American Air Liquide, a firm based in Houston, Texas, recently implemented a complexity-oriented decision making approach. The following information was acquired through multiple employee interviews, associated document examinations, and observations of the Operations Control Center at American Air Liquide. The company produces industrial and medical gases such as nitrogen, oxygen, and hydrogen at about 100 manufacturing locations in the United States and delivers to nearly 6,000 customer sites using a mix of pipelines, railcars, and more than 400 trucks. In the past, its distribution routing was based on analytical optimization methods. However, this approach had a difficult time integrating environmental volatility, feedback from truck drivers, and dynamic sourcing opportunities. After working with NuTech Solutions (formerly Bios Group), they created a new complexity-based solution that leverages neural networks and agent-based modeling (with ant-foraging algorithms) to integrate decisions across their multimodal and multimodal supply network. Most important, the new solution method solves both sourcing and routing together in the optimization process. Charles Harper, director of National Supply & Pipeline and Supply Operations, summarizes the benefits of their complexity-based approach:
After switching over, we drive less miles, we don’t do stupid things, and we move people to different jobs that didn’t exist before. All those things add up to savings. It’s been mind-blowing to see how much opportunity there was. The knowledge we gained from implementing the complexity-based solution helped us realize what the real-time incremental cost of the liquid going into customers’ tanks really was. Our supply network can now flexibly adapt to volatility in the environment due to differentials in power prices or even hurricanes. Complexity-based solutions are extremely applicable and people need to start using them or they’re going to lose out.
American Air Liquide is far from being the only firm that is using the structural complexity (interconnectedness of firms) and adaptivity (dynamic learning of individual firms) principles of Complex Adaptive Systems (CAS). Boeing has effectively used CAS principles to redesign their 787 Dreamliner supply network, reducing the risk of expensive cascading supply network delays. Similarly, using CAS principles, Citibank Credit Risk uncovered $200 million in hidden expenses, Proctor and Gamble reduced supply network inventory by 25% and saved 22% on distribution expenses, and Southwest Airlines saved $2 million annually in their freight delivery operations. As seen in these examples, a CAS oriented approach can help firms reap benefits such as increased efficiency, rapid flexibility, better preparedness for external uncertainties, increased awareness of markets and competition, and improved decision making.
Source: Pathak, S., Day, J. M., Nair, A., Sawaya, W., and Kristal, M. 2007. Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective. Decision Sciences Journal, Vol. 38, Iss. 4., 547-580.