💣Continuous Decision unlocks the real-time decisioning that deals with feedback, changes, and uncertainty
In decisioning scenario, the assumption is that the decision model executes against a case and will have a definite answer based on the decision model in the first cycle (or iteration) of decision execution.
This is a very simplistic view of cases, situations, and decision models.
✨Often, based on the executed decisions on a specific case, a decision influences the future of the case. Although the case is the same but it belongs to an altered situation where the executed decision has changed the situation of the case. In this new state, the already executed decision is either still applicable or a new set of decision models for the new states are needed.
This means that the final outcome has not yet been determined by the first cycle of decision execution. We still need to continuously execute more decisions on the case until the final outcome is conclusive. Sometimes, the model determines the outcome is inconclusive, and an alternative approach (manual review, domain expert input, marking the case infeasible, etc.) is needed to finalize the outcome.
💡The kind of business decision where a continuous change of states or circumstances over an extended period of time does not allow the final outcome to be conclusively determined in a single cycle/iteration of execution is called continuous decisioning.
There are many reasons the state of the case might change. Therefore, the situation will change, and consequently, the decision should adapt based on the new state and situation. Changes will happen:
🔹from the external environment to the case (i.e. uncertainty)
🔹because of the outcomes of automated and executed decisions on the case
🔹case lives over time, and therefore, the circumstances of the case change
A model for continuous decision MUST capture these complex behaviors and states in a cohesive form otherwise a static model based on rules, machine learning etc. in a complex world full of uncertainty and constant changes cannot become adaptive.
💥The Continuous Decision Model (CDM) not only orchestrates between all data ai ml LLMs businessrules optimization and other techniques but is also event-driven, adaptive and dynamic to encompass the changing environments and circumstances where the case lives over an extended period of time.
Learn more how Continuous Decision Model (CMD) orchestrates automated decision across the full lifecycle of a case at https://lnkd.in/g3fB5hVw
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Published April 9th, 2025 at 07:30 am
