Post by account_disabled on Feb 20, 2024 6:05:34 GMT 1
Risk management is one of the strong points of predictive analytics. Predictive analytics supports decision making by providing a holistic vision that multiplies the business's options in the face of risk and fraud that, how else could it be detected? Advanced analysis leverages information to mitigate threats, redirect weaknesses and exploit opportunities, and decision-making benefits from this security, which is transmitted to the entire organization. Decision making Always making the right decision is difficult but, thanks to the power provided by data, systematic correct decision-making is now feasible , which is none other than the one that brings together the following attributes: It is carried out punctually : at the exact and necessary moment, when it can really change or drive the course of a determining action.
It occurs under conditions of reliability: thanks to confidence in the quality of the data, which is supported USA Student Phone Number List by the absence of duplications and gaps; and the absence of incompleteness, imprecision and errors. It is relevant: because it helps improve a reality, either by correcting an element that has lost strategic alignment or by promoting an initiative that will generate value. Decision making is the result of deep work: understanding the past, informing yourself about the present and predicting the future. When this three-dimensional perspective converges in a decision, its effects are consistent, effective and accurate. Risk is left aside and vision focuses efforts. Behind every decision making there is a choice. The person responsible for doing it requires: 1. Data – Data itself is worthless. Raw data resembles chance, chaos or disparity and, therefore, if it cannot be processed properly, decision making will suffer from incompleteness, due to a lack of context, making it factually erroneous and increasing risk.
Of the course of action 2. Information : Information is derived from a set of processed data when context and meaning have been added . In its view, a more in-depth analysis can be carried out , so, at this stage, decision-making could take a better direction, although it would still be vulnerable to risk, due to lack of perspective . 3. Knowledge: when data is translated into information, when contextualized, and this, in turn, is analyzed and validated, knowledge is obtained . This is the highest level that can be achieved in terms of risk management, it is the most fruitful scenario for decision making as it is actionable with a high degree of accuracy , because there is no proof of concept. Risk-free decision making moves away from intuition and subjectivity and seeks the application of logical models, inspired by mathematics and statistics that, with their rigor, serve as a structure for a conscious and focused choice. This type of decision making is proof that, by experiencing good visibility, it is possible to take advantage of opportunities, innovate and adapt to the approaches that the future holds for the business.