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
August 9, 2019

At Princeton Consultants, we have started to do the majority of our optimization model development using python with the pandas library (https://pandas.pydata.org/). We have successfully developed models using the Gurobi (https://www.gurobi.com/) python interface, and the docplex (http://ibmdecisionoptimization.github.io/docplex-doc/) python interface for IBM ILOG CPLEX Optimization Studio (https://www.ibm.com/products/ilog-cplex-optimization-studio). Based on these successes, we have codified our approach for rapid optimization model development. Our steps for success include:

July 18, 2019

Dave Shanno, my colleague and friend who helped jump-start my career over 30 years ago, recently passed away. Dave was a brilliant mathematician and academic researcher who especially valued the usefulness and implementation of solutions—his perspective inspired me and many others in Operations Research. Today, machine learning is just one area that is benefitting from his work. In December, 2017, I interviewed Dave for the INFORMS Oral Histories program (video and full transcript are here).

June 25, 2019

I was recently invited to speak to executives at the Retail Industry Leaders Association (RILA) about tech disruption in freight transportation. Following is a lightly edited excerpt from my presentation.

The premise of our survey was that disruption is real—it's happening. We asked a sanity question, “Do you agree?” At the close of the survey, we wrote, “We believe that disruption is creating new winners and losers. That people should look at their strategy, their sales, operations, IT. What do you think? What are you doing about it?”

June 4, 2019

Periodically we draw from other Princeton Consultants practice areas for helpful content.

When does a project go bad? Signs of trouble don’t appear in status reports until the project is well underway. After all, it takes some time for the budget to slip significantly, and even if early dates are missed, there is a bias toward explanations like “growing pains”, “the team learning to work together”, and “IT is overallocated”.

May 7, 2019

A highly visible and successful optimization project can generate an abundance of harvest opportunities. Beyond the projected payback or return on investment, is there another way to set priorities when faced with such abundance?

April 10, 2019

On a March 22 conference call with Stifel Managing Director of Research David Ross, I presented the results of our annual survey of transportation executives, who were asked to predict the impact by 2025 of self-driving trucks, drones and robotics, Big Data / AI / Machine Learning, the Internet of Things, Uberization of freight, and Blockchain. Following is a lightly edited transcript of the discussion of the second part of the survey, which asked executives to predict the impact of these tech disruptors on key business areas (1 = low impact, 2 = medium impact, 3 = high impact).

 

March 12, 2019

Following are more transcript highlights from our January 29/30 webinar with Ugo Feunekes of Remsoft and Gurobi, which can be watched on this Gurobi webpage.

February 14, 2019

On January 29 and 30, I conducted a webinar on model review and validation about a specific project that entailed challenges and solutions of great potential interest to the larger community of optimization practitioners. Anita Bowers and Gwyneth Butera of Gurobi were the hosts and moderators. My co-presenter was Ugo Feunekes, the co-founder and CTO of Remsoft. Following is a lightly edited transcript of highlights of the webinar, which can be watched on this Gurobi webpage.

January 18, 2019

On January 15, Steve Sashihara returned to Road Dog Trucking Radio to discuss disruption in freight transportation and the results of Princeton Consultants' recent survey. Following are excerpts of his conversation with host Mark Willis and callers.

Mark Willis: Drivers, when you think about the future of trucking, you might think, OK, autonomous vehicles, more technology in the cab, the Uberization of freight. Are we going to see more apps coming to the forefront to help your job out there, to make it easier for you? Yes, to all of the above? That’s certainly going to be the motion that we’re going to be riding as technology drives what's going on in the industry. Great to have on board Steve Sashihara, the co-founder and CEO of Princeton Consultants, an organization that blends advanced analytics and data science with management consulting. They help companies in transportation and other industries achieve transformational improvement, service, and efficiency. Steve, thank you for doing this and thanks for chatting with the drivers, the front line if you will.

December 11, 2018

Accounts have a fairly narrow definition of assets. To optimizers, assets include any resource that an organization owns or controls that can potentially add value to the business. Some are traditional accounting assets, such as buildings, equipment, and inventory. Others are human assets, such as your employees, vendors, and customers. Still others are intangible assets, such as your reputation, brand, customer loyalty, intellectual property, and access to capital. Whatever the asset, optimizers are driven to maximize its yield.