Research and Implementation of Digital Transformation Methods for Process Manufacturing Enterprises Based on Employee Performance

DOI

10.2991/978-94-6463-490-7_22How to use a DOI?

Keywords

Performance Evaluation; Indicator Library; Indicator Weight; ANP

Abstract

Process manufacturing enterprises usually adopt KPI (Key Performance Indicator) or OKR (Objectives and Key Results) methods to assess the performance of employees. The collection of assessment indicators is difficult and complex, and it is difficult to meet the requirements of objectivity, accuracy and timeliness. With the deepening of digital transformation of process manufacturing enterprises in China, this paper proposes a performance appraisal method for digital employees in process manufacturing based on industrial big data technology. First of all, the comprehensive digital enterprise strategic objectives, combined with daily management needs and production norms, establish a comprehensive index database, and these indicators are divided into different dimensions, decomposed into the implementation of all levels of employees; Through the budget and plan management system to set the periodic indicators and index budget values of each position in the enterprise; The performance indicators of each employee are collected from each business system in real time, and the assessment score is calculated according to the assessment method of the corresponding indicators. Fuzzy Number (FN) -DEMATEL (Decision-making Trial and Evaluation Laboratory) -ANP (Analytic Network Process) method is used to determine the index weight objectively. The real-time performance scores of employees can be obtained by using indicator weights and presented in the form of digital performance cards. Employees may appeal against disputed performance scores. By applying the performance software platform designed by this method to a chemical enterprise, the operation efficiency of the enterprise can be effectively improved and the process of digital transformation can be promoted.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Weipeng Tai
AU  - Aoyue Ma
AU  - Qianrui Dai
AU  - Jinglin Li
AU  - Xudong Hong
PY  - 2024
DA  - 2024/08/31
TI  - Research and Implementation of Digital Transformation Methods for Process Manufacturing Enterprises Based on Employee Performance
BT  - Proceedings of the 2024 3rd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2024)
PB  - Atlantis Press
SP  - 196
EP  - 208
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-490-7_22
DO  - 10.2991/978-94-6463-490-7_22
ID  - Tai2024
ER  -