Robotic Process Automation: Beyond Quick Fixes, Towards Strategic Transformation

In an age where businesses place a premium on enhancing operational efficiency through automation, Robotic Process Automation (RPA) has witnessed significant growth in recent years. Based on research report titled ‘Robotic Process Automation Market (2023 – 2030)‘ by Consegic Business Intelligence, the market is expected to surplus USD 20,215.71 million by 2030 from USD 2,463.06 million in 2022.

Nonetheless, as businesses adopt this technology, the risks associated with its misuse have also increased over time.

What is Robotic Process Automation (RPA)?

In very simple terms, RPA refers to the application of systems (sometimes called software robots) with the primary objective of automating repetitive and routine tasks that were previously performed manually. This, in turn, leads to cost savings and an enhancement in the speed and quality with which routine activities are performed, while enabling organisations to direct their investments in the human workforce towards innovation and growth.

RPA’s Evolution in Technology

While RPA initially emerged as a straightforward solution in the domain of business processes, requiring the manual definition of event sequences for a ‘robot’ to execute, technological advancements, particularly in Artificial Intelligence (AI) and Machine Learning (ML), have had a significant impact on RPA’s capabilities. The integration of traditional RPAs with AI and ML has pushed RPA far beyond the boundaries of traditional business operations. Some instrumental changes in this transformative journey include:

• Enhanced automation through the analysis of unstructured data, pattern recognition and automated decision-making based on complex data sets.
• Advancements in cognitive automation through understanding of natural language.
• Complex process optimisations, such as those related to software development code integration, testing, and deployment.
• Self-learning RPAs through the capabilities of ML.

Common Misuses of RPAs

In the world of software development and business process reengineering, RPAs are frequently associated with low code development, thus serving as a means to expedite the development process. However, organisations must keep in mind that:

1. Justifying the development of RPAs should not be based on the scarcity of available software developers/engineers.
2. RPAs should not be used as a substitute for integration interfaces, nor should they be tasked with automating the entire end-to-end process.

Although, I must admit that the above offer immediate benefits, they pose significant long-term risks. 

Let’s imagine a scenario where an organisation is using a frontend and a backend system. RPA was built to copy and transfer data from the frontend to the backend system upon clicking the submit button on the former system.        

In this scenario, even a minor change in the user interface (UI) of the data entry screen is likely to impact how the RPA operates, necessitating a change in the RPA. Unfortunately, the critical changes to the RPA are often overlooked during development, leading to a breakdown of the solution upon the release of UI changes. 

Furthermore, in efforts to deploy the RPAs as quickly as possible, organisations often do not apply the same level of robustness as they typically do in standard software integration development. This does not only apply to the technical side of RPA, such as the lack of automated tests, but also at a wider organisational level including the absence of formal deployment procedures and standards.

The situation becomes considerably more complex when a single RPA is tasked with extracting information from multiple systems and performing complex computational tasks before transferring the computed data to other systems or databases.

Exploring Additional RPA Challenges

Like any other innovation, RPA comes with a number of challenges, including: 

• Integration and Scalability issues – As discussed earlier, integrating RPAs with multiple systems and platforms can lead to complexities that demand ongoing maintenance. Complexities often include incompatibility issues which require significant team effort to resolve during development.  

• Data Security and Compliance – As bots are also susceptible to security breaches, organisations need to ensure that they adhere to data protection regulations and compliance standards. This, unfortunately, is also often overlooked during RPA development.

• Employee Resistance and Job Concerns – Automating manual processes often faces resistance from employees who fear job displacement.

• Implementation Costs – The initial investment in software, training, and infrastructure is substantial, requiring organisations to carefully evaluate these costs in relation to the expected benefits.

• ROI Measurement – Quantifying the return on investment (ROI) from RPA can be challenging. Organisations must establish key performance indicators (KPIs) and track them to assess the true impact of RPA on efficiency, cost reduction, and other factors.

Managing RPA’s Risks and Challenges

An essential factor in helping organisations addressing risks and challenges emerging from the transition to RPA is a carefully planned and communicated strategy.  Apart from establishing realistic goals, the strategy should also outline how the organisation is planning to position RPAs in the future. 

The choice of the robotic process management automation tool/s is also crucial for organisations to achieve their RPA targets, especially in view that some tools have limited functionalities and capabilities that may hinder the benefits that organisations can derive from RPA development.     

Careful planning and resource allocation when expanding RPAs to handle additional processes is another means of managing risks. Without a planned, scalable approach, the full potential of RPA may remain unrealised. Organisations must keep in mind that some processes may not be suitable for RPA due to their complexity, lack of standardised rules, the risk of security breaches, or the handling of sensitive data. This makes it crucial for organisations to carefully determine which processes yield the best ROI before transitioning to RPA.

Achieving successful RPA implementation often demands a cultural shift within the organisation. Linking this with my previous observations regarding strategy, the strategy must also clearly articulate the future of the organisational workforce, illustrating how employees will collaborate with their digital counterparts. Change management strategies are also essential to ensure a smooth transition, accompanied by investments in upskilling and reskilling programs to ensure the availability of skilled resources for RPA projects.

Finally, as the business can be heavily disrupted every time an RPA fails, having a maintenance and performance monitoring systems/procedures is crucial before engaging in RPA development.

Robotic Process Automation is undeniably one of the most powerful digital transformation technologies available to businesses of all shapes and sizes, especially those that have equipped RPAs with AI and ML capabilities. From simply automating data entry and computing validation techniques, to executing complex health claims processing and financial reconciliation, RPAs have showcased their potential to revolutionise how organisations operate.

By employing effective strategies, fostering continuous learning, and practicing diligent management, businesses can fully leverage the full potential of RPAs to thrive in the dynamic digital landscape of today.