调味品配送超市金额数据

通过配送管理系统软件采集本公司调味品配送超市订单信息，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调味品在不同超市的配送行情，以平衡采购和配送调味品数量。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，可每月保持好调味品的采购和配送数量；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，适当调整调味品的采购和配送数量；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，以适应大幅度调整调味品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调味品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s2={(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s2大小。步骤4：当方差s2小于0.01评价该超市为超平稳型超市。当方差s2大于等于0.01并且小于等于0.03评价该超市为一般平稳型超市。当方差s2大于0.03评价该超市为波动型超市。This dataset is constructed by collecting order information of the company's condiment distribution supermarkets through a dedicated delivery management system software. First, different delivery orders are categorized by individual supermarkets to calculate the monthly delivery amount data for each supermarket over a 12-month period. The variance of the 12-month delivery amounts is then computed to evaluate the distribution performance of each supermarket, which supports the assessment of procurement and distribution strategies for enterprises in the industry. All relevant enterprises can use this dataset to understand the condiment distribution trends across different supermarkets, so as to balance the quantity of condiments procured and delivered. For example: 1. For ultra-stable supermarkets: enterprises in this industry do not need to closely monitor their market conditions on a regular basis, and can maintain consistent condiment procurement and delivery volumes each month; 2. For generally stable supermarkets: enterprises need to monitor their market conditions quarterly and make appropriate adjustments to condiment procurement and delivery volumes; 3. For volatile supermarkets: enterprises need to closely monitor their market conditions monthly to track changes in distribution trends, and make substantial adjustments to condiment procurement and delivery volumes accordingly. Additionally, this dataset can provide holistic reference for related enterprises in the distribution industry, including logistics companies and agricultural wholesale markets, enabling them to gain insights into overall market trends and formulate more scientific marketing decisions. The specific data processing steps are as follows: Step 1: Collect order information of the company's condiment distribution supermarkets via the delivery management system software, and classify different delivery orders by individual supermarkets. Denote the monthly delivery amounts to each supermarket over the year (from January to December) as y1, y2, ..., y12 respectively, and calculate the total annual delivery amount y for each supermarket. Step 2: Compute the monthly average delivery amount, denoted as y_bar, which equals the total annual delivery amount y divided by 12, for each supermarket. Step 3: Calculate the variance s² using the standard variance formula: s² = [(y1 - y_bar)² + (y2 - y_bar)² + (y3 - y_bar)² + … + (y12 - y_bar)²] / 12, thus obtaining the variance of the monthly delivery amounts for each supermarket. Step 4: Classify supermarkets into three categories based on the computed variance s²: - Ultra-stable supermarket: when s² < 0.01; - Generally stable supermarket: when 0.01 ≤ s² ≤ 0.03; - Volatile supermarket: when s² > 0.03.