Dr. Ken Fordyce

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.

Tools of the Trade: How “Forecastable” is Your Data? Complexity Exists Whether You Ignore It or Not

These “key tools” balance a need for simple with a need to handle the complexity of SCM – following the IBM adage – complexity exists whether you ignore it or not, best not to ignore it.

RCCP Versus MPS: How Are They Connected? Elixirs and the Wrong Question

A reasonable question supply chain folks often ask themselves is ‘What is the relationship between Rough Cut Capacity Planning (RCCP) and Master Production Scheduling (MPS)?’ However, this is the wrong question to ask oneself. This blog will address the transition from AS to central planning as best practices and demonstrate that with a firm’s due diligence they can make the transition successfully. This is critical for what-ifs and effective use of optimization.

By |2021-09-08T11:03:35-04:00September 8th, 2021|Central Planning, RCCP, Supply Planning|0 Comments

Classical Supply Chain Management Confronts its Quantum Revolution – the Path to Rapid Intelligent Response (RIR)

COVID-19 direct and ancillary events have made clear that uncertainty is an inherent part of the demand-supply network structure. Every firm, on a regular basis, faces “risk situations" such as manufacturing excursion, unexpected new demand or loss of demand, component supplier interruption, etc. This has placed risk management and rapid intelligent response (RIR) front and center in SCM discussions.

Five Steps to Develop an Effective S&OP Process – Step 4: Balance Supply and Demand

Over the past 5 weeks, Jeff Ondria has hosted a set of short interviews on LinkedIn about the five distinct steps to develop an effective S&OP process. In today's blog, we discuss step 4 Balancing Supply & Demand where we will answer some key questions with respect to balancing supply and demand.

CPE Planning Level, IBP, Elixirs, and the Ongoing Challenge

In SCM there is an ongoing flow of elixirs (magic potion) from ‘false prophets’ claiming that they are an easy path to improved performance. A recent elixir is IBP followed by “doing central planning at the family level” to neutralize the uncertainty associated with estimating demand at the product level. This blog will illustrate the challenge in this effort since factories produce products, not families.

Target Inventory and Central Planning Engines (Models) – Avoiding the Runaway Train

Often inventory is considered the simplest component of supply chain management that can successfully be managed separately. The purpose of this blog is to provide some observations to avoid the runaway train. We will first review the basics of CPE and then address the use of target inventory (specifically ending finished goods inventory EFGI) in CPEs.

Tools of the Trade: How to Compare / Combine Diverse Time Series – “Normalizing”

A reoccurring challenge in comparing and combining diverse time series in demand forecasting is the “scale” – as it is in combining metrics. Rescaling is a powerful but simple method to help with this issue enabling demand planners to focus on similarities of shape. This blog provides an example of one method called normalization.

AI/ML, SCM, The Holy Grail, and Helpful Information from Foresight

In this blog, we point the reader to a recent article “Humachine”, which identifies the general challenge of implementing decision technology to improve SCM decision making resulting in improved organizational performance and the importance of experience in the trenches.

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