This blog article highlights the relevance of Robotic Process Automation (RPA) as a key building block to an organization’s hyperautomation vision, the key challenges and how to overcome them.
The Covid-19 pandemic has drastically shown how we think about the importance of resilient processes. It became clear how digitalized companies are able to successfully navigate these difficult economic times and stand out from the competition. A key component of becoming a highly digital and efficient company is without a doubt automation in the form of Robotic Process Automation (RPA).
How does RPA work?
RPA is a configurable software tool that can automate repetitive and rule-based business processes which rely on structured data and have deterministic outcomes. It mimics the interactions of a human worker and can operate across multiple systems and applications. The main benefits of RPA are that it can be implemented comparatively quickly and modified quite easily, as it does not require any change in the existing IT systems and applications. If implemented correctly, RPA can save a lot of time and reduce operational costs. Although, RPA became a topic on every CTO’s agenda, leading to widespread business adoption and vendor revenue growth, it quickly lost steam. What has been observed during the last years is that failed RPA projects have contributed immensely to RPA becoming just one of many buzzwords providing less than optimal value outcome. The reasons for this are manifold, so in the following we have summarized the most important obstacles and at the same time point out how to overcome them.
1. Processes: setting the requirements and selecting the right use cases
Sometimes organizations just select the first use case that comes to mind without checking the suitability of the processes. Wrong expectations or a missing understanding of the technology can easily result in the selection of random use cases. Being aware of what RPA can do and where it has its limitations, is a prerequisite for selecting value-added use cases. Defining clear process criteria and requirements, scanning the process landscape, evaluating and prioritizing processes regarding their complexity and business impact are the first and crucial steps to avoid unnecessary spending and fully leverage the potential of RPA. RPA can be used for much more than just attended automation to support employees in moving data around the company faster. The real value of RPA should instead be seen in its transformative ability to drive business through both attended and unattended automation (operating without human intervention). A major benefit of RPA is its wide applicability across different industries and functions. A good example for a use case in MDM is the automation of data maintenance, as this process usually is very prone to human errors and requires high manual effort.
2. Data: having an effective MDM to guarantee good and reliant data
Data builds the backbone of mostly every business and its underlying business processes. Thus, without solid master data, stable and robust business processes cannot be achieved. To pursue any form of digitalization or automation, it’s crucial for every organization to look at the data basis on which any initiative is built. With effective Master Data Management, an organization can ensure that the business processes get data at the right time, in the right place and with the desired quality. If you are interested in how to get out most of your future or current MDM program to be ready for automation, please read our article on “Next Generation Data Management”.
3. People: speaking the same language
A missing or insufficient transparency or communication of the initiative to the employees and all other stakeholders can easily lead to resistance. Be aware of possible anxieties of your employees and make sure that IT and business work hand in hand from beginning. Even if business should lead the project, it is critical to integrate IT at an early stage. Business and IT must have the same understanding and work cohesively. Therefore, business must clearly communicate all necessary background information and requirements for the project to IT. Based on this knowledge, IT can help business to validate feasibility from a technical and systemic point of view. In this way, potential problems can be detected before and not during the implementation. Even more important is to have a clear communication to all employees, especially to the ones working within operational tasks. They may fear losing their jobs because they think automation could make them redundant. Make sure to convey the key message that RPA is going to support employees with their operational tasks and will not make them obsolete. By taking over the boring and standardized tasks, RPA enables them to work on more challenging and value-adding tasks. Job profiles and the respective skill requirements are going to change, but not the need for human workers.
4. Technologies: having a strategy in place
Often RPA is only applied to automate individual separate tasks instead of focusing on a more holistic process-based approach. A missing strategic direction and integration of RPA within an automation roadmap also makes it hard to convince management about the business value of the project. As great as the benefits of RPA are, the technology has clear limitations when it comes to processing unstructured data and completing tasks which require cognitive capabilities. Thus, combining RPA with other technologies (e.g. process mining, machine learning, analytics) is not only logical, but necessary. Gartner calls this combination of complementary tools and technologies hyperautomation and placed it as one out of ten strategic technology trends for 2020. Developing a clear hyperautomation vision on what you want to achieve in the next years and deriving an automation roadmap are key steps to further increase the value and outputs of your automation – but be aware of the changing RPA market and offerings. Figure 1: Key pillars for successfully implementing RPA
RPA market and offerings are going to change within the course of hyperautomation
As outlined, the future of automation projects lies in the combination of different tools and systems. This change is also recognized by RPA vendors as they integrate more and more complementary technologies into their solutions. On the other hand, complementary tool providers are increasingly integrating RPA as a main functionality in their products. This will drive the transformational change and enable RPA not only automate individual tasks, but to support the optimization and automation of even more complex processes (attended and unattended). CAMELOT offers a holistic approach for RPA enterprise information management and can support organizations with our experience during different stages of exploration or implementation in the context of hyperautomation. For further information please get in touch with us. We would like to thank Bhavana Jotwani and Paul Morales for their valuable contribution to this article.