INDEX
- The Emergence of Digitization & Industry 4.0
- The Supply Chain at the Centre of the Digital Enterprise
- Expected Impact of Digital Transformation on the Cost
- The Relevance and Implementation Status of Technology Concepts
- Technology Solutions by Development Stage and Adoption
- Preliminary Considerations for Fourth Industrial Revolution-Driven Supply Chains
The Emergence of Digitization & Industry 4.0
Digitalization involves interconnectivity, automation, machine learning, and real-time data. It integrates physical operations with intelligent technologies and big data, forming a cohesive ecosystem for businesses and governments. This transformation is known as Industry 4.0.
The Supply Chain at the Centre of the Digital Enterprise
As technology becomes more affordable, labour cost differences across countries will matter less when deciding where to produce. Digital supply chains will be central to distributing digital products and managing workflows. This shift will reshape globalization, increasing the importance of regional and local trade while reducing reliance on intercontinental flows.
Expected Impact of Digital Transformation on the Cost
A wide range of these technologies is already affecting production systems and supply chains. When combined and connected, they create new opportunities to deliver value across many levels including individuals, society, industries, businesses, and the factory floor.
The Relevance and Implementation Status of Technology Concepts
Five key technologies, which are currently at different stages in terms of level of readiness and adoption across industry sectors, are expected to significantly impact supply chains, both individually and in combination:
- internet of things
- artificial intelligence
- advanced robotics
- enterprise wearables
- additive manufacturing
Connected devices ensure the availability of real-time data, enable the geographic distribution of operations and manufacturing, and result in improvements in operational efficiency, processing time and operating and management costs.
Technology Solutions by Development Stage and Adoption
As technology advances, shippers and providers can assess their transformation progress compared to the wider logistics sector to identify key capabilities and technologies. With many use cases available, it can be hard to know where to invest and how to capture value, especially with newer, less adopted solutions like digital freight procurement in transportation.
Technology use Cases Applied Across Supply Chains
End-to-end real-time supply chain visibility platform
Business problem
Lack of end-to-end (E2E) visibility across supply chain performance, to enable decision making
Solution
Installed end-to-end real-time supply chain management software for centralized inventory management & supplier and site performance monitoring.
Preliminary Considerations for Fourth Industrial Revolution-Driven Supply Chains
Supply chain performance:
To transform supply chains, a new level of supply chain visibility needs to be achieved. Fourth Industrial Revolution technologies, such as the internet of things and artificial intelligence, will prepare the ground for the necessary transformation.
New roles and capabilities:
In the context of current and future dynamics, the enhancement and change of roles and capabilities – such as the implementation – will define competitiveness and “compatibility” advantage in the Fourth Industrial Revolution. Along the supply chain, the roles of stakeholders are likely to change. Companies need to prepare for this development.
Ecosystem for skilling:
Shortage of talent and the right-skilling challenge will remain. These technologies but also new innovation and partnering models already require new competencies and skills – at all levels. A multi-stakeholder ecosystem for skilling is needed.
Neutral platforms:
The shaping of the Fourth Industrial Revolution is a co-creation effort that requires spaces for the exchange of ideas, information and experience to support the implementation of new roadmaps. These co-creation platforms have to be neutral and as much digital as traditional in nature.
Industry Examples
AI widespread adoption
Demand Forecasting
Use Case: Retailers and manufacturers use AI to anticipate demand, ensuring that they stock the right amount of inventory.
Inventory Management
Use Case: AI models can predict optimal inventory levels based on real-time demand, sales data, and market trends.
Supply Chain Risk Management
Use Case: AI monitors geopolitical events, weather patterns, and other variables that may disrupt the supply chain.
Route Optimization
Use Case: AI can help logistics companies determine optimal delivery routes to minimize delays and reduce fuel expenses.
Warehouse Automation
Use Case: AI-driven robots in warehouses streamline sorting, packing, and order picking, reducing operational costs.
Industry Examples
AI new adoptions
Supplier Relationship Management
Managing supplier relationships is critical to ensuring timely deliveries and high-quality materials. AI helps businesses evaluate supplier performance, track delivery reliability, and assess supplier risk. This allows companies to make data-driven decisions and maintain strong relationships with reliable suppliers.
- Use Case: AI analyzes data on supplier performance, enabling companies to select the best partners and manage supply risks.
- Example: Unilever uses AI to monitor supplier performance and track sustainability metrics, ensuring that suppliers meet environmental and ethical standards.
Industry Examples
AI new adoptions
Sustainability and Environmental Impact Tracking
AI helps organizations track and minimize their environmental impact by monitoring carbon emissions, fuel usage, and waste. AI-based analytics tools provide insights into how companies can optimize their supply chains to reduce their carbon footprint and support sustainability initiatives.
- Use Case: AI tools measure environmental impact, enabling companies to adjust their processes to reduce emissions.
- Example: Nestlé uses AI to track carbon emissions across its supply chain, allowing it to set reduction targets and meet sustainability goals.
Industry Examples
AI new adoptions
Pricing optimization
Pricing optimization today is not as easy as it used to be. The customer now has access to resources like online catalogs, specialized search tools, etc, to compare the prices of different products, which makes setting the optimal price a top priority for businesses.
Dynamic pricing:
By continuously monitoring factors like competitor pricing, customer behavior, and market conditions, intelligent algorithms can adjust prices in real time to capture the optimal price point.
Personalized pricing:
Machine learning models can identify distinct customer segments based on purchasing history, price sensitivity, and demographic data. Businesses can then determine the ideal pricing strategy for each segment and maximize revenue without alienating price-conscious buyers.
Promotional strategy optimization:
AI can simulate the impact of various promotional strategies and recommend the most effective discounts or bundle deals to drive sales and profitability. This goes beyond simple rules-based discounting, using advanced algorithms to predict the complex interplay between pricing, demand, and customer behavior.
Sustainability and Environmental Impact Tracking
We’re at a global inflection point. Technology is advancing faster than human capacity to adapt.
- We must reflect: Where is the human in the equation? What is the human’s unique value proposition in an AI- driven world?
Rate of change has never been so high
- Example of recent Google announce on payment form search point – where does this leave Amazon etc?
How the world sees AI
- East (Chines) see AI as infrastructure – 15 year game plan with all devices as data inputs
- West market short term thinking on AI as thinking tool.
Your job is not going to be taken by AI, but by someone using AI.
- Companies have a big role to play. Helping people grow – with technical skills, learning strategies, resilience, and foundational skills like critical thinking – is essential to keeping them relevant throughout their careers.