Logistics Scenario Planning: Creating Disruption-Proof Operations

Does an agile and disruption-proof supply chain sound too good to be true? Well, advanced digital technologies are making it possible.

Does your logistics business experience seasonality? Could weather disruptions impact a key customer? Will your customers need adjustments in transported capacity due to the launch of a new product?

Imagine the world of logistics as a grand puzzle, where smooth operations and adaptability are vital. Logistics professionals are constantly tackling new challenges that impact the rest of the supply chain, and the extent of knock-on effects can be complicated to predict. That’s where Logistics Scenario Planning comes in, a toolset that helps companies chart their course amidst uncertainties.

Logistics companies must have the resources available to confront potential supply chain disruptions head-on. So, how do these organizations plan for the unexpected and manage risk in a resilient, reliable, and flexible way?

Focus On Logistics Scenario Planning

Everything from demand and stock to transport, capacity, labor, and communication have a ripple effect across the supply chain. Therefore, logistics scenario planning with digital twin technology companies is essential. Digital twins create virtual representations of processes to assess options, risks, and likely consequences before future incidents occur. There are already great examples of adopting this technology for the benefit of the sector.

For example, rivers play a crucial role in the flow of goods across the EU. Yet, climate change causes heavy draughts that have left water levels so low that it is practically impossible for barges to carry essential exports like wheat, chemicals, and oil. 

Logistics scenario planning teams can use transactional data on goods and supplies flowing into and out of ports and airports. Planners can explore different configurations, such as changes to demand and usage, where to source new supply, transportation substitutes including rail and aircraft, and labor requirements. It then also becomes clear that the scenario planning process would benefit from automation — and then your team can proceed to build it with the help of Artificial Intelligence (AI). 

Organizations must leverage AI algorithms, to analyze historical, real-time, and external factors data to identify patterns and bottlenecks within the supply chain. With this data, digital twins can begin to detect, predict, and provide options for potential scenarios. 

Pay Attention to Data Cleansing

Data is our eyes for the future and the past. When we look at historical data through analytics systems, we can understand why events occurred, what impacted them, and how we can avoid them again. But the data must be correct and precise for AI and scenario planning to work.

Say a trucker knew the probability of each truck’s arrival time and that ten trucks would be late. This knowledge opens up opportunities to create solutions before problems arise. For instance, logistics professionals could look to source replacement inventory from a nearer location and replenish it with the late stock. In addition, they could reach out to other providers to organize forward freight and update customers and ports on potential delays.

The difficulty is that data comes in many forms, from numerical to audio to video to textual. Data teams must clean the data and convert it into standardized formats to cross-analyze patterns across the dataset. This includes: removing duplicates, standardizing capitalization, fixing errors, language translation, and handling missing values.

This way, they can access data from telematics to driver behavior to telephone updates, and formulate an optimal plan with their digital twin scenario tools.

“What-If” Scenario Simulations: A Business Case

As logistics networks become larger and more complex, it becomes essential to leverage logistics scenario planning. As an example, in order to achieve faster transit times for groupage shipments and improve vehicle utilization, DB Schenker Bulgaria has leveraged Transmetrics expertise to configure multiple network scenarios and run various ‘what-if’ simulations.

Using different growth projections for the demand and considering various network parameters, the AI-powered algorithms could measure the efficiency and resilience of numerous network setups. By comparing the scenarios, the project teams found the best way to adjust the network infrastructure and achieve the most optimal linehaul plan.

The abovementioned case is just the tip of the iceberg, and there are many more instances that could prove useful for logistics service providers:

• What if you need to handle the increased number of shipments due to Black Friday? With logistics scenario planning, organizations can forecast peaks in demand, and simulate the effect of increased throughput on their network to identify potential bottlenecks or opportunities to purchase more capacity in advance, hence saving costs.
• What if you add a new hub or shut down the existing one due to a strike or poor weather conditions? The scenario simulation tool can uncover the potential impact of such activities and help you allocate your resources in an efficient way before the disruption occurs. You can also simulate if a hub has limited capacity due to the building maintenance or construction, and assess how your operations will perform with just a fraction of the regular output for this location.
• What if you want to experiment with routes in order to find the most efficient one? Scenario planning tools can demonstrate the effect of taking the quickest route or adding stops along the way. By mixing different route scenarios, you can find a way to ease the load on busy hubs and keep the network flowing.
• What if you want to change your service levels? Currently, your business may deliver at 100% service level. However, the scenario simulation can uncover that tweaking it to 97% could save 1% on transport costs. It’s all about finding that sweet spot between perfection and savings.

If used correctly, logistics scenario planning in combination with other logistics technologies can be a game-changer. It can help your business anticipate, adapt, and excel in the ever-shifting environment of logistics.

But one should not forget, that such tools are data-hungry. They become increasingly trained and accurate when you tap into new data sources. Today, companies need to know about the size of pallets, spot rates, and transaction data to manage multi-order capacity.

To achieve disruption-proof operations, organizations must make their data reliable, leverage it to assess best and worst-case scenarios and focus on finding the optimal plan that delivers service excellence and saves costs. 

Ready to leverage logistics scenario planning? Get in touch.