You might’ve heard the term demand forecasting – a process used across multiple business areas to make estimations based on past and present data, depending on your goal. Pretty simple, right?
But what if I told you there's much more to demand forecasting in logistics than meets the eye?
In today’s article, we’ll clarify the following:
- What demand forecasting is in logistics
- How it works
- The challenges it faces
- The importance of demand forecasting
- Popular demand forecasting methods
- And ways to implement it
What is Demand Forecasting in Logistics?
Demand forecasting in logistics refers to predicting future demand for goods, storage, transportation, and services within the supply chain. It involves analyzing historical data about orders, delivery, rates, and customers during different periods, attaching market trends and other periodic factors to make informed projections about future growth or decreasing demand.
In the logistics industry, demand forecasting can be applied at various stages of the supply chain, including the collection, distribution, and delivery of goods. It’s essential for logistics managers, as it helps them optimize their operations and make informed decisions about their resources to internal teams and clients.
Accurate demand forecasting is crucial for businesses in the transportation industry, as it allows them to plan for future shipping and capacity needs and optimize their operations. It also helps them identify potential bottlenecks and mitigate disruptions to the supply chain – avoiding urgent switches of carriers, delays, and overpriced rates.
For example, a trucking company can use demand forecasting to predict the number of shipments it will receive from shippers and freight forwarders in the coming months and plan its capacity accordingly. This might involve leasing more trucks, preparing their vehicles for special cargo, or hiring more drivers if the forecast predicts an increase in demand. Without such preparation, this company would have to say no to new business opportunities.
How does Demand Forecasting work?
Demand forecasting, in its most perfect form, combines quantitative and qualitative historical information and gives insights based on all the available different forms of data.
Qualitative data can be gathered from various sources like market research reports, economic trends, news, and freight rates of the company and competitors. Internally collected data, such as customer reviews and preferences, also help create the big picture. Quantitative data is collected internally from sales during normal and peak periods, web and search analytics, etc.
How Demand Forecasting can help with Demand Planning
Many factors continuously affect market prices and freight rates. These are the challenges demand forecasting can solve:
- Collecting and analyzing various freight and economic data to accurately estimate load volumes and capacity;
- Creating models to estimate them across multiple transportation modes (road, ocean, rails, air);
- Identifying seasonal events that can increase loads or disruptions that can change it across different regions;
- Monitoring weather and news that can cause disruptions in the chain;
- Getting input on how much capacity is being used and what can be optimized;
- Analyzing opportunities where it’s better to use spot over contract rates or vice versa to secure to avoid bad investments.
Demand Forecasting Methods
Out of several methods of demand forecasting, some are:
Macro forecasting: Huge cultural shifts are considered for global business opportunities – and increased demands.
Short-term forecasting: Sales events are taken into consideration that might cause price hikes.
Long-term forecasting: Year-long analysis creates a robust picture of the change in demand due to expansions.
Implementing Demand Forecasting
Upgrade your S&OP
Upgrade your S&OP (sales and operations planning) beyond the spreadsheet. Low-visibility environments like Excel sheets limit your means, due to the complex amount of information needed for a efficiente demand forecasting.
Besides the difficulty, you and your team are going to spend a good part of the day receiving quote and capacity requests and trying to fit them into the spreeadhet, when you could be reaching for new business with detailed and updated rates and service opportunity.
Better data access
63% of forecasters list a lack of data visibility when planning demands. Digitalizing and ditching the spreadsheet is the first step for optimizing your transport planning process, but to guarantee the best decisions:
- Identify the specific areas where data visibility is an issue. From there, you can take measures to address them;
- Integrating better software suites can make your systems more agile and flexible;
- Changing integration settings or access control within existing tracking software;
- Establish a single centralized system that brings data from everywhere else frequently enough to be considered definitive.
Your forecasts improve when you work with higher-quality and updated data – not just more data.
Use Industry 4.0 Technologies
As we enter the future, incorporate cutting-edge technology to stay ahead of your competitors.
- IoT devices on the factory floor
- Cloud-based planning modules
- RFID chips in shipping containers
And so on can help you leverage data more easily. This data visibility and real-time integration better augment your forecasts. You can get live snapshots of your demands as a bonus.
Conclusion
Logistics and transport demand forecasting may seem like an advanced process, but it’s actually crucial to bring effiency and growth to your transport planning team. Thought it’s not something that can be simply implemented from one day to the other, your entire operation will benefit from it.
If you’re still not sure and want to know more before starting, check this article about the risks of the lack of supply chain visibility.
