With an acceleration in the number of digital initiatives, several Indian enterprises have used the power of automation to support their digital transformation efforts. Different organizations have used different strategies with respect to their automation journey. Many organizations started their automation journey using technologies such as macros, data scraping, and desktop automation. While these enterprises were successful in automating certain tasks, the challenges far outweighed the benefits. Difficulties in integration, security risks, and governance issues were a few of the challenges faced by enterprises who had adopted these tools. The next phase in the automation journey was made possible by adopting Robotic Process Automation (RPA) tools. However, enterprises have encountered several roadblocks using RPA and found it lacking to achieve true digital transformation.
What is lacking in RPA?
With the advent of RPA, processes that were repetitive, error-prone, and without variations, became obvious candidates for automation. But this version too had its challenges. One obvious challenge was the dependency on the underlying application. A disruption in a single isolated process would trigger a change in the application the bot runs on, which would subsequently lead to a breakdown of the entire RPA deployment on top of the application
Other challenges with respect to RPA include:
RPA falls short when it came to execution – with some projects taking up to 9 months in some cases
RPA lacks the ability to create front-end user interfaces and define new workflows
RPA has limited ability to automate processes end-to-end, that are susceptible to breakages due to application interfaces changes, process changes, etc.
With the constant need to fix issues around application upgrades and process changes, bot maintenance can be expensive- sometimes exceeding the cost of initial bot development
The governance of bot farms becomes challenging for IT, especially with enterprises leveraging bots from multiple vendors
How Intelligent Automation can provide the required answer
Intelligent Automation includes the orchestration of three layers of technology:
Automation technology: At the core we have Automation technologies – such as Process Mapping and Intelligence (e.g., Process Mining, Task Mining, and iBPMS); Data-led Transformation (e.g., Intelligent Document Processing); Workflow, Process, and Task Automation (e.g. Low Code, RPA, API, and Intelligent Virtual Agents)
Intelligence technology: The Automation technologies are further bolstered by Artificial Intelligence (AI) and machine learning technologies. For example, Computer Vision, Natural Language Processing/Natural Language Generation, Conversational AI, etc.
Infra technology: Automation and Intelligence tech are in turn powered by Next-Gen Infrastructure
This model, in contrast to RPA, enables organizations to adopt a more holistic approach towards automation. It enables proactive identification of new processes with automation potential, aligning/preparing these as required, and finally automating these. This model also enables organizations to scale their automation initiatives with ease.
With the right enterprise low-code platforms, enterprises can kickstart the next phase of their intelligent automation journey and manage end-to-end software development. Low code can help every step of the way: from ideation to scaling up with agile DevOps, on a single platform. Ultimately, leading to the ability to design and develop strategic products rapidly, with immersive UX and built-in security. To ensure maximum value from any automation initiative, it is essential to have a holistic and well-defined approach – an approach that covers people, process, and technology. Only then can enterprises realize the vision of truly being a digital enterprise.
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