Driving innovation in document automation
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Digitisation is becoming more and more prevalent in the everyday operations of procurement. To implement digital processes, operational activities must run automatically and efficiently. Manual tasks must be completed quickly and error-free so that employees have more time for value-adding tasks. Process optimisation can be achieved by utilising either Robotic Process Automation (RPA) or Artificial Intelligence (AI). Intelligent automation solutions for procurement using RPA or AI are often used for the same goals, but their fields of application, strengths and weaknesses differ significantly. What are the reasons for procurement to choose either RPA or AI?
Intelligent automation tools such as RPA and AI are used to complete manual tasks quickly and error-free so that employees have more time for essential and value-adding tasks. In addition, automated operational processes lead to shorter processing times, process optimisation, higher quality and lower costs.
The use of intelligent automation solutions within operational procurement is inevitable, and the benefits are too valuable to ignore. Despite this, many procurement departments still employ manual processes and struggle with many error-prone activities as a result. Most activities are often carried out manually, including receiving and checking purchase order confirmations, obtaining quotes, sending orders to suppliers, manually entering the data of incoming customer orders and more. Using digital tools for automated document processing leads to process optimisation, digital workflows and more time for value-adding activities.
RPA can only be used where processes are already digitised. The software robots cannot work with ambiguous documents either. Consequently, they can currently only be used for structured processes and routine activities.
Software robots are extremely inflexible. The platforms on which RPA interacts change frequently, and the required flexibility often cannot be configured. Software robots cannot react flexibly to deviations or variants, for example, when process input data is not structured, or decisions within the process are complex and non-linear. Changing regulations or updates that require minimal changes to an input screen can set back an RPA project by months.
The more applications a software robot serves, the more challenging scalability becomes.
Employees must check that the software robot does not make any mistakes. For example, if OCR (Optical Character Recognition) is used to read PDF files, the reading process can be faulty. Since RPA technologies cannot recognise errors or check data readouts for plausibility, these errors could then be transferred unnoticed to a database.
RPA requires a particular data quality. The effort required for its preparation and cleansing is often underestimated. However, good data quality is a mandatory prerequisite for the successful digitalisation of business processes and automating workflows.
If we look at the disadvantages and limitations of RPA, it becomes apparent that the benefits are somewhat limited. However, the good news is: software solutions for procurement like the Netfira Platform offer value thanks to innovative AI technology.
First and foremost, AI scores with high flexibility. AI can automate complex processes lacking clear rules. It can be used in many ways, reacts flexibly to variants and deviations; updates and adjustments to the application systems are no problem. This basic flexibility also goes hand in hand with easy scalability. This is crucial, as procurement in times of Industry 4.0 in particular needs to be flexible, agile and efficient.
Another significant advantage of AI for purchasing is that it can support the exchange of information and, at the same time, relate content. During processing, it imitates the human behaviour of those involved in the process. In operational procurement, this applies to the automated extraction of data, the validation of information, the comparison of data and information, and the further processing or transfer of the correct information to the downstream company systems.
In contrast to RPA, AI can process unstructured data in free texts or documents such as order confirmations and customer orders. Deviating terms in supplier documents, ambiguous units of measurement, or rare languages are no longer a problem because – unlike RPA – AI learns continuously. It becomes more and more precise over time because the learning effect increases proportionally with the volume of data fed into it.
If you want rule-based, simple and repetitive tasks in procurement to be performed automatically, you can easily rely on RPA. However, in comparison with AI, RPA falls short of what is now possible. If you want a comprehensive and future-proof intelligent automation solution for procurement, you should choose AI-driven tools like the Netfira Platform.
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