RPA way forward — RPA 2.0 / RPA 3.0

RPA Way forward Journey post RPA 1.0

Hello Automation enthusiasts, Its quite a high time, many of the RPA CoEs are planning to scale up their Centre of Excellence. If your organization has established a RPA CoE which is functional from past 1–2 years with use cases varying from UI navigation to reporting dealing with ERPs, this article give steps to be considered while scaling up of your CoE if you haven’t planned yet or searching for reference materials to begin with.

Below are the steps in a nutshell if you haven’t given a proper outline to your CoE during RPA 1.0

• Define / Redefine the roles and proper responsibilities with their boundaries to avoid Duplication of Effort.
• Establishing a governing council
• Scaling the internal CoE team
• Scaling and upgrading the infrastructure
• Transforming from RPA to Hyper-Automation — Upgrading Product usage
• Assessing and adding multiple RPA Vendors

1. Define / Redefine the roles and proper responsibilities with their boundaries to avoid Duplication of Effort.

This is the first step which you have to consider while scaling up your CoE to 2.0 in case if you haven’t defined the roles during your 1.0 journey. Many of the organizations have set up a CoE where roles are either shared or being overloaded. This results in duplication of the work due to which it will be very difficult to scale up. I am pretty sure that you have defined few of the below rules but its very good to re-visit and define every roles.

1. RPA Sponsor — will establish the technology as an enterprise-wide strategic priority and will underwrite corporate resources.
2. RPA Champions — will evangelize and drive RPA adoption across the organization. They are responsible with ensuring a healthy automation pipeline, while leading the operational management of the virtual workforce.
3. RPA Change Manager — will create the Change and Communication plan aligned to the deliverables of the project. Manages the existing support team.
4. RPA Business Analyst — will be in charge of creating the process definitions and process maps used for automation.
5. RPA Solution Architect — are the ones who define the architecture of the RPA solution and oversee it end-to-end, assisting both in the development, and in the implementation phases.
6. RPA Developer — are in charge of developing, testing the automation workflows and supporting the implementation of the RPA solution.
7. RPA Infrastructure Engineer Part of both the deployment team and future operations team, they are mainly in charge of the infrastructure support for server installations and troubleshooting. The Engineer also contributes to the completion of the solution architecture for the Robotic Process Automation project.
8. RPA Supervisor — will manage, orchestrate and control the virtual workforce as part of the operational environment.
9. RPA Service Support — acting as the first line of assistance for the RPA solution in deployment.

2. Establishing a governing council

The RPA CoE Council is essentially a steering committee that provides overall governance and direction. It should meet regularly and include key representatives from the business, IT, Finance, audit, RPA CoE and others who will ensure the outcomes of RPA initiatives are in line with the objectives and expectations of executive management. The CoE Council should focus on driving RPA adoption across business units to create economies of scale and into the design and performance of the organization.

You can even plan something like a Monthly progress report which you can communicate to the respective vertical heads regarding the utilization of the existing BOTs in production there by bringing awareness to increase the BOT utilization which actually contributes to better RoI.

3. Scaling the internal CoE team

Its evident that most of the CoEs are being run by strategic partners rather than in-house team. Since you have witnessed the successful journey of 1.0, now you have to switch towards running the CoE with an in-house team.

The team is one of the critical factors in the success of automation implementation or scaling of the existing CoE, so building the team with a clear division of roles and responsibilities is of the utmost importance when establishing a COE and it’s also important to scale the team and gradually shift to complete in-house team as the number of automation projects implementation increases. It is also important to plan training and upskilling the team members in advance based on their role in the project to be in line with market trends and standards.

4. Scaling and upgrading the infrastructure

1. Complete migration of RPA infrastructure to cloud (AWS) instead of traditional VM / standalone machines. This reduces the TCO.
2. Complete migration to cloud and web based solution i.e. A2019 keeping support from product team in mind as Automation Anywhere has announced End of Sale (March 1, 2021) and End of life (Sept. 1, 2022) for Automation Anywhere v11. You can check out my other articles about the differences between A2019 and Automation Anywhere v11.

5. Transforming from RPA to Hyper-Automation

What is Hyper Automation?

It’s the extension of legacy business process automation beyond the confines of individual processes. By marrying AI tools with RPA, hyperautomation enables automation for virtually any repetitive task executed by business users. With a range of tools like Robotic Process Automation (RPA), machine learning (ML), and artificial intelligence (AI), working in harmony to automate complex business processes — including where subject matter experts were once required — hyperautomation is a means for real digital transformation.

How to achieve Hyper Automation?

First, Scaling and upgrading of the infrastructure has to happen as this is the backbone (cloud based, integrated with AI sense) of the Hyper Automation or Intelligent Automation.

Next, Hyper automation has 4 wings and Automation Anywhere’s 4 products –

• Intelligent Process Discovery — Accelerating the automation pipeline with AI-driven process discovery. Automation Anywhere product — Discovery BOT. Automation Anywhere Discovery Bot is the only process discovery solution natively built into the leading intelligent automation platform. It accelerates and scales automation across the organization by recording user activities, discovering business processes, helping identify automation opportunities with the highest business impact, and generating bots to automate them. All in a single platform.
• Robotic Process Automation — This is already being used. Only focus needed is to migrate to A2019 which is the future of RPA as this is cloud and web based solution. Automation Anywhere product — A2019
• Intelligent Document Processing — Extract data from complex documents / unstructured data from a wide variety of formats. Automation Anywhere product — IQ BOT. IQ Bot delivers intelligent document processing with cognitive technologies such as computer vision, optical characters recognition (OCR), fuzzy logic and machine learning (ML) to capture, extract, and classify unstructured information. IQ Bot creates Digital Workers and bots that are flexible, adaptable, and able to learn on the job.
• Analytics and Insights — RPA analytics in real time at the bot, process and business levels. Automation Anywhere product — BOT Insights. Hyperautomation analytics derive from the data bots gather as they work. Bot Insight is built on embedded self-measuring and monitoring within every bot that returns complete information on not only what the bot does, but also what it encounters along the way. Bot Insight uses this vast process-level detail for hyperautomation analytics that reveal what’s meaningful and predict what’s next.

6. Assessing and adding multiple RPA Vendors

We should assess the other RPA tools in order to integrate in our existing CoE. One may think that only one RPA tool i.e. Automation Anywhere in our case is sufficient and it can be used to automate all the use cases. But there are different angles to it. Intelligent automation will most likely not be achieved with one platform or one vendor. They have added AI as an “add in” and not necessarily their strong strength. Similarly, few RPA vendors play well only in few fields and may lack many functionalities which are required to automate the business process easily and the same functionalities can be found in other RPA tools.

For example, Tool A has a good OCR and Tool B has a good process mining capability. Thus by having one more RPA tool, we can achieve the process automation easily depending on the requirement with less efforts if automating the same using other tool is a tedious task.

It’s important to keep the same momentum you had while establishing RPA CoE 1.0. Hope this article gave you an idea where to begin with in order to scale up and strengthen your RPA journey 2.0 / 3.0. Let’s also have a mission of creating a personal assistant to each one in the organization through the CoE in the form of an Attended BOT in the 2.0 journey. This definitely scales up the CoE organization wise.

Thank you! Happy sharing!