How to Improve Your Statistical Forecast Using Machine Learning
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.
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.
New tools can use AI to respond to queries, but can they really replace the value in the difference between knowing and acting?
Businesses can almost guarantee a jump in returns following the holidays. How can you account for returns in your demand forecasting?
Each year, visitors read our supply chain blog to take advantage of all that we have shared. This is the round up of our top posts.
Demand planners are facing unprecedented pressures caused by the all-time high number of planning combinations. Supply chain planning software can help.
Demand forecasting is often done in planning buckets such as months or weeks. But what about the pattern of demand inside a period? Whatever pattern it is, a demand planner should strive to understand it.
Every business can benefit from having a proper demand plan. A pivotal part in this process is collaboration.
Is there an equivalent to the Hippocratic Oath for forecasters? What harm(s) can a forecaster easily avoid? This blog explores some examples.
Having a good forecast is essential to demand planning. It ensures the right goods are produced at the right time and reach the right customers. What’s more is that demand planning is situated at the start of your supply chain, playing an integral part in a streamlined supply chain.
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.