Navigating Long Leadtimes Through Forecasting

By Ammar Khan, CEO at Calderon Textiles

Competitively priced and high quality products are produced in areas globally where there is competitive advantage. Textile manufacturing and US based importers source products in Asia because of competitive advantage. This competitive advantage is created because of proximity to raw materials, labor costs, mature established industries, and adjacent supporting businesses amongst a host of other reasons. The drawback is that the cost effective and high quality products come with a price that is in long leadtimes. In this article we will explore why the supply chain and manufacturing leadtimes are elongated, the power of forecasting, and tactics to harness the benefits of forecasting and beyond!

Google describes leadtime as the time from initiation to the time of completion and while sourcing textile products there is manufacturing leadtime, time needed to make the product, logistics leadtime the time from factory to your distributor, and shipping leadtime is the time from inventory in a distributor’s warehouse to your plant operations. A laundry needs to hold as much inventory as the shipping leadtime while a distributor needs to hold as much inventory as the manufacturing and international shipping leadtime, this way there is enough inventory to last while the next round of products ship and arrive.

The longer the leadtime the greater amount of inventory needed to carry to overcome uncertainty and inconsistencies in the supply chain, safety stock. Safety stock is crucial to safeguard against stockouts which lead to lost sales. While too much inventory is also problematic because inventory tying up capital and a hassle for storage.

Manufacturers often have elongated leadtimes because they must source and purchase raw materials, plan production schedules, build work in process inventories, and pass through quality control testing and standards. If manufacturers could produce the same products 24/7/365 there would also be no downtime, changeover time, or lead time to build WIP inventories. Mass production for generic stock is less common today and laundries use differentiated products or unique array of product depth to stand out from competition. Whether a pink stripe bar towel, heavy weight kitchen towels, or hunter orange napkins manufacturers must be ready to make specialized products. These products are made in batch production and make-to-order companies cater to specific customer demands, building products only after an order is confirmed. Now while that is not practical it is possible to reduce these lead times through forecasting.

Forecasting in supply chain management is a crucial process that helps organizations make informed decisions and plan for the future. By accurately predicting demand, supply chain managers can ensure that optimal resources and materials are on hand to meet customer needs and avoid excess inventory, stockouts, and production downtime. While laundries may find it difficult to predict their demand, reasonable estimations are valuable to ensure continuity of supply.

The question that arises: why not use historical demand to predict the future? There are several factors influencing why a business may have a change in demand, including focus on a new product line, increased emphasis on a market segment, newly awarded business, or a change in strategic direction. These insights, along with feedback to your distributor, will increase the chances of inventory being readily available when changes in business occur.

For example, if a company forecasts and communicates a rise in demand for cleaning and disinfecting towels, the supply chain can react and adjust production and procurement processes to meet the increase, thus reducing the risk of stockouts. Conversely, if demand is expected to decline, forecasting can help companies minimize excess inventory and reduce waste and costs.

Is a forecast a promise to purchase? Distributors will value the collaboration and sharing of information. Forecasts within a 20% range for interchangeable products with high customers demand do not necessitate a promise to purchase. Highly individualized or customized products (e.g., private labels) will require a commitment to purchase in many cases. But a promise to purchase can make a compelling reason for distributors to have inventory availability assurances in place.

What if I do not have a forecast or do not know how many I will purchase? Begin with historical usage, then work item by item to brainstorm whether there are any changes in your current business that would require tweaking your expectations. For example: will your rental or revenue increase by 10%? If so, should you increase the forecast by 10%? In the absence of real-time data, collaboration will help. This inventory assessment and forecast-adjustment exercise should be done at least every six months or if there is a foreseeable change in business, such as new accounts added or loss of accounts.

Why should I spend my time forecasting? That is the supplier’s job! Forecasting helps the laundry by enabling them to have the right inventory at the most cost effective price. If forecasting collaboratively the supplier and laundry can ensure that the right amount of inventory is available and when needed. The optimal inventory leads to:

improved customer satisfaction reducing stockouts and having on time delivery
Lower carrying costs by minimizing excess inventory and storage space requirements.
Increased profitability by optimizing inventory levels and making informed purchasing decisions.
Enhanced agility by enabling companies to adapt quickly to changing market conditions.

The Future of Forecasting

The future of inventory forecasting in laundries is intelligent and interconnected. AI will analyze real-time data from RFID-tagged inventory and external sources, feeding machine learning models that predict demand with incredible accuracy. This allows for dynamic adjustments, optimizing production, procurement, and logistics in a constantly evolving global supply chain. Imagine an entire supply chain collaborating to automatically adjust production, shipping, and orders based on real-time demand shifts, ensuring perfect inventory levels and lightning-fast production cycles. To enable the future of forecasting we must begin to recognize, prioritize, and develop creating systems to forecast!