Beyond Process Automation: Cognitive Automation and Decisions Deficit

Taylor Wills
Beyond Process Automation: Cognitive Automation and Decisions Deficit

Machine learning and artificial intelligence can augment legacy systems to make better business decisions

We are used to thinking of automation as delegating business processes and routine tasks to software. But cognitive automation (or intelligent automation) brings this notion to another level. It has the capabilities to help enterprises become more sustainable and efficient. 

Process Automation: A One-Time Simplistic Approach

Current technology shows results in hyperautomating repetitive tasks. These automation tools free your employees’ time from completing routine monotonous tasks and give them the freedom to do more strategic tasks and push forward innovation. By nature, these technologies are fundamentally task-oriented and serve as tactical instruments to execute “if-then” rules. 

Process automation (or robotic process automation) works great if you have all the documents prepared and the rules prescribed. But what if you don’t have enough information by now or the data you use is outdated and requires adding new context-dependent factors? What if you don’t have time or workflow resources to continue to adapt these tools with ongoing rule changes?

Process automation proponents are touting the potential of artificial intelligence to address some of these factors. However, their vision appears to be limited to structuring unstructured data from documents, while the current RPA technology doesn’t possess enough capabilities to handle these situations. As a result, a decision maker sees the little-to-incremental benefit, as process automation solves only part of the problem.

Handling the whole problem is possible with manual intervention, and the previously accelerated processes need immediate reverting. In these scenarios, there may be a future with software robots for every person, but will every bot also need a person to manage it?

Decision Automation: Smart Automation 

Cognitive automation addresses automation in a different way. Its set of capabilities includes human-like analytics skills and sophisticated data mining. It carefully tracks the data and analyzes it smartly to provide data-driven recommendations. And once a decision is made, it orchestrates the execution in the underlying transaction systems.

Cognitive technologies aim at establishing a more sustainable and efficient enterprise. It never stops learning to remain up-to-date, and it makes the automation process as easy and controlled as possible. Cognitive automation is a systematic approach that lets your enterprise collect all the learning from the past to capture opportunities for the future.

First, it maps the data. With cognitive automation, you get an always-on view of key information within your enterprise. It establishes visibility to data across all of an organization’s internal, external, and physical data and builds a solid framework. You get a constantly refreshed image of data with a unique algorithmic library.

It’s almost a “digital twin” of the enterprise. It’s not another black-box technology. You can see each data point and track the logic step-by-step, with full transparency.

Then, it makes contextual recommendations. Depending on the chosen capabilities, you will not only collect or automate but also act upon data. In contrast to the previous “if-then” approach, a cognitive automation system presents information as “what-if” options and engages the relevant users to refine the prepared decisions.

It doesn’t set recommendations out of anywhere or execute them blindly. Cognitive automation is the system of engagement to really connect users and provide them with valuable insights.

Finally, it’s involved in continuous learning. A cognitive automation tool learns from the decisions you make and adjusts its future recommendations accordingly. What’s more, it constantly reviews the previous actions, looking for repeatable patterns you can automate.

Cognitive automation doesn’t merely accelerate mundane tasks. It’s proactive in picking the right decisions to automate. 

Cognitive Automation and the Decisions Deficit

How does cognitive automation provide a step-change in efficiency by focusing on decision making? Even today, there are decisions that are not being made on a daily basis. There is simply not enough time or people to gather the right information, analyze the data, and make informed choices.

Organizations address these challenges by categorization — usually labeled in buckets of what’s strategic, and what’s not. And it boils down to the 80-20 rule, where companies spend 80 percent of their effort on the 20 percent of their most important (“strategic”) items. Usually, the issues that are not deemed strategic are left undecided. 

And sometimes there’s not enough time for some of the strategic issues to be addressed.

Cognitive automation helps to address the "decisions deficit" by not only making complex decisions better but also enabling the organization to cover the 80% that’s not being decided at all today. And if you add up the impact of these undecided issues, it’s potentially massive.

The technology lets you create a continuously adapting, self-reinforcing approach where you can make fast decisions in the areas that require human analytical capabilities. The system gathers data, monitors the situation, and makes recommendations as if you had your own business analyst at your disposal. And when you’re comfortable with the system, you can begin to automate some of these work decisions.

This way, cognitive automation increases the efficiency of your decision making and lets you cover all the decisions for your enterprise. It’s not about the task or process. It’s about the decision.

Taylor Wills
Staff Writer
October 25, 2021