Many repetitive tasks can benefit from technologies such as Robotic Process Automation (RPA) to be automated and increase productivity in organizations, especially in finance sectors. However, there are many cases if we look at the nature of those tasks; they are there because someone is trying to make a decision that involves manual tasks.

Here is, for instance, a daily workflow, a person doing a series of tasks that involves

  1. Collecting data from multiple systems and files,
  2. Entering the values in other forms of systems or excels
  3. Filling templates based on results
  4. Sending them as a form of the report; e.g., notice, recommendation, notification, etc. to people

The obvious option of these typical scenarios is to slap an RPA on the problem to automate it. However, if we look at those tasks, what you might find out is those tasks can be separated into 3 segments:

  1. Collecting data (pre-processing)
  2. Completing the calculation, finding recommendations, etc. (other tasks, i.e., logic)
  3. Building and sending reports (post-processing)

And the new way of organizing them is based on pre-and post-processing tasks, and in the middle, you have all the other tasks (i.e., logic) to find out recommendations, calculations, etc.

Why do You Do This?

The reason you need to do this is very simple; to increase operational capacity effectively and efficiently. But, now that these tasks are defined in these stages, doesn’t it resemble the decision cycle?Now in this model, the decision making of a recommendation, calculation, following audit procedures and policies, etc., can use the proper decision techniques, i.e., decision requirement diagram. Pre-processing is collecting and transforming the data for the decision making, and post-processing is carrying out the actions, e.g., preparing the template based on results of decisions and sending them to people.

Because of this separation of concerns, you are giving the organization more freedom, design, and reuse of the organization’s actual IP of the organization, i.e., the decision logic in the middle.

This means you can fully integrate technologies such as business rules automation, decision modeling, etc., to handle modeling and execution of decision logic to your RPA.  What are the benefits?

You might ask, this is so good to be true; what the catch is?

This approach has multiple challenges that sometimes out weight the benefits, at least for a specific scenario. There are multiple barriers to overcome for implementing this approach

  • acquiring new technology for decision-making
  • adaption of the new technology
  • integration of the decision automation into the RPA solution

All of these mean the need for investing from the organization in other technologies as well as RPA, which will translate to more time and money to spend. But what if you could address these challenges in a more seamless, cost-and-time effective manner?

Meet Decision Robotics

Decision Robotics is a robotics technology that has fully integrated decision-making capability. It allows you to do all you can with the RPA but more fully integrated business rules, ML, and decision techniques.Decision Robotics

Orchestrate all the pre-and post-processing tasks, build the decision logic right in the familiar, no-code platform. Model and build the post-processing tasks based on the decisions’ outcomes and deploy and execute the whole workflow.

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The benefit of decision robotics is the power of combining both decision-automation and RPA in a unified platform that does not compromise on what’s important for organizations from either repetitive tasks or decisions automation, whilst it addresses integration challenges adaption and cost of managing multiple technologies.

Particularly, in regulated industries such as financial organizations, i.e., banking, lenders and insurer, and health industries that are significantly driven by both market dynamic changes and regulations, decision robotics can deliver significant business value.

Published August 5th, 2021 at 04:54 pm