In supply chain businesses, inventory management efficacy is one of the major components that play a critical role in success (or failure! *gasp*).
Before automation was used, decisions were often based on assumptions, and manual processes were fraught with errors and lack of real-time insights was a major source of inefficiency (imagine doing guesswork on a daily basis).
Enter the power of AI, a force that has changed the typical ways of business. And if you’re the type who fears AI taking over, fear not, because it’s been here for a while (and it’s here to stay), but only to serve our businesses for the better. The global conversational AI market is expected to grow at a CAGR (compound annual growth rate) of 22% during 2020-2025, reaching almost $14B by 2025.
We’ll explore how AI automation is revolutionizing (and optimizing!) inventory management within supply chains and how you can use it too. With the use of dynamic data analysis, streamlined communication, and minimization of human error, conversational AI is poised as an ideal solution to age-long problems.
The Role of Inventory Management in Supply Chains
Definition of inventory management
Importance of efficient inventory management in supply chains
Apart from supply chain visibility and real-time data monitoring, businesses try to maintain optimal levels of supply to meet demand but at the same time keep the cost to the minimum, and avoid supply chain disruptions. Effective inventory management creates resilient supply chains, affects how products reach customers, and ultimately, affects the company’s profits.
Traditional challenges in inventory management
Traditional inventory management is not a problem-free process for both supply chain managers and company owners. Here are some of the usual supply chain and operations problems:
- Inaccurate demand forecasting
- Manual data entry errors
- Limited visibility
- Inefficient replenishment processes
- Poor communication with supplier
Understanding Conversational AI
Principles of conversational AI
To solve the common issues many companies have with their supply chain management, conversational AI comes in to help with logistics operations. It is one of many AI technologies, and one its main use cases is it replicates human conversations by using natural language processing (NLP) and machine learning algorithms.
Its principles revolve around understanding and producing language in human form, interpreting user intent, and giving appropriate and contextually relevant information or actions. Through NLP tools, conversational AI systems can understand spoken or written natural input which results in smooth interactions between humans and technology (seems crazy, I know, but this is the future).
Applications of conversational AI in various industries
Conversational AI can be utilized in almost all domains ranging from customer service to healthcare, finance, and retail to name a few.
Applying AI to supply chain and warehouse management, you could track your inventory levels and meet customer demands in time. Smart supply chains that utilize AI have taken advantage of predictive analytics to realize more efficient utilization of resources, more consistent cash flow, and better overall operations.
So many businesses have also maximized their e-commerce businesses with chatbots and virtual assistants enhancing user experiences in customer service.
How conversational AI works in inventory management and its benefits
Conversational AI tools provide integration with existing logistics and supply chain systems to streamline processes and improve decision-making. Employing AI can work in end-to-end supply chain processes in many ways:
Data Collection and Analysis: AI systems track real-time inventory levels, record product movements, detect discrepancies, and send up alerts for low stock or overstock situations. AI also gathers and analyzes this data in order to pinpoint patterns, trends, and potential problems.
Forecasting and Demand Planning: With the use of AI, generative AI algorithms, and predictive AI, finding historical data becomes easier. Based on past data, AI can also predict customer behavior, helping companies determine future demand.
Supplier Communication: Like with customers, AI-based chatbots can also interact with suppliers up to the placing of orders, tracking orders, and handling queries. AI can then help supplier relationship management as it can also help renegotiate terms, adjust delivery schedules and replenish inventory correctly.
Customer Satisfaction: AI-powered chatbots can further engage with customers to provide instant updates on product availability, order status, and delivery schedules, improving overall customer satisfaction. A lot of companies who have used supply chain planning with the help of AI to optimize have benefited and created interactive shopping experiences.
Workflow Automation: With supply chain tasks, many companies can use AI to analyze and support supply-chain management with stock recounting, issuance of purchase orders as well as inventory auditing, which assists your entire supply chain in terms of risk management.
Integration with Other Systems: Other cloud-based AI easily blend with various inventory management systems such as ERP (or Enterprise Resource Planning) and eCommerce platforms. It grants data uniformity and an information stream which helps moving between departments within the organization.
Scalability and Adaptability: Implementing AI can easily be used to scale many supply chain platforms with growing inventory volumes, transportation and logistics, and adapt to changes in demand or business requirements, making them suitable for businesses of all sizes and industries.
Conversational AI and Tools for successful implementation
Selecting the right AI tools in supply chain management is key to successful implementation for many organizations. These specialists in AI applications and integrated AI have the expertise to take care of your specific supply chain needs to perform at maximum capacity and efficiency.
Here are some examples of chatbots that help in inventory management. These tools have features such as providing information on product availability, order status, and inventory forecasts, and even engage with customers or employees to provide real-time updates on inventory status, answer inquiries, and facilitate order management processes:
- Microsoft Azure Bot Service
- IBM Watson Assistant
- SAP Conversational AI
- Zendesk Chat
Beyond tools, you can also consult logistics experts to get specialized insights and practices that are worthwhile in their industries. These are examples of companies that use AI for supply chain companies as a solution to inventory management woes:
- Yellow AI
- Warehousing and Fulfillment
- Feedyou
- Convy
- Landbot
- Ideta
Conclusion
Conversational AI has changed how inventory management is done by collecting up-to-date information, enhancing communication, and reducing errors in real-time.
It has the potential to revolutionize supply chain operations giving greater efficiency, agility, decision making abilities, and customer satisfaction that powers up operations management for many organizations as whole. Getting experts and tools powered by AI are solutions strongly encouraged to be adopted by businesses to outperform competitors and to be future-ready in the dynamic market environment. Acceptance of conversational AI marks a new era of intelligent and responsive supply chains that are equipped to win in the digital era.
This is a guest post by Will Schneider, President of WarehousingAndFulfillment.com, who is a seasoned expert with a profound passion for optimizing business operations through efficient warehousing and fulfillment solutions. With a background in executive management for mid-sized 3PLs, he boasts valuable expertise that spans over a decade in the realm of fulfillment outsourcing.
