Do your Data Scientists know their WHY?

HBR recently released an article about the impact of Data Scientists understanding of the why behind the work they do. It struck me as odd for a moment because, at Rahab's Daughters, our Data Scientists all do the work of data science for us because the "why" is because we want to assist in exits for those who want out, but we first need to figure out who they are.

Most things are harder if you don't know "why" you need to do them. Data scientists should know the "why" behind a project or analysis in order to ensure that their work is aligned with the goals and objectives of the organization or stakeholders. Understanding the underlying problem or question being addressed can also help inform the choice of methods and techniques used, and ensure that the results are interpreted and communicated in a meaningful way. Also, a clear understanding of the work's context and why it's being done can help data scientists figure out if there are any ethical concerns or biases that need to be fixed.

Data scientists are one of a kind because they can use a wide range of skills and knowledge to find insights and value in data. Most of the time, they have a strong background in statistics and computer science, as well as knowledge and experience in their field. This allows them to effectively collect, process, and analyze large and complex data sets, and use advanced techniques such as machine learning and artificial intelligence to uncover patterns and trends that may not be immediately apparent. Also, data scientists can often explain their findings and recommendations to both technical and non-technical audiences.

Another key characteristic that sets data scientists apart is their ability to think critically, creatively, and inquisitively about data. They are able to formulate research questions and design experiments to answer them, which is a key step to extracting insights from data. They are also able to work together with teams from different departments, using their data-driven insights to help make decisions and drive business results.

Knowing the "why" behind a project or analysis helps data scientists stay grounded by giving them a clear picture of what their work is for and what they want to achieve. This can help ensure that the data analysis is focused on addressing the right problem and that the results are meaningful and relevant to the organization or its stakeholders.

When data scientists understand the "why" behind a project, they are also more likely to consider the ethical and societal implications of their work. By knowing what biases, assumptions, or unintended effects their analysis might have, they can take steps to fix these problems and make sure their work is fair and unbiased.

Also, knowing the "why" can help data scientists keep things in perspective and not get lost in the analysis's details. When they know the bigger picture and goals of the work, they are better able to set priorities, focus on the most important parts of the problem, and explain their results in a way that is clear and convincing.