Like any manual task, process mapping is prone to human error. APD reduces this risk by accurately capturing processes as they occur, resulting in more accurate data and insights.
APD makes it easy for companies to scale their process discovery efforts. As a company grows, so do its processes. APD can keep up with that growth, providing consistent, accurate process maps and timely process analytics.
Process Discovery Use Cases by Industry
Automated process discovery is a versatile tool that can be used across various industries to optimize business processes, improve efficiency, and reduce operational costs. Here are some compelling examples of how different industries are leveraging process discovery:
Examples and applications The Evolution of Process Discovery
Process discovery has evolved significantly from manual efforts to sophisticated automated solutions. Here’s a quick overview of this evolution:
From manual to automated Understanding Stakeholders in Process Discovery
Successful process discovery initiatives involve a wide range of stakeholders, each playing a critical role in aligning with business objectives. Here are some of the key stakeholders and their responsibilities:
Roles and responsibilities Examples of process discovery tools
The field of automated process discovery is vast and you can find many solutions for different types of organizations, business processes, and key use cases.
Mining
Process mining tools use event logs from information phone number in the philippines systems to discover processes. They provide an accurate and objective view of processes, but require clean and complete data to be effective. Process mining tools provide business users with a deep level of analysis for process improvement, often covering thousands or even millions of process variations. Process mining tools can be used for both process discovery and continuous improvement of business processes.
Task exploitation
Task mining is another form of APD that involves using task capture and AI to analyze user interactions and uncover processes. It is useful for processes that involve a lot of human interaction and can provide insights into how tasks are performed. Task mining tools are particularly useful for finding automatable processes because they identify in detail the manual tasks performed in workflows, and can identify inefficiencies that are not categorized in IT systems’ event logs.
Self-built process analyses
The third option to automate process discovery is to use process mining algorithms and data science to create your own process discovery dashboards and models within BI platforms. Today, there are many open source libraries, for example process mining algorithms that allow you to do your own process discovery using programming languages such as Python and standard BI visualization tools, such as Tableau or Power BI.
