🛑There are several levels of gaps between data and outcomes. Data will NOT enable you to make better decisions and, thus, better outcomes.
The belief data that will help you achieve better outcomes is like believing that buying books makes you a successful person in life.
Sure, you have to buy books, read them, practice them, experiment and apply the knowledge, fail and learn from it, and then, if you do this enough, you can turn your life around.
💢Data is similar in some sense. From data to information, insight, action, and then outcome, several BIG gaps need to be addressed.
🔹Data to Information: Data is a raw record. Once processed in the specific context, it becomes information. A “decision model” should be responsible for creating the information from the data in the context.
🔹Information to Insight: Adding meaning in a context to information will transform it into insight. This meaning requires interpreting information and drawing conclusions in a context by a “decision model.”
🔹Insight to Action: There is no point in just having an insight because inaction insight does not change anything. A “decision model” should fill the gap on what the next best action is based on a specific insight in a given context.
🔹Action to Outcome: Not every outcome is desirable based on an action. To ensure the quality of the outcome, a “decision model” is needed to ensure the outcome is not accidental and can be reproduced with a certain quality.
✨Any organization needs a “decision model” in every step of this transition.
What is a Decision Model?
The “decision model” is not a rule ai ml llms optimization process etc. The decision model is a hierarchical representation of business decisions made and executed daily as part of the business operation.
💡How do you create one?
– Look at the business operation and identify all the business decisions they make
– Decompose them into smaller parts (i.e. decision units)
– Identify the relationship and dependencies between the decision units
– Identify the inputs and outputs of the decision units
– Specify the metrics of each decision unit
– Determine the nature of each decision unit (predictive, deterministic, probabilistic, etc.)
Congratulations, you have created a multi-step and hierarchical “decision graph,” i.e., a decision model that depicts a holistic view of business decisions.
🚀Now, you can integrate multiple techniques, such as machinelearning businessrules optimization dataprocessing, to execute and automate them as a holistic decision model compositeai.
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Published December 29th, 2025 at 07:30 am
