An enterprise data management strategy defines how data within the organization is acquired, stored, organized and leveraged for various business objectives. The key pillars of an enterprise data management strategy include:

Identify Business Value

Data has to be leveraged to achieve business value. There are several ways in which data can be leveraged to improve digital products and associated services. It’s necessary to understand the business, trends in data management, user psychology, existing pain areas etc to identify areas where data can be leveraged to add business value.

Build Solution Approach

There are several ways in which data can be leveraged to achieve business objectives, and some are better than others.  Its important to design a high level approach for building a differentiated solution for users keeping both time and cost considerations in mind.

Build User Engagement Strategy

It is important to engage with prospective users of your solutions, both internal and external, to understand their needs so that the solution can be positioned appropriately, promoted to the right set of users, and get their feedback to ensure continuous improvements and alignment with user needs.

Build Execution strategy

An enterprise data strategy is hard to implement, because the business that gets onboarded first, ends up paying substantially more than those that hook on to the solution at a later stage. It is very difficult to get early internal customers.

Hence it is important to identify business functions that will benefit the most through the solution, make them stakeholders in the initiative, and provide them a value proposition that is compelling enough for them to become early adopters of the solution.

Many companies use regulatory compliance initiatives as the starting point to build an enterprise data management, as getting an early funding for regulatory compliance initiatives is much more easier than other strategic initiatives.