Data transformation is changing the Data-driven organizations know the value that is created when large volumes of data are monetized. Data is most useful when it has a direct business contribution, such as delivering intelligence to enhance product value and competitiveness, improving financial contributions from cost optimization and process efficiency, or boosting sales through targeted marketing campaigns and deeper client engagement resulting in improved NPS. The broader context of managing data or doing more with data is only real when there is a direct correlation between the data and tangible contributions to the business.
If organizations focus on what data can accomplish, this will enable them to drive more programs around data management, which require commitment from employees and the belief that smarter adaptation of the data could create new value across multiple facets of the business.
What is a data monetization strategy?
For organizations to develop a data monetization strategy, they can start with categorizing the initiatives into three major buckets:
(a) Driving efficiency or automating the way work is conducted by the employees;
(b) Changing the way products are designed and built; and
(c) Prioritizing the types of revenue sources that can be targeted for improvement.
With these three elements, organizations have the foundational aspects of how data can be monetized to create value. To be successful with data monetization, it is critical to get more data in the hands of the employees with a focus on data assimilation and data quality. Also, the appropriate infrastructure must enable data management and classification to deliver transformational value. Data management practices at high-performing organizations usually have C-Suite leadership that promotes the democratization of data across the enterprise along with empowering data technologies.
How do you create a data monetization strategy for enterprises?
Creating a data monetization strategy is the first step of a broader data monetization effort. Identifying where the organization wants to prioritize impact will lay the foundation for the types of data to be examined and understood. Typically, this is where the Chief Data Officer sponsors the initiative and works with the functional leaders to establish a roadmap of value creation elements based on enterprise data consumption. The roadmap adaptation plan is a critical part of which data will be accessed, what infrastructure will be utilized, and which resources are required to transform that data into value-rich monetization. The core elements of the data strategy should include both the long-term and short-term business requirements, collaboration across disciplines to minimize data silos, and establishing the KPIs expected from the data monetization efforts.