Data as a strategic asset – pivot to productization & monetization at scale

As companies reinvent themselves in the new world, they use data to look more deeply into their own operations; they take a closer look at their existing customers and scan horizons for new customers. And, they explore ways that partners and customers can do the same. They not only monetize their data by using it internally but they begin to commercialize and collaborate with their data externally.

The companies that see this opportunity tell us that they used to have a data strategy — now their strategy is data. This new paradigm requires thinking about data as an asset and a potential product. In this context, we should consider data as the building blocks of a manufactured or refined product that can be monetized.

Why productize, share, and collaborate more with data?

A frequently cited McKinsey study estimates that data collaboration generates $3 trillion annually. And data collaboration starts with data sharing — making data available for others to use and derive value from. So what should we consider?

Which data? Start with a specific domain such as “customer data” or “product data.” Customer data could come from multiple sources and include customer profiles, transaction data, interaction data, third party sources such as demographics, etc. Product data might include network data, probe data, sales and returns, defects, supply chain, etc.

Which use cases? The question then is, who would use this data and how? The best place to start is by asking how data is already being used, both internally and externally, and then see if others could use it in the same way. For example, CSPs use network traffic density in cities to determine where to place targeted retail outlets. Lo and behold, retailers, developers, and urban planners can also use that data for site selection.

Which form of product or service? That brings us to the actual data product or service, and the different forms possible. It’s not always just about the data itself. Productizing the data requires a developer or a data scientist to do something with it, such as building an application or analytic model, to deliver business value. However, if the data product or service is an application or an analytic model that delivers insights directly to customers within a business workflow, a decision or action can be taken immediately.

When offering the data itself as a product, data sharing provides a better option than copying and sending the data via a download or file transfer. Not only does copying and sending require more effort, the data is also out-of-date immediately as it is only a snapshot at a point in time. Access to the data is also more difficult if not impossible to revoke.

What’s the value? What is my data worth, and what do I charge for it as a product? Some data providers have told me that it’s like target practice, narrowing in on the bullseye by testing prices and gauging demand at each price. Others extrapolate from a value that they derive with an internal use. Another approach is to work directly with a customer or partner to benchmark and measure incremental value accrued with the application of the data. For example, a marketing campaign achieves a certain conversion rate, but with new data to identify specific targets, conversion rates increase. A share of the lift can be attributed to the data. In all examples, it’s about adopting an agile approach to testing new data offers, and determining the value they deliver. In the end the market will determine the price.

How to go to market? For most companies, data commercialization is not their primary business. GE Aviation and Siemens Mobility offer data products and services, but they are still airplane engine and locomotive manufacturers. Successful commercialization often starts with the right go-to-market partners or channels. Industry Data Clouds facilitate data sharing (and selling), either directly with a customer, supplier, or partner or via a data exchange set up among an ecosystem.

With broader exposure and commercial features, the data marketplace provides a home to hundreds and thousands of data providers. Many CSPs and their strategic suppliers are exploring options to provide enterprise data into the Marketplace to identify new data sources to enrich analysis and improve business performance.

5 steps to start productizing & monetizing your data

In summary, to build and deliver data products and services, either to internal stakeholders or to external partners and customers, consider starting with these five steps:

1. Establish data sources or domains as the raw material for potential data products
2. Identify potential use cases with internal & external stakeholders
3. Determine the best form for the data product or service
4. Adopt an agile approach to testing new offers and determining their value
5. Create and develop the right go-to-market strategy, partners, and channels