Establish a RPA Centre of Excellence to drive Automation
Several organisations are attempting to implement Robotic Process Automation (RPA) to automate their business processes. However, studies show that over 50% of the implementations of RPA fail owing to several reasons. We recommend establishing a Centre of Excellence for RPA in your organization that will enable governance, implementation of best practices, curating a structured framework for development and managing automation initiatives and necessary support post implementation. We have outlined an approach to create an enterprise CoE for Automation so it can help companies navigate this path and have much higher success rate in RPA implementations.
Clearly Define the Automation Vision and Strategy
It is important to clearly define the purpose of the RPA CoE, its objectives and ensure the alignment with business goals. Finalize the measures to establish the business case and how cost and operational objectives can be driven. Pl refer to paper on Formulating a Business Case for RPA. It is also important to align all the departments in the organization to align with the vision and obtain the sponsorship of Executive Leadership in the organization.
1. Alignment of Business and People: Clear objectives to set business priority and focus on objectives like cost reduction, efficiency, customer experience and compliance.
2. Define Scope and Scale: This initiative is usually enterprise wide and cuts across departments, needing tasks, activities and coordination. It may be good to take one department or business area at a time and then scale the others over period of time taking learnings from the previous experience.
3. Key Measures & Operational Metrics: Institutionalize the success criteria for automation with critical measures and operational metrics that are qualified by the business case as target to achieve. These metrics and targets must be tangibly measurable without ambiguity.
Centralized Model
In a Centralised model a single CoE team governs and manages all RPA initiatives and activities across the organization or enterprise.
This model enables a central command and control thus enabling better standardization and a strong governance. Reporting and control measures can be implemented much faster.
This is usually good when one is starting the RPA CoE and Automation journey. Maturity can be evolved quickly and is most suitable for organizations that have little or no automation in place.
Decentralized Model
This model mostly suits a large enterprise that have multiple business units and are geographically dispersed. Each business unit may have their own RPA programs that suit their specific needs.
A Decentralised model allows organizations to adopt RPA tooling much faster across the enterprise however this my result in a lack of standardization. It will be a good idea to see how departments can collaborate between them and share learnings
This model is ideal for a large enterprise or a large conglomerate that has very diverse needs. Globally distributed or regionally distributed enterprises can adopt this model since it can be scaled quickly.
Hybrid Model
In the hybrid model a central command and control team governs and ensures best practices are adopted and standards are formed for business units to adopt. They may also run this on a central infrastructure.
The individual Business Units can adopt the standards and best practices while they run their own automation development and execution.
The hybrid model is most suitable for global enterprises, and it ensures governance, controls and flexibility.
Create and build a CoE team with the right skills
It is of paramount importance to build a good CoE team with the right skills, roles and empowering them to drive the automation program. The CoE Team must have process knowledge, transformation ability and the software tooling skills besides the right leadership to drive the digital transformation. They must be empowered to take decisions aligned with the executive leadership team. The table depicts typical roles that need to be part of a CoE Team. There may be additional roles based on the type of model that is being implemented in the organization.
| Role | Function | Skills |
|---|---|---|
| Automation Head / CoE Head | Ensure Governance, strategic and operational alignment with business objectives and outcomes. The Head must be a change agent in the organization. | Has led diverse teams and skilled to navigate across departments / business units enabling change. |
| RPA Solution Architects | Aligned with Business objectives, enables the right toolset to be implemented, meeting functional and technical requirements. Designs the solution optimally considering constraints, performance, scalability and maintainability. Ensures software change management and configuration management practices. Review PDD and SDD and ... | Has led teams developing bots and is current in technical skills with the ability to solve key challenges and lead teams. Needs to be conversant with the technology stack and tooling to drive the transformation. |
| Role | Function | Skills |
|---|---|---|
| Process SMEs / Business Analysts | Support the team with in-depth process knowledge on enterprise systems and having the ability to document the as-is process as well as visualize the to-be process without any disruption to business. Review PDD, SDD Documents and conduct UAT of the system. Review PDD and other deliverables. | Expertise and domain knowledge in the key functional area. Knowledgeable about regulatory norms and compliance needs. |
| Infrastructure Lead | Leads infrastructure team to deploy RPA tooling building necessary hardware and software environments. Ensures adherence to standard processes followed in the organization. | Expertise in hardware, cloud and software environments. Has handled multiple environments like development, test and production. Has led teams to deliver transformation projects. |
| Security Lead | Drive Enterprise Security on Cloud as well as intranet systems. Ensures adherence to security practices and responsible for security and penetration testing. | Expertise in enterprise security and standards. Experience in implementing complex enterprise systems from a security standpoint. |
| RPA | Develop and configure bots | Good development skills |
| Role | Function | Skills |
|---|---|---|
| Developers | based on the requirements. Build the PDD and SDD documents. Build Handover document. Follow enterprise standards and ensures good configuration management. Documents all the steps and builds bots as per design. | skills, knowledge of the RPA tooling. Has experience in building bots and understands solution architectures. |
| Change Management Lead | Drives adoption of new processes, and smooth transition from old to new process. Ensures training and people transition. | Change management, transition management, communication and people management. |
| Testing Lead | Responsible for test data creation, ensures testing processes and standards are followed. Follows agile or waterfall testing principles. Ensures test coverage and Reporting. Defect Management and test cycle management. | Skilled in testing bots and test reporting. Test data management, exception management reporting and documentation. |
| Support Lead | Monitors bots for exceptions, performance, upgrades, life-cycle and enhancements. Has ability to handle issues, seek workarounds, identify defects and ensures minimal or no business impact. | Expert in supporting bots in production, experience in handling different environments and deployments. |
Invest in the Right Technology Tooling
Its important that you choose the right technology tooling that best addresses the business case, with the right features, scalability, ease of use, costs and compatibility with the underlying enterprise systems that the business runs on.
Some of the well known tools in the market are:
- UiPath
- Automation Anywhere
- Blue Prism
- Power Automate
Factors to Consider:
- AI/ML capabilities and Intelligent Automation, Support for structured and Unstructured Data and handling of documents
- On-premise v/s Cloud deployment model support
- Security, compliance, reporting, product support and governance
- Licensing Models
Process Discovery and Process Mining identify the right candidate processes
Some of the widely adopted criteria include the below:
- High Volume and Repetivie in nature
- Rule base and without too many exceptions
- Time Critical to Business
- Processes that have high human errors
It is important to use a clear RoI based assessment to evaluate the processes being considered. One must also use a criteria to evaluate the impact to business and consider the complexity of these processes. Its good practice to choose High Impact Low Complexity and mature towards High Impact – High Complexity.
Development, Testing and Deployment of Bots
Leverage the right technology partner who can provide the necessary services to build efficient bots. Its important that the partner has the necessary capabilities and experience and is reliable to enable digital transformation. Ideally the partner must have a good delivery framework leveraging Agile or other development cycles, ensures adequate testing, configuration management. One needs to also test for scaleability and security prior to deployment.
Adopt a good governance model and establish standards
Its vital to establish a good governance model especially when you have a virtual team who perhaps have more tasks besides being part of the RPA CoE. Establish program governance and good change management practices that will enable transformation and transition from old to new processes. Follow data protection and practices, align with GDPR, HIPPA, SOC2 standards and implement compliance practices. Have audit mechanisms that will monitor and control the processes while evaluating performance and RoI.
Scale processes, optimize and monitor continuously
Commit to long term business and operational goals, monitor bots and enhance architecture to optimize continuously. Consider the following:
1. Performance Analytics: Track all key metrics like error rates, TaTs, utilization, idle time, peak load performance and other relevant parameters.
2. AI/ML: Build in cognitive automation capabilities that can help with intelligent decision-making and continuous improvement of processes.
3. Scale the Automation Solution: Enable new business functions and expand the automation scope across departments, business verticals and regions.
To conclude establishing a RPA CoE requires a structured approach that combines people, process and technology. Establishing the right model for the CoE, selecting the people, right tooling and implementing a good governance will drive enterprise-wide digital transformation and automation success.
