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Automation of business processes with robotic process automation
Robotic process automation (RPA) works quickly, but not everywhere - what your company needs to know and how to build bridges between (legacy) systems
Nowadays, the digitalization and automation of processes is a decisive success factor for companies in order to maintain or increase competitiveness, keep costs under control and generally operate more efficiently.
However, many companies and administrations face the challenge of having to become more digital on the one hand, but not being able or willing to completely redesign the existing processes and systems involved on the other. In this area of conflict, RPA can be a valuable tool for automating existing processes.
This blog provides an overview of the use cases for which RPA is suitable, what needs to be considered when introducing it, which operating models are conceivable and highlights the differences and synergies with BPM and AI.
What is RPA? An overview of scenarios, results and implementations
RPA, short for Robotic Process Automation, is a technology that can be used to automate existing processes across system boundaries. This is done using software-based robots or bots that can simulate human interactions with systems and applications. For example, they can start and operate client applications with graphical user interfaces, retrieve information from online sources via the web browser and enter or transfer data.
How do I identify suitable application scenarios?
In principle, automation using RPA is particularly suitable where processes are already standardized and consolidated, i.e. where few changes to the process flow are to be expected in the future. Other suitability criteria for the applicability of RPA include
- Rule-based process: Automation with RPA is based on the underlying, structured data of the process and follows defined paths based on defined rules.
- High volume: The higher the volume of the automated process, the faster a positive business case can be generated by RPA, as the corresponding human capacities are freed up for value-adding activities. This applies to both short-running, high-volume processes, such as document posting, as well as long-running background processes.
- High manual effort: The greater the manual human involvement in the process, the more likely it is that efficiency gains can be realized.
On the other hand, RPA is not particularly suitable for the following cases:
- The data is available in unstructured form and has not been pre-processed accordingly.
- For frequently changing processes or applications, such as changing input screens or user interfaces.
- Processes in which complex decisions or human judgment are involved or in which individual processing is required.
- Processes with many special cases. The implementation effort here quickly increases massively.
What successes can be achieved with RPA?
The potential benefits after successful RPA projects are basically the same as those of automation and digitalization in general, such as
- Increased efficiency and associated cost benefits through shorter throughput times or increased processing volumes
- Increased quality through consistent execution and avoidance of errors
- Traceability and evaluability of the process based on the data involved and the automation runs
- Increased employee satisfaction due to the reduction or elimination of repetitive tasks and "busywork"
From a strategic point of view, automation using RPA can often be used to implement a quick "80% solution". Accordingly, the technology is often used in cases where automation and increased efficiency are urgently needed, but where the effort required for the full integration of systems via interfaces, for example, is not (or no longer) feasible or does not yet make sense. A common example of this would be the connection of an ERP or CRM solution to peripheral systems that will be replaced in the next two years, but are essential for a company until then.
What forms of implementation are there?
At the implementation level, a distinction is generally made between two methods of automation using RPA: attended and unattended.
Attended automation usually runs on the client and in the context of the user who starts the robot. It supports the user in their personal day-to-day tasks and, thanks to the higher working speed of the robot, saves time and reduces the workload of monotonous or repetitive tasks. An example of this is a monthly data consolidation in Excel with subsequent report generation, which requires several hours of time and possibly human intervention at one point or another.
In contrast, unattended automation runs fully automatically on an on-premise or hybrid infrastructure or in the cloud without human intervention. The automations are usually started based on schedules or defined triggers. Unattended bots are suitable for background processes such as nightly data processing or continuous automated postings based on incoming documents in a mailbox.
Success factors for the introduction of RPA
As described, RPA supports digitalization through rapid implementation based on existing technologies, platforms and applications. But what needs to be considered in particular during implementation to ensure success?
Planning & Governance
It is not uncommon for the ideas of the specialist departments and IT to clash when introducing RPA. The desire for decentralized, fast and independent implementation, or citizen development for short, contrasts with the need for central control, quality assurance and compliance with security guidelines and standards.
It is therefore highly recommended to develop basic governance with defined rules, roles and processes for the use of RPA as well as a clear operating model at the outset.
In practice, a hybrid structure has proven successful, in which the IT department provides the specialist departments with the tools they need, sets the guidelines and ensures compliance, but also acts as a partner and consultant for the design and architecture of new automations, for example, and provides best practices and reusable bot templates.
Process suitability
The first step is to select a suitable process, which ideally should already be documented. In addition to the general criteria already mentioned, an ROI analysis should always be carried out at the start of any RPA initiative. This involves comparing the implementation and operating costs with the calculated savings through, for example, shorter throughput times, increased capacity or quality gains.
In our experience, an RPA implementation pays for itself in less than 12 months with a well-chosen process. This is all the more true if the fixed costs, such as for licenses and operation, are gradually spread over several processes as the RPA infrastructure is used more and more.
Tool selection
In addition to various open source tools and frameworks, there are now a large number of RPA solutions from both specialized providers such as UiPath, the quasi-market leader, and the well-known big players in the software industry such as Microsoft and SAP.
In addition to the automation engine itself, these offer various development tools, both for professional developers and for so-called citizen developers or power users, which enable automation to be driven forward directly in the specialist areas.
Another advantage compared to freely available tools or scripting languages is the simpler integration thanks to existing connectors for common enterprise software such as Salesforce, SAP or Microsoft 365, as well as features for the central administration and monitoring of automations.
As an independent and neutral partner, atrete supports you in selecting the right solution from the multitude of available RPA tools and frameworks in an objective and needs-oriented manner.
Transformation and competence building in the organization
Finally, training, communication and change management are also important aspects of the initial introduction of RPA. Clear and open communication in particular can help to counteract the prejudices that often occur in automation projects.
The still common fear that capacities freed up by RPA will lead to a reduction in personnel has now been largely refuted, but should still be addressed. As a rule, employees are relieved of routine activities that add little value and can, for example, work on the further development of the process instead of being part of the process themselves.
In order to achieve widespread adoption for the topic of RPA or automation in general, it makes sense to set up a corresponding cross-departmental community. It promotes internal exchange and offers the opportunity to present successes and make them visible throughout the company. This often leads to the discovery of further automation potential as new stakeholders become aware of the technology and its possibilities.
RPA vs. BPM vs. AI - differentiation and synergies
In contrast to BPM (Business Process Management), which represents a holistic approach with methodologies for the design, modelling, improvement and introduction of processes, the use of RPA does not, strictly speaking, optimize the process itself, but merely automates it. In practice, however, potential for improvement can often be identified as early as the recording or documentation of the existing process, so that it is not uncommon for the process to be optimized as a side effect of automation.
Finally, the distinction and synergies between RPA and the omnipresent topic of AI should be discussed. RPA and AI were and still are often mixed up and confused, but the distinction is relatively simple. As already described, classic RPA is rule- and data-based and follows predefined paths. The strengths of AI are known to lie in use cases such as the processing of unstructured data, machine learning based on training data and past runs or the (creative) generation or translation of content.
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For further insights into our experiences in the AI environment, we recommend taking a look at our recently published series
AI-supported IT transformation
By combining or embedding AI and machine learning functionalities at certain points in a process automated by RPA, advanced scenarios can be mapped where classic RPA reaches its limits. A common scenario, for example, is the extraction and recognition of data from unstructured documents such as invoices with an inconsistent structure and the subsequent further processing of the information by RPA.
With the advent of AI agents, these worlds can now be integrated even further. As a goal-oriented assistant, the AI agent provides the interface and potentially has a wide range of knowledge sources, models and tools at its disposal. RPA can be integrated here to carry out transactional and defined steps in connected systems in the background for certain requests that would otherwise not be possible for an AI model.
In the overarching interaction, BPM regulates the overall flow of the process, the agent recognizes and decides and RPA executes. AI agents unfold their benefits in interaction with RPA and BPM, especially if clear guard rails, approvals and protocols control the execution.
The major providers have also recognized this potential and are expanding their product range accordingly with AI and machine learning functionalities and marketing these under buzzwords such as "intelligent automation".
Conclusion
The introduction of robotic process automation (RPA) offers companies a wide range of opportunities to make processes more efficient, cost-effective and future-proof. A clear strategy, the selection of suitable processes, the right choice of tools and structured change and governance management are crucial for sustainable success.
atrete accompanies you on this journey - from the initial idea to successful implementation and beyond. Benefit from our experience and our neutral view of your challenges. Among other things, we support you with
- Development of an individual digitization strategy
- Analysis of your organizational and technical processes and identification of automation potentials
- Project management and support for the introduction of RPA solutions
- Neutral selection, tendering and proof of concept (PoC) for RPA software and solutions
- Automation in the IT infrastructure (Automation PA)
- Development and establishment of governance structures
Do you have any questions or would you like to find out more?
Feel free to get in touch with us - we look forward to exchanging ideas and working with you to shape the next steps towards a digital future!
