At the beginning of the new year, a battle against the “epidemic” has become the theme of everyone.
Personnel from various fronts such as medical and health care, transportation, and education services sounded the rallying call at the same time. Hundreds of millions of ordinary people in China fully cooperated with self-isolation to ensure the health, stability and harmony of the rear.
Behind this “steady happiness” in the face of fierce battle and danger, is the all-round guarantee of medical supplies, living supplies and price stability that we have devoted all of our efforts to the whole country. What supports all this is a strong supply chain behind it.
In the face of this “supply chain exam” in a race against time, many industries and enterprises must answer the following questions:
How to quickly resume production, repair the supply chain, and reduce the major impact of sudden crises?
How to more accurately predict potential problems and prepare for possible future emergencies?
How to deeply understand customer needs, quickly respond to market changes, and turn crises into opportunities?
Transforming and innovating existing supply chains is a general trend. Supply chain executives at top companies are committed to developing strategies for digitizing supply chain processes. When digital operation practices are combined with artificial intelligence, the supply chain is trained, which in turn enhances human decision-making capabilities, realizes intelligent upgrades, and transforms into a cognitive supply chain.
The IBM Institute for Business Value released a global research report “Welcome to the Cognitive Supply Chain”, interviewing more than 1,600 Chief Operating Officers (COOs), as well as supply chain, product development, procurement and manufacturing executives, and digging deep into the cognitive supply chain Its capabilities, advantages and expectations can realize value, in order to help enterprises build a complete and efficient supply chain system and build a platform for whole ecology and whole chain collaboration.
Supply chain executives surveyed at more than 50% of outperforming companies
Say they will focus on investing in cognitive computing/AI or cloud computing in the next three years
86% of surveyed supply chain executives at outperforming companies
Indicates that cognitive computing/AI will transform their demand planning and forecasting capabilities
Manufacturing executives at 92% of outperforming companies
Indicates that cognitive computing/AI will improve their performance in production planning
Supply chain and artificial intelligence are a natural match
COOs are pinning their hopes on AI to solve many end-to-end supply chain process challenges, and outperformers are investing more heavily in AI. Artificial intelligence has become an essential element in the innovation and transformation of the supply chain of cognitive enterprises. They are actively reshaping business models, strategies and technical capabilities to apply AI to their products and daily operations. The most common application scenarios are for material quality, preventive maintenance and risk management from supply to production to customer supply.
In sales and operations planning, AI is applied to manage demand fluctuations, supply constraints, production scheduling, and dynamic distribution issues, enhancing human interaction by allocating resources, dispatching people, and scheduling processes. In addition, alternative courses of action can be suggested for unforeseen events and transport disruptions. In manufacturing, cobots equipped with artificial intelligence software can “see” their work environment and move around cooperating humans in a safe manner during production.
How Businesses Can Use Cognitive Computing and AI to Solve Supply Chain Challenges
Material Quality and Risk Management
54%
twenty four%
Sales and Operations Planning
51%
39%
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Financially outperforming companies
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Three Future Application Trends of Cognitive Supply Chain
01
Innovative product development
95% of outperforming companies see AI as a core element of their innovation success.
How to quickly and accurately capture market demand is a problem that every product development executive is thinking about. Outperforming companies are trying to embed AI into their products and operations to support product development, market analysis, and product manufacturing. When used to detect demand signals, AI can help companies determine changing demand behavior, optimize inventory levels and replenishment plans, and support product lifecycle management that enables continuous looping.
Product development challenges, priorities, planned investments
challenge
?
lack of engineering skills
?
Insufficient competitive analysis
?
Energy and environmental monitoring is expensive
priority task
?
cloud computing
?
Internet of Things
?
Drone/Robot
planned investment
?
Safety and Regulatory
?
energy management
?
Customer Experience
02
Smart Procurement
40% of CPOs expect AI to bring more value in risk mitigation, expense analysis, global logistics and distribution.
Procurement challenges, priorities, planned investments
challenge
?
Integrate with suppliers
?
Risk Mitigation
?
Global Sourcing
priority task
?
Regulation and Sustainability
?
Global Supply Chain Network
?
Internet of Things
planned investment
?
Inventory and Distribution Control
?
Security and Surveillance
?
Supply Chain Management
03
Intelligent automated manufacturing
Among the automation technologies adopted by outperforming companies, digital manufacturing ranks third after IoT and location technologies.
Manufacturing executives are actively adopting a new generation of automation innovations, working hand in hand with their product development colleagues to bring innovative products to market and drive growth and profitability. They quickly implement fundamental IoT and cloud technologies, and make heavy use of artificial intelligence to make production decisions in real time.
Manufacturing challenges, priorities, planned investments
challenge
?
skills shortage
?
Governance and Traceability
?
product development innovation
priority task
?
cloud computing
?
3D printing
?
Internet of Things
planned investment
?
Analytics and Cloud Computing
?
Robots and the Internet of Things
?
Cognitive Computing/Artificial Intelligence
Artificial intelligence is the support for the development of automation technology and digital operations in the future. When combined with a more powerful IoT ecosystem, artificial intelligence can learn from other connected devices, improve the management level of each link of the supply chain, and achieve proactive forecasting Responsiveness to help companies reduce costs, improve operational efficiency and innovation.
Cognitive Supply Chain “Three Steps” Strategic Deployment
As early as ten years ago, the IBM Institute for Business Value predicted that the future smart supply chain will have the following characteristics:
IoT. Information will increasingly be machine-generated, inventories will be automatically counted, containers will self-detect their contents, and errors will be reported automatically.
interconnected. The entire supply chain will be integrated, not only including customers, suppliers and IT systems in general, but also the components, products and other smart tools used to monitor the supply chain.
Intelligent. Advanced analytics and modeling techniques will help decision makers better analyze extremely complex and volatile risks and constraints to evaluate alternatives, and even automate decision making to improve responsiveness.
In just ten years, our prophecy has come true. Now, we are entering the next stage of our journey towards a cognitive supply chain.
To do this, we must develop a strategic plan, execute the plan against the roadmap, and realize value. Working with companies across the globe that have successfully achieved digital transformation, and surveying and researching their paths to change, we have identified three courses of action:
01
Develop a clear strategic vision and roadmap
Integrate business strategy with target operating model and ecosystem strategy, develop a clear strategic vision and plan, and follow a transformation roadmap. Leverage agile development methodologies to create prototypes based on cognitive supply chain use cases. Continue to build and deploy IoT products and operational control devices powered by enterprise cloud applications for real-time insights. Develop a scorecard to monitor the implementation of the prototype.
02
Get a comprehensive view of enterprise data and activate AI
Data is the core competitiveness of artificial intelligence. If artificial intelligence is likened to a racing car, data is the fuel that drives the racing car. Only by fully mastering their own data can companies fully leverage AI in the supply chain to maximize value, solve operational problems identified in use cases, and improve response speed, delivery, and product quality.
Further reading:
Six Key Strategies for Digital Winners—The Power of an AI-Driven Operating Model→
AI can extract the most value from datasets in the following four areas
1. Supply Chain Management
?
customer communication
?
Shipping methods, routes and rates
?
Competitive Pricing and News
?
Weather/Storm Disaster Data
?
Geopolitical Data
2. Product Development
?
Previous Product Analysis
?
Customer Generated Data
?
Industry and Open Source Surveys
?
social media data
?
Patent and Product Information
3. Procurement
?
Global Inventory
?
Purchasing Process
?
cost analysis
?
Supplier Evaluation
?
contract
4. Manufacturing
?
Production arrangements
?
machine monitoring
?
Inventory and Material Costs
?
Customer order management
?
Machine Repair History
03
Develop AI skills in employees
Businesses and institutions will need employees with digital problem-solving skills, increased levels of performance and innovation to drive growth, growth and success in a competitive marketplace. Basic computing techniques and a background in mathematics form the basis of most artificial intelligence programs. Also, it is important to understand the difference between data analysis and machine learning engineering.
The emergence of sudden crises is like a mirror, allowing us to see our own shortcomings. More and more businesses will realize the potential of artificial intelligence and the importance of enabling smarter business decisions.
Nietzsche said: What doesn’t kill you makes you stronger.
When the epidemic disappears and all industries recover, the development of the supply chain will usher in historic innovations and great changes!
are you ready?
