From transit to triumph
Transportation times in the planning of production networks
„Better to have than to need“, my father used to say. If you were to apply this folk wisdom to a production network, you would quickly realize that excess inventory can quickly become very expensive. In this article, we explore how incorporating transportation lead times into tactical planning can help reduce the need for valuable storage space and optimize overall production efficiency.
Challenges for production networks
Imagine a production network with factories or warehouses in different countries. Materials or intermediate products often have to be sourced over long geographical distances. While this can lead to cost savings as prices for goods and intermediates decrease compared to local sources, these benefits must outweigh the higher transportation costs to be beneficial.
Mobile storage
Not all goods and resources required for production need to be stored in conventional warehouses. They can be stored in „mobile warehouses“ during transportation, which significantly reduces costs. Good long-term capacity planning therefore takes into account long transportation and delivery times without compromising production and service quality. An important building block on the way to lean production.
Of course, such a system also has disadvantages. Unexpected delays can lead to expensive production downtime. This not only results in direct costs, but also a reduced service level, which ultimately jeopardizes customer satisfaction.
Safety stocks can help here, but lead to higher inventory costs. The trick is to allocate resources based on a good demand forecast so that machines, raw materials and personnel are available in sufficient quantities and at the right time to meet demand. The challenge is to maintain sufficient safety stock to keep production running without building up excess inventory.
The limits of manual planning
The art of long-term capacity planning, taking transport transit times into account, is to reconcile the following factors:
Material and transportation costs
Material must be procured in the right quality and at the right price without transportation costs destroying cost efficiency. This can mean not only procurement over long distances, but also procurement using slow means of transportation (e.g. sea freight).
Production reliability and service level
Production downtime is not only expensive, but also damages customer relationships. It is therefore important to ensure smooth and efficient production and maintain service levels by planning transportation times and downtime probabilities.
Storage costs and safety stocks
Storage costs can be reduced by using the transport as a „mobile warehouse“. This reduces the space required for material storage. Added to this is the safety stock that must be kept in reserve to maintain production in the event of transportation delays or failures.
Finding the right compromise between all these factors for an entire network through manual planning is almost impossible. It becomes completely impossible when unforeseen events require rapid rescheduling.
Digital solutions for complex tasks
The most important step in overcoming this challenge is the digitalization of the supply chain. In this context, the term „Digital twin“ is used. This term is misleading insofar as an entire company is never digitized, but only the part that is necessary for the result. The trick is to find a level of abstraction that provides an optimal answer to the question without becoming too complex and consuming an unnecessary amount of computing time.
Once the digital image has been completed, the impact of decisions on the entire network can be simulated. For example, the question of what a delay in the delivery of a key component would mean in terms of costs and service level can be answered. The effects of countermeasures can also be calculated. For example, what would happen if this component was flown in in a smaller batch instead of waiting for the delayed container ship to arrive?
In such a system, powerful algorithms allocate the available production and transport resources in order to maintain a defined capacity utilization and service level at minimum cost - regardless of how the underlying conditions change. With the help of prescriptive analytics, OPTANO provides concrete recommendations on how to achieve the defined target. This is why we often use the term intelligent decision support.
Mastering transport transit times for maximum efficiency
Incorporating transport times into production network planning is critical to optimizing efficiency and reducing costs. By using digital solutions and advanced optimization software, companies can balance material and transportation costs, maintain production reliability and minimize storage costs. This approach not only promotes lean production processes, but also ensures that resources are used efficiently to meet demand. Ultimately, striking the right balance between these factors is the key to a lean and robust production network with high service levels.
So I have to correct my father a little: It shouldn't be „It's better to have than to need“, but „It's better to have what you need when you need it“.
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