Sales and Fulfillment
How can AI enhance supply chain optimisation?
Artificial intelligence (AI) in the supply chain is at the forefront of innovation. The supply chain is changing and evolving faster than ever, and the increasing use of AI applications is becoming apparent. In the next few years, AI will revolutionise the supply chain market by accelerating productivity and efficiency. The global market size of AI in supply chain management will reach $14.3 billion by 2028, growing at a CAGR of 20.17% from 2021 to 2028.
The pandemic has introduced a host of risks and uncertainties in the supply chain, prompting the need for an AI-powered, data-driven operating model to realign and optimise supply chain functions. Over 60% of supply chain businesses will adopt AI in the next 5 years to transform their operations to become more responsive and forward-looking through the post-pandemic era. IoT- and AI-powered supply chain optimisation can enhance network responsiveness, ensure agility, and improve end-to-end transparency. As a part of digital transformation, AI can help manage sudden disruptions and deliver as per the business objectives.*
Why use AI in supply chain management?
While it is plain as day that AI systems offer the perfect combination of speed, scalability, granular data, and innovation, they add value to the business models in more ways than once imagined:
- AI can radically improve the components of supply chain management by offering real-time insights and intelligence.
- AI-based solutions can automate day-to-day operations and forecast the best possible outcomes for future scenarios.
- The implementation of AI in supply chains is beneficial for inventory management, supply planning, productivity, capacity utilisation, logistics, manufacturing, warehousing, and customer experience.
- AI can drive dynamic pricing and streamline introducing new products in the market, marking a shift from history-based forecasting.
How AI can help reshape supply chain management ?
A study by McKinsey & Company established that over 63% of businesses increased their revenue, while 44% reduced their expenses with the adoption of AI into their networks. AI can enhance the features of supply chain management by[2][3]:
- Performing predictive maintenance
- Optimising manufacturing processes
- Improving warehouse management
- Enhancing safety
- Reducing the margin of error
Heavy warehouse equipment, such as forklifts or cardboard balers, requires regular maintenance for safety and productivity. However, this may result in downtimes and interrupt the business operations. AI can develop algorithms that predict the potential for equipment failure and subsequently determine the need and optimal timing for maintenance and servicing. By conducting maintenance only when its required, businesses can enhance productivity and safety protocols compared with scheduled maintenance routines.
To improve the efficiency and cost-effectiveness of operations, businesses have to monitor cycle times, downtimes, lead times, quantities of goods, supplier reliability, margins of error, and costs. A significant advantage of AI is that it can run in the background and suggest continuous improvements throughout the product development cycle by analysing its value, cost, and quality.
Efficient inventory management means quicker order processing, better dispatch and delivery speeds, and higher customer satisfaction. By analysing inventory data and sales trends, AI can enable demand planning and forecast decisions for profitability.
AI can improve the safety of personnel and machinery by handling equipment that poses safety hazard for workers. Predictive AI models can also analyse data on potential dangers in the workplace and implement contingency plans to reduce work-related injuries.
AI can be applied as a deep learning network to lower the errors in logistics and supply chain process operations. For instance, AI can examine storage and transportation records and validate them with the manifests. By checking for consistency in data, the margin of error is greatly reduced.
Integrating AI in supply chain optimisation: How can Infosys BPM help?
From data analysis and decision-making to demand forecasting, AI capabilities in supply chain optimisation are endless. Our AI-driven supply chain optimisation services help clients transform their supply chain management by obtaining excellent insights into supply chain disruptions and fluctuating customer demands.
Our AI-powered supply chain optimisation solution is an integrated planning approach–based framework that includes:
- Supply chain diagnostics
- SC shared services advisory
- SC control tower
- Forecasting as a service
- Inventory optimisation
*For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive yet modular suite of services is doing exactly that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.
