The Gartner Supply Chain Podcast
Improve Decision Quality With Reciprocal Human-Machine Augmentation With Noha Tohamy
Nov 29, 2021
Supply chain expert Noha Tohamy joins host Thomas O'Connor to discuss improving decision quality with reciprocal human-machine augmentation. They explore strategies such as crowdsourcing and data literacy, and provide real-world examples from Cisco and Western Digital. The podcast highlights the importance of leveraging the combined intelligence of humans and machines for better decision making in supply chain management.
19:25
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Quick takeaways
- Leveraging crowdsourcing principles that involve humans and machines as equal contributors can enhance decision quality in supply chains by combining domain knowledge and advanced analytics.
- Investing in comprehensive data literacy training programs can enable supply chain staff to speak and understand data, thus augmenting decision-making capabilities and improving distribution quality.
Deep dives
Harnessing the Combined Intelligence of Humans and Machines
The podcast episode explores the concept of reciprocal human-machine augmentation and how it can drive better distribution quality in supply chains. Automation and advanced analytics are being widely adopted in supply chains, resulting in a need to capture and preserve human domain knowledge. The key is to develop a framework of reciprocal human-machine augmentation, which involves the mutual sharing of knowledge between humans and machines to enhance decision-making abilities. The goal is to simultaneously capture and improve domain knowledge while upskilling supply chain staff to effectively use data and analytics.
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