The Data Ready Organization
How to prepare for a DATA Future?
If you want to start a conversation to talk about how your company can become Data Driven, then please fill the following form.
Data Literacy will be a requirement for organizations to obtain value from their data, and will be the one big differentiator to drive innovation on services that become increasingly automated every day that goes by:
Establish a Strategy that can be easily communicated.
Vision is very, very important. For being able to initiate an organizational transformation and becoming data ready, we must be able to produce a roadmap that will explain the effort and the time it will require to get us from A to B.
Build a strong data foundation.
Going from a hosted, on-premise systems environment to a modern Data Lake is possible once the evolutionary steps are clear. It depends on the nature of the organization, and the business on how a solid data foundation is built, but providing one source of truth and validating it is critical for progress and less rework.
Re-Design your culture to be able to adapt to the new processes.
A lot of the preparation for growth happens when we can open our data silos, throw down the barriers between departments, and work on a common understanding of the business reality. A Data Culture is necessary to provide a safe environment for experimentation and having a workforce that is eager to learn and validate their progress cientifically is a differentiator for success.
Obtain support from C-Level.
The journey to the Data Driven organization needs support, especially from your project sponsors and key stakeholders, which can help communicate and celebrate the milestones on the path to a data ready organization and the value it brings to everyone involved.
Deliver value to the greater audience.
Once we start deploying projects and proving the value of the investments, a lot more projects, requirements, and stakeholders will show up wanting their turn with innovation and great ideas where to implement Machine Learning and Artificial Intelligence projects, to deliver value consistently, we must not derail from the data strategy we set sails with and make sure we have validated our hypothesis' correctly and are not simple suffering confirmation bias.
