The spectrum of Decision Intelligence (DI) extends over several levels of autonomy. With Decision Automation (DA), humans set up control tasks for autonomously operating decision processes.
Similar to autonomy levels required for assisted driving, the spectrum of Decision Intelligence (DI) spans several levels. With Decision Automation (DA), humans delegate the entire decision-making process to the machines.
DA is one of many processes that DI can utilize to make daily decisions in the running of companies and organizations. The use of Artificial Intelligence, machine learning and process automation empowers users to make comprehensive and unbiased decisions based on existing data.
For tasks that the user would rather be carried out by using experience or cognitive considerations, support through analyses or data visualizations (Decision Support) is usually sufficient. For recurring processes, on the other hand, supplementary support (Decision Augmentation) is the optimal choice. In this case, the analyzed data is used to generate recommendations and predictions.
In other words, DA requires just minimal human involvement within the decision-making process. The machines perform both the decision step and the execution step independently. Of course humans maintain an overview and monitor for risks and any unusual activities whilst they regularly review the results in order to improve the system.
Automated systems are the fastest and most profitable solution for routine tasks in business and customer operations as well as in production. Programmed processes can execute schematic tasks and run error-free and without pausing. As such, automated decisions increase productivity while reducing risks and error rates within the decision-making process. They are most useful in situations where solutions to recurring management problems are required.
An efficient DI system will allow all three levels – support, augmentation and automation – to be selected. This gives users the chance to employ different levels of automation according to their skills and confidence in the technology.
Another benefit is the ability to switch to a different level during an event of extreme changes in conditions. For example, during the Covid-19 pandemic the previous year’s data became unusable for predictions in most instances.
To get started with DI, it is best to categorize your business decisions by frequency and complexity using a matrix diagram of the three levels mentioned above. For the simplest and most frequent decisions the use of DA is suitable, while the most complex and least frequent decisions fall into the category of Decision Support.
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Paretos is the leading AI-based Decision Intelligence software for optimized decision-making processes. With paretos, businesses can identify, plan, execute, and track business potentials through automated processes across the entire organization.
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