Two examples of processes we have recently mined are the Purchase to Pay (P2P) and Order To Cash (O2C) processes for industrial clients. In general, our clients’ data sources support process mining. Yet, we usually find areas for improvement.
In these assignments we identify the “algorithmic happy path”, which is the most efficient scenario for the most frequent activities and process connections. After that, we explore the deviations from the happy path, and the root-causes of these deviations. For instance, we may find that, for specific vendors, there are high throughput times that only occur with the same purchase item groups. Currently, one of our clients has planned actions to mitigate such processes that are either slowing down the overall processes, or are causing repetitive manual tasks. Further concrete action points and the extension of process mining to cover other processes are currently ongoing.
One of the main advantages of process mining is the transparency it provides regarding end-to-end processes – a transparency that may not even be possible through traditional means. Understanding the entire process is a pre-requisite for transforming it.
Furthermore, we are also able to carry out continuous monitoring of a process and trigger automated actions based on the data. This enables firms to react immediately to issues in their business environments, which may even contribute to their competitive edge.