Enterprise Times met with Marc Vietor, Chief Product Officer at Aris. The company says it helps turn process into value. Its solutions manage the entire process lifecycle with a single, integrated suite. As a result, helping businesses to remove process blind spots as they attempt to optimise ways of working and increase the automation of key processes. Marc highlighted the importance of process intelligence and data quality, emphasising the role of task mining in identifying inefficiencies and improving business processes. Marc provided his top five tips for enterprises looking to implement an integrated process intelligence solution into their business infrastructure.
1. Focus on data quality
Enterprises need to start with a project involving a small process, a low-risk deployment. A task mining initiative will demonstrate value and measure specific outcomes for each use case. An integrated solution that combines system-led data with manual process steps will be used. Furthermore, businesses must create quality data by tracking timestamps and screen interactions.
2. Don’t forget about compliance management
There is a need to understand and manage risks associated with AI usage. Stakeholders must implement solutions that help track shadow AI, the non-company issued AI tools used by employees. Businesses must ensure compliance with regulations like the EU AI Act and identify potential policy violations in business processes. This could be achieved by maintaining security and compliance frameworks.
3. Consider the implementation strategy
Businesses need to focus on high-value processes first. Use an MVP (Minimum Viable Product) and agile approach for implementing an AI application. Choose a comprehensive, integrated solution that covers process mining, task mining, modelling, and automation. Organisations should aim to create transparency across different tools and manual steps.
4. Think about technology considerations
Leverage AI for content creation and process knowledge. Businesses need to use tools that can integrate with existing systems. (SAP, JIRA, etc.) Implement solutions that provide actionable insights and predictive capabilities
5. Raise the organisational Awareness
Educate internal teams about AI risks and proper data handling processes. Organisations need to understand potential inefficiencies and opportunities for process optimisation. As a result, they should develop a holistic view of business processes across different departments and systems.
