Try saying ‘probabilistic’ three times fast. It’s a bit of a mouthful. However, it’s more than just a tongue-twister, it’s a great tool for predicting inventory needs. The root of probabilistic is probability and that’s exactly what the probabilistic model is based on — probability.
So I bet you’re wondering how probability will help you with your inventory control. We’ll get into that shortly, but let’s understand what probabilistic really means and then we’ll find out how it can be applied to inventory control.
What is a probabilistic model?
This is a model based on probability that helps predict future events while taking into account randomness and variables that can occur. Probabilistic modelling looks at different options that can take place in the future by calculating random options into the equation.
When you implement a probabilistic model, these variables add a level of complexity and information around uncertainty. Of course, its aim is not to create exact predictions, but it can help hypothesise the different future events likely to happen.
If you want exact predictions, you need to turn towards deterministic modelling. This strips out all of the random variables and leaves you with an exact prediction. This type of modelling helps predict future demand, without taking on board any uncertainties. It gives you a single outcome for an event. It’s more of a black and white prediction, where the answer is clear.
Probabilistic modelling would be several different shades of grey, with each grey colour representing a different prediction with different variables and randomness plugged into it. This is a much more realistic modelling tool than deterministic.
How is the probabilistic model used in inventory control?
Probabilistic modelling is a much more realistic approach to modelling. When used to predict future demand of products, it allows you to look at a variety of outcomes and plan your inventory purchasing, lead times, and production.
When you use probabilistic modelling, it can significantly help the way you approach inventory replenishment. Predictions might not just take into account previous demand and demand patterns. Rather it might take into account a variety of weather patterns that have been known to impact shipping at different points of the year. It can advise on a suggestion of times that might be more desirable to place replenishment orders.
The probabilistic methods take into account information readily available about the economy, geological issues and engineering data to collate an estimate for healthy inventory stock quantities. It will look at the related probabilities of each inventory stock items and the prospects that surround them.
People don’t like uncertainty, despite it being a key part of life. Probabilistic modelling tries to take the uncertainty and lessen it. You can create probabilistic inventory prototypes with a variety of supply and demand situations. It is more applicable to real-world scenarios and people can generally relate to the outlined circumstances. However, probabilistic models can be cumbersome and the more variables and randomness that’s included, the harder it is to analyse.
Overall, probabilistic modelling can play an important role in planning and supporting your inventory control.
Article by Melanie Chan in collaboration with our team of Unleashed Software inventory and business specialists. Melanie has been writing about inventory management for the past three years. When not writing about inventory management, you can find her eating her way through Auckland.