Perfect Order Measurement equips the enterprises and their partners with advanced analytical tools to get insights into the order fulfilment processes with a view of perfect order indices and its influencing factors. It encompasses all aspects of a perfect order, and includes on-time and in-full fulfilment with correct documentation and no damages. It provides a comprehensive analysis of perfect orders across multiple dimensions like customers, suppliers, product categories, locations and time horizon.
Leveraging Machine Learning, it delivers easy to use descriptive and predictive analytics capabilities, built on a scalable and a sustainable technology platform.
Perfect Order Measurement enables order fulfilment teams and sales teams to derive insights into the order fulfilment operations and achieve a higher degree of perfect orders across different channels.
Proven data platform for data acquisition, cleansing, enriching and harmonizing data across the supply chain network.
Multi-dimensional analysis of order fulfilment for enhanced perfect order visibility and proactive order management.
Predictive profiling of orders against delivery risks analyzed across different dimension such as customer, location, product categories etc.
Rule-based detection and scheduled alerting for managing order risks in a timely and proactive manner.
Summarized view of total open orders, shipments and invoice numbers for each day of the calendar month.
Make sense of the complex supply chain data using AI/ML to achieve higher degree of perfect orders
Connect, Collaborate and Grow with your business partners by leveraging the power of a Multi-enterprise Business Network
Download this flipbook to hear from experts at FinXEdge discuss the strategies and tactics needed to be resilient against credit losses and increase collections ROI, in the short, medium and long-term
Data Harmonization addresses these challenges by contextualizing external business data for each enterprise and making it insight-ready, by leveraging automation and machine learning techniques.