Make To Stock (MTS) is a process through which products are made and supplied for the inventory using demand forecasts. It is aimed at creating immediate availability of products to the customer and if managed well it can contribute to a more resilient supply chain.
Make To Stock (MTS) is considered to be a traditional production strategy used by some businesses for their inventories. Through this, a match is made between what is there in the inventory and the anticipated demand from the consumer’s end.
Thus, a company using the Make To Stock Process generates an estimation of probable orders and supplies stock accordingly. An important aspect of an MTS strategy is the definition of a safety stock level. The safety stock is a quantity of stock to protect against volatility and planning will always try to keep inventory above the safety stock level.
The MTS functions through possible and potential forecasting of the demand of a particular product. An appropriate demand forecast means efficient production and mitigating excess costs. This method helps a company to prepare and embrace for any increase or decrease in demand beforehand. Past data is analyzed to make forecasts of future demands in the market. An important aspect of an MTS strategy is the definition of a safety stock level. The safety stock is a quantity of stock to protect against volatility and planning will always try to keep inventory above the safety stock level.
MTS has both pros and cons. If the correct prediction can be made about future demand, then it will significantly cut down costs. Unnecessary production can be done away with and only the units required will be produced.
However, any mistake in the prediction process or unknown shocks and challenges from the economy will spell disaster. A faulty prediction would mean stockpiles or stockouts and ultimately lead to a huge loss of revenue. The biggest disadvantage is perhaps either the overflow or empty inventories.
Any readjustment that takes place is usually costly and the costs are borne by either the consumer or the company. Thus, companies with cyclical or seasonal sales patterns might suffer a loss if there’s a sudden dip in demand in a particular year.
There are certain companies in the manufacturing sector that use the MTS approach to gear themselves for a season of higher production levels. Suppose there are two companies in the market: Company X and Company Y. X is responsible for supplying raw materials to Y, who are toy sellers. Suppose the previous data shows that the highest sales are recorded in the last quarter of a year (perhaps due to Christmas and New Year).
Using the Make To Stock method, X prepares itself for a greater supply of materials before the last quarter begins. Using the same strategy they also prepare for a dip in sales in the following quarter. However, if there is any fault in the computation or a market shock, then this approach will stumble and lead to humongous losses.
Consider a pharmaceutical company A which sells cough medicine. It will typically keep stock in each individual market (medicines have generally country-specific packs) so that it can supply the wholesalers on short notice. To manage this stock efficiently using an MTS strategy Company A is relying on forecasts and tries to predict several months in advance how many units of cough medicine will be sold in each market during the cold season. But cough is unpredictable. Some years people get more sick than others. In addition, competitors can always come with new, better or cheaper alternatives. Therefore the chances are high that in some markets Company A will experience overstock of cough medicine while in others it will be in stock-out!
The food and beverage industry also runs a huge risk of wastage of inventory because they deal with perishable items. Any dip in demand can be a doom for the business. Moreover, sudden outbreaks of disease in vegetable and fruit plants will result in an added burden. So what can be done in such circumstances? There are additional methods and approaches to tackle the issue.
The biggest drawback of the MTS approach is inaccurate forecasting. There’s no way to make a concrete prediction of consumer demand by simply looking at old data sets and purchasing patterns. And even the best artificial intelligence can’t generate accurate predictions beyond a short time horizon. This fact, combined with the standard planning algorithms that try to avoid inventory going below the safety stock, generate a lot of additional volatility. There are vertical systems in place which fail to seamlessly integrate any critical and sudden demand spikes. This leads to a direct supply shortage and stockouts. Additionally, most systems don’t have a seamless collaboration strategy in place which leads to serious imbalances between domestic and international partners. This ultimately leads to a serious lack of synchronization in logistics and a lack of procedures to prevent risks.
This can be done by adopting a Real-Time Value Network and using the MTS Replenishment Best Practice Template. It is implemented through a demand-driven approach or a hybrid MTS/MTO landscape. This will help companies keep a tab on real-time demands based on live data feeds. It effectively means regular inventory management by optimizing stocks at all contact points. Additionally, it leads to reduced risks and ultimately better liquidity control and revenue generation.
All hassles can be avoided if one adopts a demand-driven approach for the supply chain. Patrick Rigoni and his team can help you understand and learn all about the demand-driven methodology and make the most of supply chain performance.
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