板栗仁销量预测分析数据

1.数据采集：采集公司的销售和订单信息以及后台库存信息。2.数据处理：对采集到的原始数据进行处理，去除缺失和异常数据，并根据时间和产品进行汇总。 3.数据分析：采用加权移动平均法预测销量，预测销量S=（S1*k1+S2*k2+S3*k3）/（k1+k2+k3），S1：本月的销量，S2：上月的销量，S3：上上月的销量，k1、k2、k3为权重系数，根据S1、S2和S3对下月销量预测值的影响程度确定，分别为分别为4.5、3.5、2。库存健康监测P=实际库存/预测销量，P＜1.5，“库存不足”，1.5≤P≤2.5，“库存健康”，P>2.5“库存积压”。4.数据应用：通过销量的预测，可以帮助企业提前合理预测销量，库存应该备货多少，若库存不足，则发出预警信号，需要及时考虑补货，若库存积压，则需要推出活动及时清理库存。1.数据采集：采集公司的销售和订单信息以及后台库存信息。2.数据处理：对采集到的原始数据进行处理，去除缺失和异常数据，并根据时间和产品进行汇总。 3.数据分析：采用加权移动平均法预测销量，预测销量S=（S1*k1+S2*k2+S3*k3）/（k1+k2+k3），S1：本月的销量，S2：上月的销量，S3：上上月的销量，k1、k2、k3为权重系数，根据S1、S2和S3对下月销量预测值的影响程度确定，分别为4.5、3.5、2，本数据样例中S1为2024年4月的销量，S2为2024年3月的销量，S3为2024年2月的销量，S为5月的预测销量。库存健康监测P=实际库存/预测销量，P＜1.5，“库存不足”，1.5≤P≤2.5，“库存健康”，P>2.5“库存积压”。4.数据应用：通过销量的预测，可以帮助企业提前合理预测销量，库存应该备货多少，若库存不足，则发出预警信号，需要及时考虑补货，若库存积压，则需要推出活动及时清理库存。

1. Data Collection: Gather the company's sales, order information and backend inventory data.
2. Data Processing: Process the collected raw data by removing missing and abnormal records, and aggregate the data by time period and product.
3. Data Analysis: The Weighted Moving Average method is adopted for sales volume forecasting. The formula for the forecasted sales volume $S$ is: $S = frac{S_1 imes k_1 + S_2 imes k_2 + S_3 imes k_3}{k_1 + k_2 + k_3}$. Where $S_1$ denotes the sales volume of the current month, $S_2$ denotes the sales volume of the previous month, and $S_3$ denotes the sales volume two months prior. The weight coefficients $k_1$, $k_2$, $k_3$ are determined based on their respective influence on the next month's sales forecast, with values set as 4.5, 3.5 and 2 respectively. In this dataset sample, $S_1$ corresponds to the sales volume in April 2024, $S_2$ to March 2024, $S_3$ to February 2024, and $S$ is the forecasted sales volume for May 2024. Inventory health is monitored using the indicator $P = frac{ ext{Actual Inventory}}{ ext{Forecasted Sales Volume}}$. Specifically, "Insufficient Inventory" when $P < 1.5$, "Healthy Inventory" when $1.5 leq P leq 2.5$, and "Overstocked Inventory" when $P > 2.5$.
4. Data Application: The sales volume forecast can help enterprises reasonably predict future sales and determine appropriate inventory replenishment quantities. If the inventory is insufficient, an early warning signal will be triggered to prompt timely replenishment; if overstocking occurs, promotional activities should be launched to clear the excess inventory in a timely manner.