Visualizing and mitigating delivery schedule deficiencies and inaccuracies using big data analytics

Paper in proceeding, 2018

The purpose of this paper is to describe and categorize deficiencies and inaccuracies in delivery schedules shared in European automotive supply chains, and to propose how to monitor and mitigate delivery schedule deficiencies and inaccuracies. We analyse 2.9 million schedule records received by a  upplier during two years. Findings do not identify any critical data deficiencies but describes the existence of time and volume related schedule inaccuracies. It proposes mitigation strategies for monitoring these two inaccuracy types, and strategies for handling inaccuracies and schedule groups with perfect forecasts.