Co-pilot AI
Overview
Co-pilot AI is a powerful tool that helps buyers and supply chain managers mitigate supplier chain risk and streamline the procurement process. By leveraging advanced analytics and machine learning, co-pilot AI can identify potential supplier chain risks before they become major problems.
For example, co-pilot AI can analyze supplier data to detect potential issues such as delivery delays, quality concerns, and pricing fluctuations. This allows buyers and supply chain managers to take proactive measures to address these issues before they escalate into larger problems.
In addition, co-pilot AI can automate many aspects of the procurement process, such as supplier selection and performance monitoring. This streamlines the procurement process, freeing up valuable time and resources for buyers and supply chain managers.
Overall, co-pilot AI provides a comprehensive solution for managing supplier chain risk and optimizing procurement operations. Its advanced analytics and automation capabilities allow buyers and supply chain managers to make data-driven decisions, minimize risk, and increase efficiency.
Role:
As a UX design manager, I led the design strategy and execution for the Strategic Procurement Suite, including Strategic Sourcing, Product Sourcing, and Strategic Contracts. One of my key projects was creating a high-fidelity design and conducting research to support the SAP Sales team in closing a deal with a critical customer. The demo I created showcased the powerful capabilities of the SAP autonomous procurement/AI concept and how it can streamline and enhance the customer's procurement process.
Tools:
- Sketch
- Figma
- Invision
- Zeplin
Problem
Buyers and supply chain managers face numerous challenges when it comes to identifying and mitigating supply chain and sourcing risks. These risks can arise from various factors such as material shortages, political climate, war and natural disasters, supplier financial or R&D issues, and many more. Here are some pain points:
- Lack of Visibility: One of the major challenges for buyers and supply chain managers is a lack of visibility into their supply chain. They may not have access to accurate and real-time information about the suppliers, which can make it difficult to identify and mitigate risks.
- Difficulty in Forecasting: Buyers and supply chain managers often face difficulty in forecasting supply chain and sourcing risks. They may not be able to anticipate factors like natural disasters or political unrest, which can have a significant impact on their operations.
- Over-Reliance on Single Sources: Many organizations rely heavily on a single supplier or a single source of materials. This over-reliance can leave them vulnerable to supply chain disruptions if that supplier or source experiences any issues.
- Limited Alternatives: Buyers and supply chain managers may not have access to alternative suppliers or sources of materials. This can limit their ability to respond quickly to supply chain disruptions and mitigate risks.
- Cost and Time Constraints: Mitigating supply chain and sourcing risks can be costly and time-consuming. Buyers and supply chain managers may face budget constraints or tight timelines, which can limit their ability to invest in risk mitigation strategies.
- Communication and Collaboration: Effective communication and collaboration between buyers and suppliers is critical in mitigating supply chain and sourcing risks. However, this can be challenging if there are language or cultural barriers or if there is a lack of trust between the parties.
Addressing these pain points requires a proactive approach, including investing in technology that can provide real-time visibility and accurate forecasting, diversifying suppliers and sources of materials, and building strong relationships with suppliers through effective communication and collaboration.
Solution
One solution to address these pain points is the implementation of a co-pilot AI system in procurement processes. This AI system can help buyers and supply chain managers detect and mitigate potential supplier chain risks that arise due to various factors such as material shortages, political climate, wars, natural disasters, and supplier financial or R&D issues.
The co-pilot AI system uses machine learning algorithms to analyze supplier data, news articles, social media posts, and other relevant sources to identify potential risks. The system can also predict the likelihood and impact of these risks and suggest appropriate risk mitigation strategies.
The co-pilot AI system can also streamline the procurement process by automating repetitive tasks such as purchase order creation and invoice processing, freeing up time for buyers and supply chain managers to focus on strategic initiatives.
Additionally, the system can provide real-time visibility into supplier performance and supply chain health, allowing buyers and supply chain managers to make data-driven decisions and take proactive measures to address potential issues.
Overall, the implementation of a co-pilot AI system in procurement processes can help buyers and supply chain managers to manage risk more effectively, streamline procurement operations, and make better-informed decisions.
UX Research
Following multiple Design Thinking workshops and UX research with users, we identified multiple pain points that users are facing with our current procurement applications. One of the main challenges was the website's navigation and information architecture, which caused users to struggle with finding the information they need and requires too many clicks to complete tasks.
Another issue that users expressed frustration about was the manual process for supplier insights and bidding management. Our existing applications was unable to pull real-time insights, making it necessary for users to manually analyze data outside of the application, leading to inefficiencies and frustration. Additionally, users found it was difficult to monitor and award the bidding process efficiently due to the lack of dynamic supplier data.
To address these concerns, I recommended modernizing the application's UX design, adding more actionable insights and sourcing scenarios analysis, and integrating co-pilot AI technology. By leveraging AI, users can receive personalized recommendations and assistance throughout the procurement journey, simplifying the entire process. Co-pilot AI can also dynamically pulled supplier data and eliminate the need for manual data analysis, improving the overall user journey and providing a more streamlined and efficient procurement experience for our users.
Design
Based on the pain points identified in our UX research, I recommended several design solutions to improve the procurement applications:
1. Streamlined Navigation and Information Architecture: To address the issue of users getting lost on the site and too many clicks required to complete tasks, I recommended modernizing the website's UX design. We propose a simplified navigation system and a clear and concise information architecture to improve user experience.
2. Real-Time Supplier Insights and Sourcing Scenarios Analysis: Users expressed a desire for more supplier bidding information with actionable insights so that they can have more confidence in their sourcing strategy. I recommended integrating real-time supplier insights and sourcing scenarios analysis to provide users with the necessary data to make informed purchasing decisions. This feature would eliminate the need for manual data analysis outside of the application.
3. Co-Pilot AI Integration: I proposed integrating the co-pilot AI technology to assist users throughout the procurement journey since the AI can offer personalized recommendations and assist users in monitoring and awarding the bidding process. This feature would improve the overall user journey and provide a more streamlined and efficient procurement experience.
Overall, these design solutions would improve the user journey, making it more efficient and effective for buyers and supply chain managers. By streamlining the navigation and information architecture, integrating real-time supplier insights and sourcing scenarios analysis, and incorporating co-pilot AI technology, we can address user concerns and provide a more efficient and streamlined procurement experience.
