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In an increasingly globalized modern supply chain, new rules come in and the supply chains keep expanding and getting complex. As trade routes proliferate and new sources of data come into play, an already complex task becomes almost forbiddingly so.
What can modern supply chain managers and logistics managers do to cope with the ever-increasing complexity of modern supply chains? They must:
- Improve forecasts
- Implement real-time data
- Take control of capacity management
- Use a “what-if” scenario
Let’s understand the Keys To Coping With Complexity In Modern Logistics in detail.
What is it about complexity that is problematic for supply chain managers and logistics managers? It makes it harder to predict the outcome of any given decision, meaning that disruptions in the form of unexpected events are more likely to arise to derail one’s plans. The most direct way to cope with this is to deal with prediction head-on and improve the forecasts with advanced predictive analytics.
By leveraging existing operational data into advanced analytics workflows, one can create forecasts that account for the growing complexity of the market and develop plans that reflect data-driven expectations. This decreases the likelihood of the unexpected, resulting in fewer disruptions overall. After all, if one knows what demand levels or freight costs will be in advance, it is less likely to be blindsided by unexpected dips or upticks.
Implement real-time data
Speed is one more thing that planners need to contend with in an increasingly global supply chain. Things move quickly, situations can change at the drop of a hat, and planners need to be able to cope with this fact. The complexity of a given situation only increases as time goes by without taking any action. For this reason, real-time integration can be a huge value-added proposition for companies seeking to decrease complexity in their logistics operations.
If it I possible to monitor situations in real-time, then it is possible to react and make adjustments more quickly, preserving the maximum amount of possible value in the face of dicey stations. In fact, one can be not just reactive, but proactive, by identifying potential pitfalls far in advance and taking actions to stabilize the logistics operations. In this way, it is possible to cut down not just complexity, but risk, resulting in more on-time deliveries and fewer unwanted snafus.
Increased complexity can decrease predictability, leading to disruptions. The other issue with increased complexity is inefficiency. Even if one is not actively courting disruptions, the more options one has at every step of the value chain, the less likely it is that due consideration is given to each possible route, tour, and shipping option. This means failing to identify the most efficient and cost-effective routes because there are simply too many possible options. This is where supply chain integration comes in.
It might seem paradoxical to solve a situation involving so many choices and options by integrating more data into the value stream, however in point of fact, the more data available the more successfully it is possible to analyze the best options. This can take the form of both prescriptive analysis processes which can help to uncover areas of ongoing waste and the increased agility that frequently comes as a resulting E2E visibility owing to the more comprehensive view of the entire value chain that it provides.
Take control of capacity management
As the number of trade routes and major shipping hubs continues increasing and expanding, it is crucial to remember that transport planning begins at home. A more global marketplace means that demand itself is more globalized, and thus more complex because not all orders are created geographically equal. For this reason, it is crucial to start from a position of control and understanding within the organization.
Specifically, one will need to determine what the maximum capacity levels are, whether that is the matter of finding a bottleneck within the production lines or calculating the total freight capacity. Additionally, there is a need to examine the ways that those level change based on customer location and other requirements. By gaining this level of insight into and control over one’s own operations, one can be sure that the capacity is not being overextended or underutilized, ensuring not to put oneself in a position where on-time deliveries become impossible.
Use “what-if” scenario
Let’s say that a successful implementation of advanced analytics workflows and increased visibility levels have achieved get a better handle on the entirety of the increasingly-global value chain. How else can one leverage this new-found visibility? ‘What-if” scenarios. Essentially, “what-if” scenarios enable to model of the entire supply chain digitally in order to simulate the effects of proposed changes or potential disruptions.
In earlier less-complex contexts this might have been the type of thing that planners could do manually – a simple manufacturing line might respond in fair ways to the introduction of a new machine or a new schedule – but the modern logistics landscape is too vast and varied for pen and paper estimation to cut it. The transport network is vast and far-reaching; how would it respond if removed a particular hub or cross deck? What about adding a warehouse? By making these determinations with more certainty, one can continue to stave off the effects of unexpected disruptions.