💣The DecisionIntelligence MUST model business decisions explicitly.
I've seen some people posting on decisionintelligence and trying to convey that DI is insight to action, or machine Learning, predictive analytics, or even rules management.
⚠️They cannot be more wrong about it.
✨The DecisionIntelligence is about business decisions.
👇Below are the main points of how DecisionIntelligence works, end-to-end:
🔹 Modeling and executing business decisions explicitly. Then, improving the outcomes of the decisions with a feedback loop.
When you model a business decision, you will decompose a complex decision into smaller, more easy-to-understand decision units. Then, each of those units can be implemented using different techniques, such as businessrules machinelearning optimization, LLMs and so on. This is called CompositeAI technique.
The decision model represents the explicit definition of a business decision.
🔹Modeling decisions explicitly does not mean using process or flow for modeling business decisions. you CANNOT use any reductionist approach to model business decisions explicitly.
🔹Once the decisions are modeled, you will need some orchestration around it to read data from various data sources, massage them, validate them, and merge them into the information required for the decision model. Then, pass the decision-read-data to the decision model for execution.
🔹Once the decision model's results are collected in the orchestration layer, they need to be reflected back into the systems processes and workflows of organizations.
🚀Modeling, Execution, Monitoring to measure the impact and improve business decisions are the pillars of decision intelligence. All are effectively mandatory for practicing DI in your organization.
➡️Learn: Modeling vs Doodling at https://lnkd.in/gzUDj9NC
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Published June 4th, 2025 at 07:30 am
