Improve Decision Quality With Reciprocal Human-Machine Augmentation With Noha Tohamy

In this podcast, host Thomas O’Connor and guest Noha Tohamy explore improving decision quality with reciprocal human-machine augmentation. A confluence of forces is eroding supply chain domain knowledge while increasing the reliance on advanced analytics in making supply chain decisions. CSCOs and heads of strategy can adopt innovative approaches to harness the combined intelligence of humans and machines for better decision quality such as:

• Crowdsourcing: Extend crowdsourcing principles to include humans and machines as equal contributors. Humans can bring their insights and predictions based on domain knowledge, while machines and algorithms can contribute data and analytics-based insights. Use this combination to improve decision quality.
• Data Literacy: Develop staff to understand and speak data and analytics. This will allow humans to better augment machines. By understanding data, humans can augment their decisions with analytics insights and recommendations.

The discussion provides two real-world examples of leveraging these strategies from Cisco and Western Digital.

See Supply Chain Executive Report: Improve Decision Quality With Reciprocal Human-Machine Augmentation for deeper and additional insights into the topics discussed during this podcast.

Explore Gartner’s playbook for a Three-Step Plan for Supply Chain Digital Transformation: https://gtnr.it/3ox1qDt