About Dr. Ken Fordyce

Before joining Arkieva, he had a very successful 36-year career with IBM, much of it in all aspects of supply chain (to use Intel’s Karl Kempf’s preferred term – demand supply networks) for IBM Microelectronics Division (MD). During this period, MD was a Fortune 100-size firm by itself. Fordyce was part of the teams that altered the landscape of best-practices – receiving three IBM Outstanding Technical Achievement Awards, AAAI Innovative Application Award, and INFORMS Edelman Finalist (twice) and Wagner (winner). He writes and often speaks about the “ongoing challenge,” both to practitioners and academics. In his free time, Dr. Fordyce enjoys writing programs in APL2 while running sprints.

Two Simple Examples to Help You Understand How Supply Chain Optimization Algorithms Work.

I work with clients that utilize our supply chain optimization software to maximize their resources. In my upcoming webinar “Should I Optimize My Supply Chain Planning?” I’ll dive deeper into the concepts of supply chain optimization and show examples of when it’s ideal to optimize and when it’s less ideal. In today’s blog post, I’d like to simplify this concept by looking at some basic equations and scenarios to explain how “solvers” or supply chain optimization algorithms work.

By |2019-04-13T23:09:07-04:00April 4th, 2018|Supply Chain, Supply Chain Optimization|

5 Key Supply Chain Efficiency Assessment Areas for 2018

If you are looking to improve your supply chain management systems in 2018, you most likely have asked the common question: How do I assess my current efficiency? This is a good starting point for anyone looking to add functionality or identify loopholes within current processes. There is no single perfect method that meets all needs and has no flaws. However, the good news is, supply chain assessments have proven to be very advantageous for many businesses.

By |2019-04-13T23:09:16-04:00January 16th, 2018|Supply Chain, Supply Chain Optimization|

Key Guiding Principles for Getting a Better Handle on Implementing Artificial Intelligence (AI) in Supply Chain Management

The role of Artificial Intelligence (AI) in business activities has again emerged as a hot topic for 2017 and 2018. In fact, Gartner predicts by 2021, 40% of new enterprise applications will include Artificial Intelligence Technologies, where AI and Machine Learning promise to solve a plethora of problems faced by enterprises today, from better decision making to increased efficiencies and cost savings.

By |2019-04-13T23:09:17-04:00December 1st, 2017|News and Trends, Supply Chain, Supply Chain Strategy|

Back to the Basics: What’s the Core Purpose of Supply Chain Management?

As supply chain professionals and SCM technology enthusiasts, our conversations and discussions are often forward-looking. Sometimes, it’s essential to focus on the here and now, before looking ahead. In this post, we’ll cover some of the basics of what supply chain management entails, and why it’s a critical component in fueling supply chain innovations.

By |2024-06-04T21:26:10-04:00November 14th, 2017|Supply Planning|

How to Determine the Best-Fit Plan with Supply Chain Optimization

The use of optimization in supply chain management is widespread, just not in supply planning.  Regular use of optimization occurs in inventory management and demand forecasting. “Best-fit straight line” is one of the most common uses of optimization. With this method, you enter or pull into Excel (or your favorite statistics software) a set of “x values” (the independent value e.g. the number of cars in a train) and a set of “y values” (dependent value e.g. the fuel cost for each train), click a few buttons and you get a “best-fit” straight line – a slope (b1), a y-intercept (b0), a measure of goodness, and a straight line drawn through your scatter plot.

By |2019-04-13T23:09:19-04:00November 7th, 2017|Supply Chain Optimization|

Optimization Puzzle: Who’s Guilty? Dormouse, March Hare or Mad Hatter?

In my role as the Director of Analytics, I enjoy working with the Arkieva team and our clients, in building optimization models which help organizations make intelligent decisions with regards to meeting demand, capacity allocation, inventory levels, factory schedules, forecasting, and cancer research. These models are built using a variety of mathematical methods including Boolean

By |2019-04-13T23:09:21-04:00August 16th, 2017|Supply Chain Optimization|

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