What makes a top trend?
In our evaluation, we’ve looked at trends in terms of timeliness and impact. Timeliness tells us when to expect the full impact of a trend. Impact tells us how much the trend is expected to affect supply chain strategy and operations.
In this article, take a closer look at the top 5 most timely trends in logistics and supply chain management as we begin 2024.
![[Translate to US – English:] Top 5 most timely trends for supply chain management, where 0 signifies a maximum impact in the far future, and 5 represents that a trend is urgent right now](/fileadmin/_processed_/a/c/csm_4flow-top-five-timely_6ad19b0e5e.png "[Translate to US – English:] Top 5 most timely trends for supply chain management, where 0 signifies a maximum impact in the far future, and 5 represents that a trend is urgent right now")
Most timely trends for logistics and supply chain management
1. E-commerce logistics
Changes in consumer behavior and rising market volumes pose a challenge to existing logistics infrastructure. The Covid-19 pandemic accelerated the transition from brick and mortar towards digital sales channels, and the e-commerce market is expected to keep growing at an annual revenue growth rate of ~11%.
Logistics service providers need to keep up with these changing demands – dynamic delivery across international borders, fulfilment, and return options require collaboration and technological integration among all stakeholders in the supply chain.
As marketing and quick order fulfilment become key factors for success, e-commerce businesses need to reevaluate their marketing plans and logistics services.
Retailers need to define their strategy and decide whether to engage in competition with quick commerce or stick to brick and mortar and accept possible losses of sales. Supply chain must follow suit.
2. Cyber risk mitigation
Influenced by the broad range of benefits AI offers, some users tend to neglect the associated risks. Chatbots facilitate the creation of credible phishing messages, including fake video recordings. And a Forsa survey revealed that 62% of logistics businesses have deficiencies regarding basic IT security.
Decision makers need to ask themselves: What happens to the data fed into AI algorithms? Are AI-generated results reliable? Who is responsible for possible errors? Can hackers use AI to harm my business operations?
Businesses should make use of the potential of AI while considering the associated risks. Cross-check AI-generated solutions. Train employees regarding the hazards of AI phishing. Evaluate how data is processed by external companies and set up rules to prevent leaking confidential data.
3. Supply chain visibility
Supply chain visibility refers to a business’s ability to both understand the structure of its own end-to-end supply chain and track goods or products in transit. Visibility enables shippers to improve customer service and cost control by managing inventory in motion, providing proactive status updates, limiting disruptions and mitigating risk.
According to a 2022 survey by McKinsey, supply chain leaders who increased their end-to-end supply chain visibility were twice as likely to report having no challenges from supply chain disruptions compared to those with less visibility.
All businesses and supply chain segments can benefit from increased transparency. Given the high degree of uncertainty in the logistics market, visibility becomes a key factor in ensuring supply chain robustness and resilience.
4. Connectivity
Connectivity involves using digital means to reduce the cost of communication and provide information. Cloud services make information and functionality available from everywhere, while also facilitating management and scalability of IT infrastructure. Third-party APIs can be utilized to receive essential information in a standardized format and to enable standardized data exchange in fleets of autonomous vehicles.
Recent disruptions have highlighted the value of reliable information on shipment statuses and product availability. Evaluate which APIs can support you in acquiring the information you need.
On the other hand, developments in AI have made data sovereignty questions more complex – investigate to which degree data can safely be provided to cloud services.
5. AI analytics and predictions
AI analytics and predictions can be used where traditional calculation methods reach their limits. Methods like machine learning and deep learning can discover patterns and correlations in large data sets that are too complex for humans to see. AI-based forecasting or big data analytics can unlock new potential for optimization.
According to a McKinsey study, AI forecasts in supply chain management can reduce errors by 20-50%.
Businesses that have data science competence should evaluate where these methods can be used to improve their results or unlock new use cases.
Questions or comments about these trends? Get in touch with us.
Authors
Wendelin Gross
Head of
4flow research
Gero Holzheid
Supply Chain Scientist
4flow research