Part 1: How Natural Language Processing (NLP) Can Benefit the Supply Chain

As more and more individuals utilize supply chain software, there is a need to simplify its usage. The next step in evolution can be Natural Language Processing (NLP) where the user expresses a desire in plain language, and the software translates it to queries in the background. This and other use cases such as the automation and analysis of content have made NLP an area of prominent growth.

Tools of the Trade: National Puzzle Day, Probability and the Board Game Risk

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.

By |2022-09-20T08:22:58-04:00January 25th, 2022|Supply Chain Optimization|

How “Forecastable” is Your Data? It’s Complex Anyway You Look at It

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.

Data Science Without Modeling Impact is a Path to Disaster – Simulation to Explore the Impact of Group Size on COVID-19 Spread

In this blog post, we will briefly review some examples of being “COVID-19 adrift” with just data and then focus on the primary task – demonstrating how modeling can be used to understand the impact of group size on COVID-19 spread.

By |2024-02-21T13:54:34-05:00December 1st, 2020|COVID-19, Data Science, Demand Management, Supply Planning|

Data Science Tools of the Trade: Monte Carlo Computer Simulation

Monte Carlo Discrete Event Computer Simulation is a particularly powerful and flexible “tool of the trade” for a wide range of challenges in supply chain and operations management. This blog provides some basics on MCDECS, the next blog will use MCDECS to explain why limiting the size of a gathering helps reduce the spread of COVID-19.

By |2024-02-21T13:56:05-05:00November 24th, 2020|COVID-19, Data Science, Machine Learning|

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