As per a BCG report “while many companies have high data ambitions, few achieve those ambitions. In 2019, only about 10% of companies reported that they had met the data targets set in 2016. Moreover, most were far from achieving their 2021 ambitions set in 2018.” 
Many companies have been unsuccessful in identifying the right data strategy that can give them sustained competitive advantage. Lack of data maturity has been a reason for this failure. To achieve their data ambitions, organizations need to focus on the impact areas based on available data and applied algorithms. Companies like John Deere, Kroger have identified their most valuable set of data using technologies such as IoT, analytics sensors etc. They have successfully used their data sets to understand their customers, and sell insights to their suppliers and third parties to create additional sources of revenue.
In this article we will explore data monetizing models, pricing strategies, and how advanced analytics platforms help in generating insights which can help the businesses get their data monetization strategy right.
Data collection strategies
Companies can use various strategies to collect or acquire data. This can include both, organic and inorganic methods.
Collecting data from customers. Using this strategy, a company can understand their customers, take decisions related to marketing, store locations, and create hyper personalized solutions. Flatiron has developed its own oncology based EMR platform by collecting data of 2 million patient records as of 2018. Lifesciences organizations use these datasets for various use cases in areas such as R&D, and clinical trials. 
Partnering or purchasing data. John Deere in partnership with Cornell University has created a data platform (Ag-Analytics, data platform that syncs with John Deere’s operations center to access and analyze farm data) which has become a source of revenue and has created significant value for their farmer ecosystem. Using this platform John Deere performs analytics of the data and farmers use these tools for estimation, forecasting, risk management of crop maintenance, and soil health.
Acquire a company. Companies that are not able to process the data or not able to get the data required from any partnerships, could go for acquiring a company. Kroger has acquired a data analytics firm 84.51, which helps its biggest suppliers to understand the behavior of customers (60 million households) that shop at Kroger. This helps the supplier design better solutions and services.
Building an ecosystem. A company that possesses a significant amount of proprietary data and can buy or partner for additional data may be able to orchestrate an ecosystem that other companies participate in. Goldman Sachs in 2012 acquired a credit-reporting firm TransUnion and converted it into a data mining giant in just 3 years. TransUnion now has a large base of data sets, it continuously analyses those data and sells it to insurers and lenders.
For these strategies to create full impact, companies need to build a data-first culture. This can be done by investing in skills specific to using analytical insights. They should also run change management programs to create new mindsets and ways of working, and break silos by making cross-functional teams to share data, and create new roles and governance process. 
Data monetization operating models
The two main roadmaps for data strategy and monetization are internal and external. The first one focuses on leveraging company’s data to improve its operations, productivity, quality of its products and services, and marketing campaigns. The second focuses on increasing the number of revenue streams - sell data as a service, sell data platforms, and create personalized products for its customers and partners.