湖州市深耳道式助听器需求分析数据

通过统计湖州市在分析时间前12个月深耳道式助听器（CIC）的历史订单量，对历史订单量进行分析得到预测模型，根据预测模型来预测湖州市未来对深耳道式助听器（CIC）的需求；通过该数据可以指导企业根据湖州市未来的需求来调整深耳道式助听器（CIC）在该地区的库存以及后续营销策略，对资源调控实现精细化管理，避免产生资源浪费等情况。另外，对制造商/品牌商而言，通过该数据可以实现精准生产与供应链优化，指导企业实现提前布仓以及存货监控，指导库存周转，避免该品牌货物在该地区的货物囤积。1.数据来源：采集了湖州市惠耳听力公司在分析时间前12个月的深耳道式助听器（CIC）销售数据，包括商品类型、来源单据号、数量（负数表示退货退款）、收费时间等。2.数据处理：A.按分析时间分时间段统计过去12个月需求数量、过去9个月需求数量、过去6个月需求数量、过去3个月需求数量、过去1个月需求数量（统计时仅计算该段时间内的正常销售数量，已排除退货退款数量）；B.根据以上数据分别计算各时间段内的单月平均需求量；以过去12个月需求数量计算的单月平均需求量为单位，计算各时间段内的单月平均需求量与其的比值；按比例调整总值为1，计算最终各时间段所得系数K；C.在该数据中，预测模型为：未来1个月需求数量=过去12个月需求数量/12*K1+过去9个月需求数量/9*K2+过去6个月需求数量/6*K3+过去3个月需求数量/3*K4+过去1个月需求数量/1*K5（最终计算得到的数值四舍五入后取整数）；D.该预测模型能够兼顾年度的长期趋势以及地域的消费差异，实现对该品类产品在该地区未来需求的精准预测。

By counting the historical order volume of Completely-In-Canal (CIC) hearing aids in Huzhou City over the 12 months prior to the analysis time, a forecasting model is developed via analysis of the historical order data, which is then used to predict the future demand for CIC hearing aids in Huzhou. This dataset can help enterprises adjust the inventory and subsequent marketing strategies of CIC hearing aids in this region based on the projected future demand in Huzhou, enabling refined resource allocation management and avoiding resource waste. Additionally, for manufacturers and brand owners, this dataset supports precise production and supply chain optimization, guiding enterprises to arrange warehouses in advance, monitor inventory, optimize inventory turnover, and prevent overstocking of the brand's products in this region.
1. Data Source: Sales data of CIC hearing aids from Hui'er Hearing Company in Huzhou City over the 12 months prior to the analysis time were collected, including product type, source document number, quantity (negative values represent returned or refunded orders), and billing time, etc.
2. Data Processing:
A. Count the demand quantities over the past 12 months, 9 months, 6 months, 3 months, and 1 month respectively by time periods based on the analysis timeline (only normal sales volumes within the corresponding time period are counted, and returned/refunded quantities have been excluded);
B. Calculate the monthly average demand for each time period based on the above data; take the monthly average demand calculated from the 12-month historical data as the benchmark, calculate the ratio of the monthly average demand of each time period to this benchmark; adjust the total ratio to 1 proportionally, and obtain the final coefficients K for each time period;
C. The forecasting model for this dataset is defined as: Future 1-month demand quantity = (12-month historical demand / 12) * K1 + (9-month historical demand / 9) * K2 + (6-month historical demand / 6) * K3 + (3-month historical demand / 3) * K4 + (1-month historical demand / 1) * K5 (the final calculated value is rounded to an integer);
D. This forecasting model balances annual long-term trends and regional consumption differences, enabling accurate prediction of the future demand for this product category in this region.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于湖州市深耳道式助听器（CIC）的需求分析，包含2379条企业数据，记录了历史销售订单、不同时间段的需求数量及系数。通过基于加权平均的预测模型，它能精准预测未来一个月需求，旨在帮助企业优化库存管理、调整营销策略并实现供应链精细化，从而提升资源利用效率。