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TDWI Upside - Where Data Means Business

How to Monetize Your Data Assets

TDWI Research senior director James Kobielus discusses how to succeed at data monetization.

On a recent “Speaking of Data” podcast, TDWI’s James Kobielus joined host Andrew Miller to discuss the Best Practices Report he just authored on monetizing data and analytics. Kobielus is the senior research director for data management at TDWI. [Editor’s note: Quotations have been edited for length and clarity.]

For Further Reading:

Data Monetization Requires Balancing Data Availability and Governance

CEO Perspective: Moving Data Analytics from Cost Center to Revenue Generator

Is Your Data Monetizable?

“In anything you do in business,” Kobielus began, “you hope to make money,” so it’s no wonder that, with data being such a valuable asset, enterprises would look for ways to use it to make more money and to drive better business results. “What business intelligence, data mining, and data uses really try to do is boost the bottom line through better business decisions from higher quality data and from predictive models that have been built from data. Monetization is really the end game from the point of view of management, especially the C-level.”

The question is how an enterprise can use its data to do more than just do cool things? Enterprises are considering how their data can help shareholders. Kobielus wrote TDWI’s Best Practices Report with an eye to determining the chief factors that contribute to data monetization success. He found what he calls “four strategies for data monetization.”

“The first one may not, at first glance, sound like a key strategy for monetization of data at all, but it is. It is data democratization -- giving everybody in your organization access to the best data you have to support data-driven analytics,” such as performing queries and producing reports. Enterprises can see the payoff of data democratization in terms of qualitative factors (such as employees working smarter), but there are quantitative factors as well, such as making better business decisions that enable the organization to boost sales, hold on to customers, or upsell to existing customers

“When we talk about data monetization, it's a maturity model, where you move from data democratization to operationalize data . That's a long-winded word that alludes to using data in the business to drive better decisions and make processes more efficient, thereby reducing costs and boosting revenue. Data operationalization is a core strategy that organizations have used from the beginning of data and business to drive the quantitative bottom line.

“Then when you look at the maturity journey for the enterprise in terms of data monetization, many enterprises are looking to move beyond operationalization into data prioritization . This takes us to the next step in terms of how to use data and data-derived assets, such as machine learning models and AI, and embed those in physical products such as edge devices that are more intelligent in cloud services and in mobile digital assistants that help your customers to do smart things all the time.

“Many organizations are productizing data and increasingly appointing people (such as data product managers) to drive direct revenues from data and AI built on that data.”

The fourth strategy for data monetization is selling data -- essentially taking the data assets you own and selling or licensing them. You can provide subscription access to customers; you’re monetizing the data directly and using your data as a currency.

Putting Strategies into Practice

According to Kobielus, “First and foremost, your organization needs a strategic framework to understand these strategies, and to assess the degree of relevance of each of them and their feasibility in your business. That requires top-down support from the executive level. You must align your investments in data and analytics around these goals.

“If you're, really committed to monetizing your data, using all the tactics possible, then you must be organizing your investments in the underlying platforms and databases and modeling tools to drive better, greater monetization of data.”

In addition to executive commitment and aligning your data and analytics investments to support greater monetization, you’ll need to consider staffing, skills, and building teams in your organization to boost monetization. “Over time, you may want to create a cadre of data product managers whose job it is to build and sell products and services that incorporate data and incorporate data-driven analytics.”

Finally, Kobielus noted, a big part of this is knowing when you're successful. That requires you to have clear metrics. People are incentivized when they know their actions are directly related to data and data-derived products, so they need KPIs and ongoing dashboard updates to show how successful they are in monetizing the data assets you have.

[Editor's note: To hear the full conversation, replay the podcast episode here.]

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