Energy and Communications
15 GB of ADSL service layer data of customers – when they did not report any faults – was ingested into the Hadoop-based IIP to find the "control signature" using signal processing and statistical techniques on connection properties (attenuation/loss, code violations, upload/ download rates, re-initializations). The fault signature was computed from the connection properties in the days leading up to the reporting of a fault.
A predictive model was developed to derive a formula which provided the probability of a current state of connection signifying impending fault report in the next 7 days.
A data science formula for the predictive model was applied to process 16.5 million records in 5 seconds on an 8 core, 64 GB RAM, 5 node clusters to predict the impending network faults for connections, DSLAM and geographic area.
Impending network faults in the next week were predicted with a high degree of accuracy to fix the network failure points.
The IIP solution based on open source stack including Apache Spark and prebuilt Infosys components was delivered in just 5 days with an impressive price-performance ratio.
Selective SAP ERP data across AP, AR and inventory processes (PO date, invoice received date, GRN date, payment terms, ASN), were extracted and transformed.
Correlations were established and calculations were done across millions of records to uncover patterns and trends impacting working capital which helped analyze smart vendors who raised early invoices of high amount as a regular practice.
A detailed drill-down analysis was done for the lowest level of granularity for individual suppliers who were raising early invoices.
IIP analyzed top 10 smart vendors and the financial impact they caused on working capital of the company and its subsidiaries. For the year the total impact of early invoicing amounted to approximatelyUSD 27 million.
Inventory data for uncovering working capital improvement opportunities was analyzed.
IIP also provided interactive analysis dashboards for the executives for efficient working capital management.