Targeted model adaptation is particularly relevant in the fields of artificial intelligence, big data and smart data, and digital transformation. This involves modifying digital models – such as forecasting models or software models – so that they fulfil a specific purpose even better.
Imagine a company using software that predicts how much of a product will be sold in the coming months. If customer purchasing behaviour suddenly changes, for example due to a price promotion, the old model might provide inaccurate results. With targeted model adaptation, the model is then specifically adjusted to the new conditions – for instance, by using new data or altering certain calculations. This keeps the prediction useful and reliable.
The advantage of targeted model adaptation: Models are kept up-to-date quickly and effectively, without having to start from scratch. This saves time and costs. With this method, companies remain flexible and competitive because they can react quickly to changes.
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