Professionals associated with logistics and supply chain are always on their heels to shape the operational chain innovatively that address the challenges more efficiently and minimizes the risk that caused otherwise. When the professionals hunt for new possibilities, technology is always there for help! Although the concept of Artificial Intelligence is six decades old, it is well on its course to take over the lives of people slowly by making it easy and efficient.
It is a common misconception that AI is a high-end technology and it may rule the lives of people and various processes in future years, allow me to say, you’re wrong! I am sure, most of us are ardent lovers of Apple iPhone and the most favorite aspect is interacting with the talking assistant “Siri”, it is the best example of Artificial Intelligence. Nevertheless, the AI is not only limited for iPhones, it had spread its wings to stock trading to medical diagnosis and to data management. AI has already become a part of our daily lives and it is not a surprising fact that it will play a key role in the international supply chain, corroborating businesses to solve various contemporary problems.
Businesses too, these days, undergoing digitization rapidly. Most of the businesses take interest in integrating AI into various processes as it is capable of performing various tasks efficiently within a short span. And use of the AI is not just limited for corporate, but also seen in various industries.
According to the survey conducted by the Accenture, which includes 11 countries and 12 industries, 70% of the corporate executives said that they are willing to invest in artificial intelligence to optimize their business operations. As per Tractica reports, investments in AI will increase from $202.5 million to $11.1 billion by 2024.
Artificial Intelligence in Supply Chain
According to the Accenture digital operations survey, organizations are rapidly digitizing their supply chain to distinguish and drive revenue growth. The report also says that 85% of businesses integrate AI in their supply chain by next year.
The main objective behind integrating AI is that the supply chains generates colossal data and artificial intelligence helps organization to analyze this data, understand different variables and anticipate future scenarios. Thus, implementing AI is completely justified as it plays a vital role in optimizing business process and establishes agile supply chain.
Assimilating Artificial Intelligence (AI) in Supply Chain eventually results in redefining an ecosystem where supply-chain link themselves to generate impeccable flow of products and information end-to-end.
The Fusion Of AI In SCM
Artificial Intelligence is always used to solve complex problems. However, since its inception, it is not completely exploited to search information and utilize its complete potential for the benefit of SCM. Nevertheless, the sub-disciplines of artificial intelligence such as GA’s and expert systems are employed to address the complex issues of Supply Chain Management involving inventory management, location planning, purchasing, freight consolidation and routing or scheduling problems.
Further, in this blog, let us outline the significant areas of supply chain management that have been explored for AI, identify the specific sub-disciplines and assess their involvement in supply chain decision-making process.
Inventory control and planning
The inventory in supply chain represents the idle resources that are essential to maintain excellent customer service. Nonetheless, it is a known fact that maintaining inventory incurs substantial costs. According to the survey conducted by the Timme and Williams-Timme, maintaining a single unit of inventory may costs approximately 15% to 35% of the product value. Thus, the organization’s success in the highly competitive market often hinders its ability to control and plan its inventory efficiently.
Aforesaid challenges can be successfully addressed by accessing the real-time information about the customer demands, size and type of the inventory and the estimated time to fulfill customer orders. Since, this kind of information is extremely difficult to estimate, predict and obtain from reliable resources; integration of AI has become essential to optimize this network and reduce the control and planning costs substantially.
The sub-discipline of artificial intelligence, which is expert system offers a promising approach to control and plan inventory management efficiently. The Expert System (ES) is capable of capturing the inventory patterns throughout the whole supply chain at all layers, in detail. Capturing such complex data enables human experts to analyze the amassed data to estimate the desirable level of inventory at each selling point without causing a bullwhip effect.
For instance, the ES is integrated into the Material Requirement Planning System (MRPS) where the data bases can be stored including historic master production schedules, material bills and order patterns. Amassing all these data helps developing systematic lot-sizing rules in order to estimate the optimum level of future orders and inventory replenishments.
Artificial Intelligence is about replacing human decision making with sophisticated technologies –Falguni Desai
Transportation network design
Transportation offers it’s own set of challenges including TSP, vehicle routing and scheduling problem, minimum spanning tree problem, fright consolidation problem, and to name a few. In specific, due to the combinatorial nature of these challenges, the GA, a sub-discipline of AI, turns out to be the most popular technique integrated to address aforesaid challenges efficiently. Besides, another popular technique i.e. “ant colony optimization of algorithm” of AI has emerged to address the transportation network design challenges such as TSP, vehicle routing and the minimum spanning tree problem.
Purchasing and supply management
Business organizations should analyze make-or-buy decision at each step by weighing all options of producing goods and services internally or purchasing the same externally by focusing on its core competency. Although the make-or-buy decision is simple and straightforward, it is filled with various “What-if” scenarios off screen. Some of the common scenarios are;
- What volume of goods should company produce?
- How much capital investment is required to produce the goods?
- How much risk is involved in producing new products or innovating technology to stay competitive in the market?
- Has the product become successful in the market and drive-in more profits?
- Will customer feel satisfied?
- Does the company employees have the expertise to produce goods that the customers desire?
Due to the intricacy and dynamics involved in aforesaid scenarios, integrating a systematic decision-aid tool is essential in make-or-buy decision calls. One such tool is Expert System (ES), a sub-discipline of AI, which helps purchasing manager to evaluate the performance of prospective suppliers, optimize the information exchange amongst purchase personnel and reduces the time taken to make the make-or-buy decision.
Besides, an automated agent-based system can be integrated to automate and optimize the online-ordering process.
Aforesaid examples clearly represent that in today’s dynamic world, embedding artificial intelligence into supply chain offers a competitive advantage. Besides, based on various surveys senior executives and procurement professionals do accept that this technology help in optimizing the entire business processes. The AI is completely armed with predictive analytics that can analyze cluster of data collected through various sources. Analyzing these data help companies to develop an efficient form of supply chain management.
As AI continues to optimize the existing technologies and expand its capabilities, no doubt, it has become one of the best innovations to address many complex issues.