Zenithar Process Mining
An Efficient Digital Transformation Initiative: Process Mining
A process is a repetitive sequence of actions, and the purpose of a process is to complete a task and create a flow accordingly. Here, process mining is a rescuer as a digital transformation initiative in order to make the processes efficient. It is also an analytical tool for discovering, monitoring and improving processes, using software event logs.
In addition, process mining provides objective results from real data and helps companies control and improve your existing processes by answering questions about both compatibility and performance. Process mining also identifies trends, patterns and details about how an entire process works additionally.
Importance of Process Mining
According to market research firm IDC, most companies are unaware that their processes are not operating at maximum capacity, losing 20-30% of their revenues in this way. For example, if a process is underperforming without realizing it, it will affect other processes as well.
It is important to acknowledge that processes are dynamic and even ideal flows do not work and these deviations from time to time can become the rule of thumb, but when everything is productive via process mining, a company has enough power to easily adapt to changes and this adaptation makes companies competitive.
Benefits of Process Mining
These days, companies must use all their capacities to compete. Therefore, they need flexible processes and to understand how things work. For example, via process mining, companies can quickly control, monitor and optimize their processes.
Process Mining
- Finds automation opportunities (where to use RPA effectively)
- Suggests better actions instead
- Improve efficiency
- Finds and predicts root causes of friction and problems
- Executes real time process control
- Makes processes visible (%100 transparency)
- Eliminates waste of time and money
- Guarantees compliance and eliminate risks
- Enhances customer experience
Process Mining Softwares We Use
ABBYY Timeline PI, Minit Process Mining and Celonis