Create Common Sense Baselines

Excellent insight. Not sure that this is done frequently, even by experienced people.  We used to call this establishing base methods and estimates of results.  Sometimes just starting with:  How is it done today? or How would a domain expert do this today?  Often useful to check correctness, check likely value of results, use with domain partners to create frameworks for the use of results.  Essential to think this up front,  because if you can't, you probably don't have a full grasp of the problem.  Good read below.  With nice realistic example:

First Create a Common Sense Baseline    By Rama Ramakrishnan  Senior Vice President, Salesforce.  

When you set out to solve a data science problem, it is very tempting to dive in and start building models.

Don’t. Create a common-sense baseline first.

A common-sense baseline is how you would solve the problem if you didn’t know any data science. Assume you don’t know supervised learning, unsupervised learning, clustering, deep learning, whatever. Now ask yourself, how would I solve the problem?  .... "