6 Ways Generative AI Can Improve Supply Chain & Procurement Productivity
- Generative AI can help find information more quickly and easily by searching through large datasets and identifying patterns.
- It creates predictive models that can help professionals forecast demand, identify risks, and make better decisions.
- It helps supply chain professionals become more agile by automating tasks and providing insights for better decisions.
June 29, 2023 | Procurement Software
Generative AI tools such as ChatGPT and Bard are poised to become a game-changer for supply chain and procurement professionals. By using this technology, professionals can improve their efficiency and productivity, and make better decisions that will benefit their organizations. These large language models can be used to improve search capacity, automate tasks, identify patterns, and make predictions that would otherwise be time-consuming. The result? Significant savings in time and money, as well as improved decision-making.
The following as some potential applications of generative AI for supply chain and procurement teams.
1. AI boosts the search ability of supply chain and procurement organizations.
Instead of relying on limited data provided by traditional search engines or reports, generative AI can make the search more organized and interactive. Generative AI is different from web search keywords (traditional web search, web crawling, ranking, bids in paid search) or reports, which often require updates on a regular basis. It can answer questions about what, where, when, and why, and it can be customized to individual needs. This means that users can get more relevant information with more targeted prompts. Generative AI supply chain capabilities can also help enterprises track trends, gather market intelligence, determine pricing, calculate costs, benchmark performance, and find lists of distributors or suppliers.
2. AI reduces preparation time for reports, presentations, and even procurement RFPs.
It can assist in generating the initial draft and quickly getting things started. In short, AI can improve productivity at the individual level. In the long term, AI could become more integrated and be offered as an embedded or add-on service.
Also read: Adopting AI Responsibly: Guidelines for Procurement of AI Solutions by the Private Sector
3. AI provides predictive models.
This application is based on dynamic data, where large datasets can be very complex and time-consuming to analyze. The range of applications includes network design in supply chain and logistics, lean inventory control, and dynamic demand forecasting.
4. AI also helps normalize human bias.
In addition to predictive analytics, AI can be used for decision support with potential trends and forecasts. This means that buying organizations do not have to rely on the intuition of managers, market intelligence reports, or close-loop model calculations. AI can perform the computations based on historical data and potential scenarios and outcomes.
Also read: ChatGPT: What Procurement Leaders Need to Know and Do Right Now
5. AI drives supply chain agility by reducing supply chain costs and cycle times.
It provides a set of recommended data and key attributes, policy and reward profile scenarios to assist managers. This includes finding the targeted cost per shipment and taking appropriate action to reduce the cost per unit, which has a direct impact on the P&L statement.
6. AI helps create a digital-first supply chain.
With the deployment of supply chain generative AI, processes become more integrated, automated, and intelligent in ERP systems such as order management, inventory management, production planning, raw material ordering, and supplier inventory control.
Conclusion
Generative AI is a powerful tool that can be used to improve the supply chain and procurement professions. By using this technology, professionals can save time, improve their decision-making, and make their organizations more agile.
Author: Kajohnpong Yang
