Identifying and exploiting the potential for optimization in business processes
In over half of automated business processes, the “happy path” – the presumed best possible scenario – is not reflected adequately in reality. As a result, companies are losing out on enormous potential in terms of excellence, efficiency and quality. Artificial intelligence (AI) can help to optimize automated processes and thus exploit the opportunities and benefits of business process automation to the full.
There are many reasons why the ideal path for automated processes is not reflected in reality in so many cases. Often, those responsible have different opinions on what exactly is the right way. Deviations are then never far behind, particularly when an increasingly complex process is in play. Other obstacles include inaccurate data and information, or the absence of key details. The excellence of the automated process then suffers and the positive effects of process automation – such as increased efficiency and time savings – do not come into effect to the desired extent.
“Artificial intelligence can help here,” comments Andreas Balsiger, Head of Product Management at Axon Ivy. “AI helps to better understand the workflows seen in business processes and to optimize their efficiency, speed and quality during implementation.” A perfect example of this is process mining, which examines, reconstructs and analyzes business processes according to digital traces in IT systems. In doing so, it uses data that is automatically collected by the user when carrying out the process, such as logs of processes, events, activities or transaction data. Based on this, workflows are then mapped, patterns, deviations and weak points identified, and workflows optimized.
The targeted implementation of AI at a company requires an automation platform as a central hub, which ensures smooth processes and the perfect synchronization of the different technologies involved. “Whatever the industry, AI offers enormous potential when it comes to automating business processes. Take machine capacities and maintenance in the construction machinery or production industry, for example. Among other aspects, automated data transmission indicates capacity limits and maintenance cycles. Machines can then be operated without downtimes and serviced earlier or later depending on the workload. As a result, benefits such as the efficient operation of equipment and the minimization of downtimes can be achieved quickly and easily,” explains Andreas Balsiger.