Demand forecasting for small or medium sized food distributors and retails is a tedious, difficult, and perilous activity. Get it wrong and it harms your profits. Spend too much time on it and you don’t have time for other value add tasks.
What is demand forecasting and its types?
Demand forecast refers to the process of estimating how many items consumers are going to buy. Demand forecasting includes techniques which involve both informal methods and quantitative methods such as educated guesses.
Get it right and your profits go up, your efficiency booms, and your stress levels plummet.
You need to start your forecasting of demand by looking at historical data. Historical sales and promotions.
That will help you a little bit.
You need lots data to forecast demand
But then what? What effects your sales levels? Is it the weather, events, traffic, location, or competitors? Do you have multiple locations? How many products do you have – and how do they all behave? There are a high number of valuable insights you can get from your data
You need data – lots of data. How do all these things interact. Think about a simple interaction of 3 things below….
Weather on a Tuesday, in a busy location, in the middle of a half-term holiday – for each and every product. For each and every day. Imagine the data you need to work that out!
Machine learning from your data
This is where machine learning comes into it’s own. In a few hours an AI model can learn all the dimensions that effect your data, and it can ignore those that don’t.
How is machine learning used in prediction?
Using Machine Learning models, businesses can make accurate predictions on what is likely to happen.
But that all sounds too hard – “AI models”?
Just ask catsAi to do it for you – without any Technology or IT. Send us your historical sales, and in a few hours we’ll be predicting your sales more accurately than you thought possible.