Case studies

Automated Anomaly Detection through Multi-Level Forecasting

An automated time forecasting tool to identify anomalies across various levels of granularity in key analysis dimensions was built for a multinational E-Commerce corporation. This resulted in a 70% reduction in the time taken to detect anomalies.

The Problem
Manual effort in identifying errors in reports can take up to 20% of time for key analysts, thus reducing productivity.

The Before State
Manual validation of KPIs across hundreds of reports and detection of anomalies was not only time-consuming, but also prone to human error.

The LatentView Solution
Built an automated time forecasting tool which helped identify anomalies across various levels of granularity in key analysis dimensions.

The After State
70% reduction in the time-taken to detect anomalies resulted in increased efficiency of analysts and better decisions as manual errors were eliminated.

Download the case study

automated anomaly detection through multi level forecasting 1
Share on linkedin
Share on twitter
Share on facebook