Decision-making
The use of data-driven decision models is growing fast. To create a decision model must start with understanding the measurement of success to ensure that the insight created from the models is relevant and actionable. If available information, or the result of processing the information, presented in the right way enables stakeholders to make decisions then it’s an actionable insight. Data-driven decision-making should permeate the entire business, be automated, and be used for strategic and operational decisions.
The importance of using artificial intelligence and machine learning to create more advanced analytics and predictive decision support to drive business outcomes …
In the business world, classical financial auditing serves the important purpose of providing an external opinion as to whether financial statements are …
Analyzing data to make informed and insightful business decisions is not a new concept. However, making such decisions is more complex, as …
Your team has bought a new deep learning-based machine learning solution to predict when any one of the 10 000 machines needed …
Pitfalls when Communicating Data-Driven Insights to Decision Makers Machine learning-based predictive models are increasingly being adopted by decision makers across small and …
All decisions concern future operations. When a company prepares decision-making materials for important matters, macroeconomic trends such as unemployment, consumer confidence indices …