Tungsten Insight and Software AG ARIS Process Mining compete in the process mining market. Software AG ARIS Process Mining seems to have the upper hand due to its comprehensive features that justify its higher price tag.
Features: Tungsten Insight provides robust process visualization and customizable dashboards, offering key insights into workflows. It is designed to cater to users seeking straightforward data representation. Software AG ARIS Process Mining offers advanced analytics and superior integration capabilities, addressing the needs of large enterprises that require in-depth data analysis.
Ease of Deployment and Customer Service: Software AG ARIS Process Mining supports scalable cloud-based deployment alongside a solid infrastructure for customer service, making it suitable for businesses seeking extensive support and flexibility. Tungsten Insight provides a simpler on-premise solution that may require less initial setup but offers limited scalability.
Pricing and ROI: Tungsten Insight is recognized for competitive pricing and faster ROI due to its lower initial costs. In contrast, Software AG ARIS Process Mining demands a higher initial investment but presents significant long-term benefits through enhanced process efficiency, providing greater value for complex projects.
Increasing digital products and services, new business models, challenger brands and competitors emerging virtually overnight—all are forever changing your market. To survive, your company—no matter its size or industry—must rethink your business models and processes. Problem is, with so many players and parts to your enterprise, where should you begin? How can you see where to optimize processes to improve the customer experience or operational efficiency? Should you rethink distribution of resources, or start first with improving processes for a specific region or product?
Find your answers with ARIS Process Mining at Software AG. With a 360-degree view of your processes, you’ll gain intelligent insights into your processes and their dependencies to find patterns, anomalies and opportunities for improvement. Compare processes in theory to processes as they are in the real world. See if processes execute as designed. This gives you a solid basis for making process improvement decisions. You can evaluate changes before making them to avoid added costs later on—and you can simulate and analyze process scenarios so you know the best way to improve them.
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