Automation Center of Excellence
CoEs, often also called “knowledge centers”, have been used in recent years to share accumulated knowledge in different areas such as marketing, pharmaceuticals, automotive, and telecommunications. A CoE can be defined as a group of highly skilled experts who work together to analyze knowledge in a specific area of interest and provide the company with the necessary support to implement technologies in compliance with recommended best practices.
Similarly, an Automation CoE focuses on integrating a strong framework and successful implementation of automation tools within the company.
Benefits of the Automation Center of Excellence
Robotic Process Automation (RPA) has become a must-have for companies looking to increase their operational performance. However, to achieve an even higher level of automation that is adaptable and scalable, intelligent automation is necessary. This is where the crucial role of automation centers of excellence (CoEs) comes in.
CoEs enable rapid digital transformation while controlling associated risks and ensuring that automation investments are managed wisely. By establishing a CoE, companies can effectively manage and monitor their initiatives with total transparency. The automation CoE thus lies at the intersection of control, speed, and agility.
- Efficient robot development cycle:
An effective Automation Center of Excellence (CoE) helps companies to centralize knowledge and learning data in the field of automation. It also provides access to best practices shared by other business units, focusing on researching RPA platforms and automation processes. This information sharing enables companies to optimize their time, speed up RPA deployment, and simplify automation-related initiative management.
- Integration of IT and RPA:
A well-structured CoE ensures the participation of IT in the project team, where they were previously considered an optional addition. IT teams manage aspects such as infrastructure, security, data confidentiality, and other strategic elements from the start of a project, reducing the risk of automation disruptions. Legacy computer systems are constantly evolving and are regularly updated, which can alter automation at the user interface level. IT teams can help prepare for and anticipate these changes.
- Scalability Ease:
Uncoordinated RPA projects can hinder success and prevent companies from achieving desired levels of automation and organizational objectives. A CoE is critical in preventing these types of failures and establishing a comprehensive vision for the company that allows for easy adaptation of RPA. If the goal is to implement automation throughout the organization, a CoE is essential for successful adoption and promotion of RPA or any other automation software.
- Improved Return on Investment (ROI):
The absence of a CoE can lead to significant costs for integrating RPA technology, as well as difficult-to-identify inefficiencies that hinder automation, RPA acquisition, and support. A thorough evaluation of potential process automation can help avoid a negative return on investment when investing in a project. Multiple factors must be considered, and in some cases, RPA may not be the best solution for improving processes.
CoE speeds up the deployment of AI.
- Deployment of AI
In a recent study by AI experts, “64% reported that it took their organization at least a month to implement a new model, and 20% reported “6 months or more”.”
This is where the automation center of excellence (CoE) can make a significant difference. It achieves three critical outcomes:
- It streamlines deployment to accelerate time-to-market.
- It sets the standard by determining the elements needed for a profitable business plan.
- It optimizes resource utilization to execute projects with increased efficiency and significantly reduced expenses.
- How do CoEs achieve these results?
An effective automation CoE uses enterprise platforms and human-automation collaboration to enable rapid integration of models into workflows. This not only allows system robots to access and apply these models in real-time, but also creates conditions for continuous improvement of models using human feedback. Additionally, they drive automated extraction, transformation, quality assurance, and data management with centralized governance and compliance to standards.
The automation CoE goes beyond just “time” considerations to achieve large-scale automation. It seamlessly integrates technology, processes, and people to deliver value-oriented business outcomes while improving operational efficiency and costs. By taking a business-oriented approach rather than simply adopting technology, it links business context to robotic process automation (RPA), AI-based technologies, process mining, and advanced analytics – and thus provides transformative results at all levels of the enterprise. This approach tackles the process fragmentation that poses a challenge to organizations. The CoE therefore shifts from the logic of automating tasks and enterprise processes to that of intelligent automation.