At an e-commerce giant, customer orders are assigned throughout the day to fulfillment centers and third parties across the United States while minimizing shipment costs, observing limits on inventory, reducing split orders, and balancing workload across the fulfillment centers. The company’s data science team created an order fulfillment optimization proof of concept in Python that would significantly improve the operation. To prepare for deployment, the company’s software engineering team converted the code into Java, leveraging the Gurobi Optimizer, and created a solution that integrated with real-time data. Because of the critical nature of the operation, company leaders sought assurance that the solution would be successfully implemented and maintained 24 hours a day, 7 days a week, and yield the desired results.
The Optimization Edge
A Blog for Business Executives and Advanced Analytics Practitioners
Technologies: Data Science, Big Data, Optimization, Machine Learning, Artificial Intelligence, Predictive Analytics, Forecasting
Applications: Operations, Supply Chain, Finance, Health Care, Workforce, Sales and Marketing
The metaverse buzz has begun and Transportation and Logistics executives should pay attention. In fact, we think it is inevitable that the metaverse—Virtual Reality (VR) and Augmented Reality (AR)—will impact the industry in a variety of ways.
Princeton Consultants employs a 7-step methodology that improves the likelihood of success and deliverability in optimization projects. Based on our solution development and deployment for many clients in varied industries, this approach helps create useful documentation, shortens the overall development time, improves code maintainability, and provides a natural feedback loop to business requirements.
How do Advanced Analytics leaders sustain great teams, companies, and agencies? The INFORMS Practice Section conducts a webinar series, moderated by Dr. Arnie Greenland, featuring presentations and interviews with leaders of a variety of organizations. On January 21 Steve was the guest; following is a lightly edited excerpt.
Tom Cook, founding partner of Decision Analytics International and past president of Sabre Decision Technologies, is a truly remarkable operations research trailblazer in the airline industry.
How can you replicate the hero’s journey in your organization? Here are three steps.
Before I go forward, you might be wondering, “Wait a minute. The UPS drivers, tens of thousands were planning their routes in their heads? Why? Didn't they have computers?” Well, in the hero's journey, there has to be a reason why no one before the hero has succeeded before.
What do Dorothy from "The Wizard of Oz," Luke Skywalker, Frodo Baggins, and Harry Potter have in common? They all participate in “the hero’s journey,” a term coined by Joseph Campbell, whose great book, The Hero with a Thousand Faces, famously asserts that the hero’s journey has been told thousands of times through history, and it always follows the same epic steps. I’d like to feature a present‑day, real‑life hero and his journey: Mr. Jack Levis from UPS.
Once you have a working optimization prototype program that has been tested and embraced by one or more users under field conditions, it is time to roll out the program to the organization and be sure that the right people are using it daily. Because the best optimization opportunities address decisions that are made repeatedly across the organization, scaling up often means motivating and training a large group of dispersed people.
Occasionally we highlight services and solutions from outside our Optimization Practice.
A regional business insurance broker’s risk control division sought a new-generation software application and automated process to audit businesses for risk and provide mitigation recommendations. Traditionally, inspectors traveled to sites and filled out paper checklists, took many photos on digital cameras and uploaded them to a local computer, transcribed information into a web browser, exported to Word document reports which required additional manual modification and layout changes, and finally emailed the final report to clients. This process was supported by an internal software application that had become outdated, unstable, had frequent downtime, and was inadequately supported.