Dashboard for the Management and Acceptance of Customer Orders

Nascimento Joana (), Frazão Nuno (), Teixeira Senhorinha () and Ribeiro Ana Cecília ()
Additional contact information
Nascimento Joana: University of Minho, Guimarães, Portugal
Frazão Nuno: Bosch Car Multimedia Portugal, S.A., Braga, Portugal
Teixeira Senhorinha: University of Minho, ALGORITMI Center, Guimarães, Portugal
Ribeiro Ana Cecília: Lusíada University, COMEGI, V. N. Famalicão, Portugal

Business Systems Research, 2022, vol. 13, issue 3, 116-129

Abstract: Background: This paper focuses on activities related to Customer Orders Management withing an auto components plant in the Automotive Industry. The main challenge was highlighted: customers don’t always regard the flexibility rules agreed with the company. Hence, planners must decide if variation in ordered quantity can be accepted in the forecast period or if adjusting is necessary. Objectives: The purpose was not only to streamline the decision-making process in the planning team but also to provide essential tools for the execution of their daily tasks – a visual and interactive dashboard to assess whether variations in customer orders were within the limits agreed with the company. Methods/Approach: Following Lean information management and business intelligence principles, a thorough process analysis was carried out, centralized and standardized reports were created that served as databases, and the dashboard was developed. Results: The proposed tool allowed reductions from 3,5h per week, spent mainly on collecting data, calculating variations, and selecting and adjusting the flexibility limits, to 0,2h a day per planner. Conclusions: Besides streamlining planners’ daily activities, main contributions regard the promotion of digital transformation, data-driven decision-making, and an automated record of customer order variations that could easily be adapted to suppliers.

Keywords: Order variation calculation; flexibility rules; customer order management; dashboard development; data analytics; digital transformation (search for similar items in EconPapers)
JEL-codes: D24 D83 L62 M11 M15 O31 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:bit:bsrysr:v:13:y:2022:i:3:p:116-129:n:1

DOI: 10.2478/bsrj-2022-0028

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