Process mining is versatile, applicable to various areas with processes. Common uses include automation, digital transformation, compliance, auditing, KPI reporting, process improvement, and ERP development.
Process mining enables you to:
While RPA is hailed as a cure-all, companies face challenges like high maintenance costs and broken bots. To maximize automation value, focus on suitable processes, understand exceptions, and continually optimize using intelligent automation components: RPA, AI, and process mining.
Process mining answers crucial questions:
- What’s the expected ROI for automation?
- Which processes are ideal for automation?
- What are common process exceptions?
- How does the automation rate differ globally?
- 2How to validate automation’s value?
Traditionally, auditors rely on interviews and documents. Process mining transforms audit efficiency, offering instant, comprehensive insights into current and past processes. This shift from subjective samples to objective, full, as-is processes enhances assurance and saves valuable time.
Process mining tools efficiently spot compliance issues, simplifying the work of compliance managers. Traditionally, sampling is relied upon, but it doesn’t ensure complete transparency due to process variations. Process mining offers real-time insights, enabling users to compare processes instantly, reducing hassle, and presenting a detailed list of irregularities.
In the competitive market, digital transformation is essential. Yet, justifying changes can be tough. Process mining tools offer change managers clear process visibility, simplifying improvement spotlights. Demonstrating automation value is effortless, supported by instant data at your fingertips.
Process KPI Reporting
Management relies on data-driven decisions and efficient KPIs. Yet, businesses often struggle with time-consuming KPI setup. Process mining models come with 1000+ built-in KPIs, saving users from waiting on custom builds. Predictive features enable proactive responses, shifting organizations from reactive fixes to preventive actions, transforming their approach significantly.
Process mining pinpoints areas for process improvement, spotlighting long lead times, unwanted variations, and sources of rework. This efficiency reduces time spent defining, measuring, and analyzing issues in Lean Six Sigma projects, allowing more time for process enhancement and control.
IT professionals rely on process mining for ERP migrations and implementations. Before system changes, understanding existing processes is crucial. Without an end-to-end view, ineffective processes might persist in the new system. Process mining addresses this by comparing existing processes to designed models, revealing variations, and offering continuous visibility. It alerts users to issues, ensuring smooth transitions and efficient deployments.
IT & ERP Development
IT professionals employ process mining to navigate ERP migrations and implementations. Before system changes, understanding current processes is pivotal. Lack of end-to-end visibility can lead to migrating inefficient processes and overlooking migration issues. Process mining addresses these challenges by comparing existing processes to designed models, revealing variations, ensuring continuous end-to-end visibility, and alerting users to problems.