It is a set of concepts, technologies and methods to assist or reduce the human component in a specific high-order, judgment-based decision-making process, situation or context. The focus and goal of decision automation are to mimic, model and automate a human decision-making process. It is deemed to be one of the most impactful technological concepts for businesses today.
A New Business Trend
Automation is trending. While AI was the dominating technological buzzword, automation remained widely untouched by mass media. Nevertheless, the term is receiving increasing attention from various industries. Decision automation especially has seemed to evolve into the trend of choice for industry leaders and professionals in numerous sectors. It is a somewhat complex topic but a promising business strategy with tremendous potential. What is it about?
Automation – A Main Driver of Progress
An Emerging Business Strategy
In recent years, an additional field of automation has emerged: Decision Automation (also sometimes Intelligent or Cognitive Automation). While Business Process Automation and Robotic Process Automation are focusing on the mechanical description of the actual execution of human tasks, Decision Automation describes the digital assistance of the decision-making process prior or parallel to the execution. Considering that the average adult makes about 35,000 remotely conscious decisions each day it becomes clear why automating decisions would have a huge impact. So, what is decision automation?
There is no universally excepted definition for Decision Automation. One approach defines Decision Automation as a set of concepts, technologies and methods to replace or reduce the human component in a specific recurrent, high-order, judgment-based decision-making process, situation or context. The focus and goal of decision automation are to mimic, model, and automate a human decision-making process. Decision Automation aims to improve, accelerate, streamline, and shorten decision-making, rendering it more transparent and trackable.
Decision Automation may be considered in complex decisions scenarios in which various, intertwined, dependent, and complex conditions need to be assessed to make a decision. While BPA and RPA primarily focus on linear processes and simple human tasks, decision automation comes into play when a high-order decision needs to be derived from a set of complex conditions that would require a cognitive, judgment-based process. Just like human decision making and task execution are intertwined, and parallel proceedings, business and IT automation approaches are often hybrids with Decision Automation elements.
Benefits and Requirements
Decision Automation aims at managing high numbers of similar cases to foster advantages of digital automation in general, allowing not only accelerated processes but a reduction of errors and costs, higher transparency and measurability, knowledge management, and an overall raised service level.
While the rule-based technology core of decision automation systems, in theory, allows the automation of most every decision-making process. Required knowledge and relevant decision criteria do not necessarily need to be digitally available but can be gathered by the users. For the authors, the problem situation at hand must be clear and well understood.
Feasibility will be determined by economic or strategic considerations. Consequently, the introduction of decision automation is desirable in high-frequency decision environments or generally situations where human participants are unable to limit or provide solutions to repetitive management problems.
They are most useful in situations that require solutions to repetitive management problems mostly using electronically available information.
Building Blocks of Decision Automation
Decision automation is generally achieved through modeling a specific decision-making process with a set of complex pre-defined rules, criteria, data, and logic (e.g. conditional decisions trees). The rules and logic allow navigating through a specific context until a clear and precise decision can be made.
Traditionally, Decision Automation has relied on a rules-based approach (with differing technologies and concepts). Today, there are applications visible with hybrid concepts based on machine learning and statistic approaches. Decision Automation uses various input sources to gather the required data to decide.
Modern tools can combine rules-based approaches with machine learning components to hybrid systems which allow for self-learning and self-correcting. Modern Decision Automation platforms also allow for enriching the decision-making process with workflow automation.
Sectors Ripe for Decision Automation
Decision automation can be determined for many different segments of company activities, including legal, sales, compliance, management, operations, support, and HR. Decision Automation is well-suited to areas where the same decisions with the same type of data have to be made on a recurring basis. Decision Automation supports subject matter experts, professionals and knowledge workers such as lawyers, accountants, tax advisors, support staff, doctors, consultants, compliance, regulatory, and HR experts.
Decision Automation can be a standalone initiative or part of a larger, overarching strategy. It can interact with and involve aspects of Business Process Automation, IT Automation, or Robotic Process Automation, e.g. when Decision Automation Modules trigger workflow actions, integrate into parallel processes, or generate documents.