Digital Decisioning, at the heart of hyperautomation creating value
Process technology like workflow management or IoT organizes the data to make decisions efficiently, but organizations make their profit or loss in the day-to-day operational decisions.
In previous blogs, six key technologies of hyperautomation were visited. This blog explores Digital Decisioning and its benefits, risks, and costs when applied to hyperautomation.
Digital decisioning is a process in which automated systems make decisions based on regulations, data, and algorithms. It is a crucial component of hyperautomation, as it involves integrating and coordinating multiple automation technologies to make more informed and efficient decisions. In addition, other hyperautomation technologies gather and organize data and information to make business value-creating decisions.
It is possible to use hyperautomation initially without Digital Decisioning. An organization could use hyperautomation to automate processes and tasks without using advanced technologies to automate operational decision-making. For example, an organization could use robots and other types of automation to perform tasks in a manufacturing process but still rely on human workers to decide how to allocate resources or respond to changes in demand. Or use hyperautomation to automate the workflow and leave the decision-making to specialized case workers. A logical next step would be automating the operational decisions the allocators or case workers make.
Augmented Decisioning could be, for some organizations, a step in between, as it enhances or supplements human decision-making processes. It involves using decision models, data and analytics, artificial intelligence, and other advanced technologies to provide additional information or insights to help humans make more informed and accurate decisions. However, the human makes the final decision and is responsible for guarding ethically and responsible decisioning and the legal implications.
Risks to mitigate
This augmenting step poses an excellent opportunity to learn, elicitate and refine the decision models gradually and to mitigate risks, such as:
It is vital to mitigate these risks ensuring that Digital Decisioning systems are developed and implemented with careful consideration of ethical and legal principles. This mitigation includes regular monitoring, auditing, and testing of the algorithms and incorporating human oversight and accountability mechanisms into the decision-making process.
In many cases, hyperautomation is used with Digital Decisioning, as advanced technologies such as decision modeling and machine learning can significantly help improve decision-making speed, efficiency, and accuracy.
Best candidates
In the previous blog, Process mining is pointed out in identifying the best candidates for Digital Decisioning:
领英推荐
Tangible benefits to reap
Overall, Digital Decisioning can be helpful in almost all situations where there is a need to improve the efficiency and accuracy of decision-making. However, it is crucial for organizations to carefully consider the benefits, costs, and risks of adopting this technology and to evaluate whether it is the right fit for their specific needs and goals. Potential benefits include:
Costs to recon with
These benefits then must be quantified and set against the costs associated with Digital Decisioning, including:
Digital Decisioning can involve both high costs and high benefits. It is crucial for organizations to carefully consider these costs and assess whether the short-term and long-term benefits of adopting this technology are worth the investment. It is also essential to carefully plan and manage the implementation of Digital Decisioning to minimize costs and ensure a successful outcome.
Final thoughts
Overall, the role of Digital Decisioning in hyperautomation will depend on the specific needs and goals of the organization, and it is crucial for organizations to carefully consider the benefits, costs, and risks of adopting this technology as part of their digital transformation strategies.
More articles published in the hyperautomation series