It's all about an agile system. Your capability to respond fast to the demand of the market decides your philosophy about inventory management. It defers from business to business. 5-10 years historical data gives u trends of market wrt season festival demographic changes political atmosphere etc . Now you can decide what amount of buffer is economically viable and accordingly u ll act. Follow TOC rules (Goldratts principles), it will guide you to meaningful decision

Эффективное управление запасами при колеблющемся спросе требует применения динамического анализа данных и адаптивных стратегий. Используйте цифровые двойники производства для моделирования сценариев и прогнозирования спроса на основе исторических данных и текущих рыночных трендов. Внедряйте сегментацию запасов по параметрам ABC/XYZ для дифференциации подходов: высоколиквидные товары требуют высокой доступности, а низколиквидные — минимальных остатков. Инвестируйте в гибкие производственные мощности и стратегическое размещение буферных складов ближе к ключевым рынкам. Комбинируйте подходы JIT (точно-вовремя) и MTS (на склад) для оптимизации цепочки поставок. Автоматизация аналитики и интеграция систем управления запасами минимизируют риски.

Meeting with fluctuating demand in tailorr made items is very tricky. You cannot build inventory oof finished goods. In such cases, you may have plans for Buffer activities like some fixtures; maintenance, stands, etc from available non moving materials tto keep workforce busy. These activities eventually help execution better when demand increases.

First of all to over come this kind of situation you need to replicate few things :- # Study the market from past ten year and make a plan for inventory management according to flow of material # localisation of vendor will help you to to improve JIT . # Direct dispatch to retailer also fulfill the gap in market during peak demand .

the first step is to adjust the forecast of demand through the customer . then the due time for raw material to reach to the factory . then try to relate between the demand and stock available for the raw material which will be used to achieve the demand . then updated forecast from time to time . to adjust the raw materil stock

It is crucial to maintaining operational efficiency and customer needs. Here are some practical strategies: Utilize Real-Time Data: Implement inventory management software to monitor stock levels and demand patterns continuously, enabling quick adjustments Demand Forecasting: Use historical sales data and market research to anticipate demand fluctuations and adjust inventory levels proactively Just-in-Time (JIT) Inventory: Adopt JIT practices to minimize excess stock by receiving goods as needed, reducing holding costs while ensuring availability Safety Stock: Maintain a buffer inventory to handle unexpected demand spikes without disrupting production schedules

Firstly, a market survey is needed for a new plant. However, if the plant is in existence, it then means you need to establish the trend of SKU usage, reorder level and sales forecast. The sales forecast is not always 100%, but a forecast with 70-80% is good to go. Secondly, proper stock keeping helps you to close out your inventory books to avoid stock out. Lastly, do not have only one vendor, a minimum of 3 vendors is not bad to avoid long lead time and stock out.

In a world where manufacturers have direct access to consumers, there are opportunities to solve the inventory gap by launching retail products to sell through social media during the slow periods. There has never been a better time for manufacturers to put their knowledge to work for themselves. It could be a small customization on a product that has already been developed or a smaller volume order with a full margin.

1. Use advanced analytics and machine learning to forecast demand based on historical data, market trends, and customer orders. 2. Collaborate with customers to gather accurate demand signals. Incorporate seasonality, regulatory changes, and competitive factors into forecasts. 3. Maintain safety stock levels to cushion against demand variability. Use statistical methods (e.g., standard deviation of demand) to calculate optimal safety stock. 4. Adopt flexible manufacturing practices to quickly switch production lines between APIs based on demand changes. Use modular facilities or single-use technologies to improve adaptability.