奶制品配送医院食堂金额数据

通过配送管理系统软件采集本公司奶制品配送医院食堂订单信息，将不同的配送订单以各医院食堂来划分，从而计算各个医院食堂每个月的配送金额数据，再计算出各年度的配送金额的方差大小，方差大小用来评价各个医院食堂的配送情况，从而用于评估所有医院食堂的采购和配送策略，所有企业可以通过该数据了解0.0奶制品在不同医院食堂的配送行情，以平衡采购和配送0.0奶制品数量。例如对于超平稳型食堂，本行业内企业无需时时关注该医院食堂的行情，可每月保持好0.0奶制品的采购和配送数量；对于一般平稳型食堂，本行业内企业需每季度关注该医院食堂的行情，适当调整0.0奶制品的采购和配送数量；而对于波动型食堂，本行业内企业需每月时时关注该医院食堂行情，了解该医院食堂的配送行情变化，以适应大幅度调整0.0奶制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奶制品配送医院食堂的订单信息，将不同的配送订单以各医院食堂来划分归类，从而将各年度每个月配送至医院食堂的金额，从一月至十二月依次用y1,y2...y12表示，并汇总计算得到各个医院食堂当年的总配送金额y。步骤2：计算各医院食堂的月平均配送金额y̅=各个医院食堂当年的总配送金额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，从而得到各个医院食堂配送金额的方差s2大小。步骤4：当方差s2小于0.01评价该医院食堂为超平稳型食堂。当方差s2大于等于0.01并且小于等于0.03评价该医院食堂为一般平稳型食堂。当方差s2大于0.03评价该医院食堂为波动型食堂。

This dataset is compiled by collecting order records of dairy product deliveries to hospital canteens of our company through the delivery management system software. Orders are categorized by individual hospital canteens, allowing for the calculation of monthly delivery amounts for each canteen, followed by the computation of annual delivery amount variances. These variance values are used to evaluate the delivery performance of each hospital canteen, supporting the assessment of procurement and delivery strategies across all participating hospital canteens. Enterprises in the industry can leverage this dataset to gain insights into the delivery trends of 0.0 dairy products across various hospital canteens, thereby balancing the procurement and delivery volumes of 0.0 dairy products.

For ultra-stable canteens, enterprises do not need to closely monitor the trends of this hospital canteen on a regular basis, and can maintain consistent procurement and delivery volumes of 0.0 dairy products monthly; for generally stable canteens, enterprises need to review the trends every quarter and make appropriate adjustments to the procurement and delivery volumes; for volatile canteens, enterprises must closely monitor the delivery trends monthly to understand changes and make significant adjustments to the procurement and delivery volumes of 0.0 dairy products accordingly.

Furthermore, this dataset can serve as a holistic reference for relevant enterprises in the delivery industry, including logistics companies, agricultural wholesale markets, etc., enabling them to effectively identify market trends and formulate more evidence-based marketing decisions.

The dataset is generated through the following standardized processing steps:
Step 1: Collect order information of dairy product deliveries to hospital canteens of our company via the delivery management system software, and classify different delivery orders by each hospital canteen. Denote the monthly delivery amounts for each canteen from January to December of a year as y₁, y₂, ..., y₁₂, and calculate the total annual delivery amount y for each canteen.
Step 2: Compute the monthly average delivery amount ȳ for each hospital canteen, where ȳ = total annual delivery amount y / 12.
Step 3: Calculate the variance s² using the standard variance formula: s² = [(y₁−ȳ)² + (y₂−ȳ)² + (y₃−ȳ)² + … + (y₁₂−ȳ)²]/12, thereby obtaining the variance value s² of the delivery amounts for each hospital canteen.
Step 4: Classify hospital canteens based on the calculated variance s²:
- Ultra-stable canteen: when s² < 0.01
- Generally stable canteen: when 0.01 ≤ s² ≤ 0.03
- Volatile canteen: when s² > 0.03