使用微软Power BI进行数据可视化的新型滚动预测框架:制药行业的案例研究.
Mariem Belghith1, Hanen Ben Ammar2, Abdelkarim Elloumi1
1Laboratory of Modelling and Optimization for Decisional, Industrial and Logistic Systems (MODILS), Faculty of Economics and Management of Sfax, University of Sfax, 3039 Sfax, Tunisia.
Annales pharmaceutiques francaises
|November 4, 2023
概括
这项研究引入了一种新的药品销售滚动预测框架,大大减少了预测误差高达75%和库存水平50%的预测误差. 该系统增强了生产规划和患者满意度.
科学领域:
- 供应链管理 供应链管理
- 制药行业 制药行业 制药行业
- 数据分析数据分析数据分析.
背景情况:
- 准确的需求预测对于制药供应链效率和生产规划至关重要.
- 现有的预测模型缺乏具体的,通用的框架,特别是对于制药行业的独特需求.
- 这项研究解决了在制药制造业中改善销售预测和可视化的需求.
研究的目的:
- 开发和验证药品销售的通用,滚动预测框架.
- 通过准确的销售预测,增强供应链经理的决策能力.
- 整合现代IT和商业智能以可视化预测结果和提高患者满意度.
主要方法:
- 使用Visual Studio C++开发了一个滚动预测框架,用于最佳预测,并使用Power BI进行准确性监测.
- 该框架整合了三种指数级光滑方法,具有未来扩展的能力.
- 该系统使用来自制药制造商的多个数据集进行了测试.
主要成果:
- 拟议的框架在药品制造商的销售预测方面表现出卓越的表现.
- 预测错误减少了高达75%,库存水平下降了50%.
- 该公司目前正在使用该框架,并计划在未来将其集成到其企业资源规划 (ERP) 系统中.
结论:
- 滚动预测框架提供准确的未来销售洞察力和营业额可视化.
- 它可以实现更有效的库存管理和生产规划,从而提高供应链效率.
- 该系统支持数据驱动的决策,最终有助于改善患者的治疗结果.
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