Understand how to forecast your supply chain to improve your relationship with suppliers and ensure you book the right cargo amount to avoid unnecessary costs.

In this article, you will learn:

  • What is supply chain forecasting
  • Why supply chain forecasting is important
  • Different methods of supply chain forecasting
  • What makes supply chain forecasting difficult

What is supply chain forecasting?

Supply chain forecasting combines data from past supply chains with insights and understandings about demand to help you make the best decisions for your business — whether it’s stock inventory, cargo booking, budget planning, or expanding to new markets.

Analysing supply accounts involves looking at data about your suppliers to understand when you need to order products from them — whether they’re whole products or raw materials — to be assembled further down the supply chain.

Analysing demand is also vital to help you understand how much of your product your customers want during any given week, month, or quarter. This is affected by several factors that can be predictable, like seasons and holidays, or unforeseen, like global events and natural disasters. Often, such events can impact various transportation modes like ocean freight or inland transportation.

Why is supply chain forecasting important?

Supply chain forecasting can play a significant role in contributing to an efficient supply chain and a flourishing business:

  • Strategic planning: Businesses can be built or broken in the strategies they take around things like an expansion to new markets, budget planning, or risk assessment. Forecasting gives you the insights to make these decisions wisely, ensuring your suppliers can meet your demand.
  • Staying on top of inventory: If you understand the demand for your products in different markets, you can work more closely and easily with suppliers to maintain your inventory levels throughout the year. This keeps shortages to a minimum, making your customers happy and minimising warehouse fees without having to store unneeded stock.
  • Improved customer experience: Customer experience is set to define supply chains in the future. By predicting customer demand, you can manage your supply to ensure orders are fulfilled on time, and you’re never low on stock. The result is a sense of trust between your customers and your business.

Methods of supply chain forecasting

There are two predominant methods of producing supply chain forecasting: quantitative and qualitative.

Quantitative forecasting

It relies on historical data to predict future sales using complex algorithms and computer programs. In quantitative supply chain forecasting, you might encounter the following methods. Each has its benefits and downfalls and should be considered carefully to determine their best use:

  • Moving average forecasting is one of the simpler methods of quantitative forecasting based on historical averages. However, it treats all data equally and doesn’t consider that more recent information may be a better indicator of coming trends than, say, data from three or five years ago. This method doesn’t allow for seasonality or trends.
  • Exponential smoothing also considers historical data but emphasises recent data and accounting for seasonality. This makes it ideal for short-term forecasts.
  • Auto-regressive integrated moving average (ARIMA) is a method of forecasting known for being highly accurate but also very time-consuming and costly. It’s well-suited to forecasting up to 18 months or less.
  • Multiple Aggregation Prediction Algorithm (MAPA) is a newer method of quantitative supply chain forecasting specifically designed for seasonality, making it perfect for businesses producing seasonal items.

Qualitative forecasting

If the historical data is hard to find, for example, when launching a new product, you need a new approach. And that’s where qualitative supply chain forecasting comes in handy. It relies on the insights, expertise, and experience of industry experts alongside more detailed research:

  • Historical analogies predict sales by assuming that the sales of new products will mirror an existing product that you, or a competitor, produce. While it can work in the long term, it’s not advised for short-term forecasting.
  • Market research will be familiar to many businesses and is the process of researching, surveying, polling, or interviewing a specific demographic. It can sometimes be costly and time consuming.
  • Internal insights are a ground-up approach to forecasting, using the insights and opinions of experienced staff members to inform predictions. As you might expect, it is not known for high level accuracy but is an option when quantitative methods aren’t possible.

What is the best method of supply chain forecasting?

There is no one-size-fits-all approach to supply chain forecasting. And regardless of which you choose, you will never be 100 per cent accurate. At least some of the forecasting is based on assumptions, and there will always be unforeseen events that defy those assumptions — like a pandemic, for example!

While qualitative forecasting has its place in situations where historical data is unavailable or unreliable, it is the consensus that quantitative forecasting is the strongest method. It uses concrete information and statistical techniques, which removes the risk of bias while producing more precise and accurate results.

What makes supply chain forecasting difficult?

Supply chain forecasting opens up a world of opportunities for your business through the access it provides to insights on future demands, trends, and supply information. But several factors can disrupt the system:

  • Regulation changes and global events: Changes in regulations between nations and continents can often disrupt forecasting — as supply chains adapt to accommodate new laws and past data becomes a little less relevant. For example, in the COVID-19 pandemic, emergency laws were passed globally to close borders, stop travel and delay trade. The impact was far-reaching, with bottlenecks at borders and congestion at ports. Combined with Brexit, it’s easy to see how regulation changes can disrupt industries and supply chain forecasting.
  • Changing trends and consumer habits: While changing trends and habits are a constant in the world of supply chains, the unpredictability with which they change means they remain a threat to forecasting. For example, in 2020, as the world closed down, consumers went online and spent over $4.2 trillion worldwide. In 2021, it amounted to approximately $5.2 trillion. So, while online shopping has grown rapidly, the sudden shift forced many small businesses to adapt quickly to avoid stock shortages or delays.
  • Seasonality and supplier lead times: Not accounting for seasonal and peak periods in supply chain forecasting will easily throw your forecasting off course. These periods in the calendar often impact ocean freight and should be planned months in advance. Or you risk missing out on opportunities to capitalize on increased demand.

An important consideration when planning your supply chains is that different suppliers or manufacturers will have different lead times — not just based on the services they provide, but due to their own seasonal or holiday calendars. This makes building solid relationships with suppliers significant.

How you can stay up to date on all relevant supply chain news

Ready to brush up on something new? Maersk helps you stay on top of trends and manage your supply chains more effectively with our logistics solutions.

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