The Three Levels of Forecasting Maturity
At IQinAbox we get to speak to a large number of stakeholders in and outside the industry, and when it comes to forecasting - and the use of data to make decisions - there are broadly speaking three categories.
Level 1: Experience based decision making
This will be the type of decisions that come natural to most people: experience based decision. This basically means that we use our experience to plan our actions and make decisions based on what we know works, what worked the last time etc.
There are a lot of companies for whom this will be sufficient, and not least a lot of decisions where this is sufficient, especially if you are dealing with a very stable environment and very predictable conditions. In most cases though, you quickly asking yourself: surely we can use some of the data we already have to automate this, or get better insight...
Level 2: Basic Statistical modelling
...and, of course, you are right. And this where the Excel-sheet (or similar) comes in handy.
You start developing some basic models based on past years' data of when you ordered feed, and maybe even start generating some averages for consumption per pig.
This will improve your forecasts and basic decisions. A simply Google search will show that basically any experiment done in the field of "standard Excel-sheet solution" vs. Human being, always ends up with the human losing...
Level 3: Advanced statistical modelling
...but they will also show that there are even more advanced ways of looking at data, that outperform Excel every time - and yes, you have probably guess that this is what IQinAbox's solution is.
The models IQinAbox use are dynamic, so when the world changes, or even a small batch of pigs change, the model changes along with it. The models do not rely on averages, or needing two years of new data to come up with a new view of the world. This is done "on the fly". It also means that you can use the model to catch outliers, not just "when everything is within the norm". 2020 and 2021 will for most industries have been in that category.
Furthermore, because it is done in the cloud, you can have your own data set, but you at the same time benefit from the millions of calculations that have been done on other similar data sets. Is there no end to all the great things that can be achieved?
What do I do if I am not at level 3 yet?
Well, to be honest, not a lot of producers or companies are at level 3. But the world is moving in that direction, and fast. The more complicated the issue is, like reducing CO2 or managing your supply chain during a global pandemic, the more we need advanced statistical models that can manage multiple variables dynamically.
They are not going to be perfect, but they will be far, far better than anything you have experienced before, and even to some extent mitigate some of the issues of poor data quality...but never entirely :-)