Performance evaluation of after-sales service partners in the power tools industry

Authors

  • Muhammad Wahid Malik Aljabar Universitas Mercu Buana
  • Sawarni Hasibuan Universitas Mercu Buana

DOI:

https://doi.org/10.30656/jsmi.v5i2.3985

Keywords:

After-sales service, Focus group discussion, Fault tree analysis, Performance, Power tools

Abstract

After-sales service (ASS) is a product support activity provided to customers; after-sales service that focuses on quality can create a sustainable competitive advantage. This study aims to the ASS performance, analyze the causes of performance constraints that occur in ASS and recommendations for improving the performance of ASS conceptually. Service partner performance achievement can be assessed from four categories, i.e. very good, good, bad, and poor, based on the actual level of performance compared to performance targets. The sample of this research is 12 ASS partners in the electrical equipment industry in West Java and Jakarta. Factors causing failure were analyzed descriptively using the fault tree analysis (FTA) method, which involved experts in focus group discussions (FGD). Based on the evaluation, 25% of partners were rated good, 50% poor, and 25% very poor. Partner performance achievement is carried out on 22 performance indicators, of which 20 performance indicators have not achieved a good rating. These indicators relate to brand issues, warranty, training, parts control and stock management, pricing, and service systems, including service centers and service facilities. The proposed concept that becomes a recommendation for improving the performance of power tools ASS is improving the operating system and the selection of partners in the service center and service dealer categories with industrial customer segmentation.

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Published

2021-12-31

Issue

Vol. 5 No. 2 (2021)

Section

Research Article

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How to Cite

[1]
“Performance evaluation of after-sales service partners in the power tools industry”, j. sist. manaj. ind., vol. 5, no. 2, pp. 105–114, Dec. 2021, doi: 10.30656/jsmi.v5i2.3985.
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