Like already said in previous blog posts, most of the companies are realizing their data as a valuable asset and its monetization potential. There are basically two point of views for data monetization:
1. Generate economic benefits by using data internally (internal data monetization) 2. Monetize data by sharing data externally (external data monetization)
Monetized data must create immediate value for end-users
Selling data might sound easy. But just collecting data, selling and distributing it, are enough. In reality, it's way more challenging. Internally, it’s often quite easy to experiment with what works and what doesn’t. Also business risk are often much lower. When externally monetizating data, data must create immediate value for end-users and the price must be right in order to fit to the market (product/market fit) and generate demand!
This following iterative steps might be good to consider before starting data monetization and when turning your data assets into revenue:
Create a long-term or at least mid-term business plan for data monetization (using business model canvas might be good for this phase).
Take inventory of your data assets.
Design data products and as a part of the designing process be diligent about data regulations and risks. I can't help but mention that Data Product Toolkit™ is good and easy way to start the design process.
Decide the most suitable models how customers can consume data, i.e. Data as a Service -model.
Estimate financial viability and make realistic cost-benefit analysis
Remember that value of data increases only in use, so try to create close community with data user and developers, so you can be part of the data value chain cycle.