Friday, October 22, 2021
One of the most valuable skills I’ve gained in my short time as a data/decision scientist is understanding the context of my work. It helps with maximizing the value I bring to the business, communicating the results of my analyses, and with prioritizing my work. In my experience there are a few context areas that I have found useful: stakeholders, your team, and the business. Understanding the context around these areas can lead to more impactful work, faster lead times, and better value-added project prioritization. These items seem obvious, but the impact can be tremendous.
While understanding the project requirements is important, it is also important to know how and why those requirements were determined. Often there are assumptions made within an analysis/project based on initial requirements gathering efforts. Understanding the context that stakeholders are working within can help limit the number of assumptions, and ensure assumptions are within an acceptable range of risk. Team context helps to ensure members are working on items that maximize their learning experience while making sure they are providing maximum business value. This leads to better team morale and a better product. Finally, business context helps analysts understand where they sit within the organization and how the users of that analysis operate. This is essential when building a tool (Dashboard, ML model, etc.) that has end users within the business, helping the analyst stay ahead of questions that are likely to be asked in the future and build the tool in a robust enough way to prevent additional re-work.
Understanding the context can be overlooked while trying to find the right algorithm, or analysis design, but can be the most valuable part of a project and is essential for ensuring maximum value for the business while maintaining a happy team environment.