Not taking into consideration the downstream application of the model
Technical incompatibility or unrealistic accuracy expectations, if not addressed at the beginning of the project, can lead to delays, disappointment and other negative outcomes. For example, it is common to apply ML to tasks like ‘propensity to buy’ - finding people who may be interested in purchasing your product. If you did not take this downstream application into account from early on in the development, you might well provide the output in a form which is not usable such as an API endpoint, when a simple file containing a list or table supplied to an outbound call centre is all that is needed. Taking our recommendation to Create a Walking Skeleton/ Steel Thread is a great way to avoid this.