Although Robotic Process Automation (RPA) is the foundation of many digital transformation efforts, it is very common for organizations to deploy their software bots in a haphazard manner. Even when deploying a single bot as a proof of concept or test case. For example, a company's accounting department implements a bot to automate invoice processing, while operations implements another to streamline shipping requests, without any coordination between the departments. This decentralized approach involves a risk that leads to problems later on.
The automation of operations often requires robots to interact with each other and access or broadcast data, and these robots usually rely on related systems and policies. But what happens when there are policy changes or when a system fails?
Simply put, their robots stop working and processes grind to a halt.
This can happen in many situations. Legacy systems and websites evolve, applications are updated, passwords expire, humans modify spreadsheets, and security patches are applied.
If there isn't some kind of standard or way to manage and maintain this digital workforce, when something changes, the robots won't know what to do, and they will be out of control.
Avoid chaos by implementing a solid governance program. As the business expands, governance becomes more important. A lack of governance is one of the most common reasons initial RPA projects fail, according to EY. Without a strong governance program and the right robot lifecycle management tools, automation initiatives will be in jeopardy. Robots require direction, management, and maintenance to keep functioning properly and deliver maximum value.
A robust governance program must include three essential components: a framework, a Center of Excellence, and robot lifecycle analysis and management tools to support your automation program. Let's explore each of them in more detail:
1. Prepare the ground for governance
To maximize the benefits of RPA, Chief Operating Officers (COOs) and Chief Information Officers (CIOs) must collaborate to establish an optimal operating and software robot deployment model. When designing and implementing a framework, this team must determine how the digital workforce will work with employees. This is similar to a compliance policy that employees typically sign when they begin working for a company.
An effective framework requires:
A business robotics tip: This team leads the program, defines its scope, and sets the objectives for tracking efficiency and execution results.
A business unit steering committee: This group is responsible for prioritizing RPA projects across all departments and business units.
A technical RPA or Center of Excellence tip: This team designs the standards, formulates working principles and guidelines, and compiles best practices.
2. Establish a Center of Excellence:
The Center of Excellence (CoE) is made up of specialists and people responsible for guiding everything related to automation, including the management and maintenance of standards and vendors; the creation of best practices; training and onboarding. It should include IT experts and experts from each business area. With this collection of knowledge, the team will be better prepared not only to make decisions about the best RPA tools to implement, but also about which processes are the best candidates for automation.
There are three basic models of Centers of Excellence, and each of them is differentiated by the way responsibilities are shared across the enterprise.
Centralized operating model: A single team is responsible for executing and controlling all aspects of the program.
Decentralized operating model: Responsibilities for executing the automation program are distributed among the organization's various business areas.
Hybrid operating model: Some aspects of the automation program are handled by a single centralized team, while others are distributed among the business units.
Choose the model that best suits your current situation and adjust it as needed.
3. Invest in robot lifecycle management and analytics
It is easy to achieve governance when RPA tools include management and monitoring capabilities such as version control. More sophisticated capabilities, such as robotic life cycle management, help your teams manage RPA deployments of hundreds to thousands of robots or processes. These tools help your users track changes, compare files, and analyze the changes made. In addition, it also facilitates the storage of backup files, so that if you have to revert to a previous working version, it is easy and fast.
As automation expands, it will become increasingly important to have a robust version control and management program. When a robot fails, and you do not have a management system or digital workforce analytics, it is almost impossible to track which of the hundreds or thousands of robots is causing a problem or where one has crossed paths with another and stopped a process in its tracks.
By empowering a center of excellence along with other tools such as robotic lifecycle management, you will adopt a more business-centric RPA approach that goes far beyond simple task automation.
A solid governance program is a key indicator of success in robotic process automation. When supported by robot lifecycle management and digital workforce analytics, the risk of your robots running out of control will be reduced.
Spanish 
English 
German