Robotic Process Automation (RPA) has emerged since 2010 as a form of business process automation technology, based on metaphorical software robots (called bots). With these software robots, organizations can digitize their workforce. In many cases, the software applications ‘learns’ the processes that people perform behind a computer, and subsequently automate these steps. In order to accomplish this, the software needs some advanced forms of technology. Most importantly, RPA technologies have the ability to build advanced workflows based on screen capturing technology.

Understanding Robotic Process Automation (RPA) requires an understanding of the business benefits of RPA, the technology and implementation process.

Screen capturing technology captures the work that people execute behind a computer. For example, someone in an HR function who makes employment contracts, scans a passport and subsequently enters this data into the company’s HR system. For all employees, this process is exactly the same and the data that needs to be inputted into the system is every time at a similar location. This would be a prime example of a process that can suitably be automated. RPA technologies can detect the steps that are executed by the HR employee, and subsequently translate this in an automated workflow.

RPA is primarily suitable for the automation of repetitive, and standardized processes. In many organizations, most repetitive processes occur in Finance, HR, Facility and IT departments. These ‘supporting’ business functions are (depending on the organization) also commonly centralized in Shared Service Centers. RPA is therefore extremely suitable for the automation of back-office processes. Prime targets for RPA include: data entry and validation, file and data manipulation, formatting, and multisystem, data entry or reconciliation.

Although this might not sound as something necessarily new (business process automation has been around for decades), one of the key differentiators of RPA technologies is that they have the ability to incorporate machine learning and artificial intelligence algorithms to ‘detect’ optimization opportunities. Additionally, a secondary key benefit is that RPA does not replace existing applications or their underlying code, but rather integrates existing data sources, combining these sources into new documents, files or databases. In this sense, RPA robots truly mimic ‘digital workers’, because they perform (or execute) many tasks that employees of an organization would do as well.

The adoption of RPA technologies has been growing rapidly in recent years. According to research from Forrester, there are more than 50 providers of RPA technology. Gartner on the other hand claims that the RPA market grew 63% in 2018, with the top-5 vendors controlling 47% of the market.

RPA has grown quickly in adoption and popularity, because of the following Business Drivers for RPA. These can be divided into two main categories:

Operational Efficiency

• Reduction of Costs – Automation of repetitive manual tasks reduces costs;
• Process Efficiency – Automation removes bottlenecks and speeds up process delivery
• Process Accuracy – Automation reduces mistakes and eliminates unnecessary failures
• Regulatory Compliance – Automated processes can be verified and audited to comply to rules and regulations

Customer Satisfaction

• Decreased Delivery Time – Automation reduces waiting times for customers.
• Process Transparency – Automation increases the clarity and visibility of processes.
• Intuitive UI – Automation provides more clear and intuitive user interfaces

The list above can be complemented with different benefits that would apply for different sectors. In the finance industry, for example, compliance and traceability are more important factors than in other industries. For companies in this domain, RPA can therefore bring additional business benefits because every step the robot processes can be logged, monitored and audited.

Depending on the size and scope of the RPA solution, RPA implementation is executed in a number of distinct steps. In any case, it always consist of 3 main phases:

The proof-of-concept is the first step in any RPA implementation project. The proof-of-concept starts with the determination of the purpose of the RPA project as well as the identification of a number of Use Cases in the organization. In this first phase, it is important to outline the objectives of the RPA program and determine Key Performance Areas for the overall success of the RPA program. Although the objectives can shift during any RPA Project, it is critical to determine the KPAs beforehand in order to determine success during operational delivery of automated services.

As part of the proof-of-concept, one or more suitable use cases need to be defined. To find suitable use cases, your organization will need to consider the current process organization, as there will likely be a number of ‘bottle-neck’ processes. Depending on these processes, there might be one or more use cases that could be suitable for the initial proof-of-concept.

During the proof-of-concepts stage, it is important to start establishing an internal RPA Framework. The RPA framework will need to contain the policies, applications and governance of the automated processes in the organization. As robots are frequently located externally from the organization’s IT infrastructure (for example, through a cloud solution), there might be governance and security issues that need to be addressed. In this initial step, the Cybiant Discovery Workshop can provide quick guidance on the identification of RPA Use Cases the status of the RPA framework.

The Pilot Phase is the second step in the RPA Implementation program and focuses on the implementation of RPA use cases. In this phase, the automated workflows are designed and implemented on the RPA technology platform. In most cases, this includes the set-up of the orchestrator, the robot controllers as well as the robot runners. Together, these three components make up the ‘robot’ that is referred to as the digital worker.

One of the most important aspects of the Pilot Phase is the (data) integration between the company’s source data and the RPA solution. As mentioned above, the robot needs to work on the data that is present in the current IT landscape. In almost all cases, this means the most ‘complex’ issue is the integration (data pipelines) between the organization’s various data sources and the RPA solution.

At the end of the Pilot Phase, which frequently takes between 4-6 weeks, the robots have been ‘running’ for an extended period of time. At the end of the Pilot Phase, it is therefore time to evaluate the results and move towards the adoption and scaling stage.

Depending on the results of steps 2 and 3 (The Proof-of-Concept and Pilot Phases), it is time to start leveraging the benefits of automation on a larger scale. In this step, multiple use cases are identified per department (or multiple departments are included). The goal of this Phase is to ensure that RPA becomes a sustainable tool in the management of the daily process organization.

The recommended approach in this step is to establish an RPA Centre of Excellence. In this RPA Centre of Excellence, knowledge about Automation best practices is established. By using this approach, the organization can ensure RPA is firmly embedded in the organization, and is not just considered a single project. The RPA Centre of Excellence can expand on the RPA framework that was established in Step 1, and it can add further processes to detect Use Cases that can potentially be automated with RPA.