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.


Patrik Jonsson

Chalmers, Technology Management and Economics, Supply and Operations Management

Muhammad Azam Sheikh

Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd

Book of abstracts EurOMA 2018


25th Annual EurOMA conference
Budapest, Hungary,

Future of sharing schedule information in automotive industry supply chains using advanced data analytics

FFI - Strategic Vehicle Research and Innovation (2018-02695), 2018-10-01 -- 2021-05-31.

VINNOVA (2018-02695), 2018-10-01 -- 2021-05-31.

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Other Mechanical Engineering

Business Administration

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