All voice KPIs at a glance – Instantly identify optimization potential
All voice KPIs at a glance – Instantly identify optimization potential
How do I manage the performance of my voice application and do I already exploit its full potential? How can I ensure that all voice employees are productive at a constant high level? What future steps can I already start planning today? If you are concerned with these questions, you will find that LYDIA Warehouse Intelligence (LWI) is the right business intelligence tool for you. The data analytics architecture provides you with process, user and device data from your LYDIA Voice application in an administration interface and at the same time carries out an analysis of these values in real time. In this way, optimisation potentials can be identified at an early stage and suitable activities can be initiated.
Transparent overview of the current status of all important KPIs of your voice application
Systematic data analysis as a basis for process improvement in your voice processes
Predictive maintenance for your mobile voice computers to reduce downtime
BI tools to identify optimisation potential
Cloud-based and on premises installation
Optional interface to IT monitoring solutions
The data transfer between mobile voice computer and WMS/ERP server may be one of the time-critical factors in your voice application. LWI evaluates the duration and number of server requests for you so that you can react promptly to delays.
With Pick Performance Analytics (PPA), LYDIA Warehouse Intelligence will soon expand its analytics capabilities with a new dimension of data-driven performance analysis for order picking.
PPA aggregates and structures voice process and performance data across multiple analytical layers, making performance trends, process patterns and deviations clearly visible. In a dynamic dashboard, freely configurable KPIs are visualized through flexible charts and tables and can be analysed both in real time and across selectable time periods.
This creates a solid data foundation for better understanding operational workflows, identifying optimization potential at an early stage, and strategically improving warehouse performance over time.
Greater performance transparency in the order picking process
Early detection of process patterns, bottlenecks and performance deviations
Targeted and sustainable optimization instead of isolated improvements
Well-founded, data-driven decisions instead of gut feeling
Strategic development of overall warehouse performance
Overcome language barriers with AI-based real-time translation. This is the future of communication in intralogistics.