各部门运费分部门分月统筹数据

为响应企业的增效降本战略目标，推进运费统筹数据的建设。对各个中心及各工厂的物料运输需求线上化，体现通过本算法得到的各部门运费分部门分月统筹数据，再将数据与FineBi可视化工具相结合。业务部门可以在任何时刻通过承担部门类型、货运类型等多维度分析各部门运费分部门分月统筹情况。逐步加强业务部门对于货运类型、分摊金额等基础数据方面的管理，能更直观的提升用户体验，同事也方便业务部门更具性价比的选择所需货运类型，并清晰有效地传达至业务部门各部门运费分部门分月统筹数据情况。各部门运费分部门分月统筹数据的算法规则包括以下几个方面：1、数据采集：在运费统筹平台通过对应的事务代码在后台表找到相关表的关联逻辑。2、数据校验：通过循环冗余位来保证代码的正确性，每个位都代表了一个可能出现的位。3、数据处理：明确业务部门需求逻辑，根据后台表逻辑在运费统筹平台数据库中搭建SQL模型。将各部门的货运类型和分摊金额均根据日期、工厂、二级部门分组汇总即使用已分组平均公式σ=√Σ（X1-X2）^3/（n+1），记不同的工厂维度为X1，不同的二级部门维度为X2。再根据公式分摊金额m=sum(W)/sum(O)*s；其中，w为各部门费用；记p1为第一条记录的运单数量，p2为第二条记录的运单数量，同理记q1为前置单数量；总运单数量O=Σ((p1+q1)+(p2+q2)+...+(pn+qn))；s为费用与总运单数量占比单项式中的基础系数。最后通过BI工具，按日期、工厂等维度进行分类统计并实现层层钻取功能，并利用组合图体现各部门运费分部门分月统筹数据情况。

In line with the enterprise's strategic goals of improving operational efficiency and reducing costs, this initiative advances the development of unified freight tariff management data. The material transportation requirements of all centers and factories are digitized and managed online. The monthly unified freight tariff data for each department generated by the proposed algorithm is showcased, and the data is integrated with the FineBi visualization platform. Business departments can analyze the monthly unified freight tariff status of each department across multiple dimensions such as responsible department type and freight type at any time. Gradually enhancing the management of basic data such as freight types and allocated amounts by business departments can intuitively improve user experience, meanwhile enable business departments to select cost-effective required freight types, and clearly and effectively communicate the monthly unified freight tariff data status of each department to relevant business teams. The algorithm rules for generating the monthly unified freight tariff data of each department are as follows: 1. Data Collection: Identify the association logic of relevant backend database tables via corresponding transaction codes on the freight tariff unified planning platform. 2. Data Verification: Cyclic redundancy bits are employed to ensure the correctness of the code, with each bit representing a potential occurrence case. 3. Data Processing: Clarify the demand logic of business departments, and construct an SQL model in the database of the freight tariff unified planning platform based on the backend table association logic. Group and summarize the freight types and allocated amounts of each department by date, factory and secondary department, using the grouped average formula σ=√[Σ(X₁ - X₂)³/(n+1)], where X₁ denotes different factory dimensions and X₂ denotes different secondary department dimensions. Then calculate the allocated amount m via the formula m = [sum(W)/sum(O)] * s; where W represents the expenses of each department, p₁ is the waybill quantity of the first record, p₂ is the waybill quantity of the second record, and q₁ is the quantity of preceding waybills in the same manner. The total waybill quantity O is calculated as O=Σ((p₁+q₁)+(p₂+q₂)+…+(pₙ+qₙ)); and s is the basic coefficient in the monomial term of the proportion between expenses and total waybill quantity. Finally, through the FineBi visualization platform, perform classified statistics according to dimensions such as date and factory, implement the layer-by-layer drill-down function, and use combined charts to visualize the monthly unified freight tariff data status of each department.

搜集汇总

数据集介绍

特点

该数据集为制造业领域的运费统筹数据，包含251条记录，每月更新，涵盖日期、工厂、部门类型、货运类型、费用等多个字段，主要用于通过FineBi工具分析各部门运费情况，支持企业增效降本战略。