Optimised supply chains – the influence of accurate forecasting

Supply chains are among the most exciting and complex problems of our time. Why? There are simply too many factors and too many uncertainties involved. The VUCA world ‘at its best’, so to speak. After the extremely expensive pandemic, Houthi militias are currently ensuring that numerous ships are diverted around the Horn of Africa (‘The Cape of Good Hope’, see Fig. 1) instead of passing through the Suez Canal. Tesla has had to temporarily halt production in Brandenburg as a result, and shipments from Asia to Europe are now set to double in price.

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That is why accurate forecasts are an important factor for the profitability and success of supply chains in our globalised and highly complex economic world. Companies use their resources highly efficiently and are also able to react quickly to changes in demand, external disruptions such as natural disasters or political instability. Precision in forecasting is the basis for this adaptability.

(Fig. 1: Suez Canal at risk: a bottleneck for the global economy, Lookout/YouTube)

Using accurate forecasts, organisations can better manage their inventory levels, avoid overproduction and reduce bottlenecks. Forecasting accuracy plays a fundamental role, particularly in the area of inventory management. Companies that use advanced analytics and artificial intelligence to make accurate predictions can reduce both their costs and the potential for customer dissatisfaction due to higher prices or availability.

An important issue is the volatility of demand. Thanks to precise forecasting models, it is possible to respond better to these fluctuations. This leads to a more efficient use of resources, which on the one hand improves internal processes and on the other hand also helps to reduce the environmental impact – an increasingly important factor in view of global sustainability goals.

Furthermore, accurate forecasts help to minimise risk by enabling the early identification of potential problems. For example, predictive models enable companies to identify shortages of raw materials or supply bottlenecks at an early stage – and take appropriate action to mitigate these risks.

Accurate forecasting is therefore a key component for a number of important current concerns: sustainability, customer satisfaction, flexibility, resilience, risk minimisation and, last but not least, competitiveness. And that's what we're going to look at in detail now.

What is forecasting accuracy exactly?

Forecasting accuracy describes the degree of correlation between the forecast and the actual results within a specified period. In other words, how well a prediction matches what actually happened. And as we now know, the more accurate a forecast, the better organisations can manage their resources and reduce operational costs.

Various methods and technologies are used to achieve a high level of forecasting accuracy. Traditionally, forecasts are based on historical data and statistical models, such as time series analysis or moving averages. These models analyse historical patterns and trends to predict future developments. Qualitative methods such as market research in the form of customer feedback and focus groups or expert opinions (Delphi method) are also used. We have dealt with forecasts and models in detail in our last article ‘A comparison of demand forecasting methods’.

However, artificial intelligence and big data analytics have significantly improved forecasting accuracy. Machine learning (ML) makes it possible to process large amounts of data in real time, identifying complex patterns that cannot be identified using traditional methods. Algorithms continuously learn (the idea of ML) from new data and adapt to dynamic market conditions, making predictions more accurate.

Another important factor for forecasting accuracy is collaboration in the supply chain. This starts with the exchange of information between different internal departments – such as sales, marketing and logistics – and is extended to include close coordination with suppliers. This enables companies to gain a holistic view of their demand trends. Methods such as Collaborative Planning, Forecasting and Replenishment (CPFR) support this process and also help to improve the accuracy of forecasts.

Inventory management and sustainability

Let's look at inventory management next – also in terms of sustainability. Inventory management is a central aspect of every supply chain and plays a decisive role in a company's use of resources and efficiency. Here are some common inventory management methods:

  1. Just-in-time (JIT): Orders are placed only when needed to minimise storage costs.
  2. Economic Order Quantity (EOQ): Optimal order quantity to minimise order and storage costs.
  3. ABC analysis: Inventory is categorised by value into A, B and C to manage important items in a targeted manner.
  4. Safety stock: Additional buffer for unexpected fluctuations in demand or delivery time.

High forecasting accuracy significantly optimises inventory management by precisely adjusting stock levels to actual demand. This eliminates excess inventory and the costs that go with it, while ensuring the availability of goods.

Furthermore, accurate forecasts help to optimise the amount of raw materials and products in the warehouse. Companies can calculate exactly how much stock they actually need, for example, to prevent bottlenecks. This improved alignment of supply and demand helps to avoid excess inventory while reducing operating costs.

And that contributes positively to sustainability. In addition to warehousing, more accurate predictions lead to a more efficient use of resources – only the required quantities are produced and stored. This prevents overproduction and avoids unnecessary waste, which in turn leads to a reduction in CO₂ emissions and greater conservation of resources. And the latter is particularly important for the energy sector. The World Economic Forum (WEF) has identified optimising our energy consumption as a ‘quick win’ – according to them, collectively optimising energy use contributes about 55% of the solution to achieving net zero by 2050.

The world therefore needs these sustainable supply chains, which, thanks to precise forecasts, minimise the ecological impact of overproduction and unnecessary transport – because pressure is coming from all sides: governments, consumers, investors and the environment itself (see Fig. 2).

(Fig. 2: External pressure is forcing companies to prioritise environmental sustainability, BCG)

In addition, optimised inventory management reduces energy consumption in warehouses and decreases the need for logistics and transport, further reducing the environmental footprint. When goods are stored in the right quantities in strategically favourable locations, transport distances are shortened, ensuring energy and fuel savings. Sustainability is a broad topic. To find out more, read our articles ‘Sustainability as Strategy: The New Frontier in Supply Chain Management’ and ‘Decarbonisation meets artificial intelligence’.

Effects on demand planning

Accurate forecasts also play an important role in demand planning. The higher the forecasting accuracy, the better the customers' needs are anticipated.

A major advantage is the reduction of out-of-stocks and overstocks, as mentioned earlier. Companies can adjust their stock levels to meet projected demand and avoid both bottlenecks and redundant stock. Overall, customer satisfaction is also improved because products are available when needed.

Speaking of flexibility: accurate forecasts also enable early adaptation to market changes. Market trends, seasonal fluctuations or unexpected external influences such as economic changes can be identified at an early stage by analysing real-time data. AI and ML identify these patterns, enabling companies to react quickly to adapt their production and delivery strategies. As mentioned at the beginning, this flexibility is particularly important in highly volatile markets.

Here, too, it is important to integrate external data sources into demand planning. In addition to internal information from marketing, sales and point-of-sale data, open order data and inventory data, data from social networks or weather data can also be used to create a comprehensive picture of future demand. This technique is called ‘demand sensing’ and again improves prediction accuracy.

Cost reduction and resource optimisation

Most of the positive effects of accurate forecasting mentioned here help to reduce costs and optimise the use of resources in modern supply chains. Companies that make accurate forecasts for demand, inventory and supply can design their operations more efficiently and achieve significant cost savings.

A central aspect of cost reduction is efficient warehousing by minimising overstock and stockouts. This lowers warehousing costs and simultaneously reduces the risk of obsolete or unused stock. Lower stock levels therefore mean less capital tied up and at the same time fewer resources are needed to manage the stock. Resource optimisation also has a positive impact on costs incurred or, in this case, not incurred. Furthermore: minimisation of overproduction, waste and energy consumption. Let us not forget – collective optimisation of energy consumption is more than half the battle for net zero by 2050. In the context of sustainability, companies are significantly improving their environmental performance.

Another advantage of accurate forecasting is the improvement in logistics efficiency, where companies optimise their transport routes and times. Fewer rush orders and better route planning help to reduce transport costs and CO₂ emissions. These are also positive aspects in terms of operating costs and environmental goals.

How to boost your supply chain efficiency

Would you like to optimise your supply chains now? A targeted strategy is a rule of three: accurate forecasting, optimised processes and innovative technologies. Here are five concrete steps to maximise the efficiency of your supply chain:

1. Use artificial intelligence (AI) and automation

The first step is to integrate AI-based tools and automation technologies into your processes. AI helps to improve forecasts by analysing large amounts of data in real time and optimising predictions. Automation helps you to be more efficient by replacing manual tasks in warehousing, inventory tracking and transport, while also reducing the potential for errors.

2. Improve collaboration within the supply chain

Increase efficiency by working closely with your partners and suppliers. Introducing Collaborative Planning, Forecasting & Replenishment could be a first step. Here, forecasts are shared between all parties. This collaboration leads to better alignment of stocks and a reduction in bottlenecks or overproduction.

3. Optimise your inventory strategies

Another key lever for increasing efficiency is optimising inventory management. With accurate forecasting, you can avoid overstocking and stockouts and precisely align inventory with demand. To do this, implement a just-in-time inventory model to reduce redundant storage costs and capital tie-up.

4. Digitise your supply chain

And we're not talking about Excel sheets when it comes to digitising the supply chain. By using cloud-based platforms, companies can increase transparency and identify bottlenecks more quickly. Digitalisation means having information in real time and being able to react dynamically to market changes in order to reduce delays in production and delivery. Or even prevent them altogether.

5. Improve logistics with route optimisation

Efficient logistics are essential for a cost-effective and sustainable supply chain. Use route optimisation software to shorten transport distances and reduce fuel consumption. Good route planning reduces costs and CO₂ emissions and contributes to sustainability in both the short and long term.

By combining these steps, you can make your supply chains more efficient, flexible and resilient to change and disruption.

Bottom line: sustainable and effective supply chains of the future

Precise forecasts based on the latest technology are the future of supply chains. In addition to economic efficiency, we must also achieve ecological sustainability. And that pays off. Not only through significant cost reduction, but also through flexibility and resilience to volatile market changes and global disruptions.

In view of global sustainability goals, regulations and laws (LkSG, CBAM, CSRD, etc.), accurate forecasting is the way forward. Companies that implement these technologies and strategies at an early stage establish a higher competitive strength and develop a strong corporate brand as pioneers in the field of sustainable business. And they make their contribution to global climate protection.

To overcome these challenges, we at Pacemaker have created our powerful Demand Forecasting Tool. Explore how it can elevate your business—book a non-binding initial consultation and experience its capabilities firsthand: Book your appointment now!

If you are interested in AI-supported supply chain solutions, book a free initial consultation: Make an appointment now!

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