金华市耳道式助听器需求分析数据

通过统计金华市在分析时间前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金华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金华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：采集了金华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。

By analyzing the historical order volume of in-the-canal hearing aids (ITC) in Jinhua City over the 12 months prior to the analysis timestamp, a prediction model is developed to forecast the future demand for ITCs in this region. This dataset can help enterprises adjust their inventory levels and subsequent marketing strategies for ITCs in Jinhua based on the forecasted future demand, enabling refined management of resource allocation and avoiding resource waste. Additionally, for manufacturers or brand owners, the dataset enables precise production planning and supply chain optimization, guiding enterprises to pre-position warehouses and monitor inventory. For distributors or retailers, it can assist in evaluating market sentiment, optimizing inventory turnover, and preventing overstock in this region. 1. Data Source: Sales data of ITCs were collected from Huier Hearing Co., Ltd. in Jinhua City over the 12 months prior to the analysis timestamp, including product type, source document number, quantity (negative values indicate returned or refunded items), and transaction time. 2. Data Processing: A. Tally the demand quantities over the past 12, 9, 6, 3, and 1 months respectively based on the analysis timestamp (only normal sales volumes are counted during the tallying process, and returned/refunded quantities have been excluded); B. Calculate the monthly average demand for each of the above time periods separately. Take the monthly average demand derived from the 12-month historical sales data as the benchmark, compute the ratio of the monthly average demand of each time period to this benchmark, then adjust the total ratio to 1 to obtain the final coefficients K for each time period; C. The prediction model for this dataset is formulated 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 prediction model can balance annual long-term trends and regional consumption differences, achieving accurate forecasting of future demand for this product category in the target region.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于金华市耳道式助听器（ITC）的需求分析，包含1037条历史销售记录，通过统计过去不同时间段的需求数量并计算相应系数，构建预测模型来预估未来1个月的需求量。其核心特点是利用企业自行产生的数据，结合算法规则实现精准预测，旨在辅助企业优化库存管理、调整营销策略和优化供应链，提升资源利用效率。