Decision intelligence is N⛔T about data, neither historical nor future data.
No matter how much we twist it. Data generation, creation, etc., has nothing to do with DI.
💡Decision Intelligence (DI) is a multidisciplinary practice that combines data science, machine learning, behavioral science, computer science, and decision science to help organizations make quality decisions that are aligned with their business objectives.
You hear the word “decision” and may think it has everything to do with data. But that's a misconception from Machine Learning (generative and non-generative) techniques or bi thinking.
The decision is about how you reason about something to conclude an outcome. That reasoning knowledge is sometimes in the heads of domain experts, may be based on policy, might be encoded and hidden in the data, etc.
✨The core purpose of DI is to enable organizations to explicitly model the reasoning knowledge around their decisions. Then, explicitly modeled decisions will be used for communication, execution, automation, and augmentation. They will be part of systems, processes, agents, and support humans and will be part of everyone's everyday jobs.
Let's not forget… we call it decision which is a lazy way to say business decision.
The business decision (i.e. decision) is the act of finding an answer to a business question. Specifying how we navigate from the question to the answer, that 🌌space between question and answer is filled by the decision models.
Learn more about DI at https://lnkd.in/ghzZ3VvM
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Published November 25th, 2024 at 07:30 am
