Data monetization can be described as an act of using data to obtain an economical benefit. As organizations continue to recognize the value and importance of data and all associated assets and insights, it is extremely important to create the right setup and frameworks in the organization.
The key element to a successful data monetization is to understand that to exploit its value, data must be accessible and available for business applications and processes. Companies can monetize their data in three ways, distinguishing between ‘direct’ and ‘indirect’ methods:
- improving internal business processes and decisions (indirect method)
- linking information to core products and services (direct method)
- selling information offerings to new and existing markets (direct method)
While the approaches differ significantly in their required skills and applications, they all represent important opportunities to differentiate themselves in the market. For example, one direct method may be the sale of customer loyalty data. Business analytics based on data in a dashboard with information on product usage can also generate direct monetary value, whereas increasing the efficiency of business processes is considered an indirect strategy.
"You can have data without information, but cannot have information without data" – Daniel Key Moran
Data monetization in practice – five important takeaways
What are the main steps to embed data monetization in your data and business strategy?
1. Understand the role and value of data in your business
Good data management is about making sure you have the proper data to support your business and improve performance. Often companies fail to accurately value their data because it is not strictly accounted for as an asset, even though it has actual worth in external markets.
2. Get your data house in order
Too many companies lack metadata – i.e. data about data – such as the data’s quality, where it is stored and what it means. Before thinking about monetizing data, companies need to identify what kind of data they process about their partners, customers, products, assets or transactions, and what publicly available data can be used to increase the value of their proprietary data. They must also work out whether that data is of value internally to cut costs, streamline operations or improve sales processes, or as an external revenue stream such as customer intelligence as a service, or both.
3. Embed data monetization into your business strategy and put the right structures in place
Too often corporate strategy is not supported by corresponding data management initiatives and vice versa. Once you understand the quality of data and have tied it to business strategy, you can then put the right structures in place to monetize that data.
4. Be open to new opportunities
The potential for data to deliver value for many parts of the business is enormous. Sometimes, though, it's difficult for companies to imagine quite what opportunities might be available to them because they are used to pursuing growth through established strategies and revenue streams. That's why all companies should be open to learning from other businesses and partnering in ways that make sense from a data point of view.
5. Communicate data’s value internally and externally to foster growth
As data becomes increasingly important, companies will need to both communicate with and educate internal and external stakeholders so they fully grasp the value data can deliver. One approach for internal awareness building is to brainstorm with those professionals in charge of data or with business function leads to show them how data can improve their business processes. What types of data could really help change their work, offer a competitive advantage or open up new revenue streams? Then there are the success stories of companies monetizing their data – these tend to win over even the most skeptical of executives.
By considering the five points above, companies can get more out of their data. We at KPMG can help you underpin your data strategy and align data and business strategy based on the value case for data. Contact us to discuss your data value, data strategy or implementation of data management capabilities more in-depth.
