Executive Insight: Supply Chain Decisions Are More Vital Tha ✓ Solved

Executive Insight Supply chain decisions are more vital than ever

Supply chain decisions are more vital than ever before and also more complex than ever before. How will companies address these challenges? One way is through the use of software and techniques for supply network design and simulation modeling. Tolga Yanasik and Thibault Quiviger specialize in the use of these tools and they describe some situations and the benefits they were able to deliver. Consider the task faced by a large steel maker that is creating its five-year investment plan. It must decide where to invest, which factories to revamp, and what production capacity to reduce in its 27 plants in Europe. Its product portfolio is made up of 16,000 different products, and many of them are processed on different production lines in different countries. The team in charge of this process is also concerned with the effect of different price policies contemplated for the different products and how this could modify their investment plan. Or consider a carmaker that is going to re-engineer its global supply chain operations to build a competitive advantage against its competitors. The questions that both of these companies must answer are similar and are questions such as: which product must be built on demand, which must be built on stock? Where to locate the different distribution centers? How much stock will be necessary to guarantee 95 percent service level to every customer with a delivery lead time of X days? Out of the total supply chain inventory, how much will be safety stock?

In another case, a company or port authority is planning to build a new container terminal. And it must decide about the new layout of the terminal, the number of cranes, the size of the parking lot for the waiting trucks, the number and location of weigh bridges and, most importantly, the number and layout of the customs gates it must negotiate with the country's government. Simulation modeling can be used to answer the questions in all three of these situations. We will illustrate some tools and methodologies that can be used by companies to make rational decisions about their production and distribution strategies. We will address three different levels of planning: strategic, tactical, and operational.

The difference between each level is the time horizon that drives different decision processes. For our discussion, we will define these time horizons as follows: Strategic: One year to five years, depending on the industry dynamics. Tactical: One month to one year. Operational: One day to one month.

The purpose of strategic design is to minimize the total cost of the supply chain under capacity constraints. Using network design tools and quantitative methodologies, people can answer the following questions: which product must be produced in which unit? Where should I build a new distribution center? Where to locate the inventories and how much to guarantee a certain service level? What is the most carbon-efficient network? Is it better to build on demand or to build on stock? What is the impact of adding a new product in my Supply Chain? What if I reduce my product portfolio complexity in terms of total cost, customer service, and inventory level across the supply chain? At which stage of the supply chain should I hold safety stock?

What about sharing this cost with my suppliers and customers and optimizing the overall inventory level? Simulation software packages allow people to build a mathematical model representing the current and potential supply chain, with all of its products, production sites, and distribution sites that are relevant for the decision-making process. People can define the constraints on the supply chain (target service levels, maximum capacity of each plant, transport options, etc.) and quantify these constraints. Costs can then be entered into the model and used to help answer design questions.

In this model, physical facilities and operating policies are put in place to tackle different problems such as factory production scheduling in the face of shifting product demand, managing production lead times that are longer than committed product delivery lead times to end customers, and coping with supply uncertainty and demand uncertainty. For example, management of inventories to cope with demand uncertainty (also known as safety stocks) is complex because every stage in the supply chain usually builds up its own safety stock to guarantee a given service level. It can be mathematically demonstrated that this approach is not optimum and tends to build up too much inventory in the supply chain. One can show in simulations that it is possible to reduce the overall value of safety stock in the chain while increasing the service level to the supply chain end customers.

The further downstream in a supply chain, the higher is the value of the inventory and safety stock. And the more upstream safety stock is accumulated, the lower the value of these stocks. Yet safety stock held closer to the end customer guarantees a higher service level. The challenge is to find the optimum locations and quantities of different products and components to hold in the supply chain so as to guarantee target service level for the end customer and also minimize the value of safety stocks. In many cases, simulations show how to reduce safety stocks by 30 percent or more while increasing service levels by 10 to 20 percent. Simulation shows this performance is achieved by reducing the safety stocks in the intermediate stages of the supply chain while increasing them in the final stage of the supply chain so as to increase service levels for the end customer.

In tactical supply chain planning, uncertainty is mainly driven by demand uncertainty, but there may be other sources of uncertainty: process times, availability of equipment, and complex interactions between workflows sharing limited resources (people, equipment, loading docks, etc.) making it hard to precisely know the overall system capacity. In these conditions, simulation can be of great help. Simulators help managers to measure the consequences of these different sources of uncertainty in the supply chain operation.

Let's consider here the example of a container terminal in Turkey. The container shipping business is booming in Turkey; a company is expanding its container terminal close to Istanbul in order to follow up on the container market demand. This company is already running another car export business, cars from the Renault Plant located close to the port and an import of steel slab for a neighboring plant. Simulation is a powerful tool to study facility operations and workflows in scenarios of high variability. Logistics is very much subject to this variability because of the interactions between these workflows which often cannot be controlled.

When considering the different product flows, capacity computation is not simple because of factors such as different product flows sharing some common resources (roads, custom tolls, weigh bridges); arrival of trucks is not constant during the day, nor during the week; weighing time and custom control times are very variable; and boat arrival times are unstable because of the crossing of the Bosphorus where many boats are queuing.

Using simulation, it was possible to verify that the current layout proposed was not optimal and could not absorb peak traffic; no new investment was required: changing the layout to make it more flexible was enough to absorb the different traffic peaks; and investment saved versus contemplated countermeasures was $4 million.

Very similar to manufacturing plants, simulation offers many benefits to warehouses. With the aid of simulation, logistics engineers can calculate how a new picking or replenishment strategy will affect the service levels or the utilization of lift trucks. Since logistics operations are exposed to more variation than factory production operations, it's crucial to monitor the behavior of these operations during extreme situations. Simulation is a highly useful tool for calculating the effect of possible variations. It enables engineers to pinpoint zones of congestion and improve the layout of warehouses to respond to this congestion. Three-dimensional simulation is especially important when designing and installing automation systems such as conveyors, sorters, or palletizers in a warehouse.

In conclusion, we have shown different techniques and uses of simulation to optimize supply chain investments and operations. We looked first at the strategic level because that's where the big money and big savings are to be found. Often supply chain managers are stuck in day-to-day operations. They tend to start from their daily experiences and try to extrapolate supply chain strategies. The difficulty of this approach lies in managers becoming focused on incremental changes to existing ways of working and failing to see the larger picture or try new ideas. Supply chains must be tailored to fit business strategy, not the other way around. Simulations of supply chain design and operations enable people to break out of preconceived ideas and try new approaches. Continuous simulation to find new ways to structure and operate supply chains is vital for companies that wish to keep up with the rapid rates of change in the global economy.

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Information technology (IT) has drastically changed how businesses manage their supply chains. It offers tools for enhancing visibility, collaboration, and agility, which are necessary for success in today's complex and rapidly evolving market landscapes. The value addition by IT to supply chains can be observed in several ways. First, IT solutions facilitate real-time information sharing among supply chain partners. This enables better coordination in demand forecasting, inventory management, and logistics operations, reducing lead times and improving customer satisfaction (Hugos, 2012).

Moreover, IT enhances decision-making processes through analytics and big data. By leveraging advanced analytics, companies can identify patterns and trends in customer demand, assess supplier performance, and optimize inventory levels. This empirical evidence allows organizations to make informed decisions, mitigating risks associated with demand fluctuations and supply disruptions (Yanasik & Quiviger, 2023).

Another significant aspect where IT adds value is in the design and management of supply chains using simulation software. Simulation modeling aids companies in visualizing and understanding complex supply chain dynamics (Yanasik & Quiviger, 2023). By creating virtual models of supply chain processes, organizations can identify bottlenecks, assess alternative scenarios, and test strategic initiatives without incurring real-world costs. This aspect is particularly crucial in the face of uncertainty caused by fluctuating demand and supply chain disruptions.

For instance, consider the case study of a steel manufacturer making investment decisions. With simulation software, the company can analyze the implications of different investment strategies across its various plants. It can assess factors such as production capacity, product distribution methods, and changes in supplier networks, ultimately leading to optimized resource allocation (Hugos, 2012).

Furthermore, in logistics management, simulation tools help solve various problems by modeling logistics operations, such as warehouse management, transportation, and distribution. By simulating the effects of operational changes on service levels and costs, organizations can explore new policies or strategies to enhance efficiency (Yanasik & Quiviger, 2023).

For example, in a container terminal scenario, simulation studies showed that the existing layout was inadequate for peak traffic inefficiencies. By changing layout options derived from simulation outcomes, the terminal could save millions without further investments (Yanasik & Quiviger, 2023).

To further improve business performance through IT, companies can implement integrated systems that facilitate seamless data sharing across supply chain functions. This integrative approach not only aids real-time information access but also supports collaborative decision-making across procurement, production, and distribution (Yanasik & Quiviger, 2023).

For instance, adopting enterprise resource planning (ERP) systems that capture data from various departments can enhance supply chain visibility, enabling firms to respond swiftly to disruptions and changing customer behaviors (Hugos, 2012). Additionally, enhancing IT capabilities with advanced machine learning algorithms allows businesses to optimize their demand planning and inventory management processes, thus significantly reducing operational inefficiencies.

In a conclusion, IT plays a crucial role in adding value to supply chains, particularly through enhanced visibility, improved decision-making, and increased collaboration among supply chain participants. Simulation software emerges as a vital tool that addresses the complexities of modern supply chains by enabling companies to model their supply chain dynamics and innovate their strategies based on data-driven insights. Consequently, the effective application of these technologies will empower businesses to improve their operational efficiency and sustain a competitive advantage within a volatile environment.

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