How OKRs Complement Data Science

Objectives and Key Results (OKRs) is the fundamental aspect of goal-setting and revolves around improved focus, increased transparency, and better alignment. This is done by organizing employees and their work towards achieving common objectives. Since Data Scientists constantly drift into enduring research or optimizing less-valuable metrics, which often leads to wasted time and resources thereby endangering a successful delivery, integrating OKRs enhances strategic guidance and measurability, which help you achieve your project goal. The underlying factor behind Data Science is to fulfill a goal. The frame or yardstick of goals might vary from researching a new model to creating a prototype for improving an existing system. Whatever might be the quest, accurate goal-setting is paramount for Data Science projects. Data Science projects are well-suited for accurate goal-setting because we can compare the key results of our model with the required metric. It’s a common knowledge that product management is a science of experimentation and discovery, hence basing predictions solely about and on user behavior, may go wrong sometimes. It is a natural human instinct to assume that our rational assessment of a problem, based on our past experiences, will yield sound conclusions and represent the likely sentiment or behavior of…

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