An analytic enterprise uses analytics to solve its most critical run-the-business problems. It takes advantage of new tools and new data sources while ensuring analytic results are used in the real-world. This is the first of three blog posts about how to become an analytic enterprise:
- Focus on business decision-making (this post).
- Move beyond reporting to predict, prescribe, and decide.
- Use analytics to learn, adapt, and improve.
Success in analytics means being business-led, not technology-led. Analytic projects that focus on data or algorithms prioritize being able to start quickly over business value. In contrast, a focus on improving business decision-making keeps business value front and center.
A focus on decision-making also acts as a touchstone, preventing a chase after the next shiny object. It provides a business justification for the data, tools, and algorithms that will be required.
Modeling the decision-making in a visual way, using a notation like the industry standard Decision Model and Notation (DMN), breaks down complex decisions and shows what analytic insight will help make the decision more effectively. These models show the impact of expertise, polices and regulations while also clearly showing what data is used in the decision.
When a decisions first approach is combined with a flexible analytic platform, analytic teams are released from the constraints of their current tools or siloed data to focus on business value.
Check out this video on how analytic enterprises put business decisions first and download the new white paper Building an Analytic Enterprise (sponsored by the Teradata Analytics Platform).