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.
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.
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 programming” with regards to supply planning and have cringed at the sound. Over the past few years a new “cringe” worthy term has emerged – “machine learning” which is sometimes used with the term predictive