糕点配送超市金额数据

通过配送管理系统软件采集本公司糕点配送超市订单信息，将不同的配送订单以各超市来划分，从而计算各个超市每个月的配送金额数据，再计算出12个月的配送金额的方差大小，方差大小用来评价各个超市的配送情况，从而用于评估所有超市的采购和配送策略，所有企业可以通过该数据了解糕点在不同超市的配送行情，以平衡采购和配送糕点数量。例如对于超平稳型超市，本行业内企业无需时时关注该超市的行情，可每月保持好糕点的采购和配送数量；对于一般平稳型超市，本行业内企业需每季度关注该超市的行情，适当调整糕点的采购和配送数量；而对于波动型超市，本行业内企业需每月时时关注该超市行情，了解该超市的配送行情变化，以适应大幅度调整糕点的采购和配送数量变化。其次，本数据还能为配送行业的相关企业（如物流公司、农贸市场等）提供整体性参考，从而有效洞察市场趋势，更好地做出科学的营销决策。步骤1：通过配送管理系统软件采集本公司糕点配送超市的订单信息，将不同的配送订单以各超市来划分归类，从而将各年度每个月配送至超市的金额，从一月至十二月依次用y1,y2...y12表示，并汇总计算得到各个超市当年的总配送金额y。步骤2：计算各超市的月平均配送金额y̅=各个超市当年的总配送金额y/12。步骤3：根据方差公式计算方差S^2={(y1-y̅)^2+(y2-y̅)^2+(y3-y̅)^2+…+(y12-y̅)^2}/12，从而得到各个超市的月配送金额的方差S^2大小。步骤4：当方差S^2小于0.01评价该超市为超平稳型超市。当方差S^2大于等于0.01并且小于等于0.003评价该超市为一般平稳型超市。当方差S^2大于0.03评价该超市为波动型超市。

This dataset is compiled by collecting order information of pastries delivered to the company’s partnered supermarkets via the delivery management system software. All delivery orders are categorized by individual supermarkets, so as to calculate the monthly delivery revenue data for each supermarket. Subsequently, the variance of the 12-month delivery revenues is computed, which serves as an indicator to evaluate the delivery performance of each supermarket. This supports the assessment of procurement and delivery strategies for all relevant enterprises. Enterprises can utilize this dataset to grasp the pastry delivery market conditions across different supermarkets, thereby balancing the quantity of pastries procured and delivered.

For instance, for ultra-stable supermarkets, enterprises in this industry do not need to closely monitor their market conditions on a monthly basis, and can maintain consistent pastry procurement and delivery quantities each month. For generally stable supermarkets, enterprises need to pay attention to their market conditions every quarter and make appropriate adjustments to the procurement and delivery quantities. For volatile supermarkets, enterprises need to closely track their market conditions every month to understand changes in delivery trends, so as to make substantial adjustments to pastry procurement and delivery quantities.

Furthermore, this dataset can also provide holistic references for other enterprises in the delivery industry, such as logistics companies and agricultural wholesale markets, enabling them to effectively gain insights into market trends and formulate more scientific marketing decisions.

The specific data processing steps are as follows:
Step 1: Collect order information of pastries delivered to supermarkets via the delivery management system software, and categorize different delivery orders by individual supermarkets. Denote the monthly delivery revenues to a given supermarket in a calendar year from January to December as y₁, y₂, ..., y₁₂, and calculate the total annual delivery revenue y for that supermarket.
Step 2: Calculate the monthly average delivery revenue ȳ = total annual delivery revenue y / 12 for each supermarket.
Step 3: Compute the variance S² using the standard variance formula: S² = [(y₁−ȳ)² + (y₂−ȳ)² + (y₃−ȳ)² + … + (y₁₂−ȳ)²]/12, thus obtaining the variance value S² of the monthly delivery revenues for each supermarket.
Step 4: Classify supermarkets into three categories based on the variance value S²:
- Ultra-stable supermarket: when S² < 0.01
- Generally stable supermarket: when 0.01 ≤ S² ≤ 0.003
- Volatile supermarket: when S² > 0.03

搜集汇总

数据集介绍

特点

该数据集记录了糕点配送至各超市的金额数据，包含年份、超市编号、各月配送金额及总金额等信息，并通过计算方差评估超市的配送稳定性。数据可用于优化采购和配送策略，并为相关企业提供市场趋势参考。