This paper aims to explore the challenges and opportunities for Small and Medium-sized Manufacturing Enterprises (SMMEs) in implementing data-driven techniques in their operations. SMMEs are often considered to be low and medium–low tech companies, even if they have machinery, as they still rely on traditional processes and manpower and lack any digital technology. Previous research has shown that medium–high and high-tech companies perform better, with higher rates of growth, than low and medium–low ones by a sustainable and significant margin. Therefore, there is a need for further research on the implementation of data-driven analytical methods and technologies in SMMEs that are both cost-effective and easy to use. This study proposes a conceptual analytical system that combines Integration Definition for Function Modeling 0 (IDEF0) and the Cross Industry Standard Process for Data Mining (CRISP-DM) business analytics method to develop a practical and widely applicable framework for data-driven techniques in manufacturing. We then developed a case study of an Indonesian company, where we collected real and direct information about specific objects, events, and activities related to particular aspects, including showing their key performance indicators (KPIs) through data dashboards, to evaluate the effectiveness of the proposed conceptual analytical system in improving operational management in SMMEs. The findings of this study provide valuable insights that can be used to develop effective solutions for SMMEs to leverage data-driven techniques and improve their operations. We also highlight implications of the findings for future research and practical applications. The final framework can be converted into a system that can be continuously and flexibly updated and customized, based on specific needs.

中文翻译：

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增强中小型制造商运营管理的价值创造：概念数据驱动的分析系统

本文旨在探讨中小型制造企业（SMME）在运营中实施数据驱动技术的挑战和机遇。中小型企业通常被认为是低技术和中低技术公司，即使它们拥有机械，因为它们仍然依赖传统流程和人力，缺乏任何数字技术。先前的研究表明，中高技术和高科技公司的表现更好，增长率更高，比低技术和中低技术公司的表现更好，并且具有可持续和显着的优势。因此，需要进一步研究在中小企业中实施既经济又易于使用的数据驱动分析方法和技术。本研究提出了一个概念分析系统，该系统结合了功能建模 0 集成定义 (IDEF0) 和数据挖掘跨行业标准流程 (CRISP-DM) 业务分析方法，为制造业中的数据驱动技术开发了一个实用且广泛适用的框架。然后，我们对一家印度尼西亚公司进行了案例研究，我们收集了与特定方面相关的特定对象、事件和活动的真实直接信息，包括通过数据仪表板展示其关键绩效指标（KPI），以评估其有效性提出了改善中小型企业运营管理的概念分析系统。这项研究的结果提供了宝贵的见解，可用于为中小型企业开发有效的解决方案，以利用数据驱动技术并改善其运营。我们还强调了研究结果对未来研究和实际应用的影响。最终的框架可以转换成一个可以根据特定需求持续灵活更新和定制的系统。