These five questions are not merely a self-assessment tool; they are a strategic compass, guiding executives towards the successful integration of data into the very fabric of their business.
Enterprise Data Transformation
Someone else’s cool AI project doesn’t make your project any less valuable. Don’t let the constant stream of exciting projects and advancements make you doubt your own vision. Keep moving forward and trust in your own unique approach.
Most of the newly generated insights are not integrated with the business process but are made available as a BI dashboard. Use these SaaS tools to quickly operationalize AI models and any other insight for maximum impact and ROI, check the adoption, and iterate quickly.
I have seen many successful data leaders develop a value dashboard that compile and the track all ROI information and KPIs that are being impact by data projects. The main idea is to basically try to translate the data work they do into dollars and time saved.
A system providing a standard and consistent set of definitions of metrics on top of the data warehouse.
The adaptation of the AI mindset and an iterative AI journey will ensure that AI investments are properly executed and more resources are put into the bets that are proven to work in the MVP phase.