嘉兴市耳道式助听器需求分析数据

通过统计嘉兴市在分析时间前12个月耳道式助听器（ITC）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嘉兴市未来对耳道式助听器（ITC）的需求；通过该数据可以指导企业根据嘉兴市未来的需求来调整耳道式助听器（ITC）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等，对于经销商/零售商而言，该数据也可以辅助判断市场景气度，同时指导库存周转，避免在该地区的货物囤积。1.数据来源：采集了嘉兴市惠耳听力公司在分析时间前12个月的耳道式助听器（ITC）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。

This dataset is developed based on the historical order data of In-the-Canal (ITC) hearing aids in Jiaxing City over the 12 months prior to the analysis timestamp. First, the historical order volume is analyzed to establish a demand prediction model, which is then used to forecast the future demand for ITC hearing aids in Jiaxing City. This dataset can help enterprises adjust the inventory and subsequent marketing strategies of ITC hearing aids in this region based on the projected future demand, realize refined resource regulation and management, and avoid resource waste and other adverse outcomes. Additionally, for manufacturers or brand owners, the dataset enables precise production planning and supply chain optimization, guiding enterprises to arrange warehouses in advance and monitor inventory. For distributors or retailers, the dataset can assist in evaluating market prosperity, optimizing inventory turnover, and preventing goods hoarding in this region. 1. Data Source: The sales data of ITC hearing aids was collected from Hui'er Hearing Co., Ltd. in Jiaxing City over the 12 months prior to the analysis timestamp, including product type, source document number, quantity (negative values denote returns and refunds), billing time, and other related information. 2. Data Processing: A. Statistically calculate the demand quantity over the past 12 months, 9 months, 6 months, 3 months, and 1 month respectively by time periods. Note that only normal sales quantities are counted during the statistics, and returns and refunds are excluded; B. Calculate the monthly average demand quantity for each time period based on the above data. Take the monthly average demand quantity calculated from the past 12-month demand as the benchmark, compute the ratio of the monthly average demand quantity of each time period to this benchmark, adjust the total ratio to 1, and obtain the final coefficient K for each time period; C. The prediction model in this dataset is formulated as: Future 1-month demand quantity = (Past 12-month demand quantity / 12) * K1 + (Past 9-month demand quantity / 9) * K2 + (Past 6-month demand quantity / 6) * K3 + (Past 3-month demand quantity / 3) * K4 + (Past 1-month demand quantity / 1) * K5. The final calculated value is rounded to an integer; D. This prediction model balances the long-term annual trend and regional consumption differences, achieving accurate forecasting of the future demand for this product category in this region.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于嘉兴市耳道式助听器的需求分析，包含3149条历史销售记录，覆盖过去12个月至1个月的需求数量及计算得出的需求系数，并基于加权预测模型对未来1个月的需求进行预测。其核心价值在于通过数据分析指导企业优化库存管理、营销策略和生产计划，实现资源精细化管理，避免浪费，适用于制造商、经销商等角色进行市场判断和供应链优化。