Move Aside RPA Cognitive Automation Has Arrived

Move Aside RPA Cognitive Automation Has Arrived

SUMIT PANDEY

As the RPA market matures, organizations are looking for solutions that go beyond traditional RPA and include deeper cognitive capabilities.

These solutions can analyze dynamic data and perform sophisticated tasks like generating insights and providing recommendations for action. They are also able to learn from their experience with each new task, improving their performance over time. Cognitive automation is the next big step in RPA, and it’s already here.

Not all cognitive automation solutions are created equal, however. An enterprise’s choice of cognitive automation solution can make or break the deployment. This is why it’s so important to understand what makes a cognitive automation solution worth purchasing, and what to watch out for when considering a new solution.

Here are five things to consider when evaluating a cognitive automation solution:

  1. Understand its underlying architecture. Look for a solution that is based on a new approach to structuring data and computing. This will make it easy for you to exchange data with third-party applications and to integrate automation with your core business systems.
  2. Look for a solution that is based on a new approach to structuring data and computing. This will make it easy for you to exchange data with third-party applications and to integrate automation with your core business systems. Be sure it can learn. Cognitive automation solutions should be able to learn from their experience with each new task in order to continuously improve their performance over time. This capability will give you an advantage over competitors who use traditional RPA solutions.
  3. Cognitive automation solutions should be able to learn from their experience with each new task in order to continuously improve their performance over time. This capability will give you an advantage over competitors who use traditional RPA solutions. Review its language support. Look for a solution that supports multiple programming languages, such as Java, Python and C#, to allow for greater flexibility in designing and creating processes and workflows across your organization.
  4. Verify its accuracy levels. Make sure the solution uses machine learning algorithms that enable it to identify patterns from the data it analyzes, reducing human error and improving its performance over time.
  5. Make sure the solution uses machine learning algorithms that enable it to identify patterns from the data it analyzes, reducing human error and improving its performance over time. Check its ease of use. Make sure the technology is easy to use and understand, even by non-technical users, such as business analysts, project managers and business unit leaders. A good cognitive automation solution should be intuitive enough that a non-technical user can figure out how to use it on their own or with minimal training or support from IT or other staff members, making it easy for everyone across your organization to use the system.

What Can RPA Plus Cognitive Capabilities Do?

  1. Create a new role in your organization called the Cognitive Automation Architect. This will be the person who takes ownership of the Cognitive Automation initiative and is responsible for the leadership, design, planning and execution of all aspects of the project. Also, make sure you have a skilled cognitive automation practitioner working on the project.
  2. Elaborate on your existing RPA roadmap and prioritize your cognitive automation project to fit in with the other initiatives that are already underway in your organization.
  3. A pilot project is necessary to gain experience and establish a strategy before you decide to scale this initiative across your entire organization.
  4. Start with a small number of high-value, high-impact process flows that are less complex and easier to implement. This can help you iron out all of the kinks that might come up during the implementation phase and allow you to have a successful launch.
  5. Identify the most suitable technology partner to help you with your cognitive automation project. Look for a partner that has experience in this area and has implemented similar projects successfully in other organizations.

Future is arriving quickly:

PAST

PRESENT

FUTURE

Segmentation

Personalization

Customer Empathy

Analytics

Insights

Self Learning

Workflow Automation

Robotic Automation

AI/Cognitive


Conclusion

Organizations need to take the next step in their automation initiatives. The easy part has been done with RPA. But now, it is time to move on to the next level — Cognitive Automation. This can help your organization gain a cognitive edge over competitors and automate business processes that have been too complex or difficult to execute manually.