Category: Supply Chain Optimization

Curbing bad habits or errors early is essential to effective supply chain management. Look at supply chain planning mistakes that haunt you if not corrected.

Squeeze the greatest profit possible from the resources your business already has available. Supply chain optimization software identifies the most valuable demand to meet.

Scheduling software is similar to GPS, organizing the movement of items, marking process steps, ensuring expected locations, and optimizing the route.

While working with various optimization models, I often encountered situations where the supply chain optimization model would make decisions to produce items even when there was no demand. This blog discusses different scenarios that led to the optimization models producing and storing excess inventory.

This blog breaks down the impact of changing replenishment frequency on inventory and service levels from a mathematical perspective.

One flick of the wrist triggers a wave of disruption that grows the deeper it penetrates the supply chain. This blog explains the bullwhip effect, how the pandemic exacerbated it and tips on how to mitigate the effect.

A lot of projects propose to deliver ROI through lower levels of inventory. Servicing the demand at desired service levels with lower inventory should save the company some money. But how, exactly?

Successful demand planning requires a stable and sustainable planning process that is continuously reviewed and improved.

If you're looking to improve your supply chain management systems, these quick tips can help you get started.

In today’s highly globalized economy, no country can remain isolated or insulated from the outside world. The world is so interconnected that one hiccup can cause a myriad of issues downstream.

When engaging in capacity planning, it is important to consider the product mix and seasonality of your business to ensure an effective and accurate outcome.

National Puzzle Day is January 29th. It is a day Arkieva celebrates because the ongoing challenge of smarter supply chain decisions involves supersized puzzles and games. This year we will focus on probabilistic forecasting using the board game Risk.  This blog will show how Monte Carlo Simulation can be used to estimate the average number of “wins”, but critically the range of possible “wins” across some interval.