What does it take to Monetize data in your organization for improved benefits?

Most banks are experiencing an upward curve in In-directly monetizating data to increase revenue. This involves analyzing the existing data trove and revealing insights that can improve the organization's business performance. The outcomes can be customer trust, satisfaction, reducing anxiety of customers while the benefit can be increase in revenue.

Having a value/realization framework along with having to formalize programs through business cases is usually helpful to socialize benefits of data management and analytics in the organization. The same framework can be used to identify the critical data to be actively managed to maximize outcomes from business processes.

The first step for an organization getting serious on data monetization is to formalize management and governance of data. Certain aspects including managing quality of customer data, mantaining their definitions, common context, reference vocabulary, mastering customer data to name a few that make data amicable for generation of deeper insights. Moreover, as a data office picks up data privacy management as a standard dimension, the Data Protection Office aligns & integrates data-privacy-management into business fabric. This also helps provice a focussed view on data security in the data landscape.

Understanding where data resides, how many purposes does it solve, in how many processes it's being used, its quality, collaboration for reports & models decide whats the value of data.

When we take a data element like a nominee name, we are now asking questions like why do we need it - Is it for a purpose that is a legitimate interest, regulatory ask, or Contractual obligation. Further questions are asked like -

1. Is it mandatory for all customers to get this from customer?
2. Can we do away with not processing certain customer data?
3. How many processes it is being used in?
4. where does it exist?
5. who has access to it?
6. how long will it be retained?

I have increasingly noticed that the enablers of data-management have been shifting to responsible data collection, making data available, simplifying data, inter-operability, standardization, Quality management.
However, most of the above enablers will reduce data provisioning cycles for analysts from a week to hours promotes self-service BI and time to leverage the insights. Having a data monetization in strategy will stregthen data value chains & operations as well whle integrating active management & governance of data into fabric.