Supply chain management used to focus mostly on cost optimization. The pandemic, geopolitical instabilities, and natural disasters changed that.
Now, supply chain leaders focus on both cost optimization and resilience – the ability to forecast and respond quickly to these disruptions. What’s critical to their success? Digital technologies that enable them to model their entire network, identify potential vulnerabilities, and make informed decisions on how to keep the supply chain moving.
To discover how to boost your supply chain resilience, join us for this on-demand webinar, where we walk through real-world examples from Ennoconn. One of the world’s leading industrial device manufacturers, Ennoconn uses graph technology from Neo4j and Gemini Data to minimize overstock, control cash flow, and survive disruptions.
- How Ennoconn uses graph technology to create digital twins and manage complex networks
- The power of graph data science in forecasting and preparing for unexpected events
- The role of graph data science in accelerating the digitalization of logistics processes
You’ll also learn how Ennoconn integrated OpenAI’s GPT-X APIs and generative AI to broaden adoption and ensure that everyone can use the application, regardless of their skill level.
No matter your industry, if you’re a supply chain technology leader looking to reduce risk and boost resilience, you’ll gain valuable insights at this webinar.
Michael leads Neo4j’s global partner enablement programs and is helping Neo4j partners build compelling services and products leveraging Neo4j’s industry-leading graph database and graph analytics platform. Trained as a scientist, Michael has over 20 years of experience delivering high-value enterprise analytics solutions and portfolios for startups, agencies, and Fortune 100 companies. Michael has been working with Neo4j graph databases and graph analytics since 2013.
In his role prior to Neo4j, Michael established EY's national consulting practice in Enterprise Knowledge Graphs and AI. At EY, Michael architected and delivered full-stack graph applications for EY clients across multiple industries and use cases, including customer 360°, recommendation engines, risk analytics, KYC, fraud detection, anti-money laundering, energy trading, digital twins, capital projects total cost visibility, master data management, data lineage, and enterprise data fabrics. Prior to EY, Michael was at Microsoft, where he managed a global portfolio of over 65 applications in the connected sales and marketing space for Microsoft’s B2B and partner ecosystems. Michael is based in Redmond, Washington.
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