Previous articles in this series explain the three main types of process automation:
Briefly, RPA and DPA are cutting-edge technologies that automate tasks and processes. RPA automates specific tasks, while DPA takes a broader approach, automating entire workflows and processes to improve human-system interaction and the user experience. By combining the two technologies, businesses can automate repetitive and time-consuming tasks within complex processes.
BPA automates multi-step processes. It requires a more comprehensive analysis of business processes and typically involves more complex development than RPA. Because of this, the IT department must deploy and manage the system. In contrast, RPA can be deployed quickly and is more lightweight, with low-code/no-code platforms available that allow business users to create bots to automate parts of their work.
The three forms of process automation can be integrated with each other and with other technologies such as AI, to create more advanced and precise process automation tailored to a user’s specific needs. Used together, all three technologies can support an enterprise’s digital transformation efforts, making processes more efficient, accurate, and reliable.
How does IPA work?
The maritime industry is so varied that, even when integrated, conventional process automation such as RPA, BPA and DPA are often inadequate. In these cases, a bespoke automation program can integrate technologies like artificial intelligence (AI), machine learning (ML), or big data with multiple forms of process automation. This is where intelligent process automation (IPA) comes into play.
As an interdisciplinary field, IPA leverages the full range of modern technologies to automate tasks intelligently and efficiently. For instance, organisations can use AI data analysis to drive data-driven decision-making, leading to the automation of tasks that were previously too complex for conventional methods. On the other hand, ML algorithms continuously learn from data, leading to improved prediction accuracy over time, while standard process automation such as RPA and DPA frees up human workers to focus on more strategic work. Furthermore, natural language processing (NLP) enhances an organisation’s ability to interact automatically with customers and employees in a more natural and conversational way, leading to more intuitive and seamless communication.
IPA has a vast impact on organisational operations. Automation of a wider range of tasks and processes leads to significant improvements in efficiency and accuracy. This impact is already being felt across several industries, including finance, healthcare, retail, and customer service.
Pros and cons of IPA
Compared with having no process automation at all, IPA’s basic advantages and disadvantages mirror those of traditional process automation: it improves accuracy, efficiency, and compliance, and reduces costs over time while creating complexity. However, as it has more flexibility than other forms of process automation and can use cutting-edge technologies such as AI, it can come with its own peculiar challenges. Due to the lack of standardisation, IPA can be expensive and difficult to set up, and may face technical challenges with data silos and integrating with existing systems.
Compared with RPA, BPA and DPA, IPA is considerably more flexible, and able to work with unstructured data. With NLP and voice recognition, it can interact freely with customers and staff, providing faster and simpler service. Despite this, it still can’t automate tasks that require creativity, empathy, judgment, or intuition – those are still better left for the humans.
When to use IPA?
The only way to decide which form of process automation is best for a particular task or workflow is to understand the workflow, and the strengths and weaknesses of each type. In general, RPA can handle simple, repetitive tasks; BPA and DPA can manage more complex multi-step processes; but IPA can handle complex end-to-end workflows.
Businesses should use IPA rather than other options if:
- the process involves unstructured data, such as text, pictures, or audiovisual information;
- the process requires active decision-making; or
- the process is a dynamic scenario.
Some examples could include validating invoices against purchase orders, assessing loan applications, or weather and traffic routing of ships. IPA can also supervise other forms of process automation, such as RPA bots. It can improve the RPA bots’ performance, then work with the resulting output.
Conclusion
IPA is a powerful process automation technology that can help organisations improve productivity, compliance and accuracy. However, organisations must balance this against the fact that IPA is more expensive and complex to implement than traditional process automation systems such as RPA, DPA and BPA. Despite the added complexity, IPA will give organisations an edge over competitors, deliver greater value to customers, and revolutionise the way organisations operate.
