In a previous post I wrote about positive and negative data valuation, and posed three questions:
- Who determines value?
- What process is used to determine value?
- Can an IT infrastructure lend data valuation support to the people and processes?
I don't currently have satisfactory answers to these questions, which is one of the reasons for launching case studies with our research partner.
One of the early insights during this process has been the discovery of a potential data insurance ecosystem. The process of insuring data against loss, corruption, or theft would certainly involve estimating not only the value of the data but also the appropriate premiums to charge for the insurance.
Can data insurance serve as an on-ramp for studying the overall topic of data valuation? In order to think further about this area I have put together the table below to begin thinking about the people and potential "data underwriting" processes. The table represents my initial thoughts and should serve to stimulate dialogue (as opposed to representing the actual state of the data insurance market).
Each task in the leftmost column is meant to represent general steps that a data insurer would take when approaching a corporation that wishes to insure one or more data sets. The middle column provides a brief description of each step, while the rightmost column theorizes what type of corporate roles would assist the data insurer in the process.
I will spend the next few posts discussing this table. In the meantime I'd be interested to hear any of your thoughts or experience in this area.