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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.

Companies are faced with the challenge of efficiently using huge amounts of data in the area of sustainability. Artificial intelligence helps to process this data, make well-founded decisions and make supply chains transparent. This blog shows how AI manages the flood of data and supports sustainability goals.

Commodity prices, such as those for oil, gas, or metals, play a central role in the global economy. Companies and investors who can rely on precise predictions are better equipped to make strategic decisions, minimize risks, and seize opportunities. However, forecasting these prices is no simple task—it requires taking into account numerous factors, including political events, environmental changes, and economic data.

Price used to be the most important criterion in procurement, but a product's carbon footprint (Product Carbon Footprint, PCF) is increasingly becoming a critical factor. Organisations must not only comply with ESG (Environmental, Social, Governance) guidelines, but also actively work to reduce their CO2 emissions. Procurement plays a central role in this: on the one hand, to build sustainable supplier relationships and, on the other, to ensure transparency along the entire supply chain.

Essen, October 17, 2024 – pacemaker and Stanford University are now collaborating. Through a partnership with the Institute for Computational & Mathematical Engineering (ICME), the AI division of thyssenkrupp Materials Services will gain access to the latest advancements in artificial intelligence, which will be integrated into pacemaker’s solutions.

International trade is facing a new challenge. With the introduction of the Carbon Border Adjustment Mechanism (CBAM) by the European Union, an important instrument in global trade and climate policy is being established. The CBAM is intended to protect the competitiveness of European companies by charging imports with a CO₂ price based on the emissions generated during their production. This measure aims to prevent carbon leakage — the phenomenon in which companies relocate their production to countries with less stringent climate protection requirements in order to save costs.

Welcome to our new series “Employee Spotlight”! Today we would like to introduce you to Thomas, one of our talented software engineers at pacemaker.ai. In this interview, Thomas gives us exciting insights into his background, work experiences and his view of the corporate culture at pacemaker.ai. For those of you who are considering joining our team, this conversation is a great opportunity to get to know one of our colleagues better and learn more about our company's values and working methods. Let's find out more about the people behind our success.

Discover why terms like CBAM, ESG, CSRD, EU Taxonomy, and GHG Protocol are becoming increasingly important and how you can keep track amidst this flood of requirements.

Welcome to our Employee Spotlight series! Today, we’re thrilled to introduce you to Kathrin, our People & Growth Manager at pacemaker. Get to know her journey, experiences, and insights in the interview below. We want to provide a closer look at the individuals who drive our success. For potential applicants, this is an opportunity to get to know the person who might be talking to you first and to gain insights into our company culture, values, and what we look for in new team members.

There is money at stake. A lot of money. The Boston Consulting Group (Fig. 1) estimates the potential overall effect of the use of AI on sustainability at between 1.3 and 2.6 trillion(!) US dollars. Companies will achieve this effect through additional revenue and cost savings through AI by 2030.

"Who Cares Wins" – this was the title of the first ESG report in 2004. 20 years later, this thesis is still proving itself. More than ever. In the highly competitive global economy, adopting sustainable practices in the supply chain is not just a moral choice, but a strategic necessity. 

Artificial intelligence is becoming a powerful ally in the urgent fight against climate change. That's because it offers innovative solutions to drive decarbonisation and create a more sustainable future in all sectors.

In today's dynamic business world, demand forecasting is an indispensable tool that helps companies make well-founded decisions and secure competitive advantages. With the advent of AI and advanced analytical tools, predictive accuracy has significantly improved, resulting in more efficient processes and increased profitability.

Supply chain demand management combines two key strategies: demand planning and demand forecasting. Demand planning is a strategic approach in which inventory and production are aligned with anticipated market needs. It requires not only foresight, but also a coordinated approach across different business functions.

Terminology such as demand forecasting, bullwhips and AI-powered demand planning are part of the vocabulary of modern supply chain management.

Global supply chains are one of the most exciting and challenging issues of our time. Whether it is Covid, the Ukraine war or most recently the earthquake in Turkey, supply chain disruptions can have serious and long-lasting impacts on the economy, society and supply chain management (SCM). This shows once again how complex and susceptible SCM is to disruption - be it due to changes in consumer demand, unpredictable events or social and economic crises.

Inaccurate data entails problems and costs. We explain what data quality is and how good your data should be.

Demand forecasting helps companies predict future demand for products or services.

We support a supermarket chain in making its supply chain fit. Pacemaker Forecast makes it possible to forecast the sales volume of over 25,000 products in wholesale and retail branches of a supermarket chain more precisely.

Data alone does not create added value. It depends on the right use case.

Companies are increasingly using data science and data analytics solutions to use the sea of data to benefit their own business.

The data science project is defined. The proof of concept successfully implemented. And now? Unfortunately, this is often the end. In fact, operationalizing data science projects, i.e. successfully turning them into productive business operations, is one of the biggest challenges.

The rapidly increasing importance of online trade presents logistics service providers with increasing challenges in terms of warehouse and delivery planning.

In recent years, artificial intelligence (AI) has developed from a buzzword par excellence to a well-established term in many industries.

Customers want to receive the right product via the right channel in the right quantity and at the right time.

The rapidly increasing importance of online trade presents logistics service providers with increasing challenges in terms of warehouse and delivery planning.

More and more customers are shopping online. More and more items are being returned.

According to the International Data Corporation (IDC), the global data volume is expected to grow to 175 zettabytes by 2025 — an unimaginably large number with 21 zeros.

Data science projects are complex processes that require a well-coordinated team. This is the perfect way to set up your team.

It has never been more difficult than today to attract, inspire and retain customers. Customers in the B2C as well as B2B sectors are increasingly demanding an individual approach and a shopping experience tailored to their needs.

Supermarket chains make supply chains fit with us. Pacemaker Forecast makes it possible to forecast the sales volume of over 25,000 products in wholesale and retail branches of a supermarket chain more precisely.

The Corporate Sustainability Reporting Directive (CSRD) introduces new reporting requirements for companies in the EU and promotes transparency in terms of sustainability. This article provides an overview of the most important requirements, affected companies and the timetable for implementation.