The ops-ification of disciplines such as software development, machine learning, and security aims to increase efficiency and reduce risk. For decision science and operations research — a discipline built on efficiency — it’s no different.
A look at how one startup is supporting sustainable and resilient city design by optimizing urban delivery logistics — starting with dispatch apps designed for eco-friendly operators.
Change can be scary or energizing. But when it comes to developing and deploying algorithms that make routing, scheduling, and fulfillment decisions, ready-made testing tools tilt the balance in favor of energizing by building confidence.
Decision optimization technology plays a critical role in everyday operations — food delivery, healthcare staffing, and subscription box assembly — but it can often stand in its own way. It doesn’t have to.
Are AI, ML, and OR the same or different? Is operations research a solved problem? How do you know if you’re ready for optimization? We asked industry veteran Karla Hoffman these questions and more.
