whether the data at hand is sufficient or if more data is needed.

Next, examine ways of analyzing the data and extracting signals. Do you have the analytical capacity to answer those questions? Inspiration for data monetization can come from questions, from data, and from analytical methods.

2. Look for Patterns

Professor Russell Walker of the Kellogg School of Management at Northwestern University identifies big data trends that point to patterns for data monetization. At the Teradata Partners conference, Walker examined how the velocity of data, new forms of precision, and opportunities for fusing different data sets can lead to data monetization.

  • Velocity is relevant when information is valuable for a short time. For example, what if a shopper who checked a price online is now using your app inside your store? For a short window, you could target that person with an in-store offer and make the sale.
  • Precision refers to examining more granular data than before. For example, Mike Loukides of O’Reilly Radar pointed out how health researchers were able to find infections in premature newborns a day earlier by looking at hundreds of readings a second. The lack of variation in the data was the indicator of an infection. Using a microscope on important data, we can create high-resolution models that can lead to valuable insights.
  • Fusion refers to the idea of combining data from many sources to create a more valuable view of an asset. Walker points to Zillow, the real estate company that combines many different data sources to provide an estimate of the value of a property. Walker called this asset surveillance, using many different data sources to understand an asset’s value. His research showed how this process could illuminate the true value of assets like billboards, real estate, or farmland.

3. Search for External Data

Speaking of fusion, enriching your data with external data will increase its relevance. McKinsey has been beating the drum about the value of open data since October 2013. In my view, large organizations should dedicate one team member to searching for valuable external data.

The search doesn’t have to be limited to open data. You could work with partners to help them uncover data they have to share as well as discussing the data you have to offer. In this way, a company can create a proprietary data ecosystem of the sort that WalMart pioneered.

4. Sharpen Your Analytics Skills

Big data is not just new because of its size; it’s new because it’s impossible to analyze it using traditional methods. Poking at a dataset with billions of records using handcrafted SQL queries will tell you a small amount very slowly. Machine learning and advanced analytics are needed to profile big data sets and extract their signal.

To become proficient, we must understand the personality of machine learning and advanced analytics. This won’t happen without experimentation and building our analytical capacity. I believe that a sophisticated understanding of machine learning and advanced analytics will smooth the path toward data monetization.

5. Understand Your Data Monetization Identity

Your organization will play a role as an expert consumer of data, an aggregator, or the creator of a new data product. By understanding which role is most natural for your organization, you will be able to find ways to monetize data.

The right way to monetize data is up to you and the goals and objective of your organization, but I do believe that these five steps will help expand awareness and get the wheels turning.