By Mandar Kulkarni, AVP, Data Science, Findability Sciences
In today’s connected digital world, maximizing productivity by reducing uncertainties is the top priority across industries. With industries promptly moving towards digitalization, supply chain management isseeing huge operational dependencies in manufacturing and logistics industries. Driving value has always relied upon the supply chain, but with a new level of risk threatening the bottom line, businesses are now seeking greater visibility and resilience in their operations.Mounting expectations of supersonic speed and efficiencies between suppliers and business partners of all types further underscores the need for the supply chains and logisticsindustry to leverage the prowess of emerging technologies like Artificial Intelligence (AI), Machine Learning, and Natural Language Processing. The is said to hold the potential to bring in interference and lead innovation inside these industries.
The AI-powered supply chain
Artificial intelligence has been equipped with computing techniques that support selecting large quantities of data, also known as wide data from logistics and supply chains. An entity can put such methods to use, and they can be analyzed to get results that can pledge processes and complex functions. It is possible to examine its performance by using AI in supply chain management. It comes up with new and better factors that impact the same area by finding the variables and issues which influence the presentation of the graceful chain.
Artificial intelligence (AI) solutions are expected to be influential instruments to help organizations tackle these challenges. An integrated end-to-end solution approach can address the opportunities and constraints of all business functions, from procurement to sales. The ability of AI to analyze WIDE data, understand relationships in external factors, end-to-end visibilities in operations, and support better decision-making makes AI a potential game changer. Getting the most out of these solutions is not just a matter of technology, however; companies must take organizational steps to capture the full value out of AI.
Challenges in Supply Chain Management
In recent years, the traditional way of supply chains has become substantially more challenging to manage. It is due to volatility in the market due to COVID-19, increased demand, decreased sales, and vice-versa and the impact of raw materials, and planning. Increased attention to the environmental impact of supply chains is triggering regionalization and the optimization of flows. As a result, industries have become more focused on supply-chain resilience.
Gaining Supply Chain Momentum with AI
The recent supply-chain disruptions and demand triggered by the COVID-19 pandemic have further increased the need for industries to develop arobust plan with utmost care and attention.Increasing the relevance and size of supply-chain or business-plan teams is not sufficient to achieve the expected performance. Companies shouldinvestigateother important challenges by:
- Demand forecast across various combinationslike (By product, geographies, branches, etc.)
- Identifying the trade-offs, and losses in saleswith thousands of correlated variables and correlating them with real-time constraints.
- Integrating AI solutions like Demand sensing, Inventory planning, market patterns, consumer behavior, spend analysis, Customer Lifetime Value, etc. to accelerate the value of the supply chain.
- Ensuring that planning, and time fencing will get smoothly executed with variability effects with time series.
Benefits of adopting AI in Supply chain management
- Transparency in demand sensing, invoicing, logistics
- Resolving consumer queries faster and more effective manner using a chatbot, consumer sentiment analytics
- Achieving procurement strategy in Spend analytics, distributor management, vendor management, distribution network management
Insufficient change management is the most significant risk to the implementation of AI in the supply chain. But getting it right can secure a competitive advantage in the short, medium, and longterm.
What is an AI-powered Supply Chain?
AI-powered Supply Chain is equipped with computing techniques that support selecting large quantities of data, also known as wide data from logistics and supply chains. It helps in analysis to get results that can pledge processes and complex functions. It also helps to examine the performance of supply chain management.
What are the challenges in traditional way of Supply Chain Management?
The traditional way of supply chains is challenging to manage because of volatility in the market that can lead to increased demand, decreased sales, or vice-versa and the impact of raw materials, and planning.
How can AI help in Gaining Supply Chain Momentum?
AI helps in forecasting the demand across various combinations like product, geographies, branches; Identifying the trade-offs, and losses in sales with correlated variables and correlating them with real-time constraints; Helps in demand sensing, inventory planning, market patterns, consumer behavior to increase the value of the supply chain.
What are few benefits of adopting AI in Supply Chain Management?
Few benefits of AI when used in Supply Chain Management: Transparency in demand sensing; Resolving consumer queries faster and more effective manner using a chatbot; Achieving procurement strategy in Spend analytics, distributor management, vendor management, distribution network management.