Our latest webinar examines the varying definitions of machine learning and artificial intelligence while discussing how they can be leveraged to improve your statistical forecast.

The adoption of machine learning and artificial intelligence is on the rise, but not at the pace of other transformations. Here are a few reasons why.

This blog discusses how utilizing a semantic parsing method can help a less experienced user transform their data questions into advanced database queries, and how it can help detect errors in datasets.

Natural language processing (NLP) in supply chain software can increase accessibility to more users. Find out how your organization can benefit.

Industry analysts, big-time consultants, and your peers are all talking about technology, digital transformation, and the future of the supply chain. It can seem like a lot of noise given the day-to-day pressure you feel while working to ensure that inventory is on hand and positioned where it is supposed to be. With all you have on your plate, are you aware of the signs that it is time for a change? 

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.

The right technology can provide a solution to maintaining optimal supply chain planning, but how can you justify the investment? 

Most folks involved in Sales and Operations Planning (S&OP) for supply chain management have heard the terms “optimization” or “linear...