How to Measure Forecast Errors in Intermittent Demand Forecasting
Stop using traditional forecast accuracy metrics to measure forecast for sporadic demand patterns. Use this method instead.
Stop using traditional forecast accuracy metrics to measure forecast for sporadic demand patterns. Use this method instead.
Most of us have had some exposure to the “AI Awakening” wave that has emerged over the past few years. Of particular interest to Arkieva and its customers is how this “new technology” integrates with the ongoing journey of creating more intelligent supply chain decision-making process to improve organizational performance.
How to determine when to use a best-fit analysis and when to use prediction techniques for demand forecasting analysis.
Is demand management illusively complex? Here's a look at some best practices in demand management and characterization.
Optimizing your supply chain involves looking at the entire process, and not just the initial solution. Here’s an example of how.
Use this example as a starting point to understand the different optimization methods, and when optimization is helpful in supply or central planning.
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.
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.
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.
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.