Everyone in a modern company wants to add value. This should be no different for a data scientist working on an idea, a project or a product. But how can one know that their activity adds value? By focusing on things that matter: matter to engineers, business leaders, product teams, customers, stakeholders, everyone. If data scientists lock themselves in their ivory towers creating proof-of-concepts, doing "research", cleaning and labelling data, running experiments far away from frontline KPIs and user feedback, no one should be surprised that their activities pure and simple: doesn't matter. This will manifest itself by lack of interest, resources and involvement from other stakeholders of the business.
Make things that matter
Make things that matter
Make things that matter
Everyone in a modern company wants to add value. This should be no different for a data scientist working on an idea, a project or a product. But how can one know that their activity adds value? By focusing on things that matter: matter to engineers, business leaders, product teams, customers, stakeholders, everyone. If data scientists lock themselves in their ivory towers creating proof-of-concepts, doing "research", cleaning and labelling data, running experiments far away from frontline KPIs and user feedback, no one should be surprised that their activities pure and simple: doesn't matter. This will manifest itself by lack of interest, resources and involvement from other stakeholders of the business.