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Why One Person Can’t Do Everything In Data

by Christopher Laubenthal

Data roles are often the first subject I discuss when building data literacy. Communicating that there are different roles for various data related tasks decreases the expectation that one person can accomplish them all. This communication becomes a survival tactic if you are one of a few data folks in an organization — particularly when your output increases general interest in data, but not interest in hiring more data staff. This situation might lead to requests for you to perform tasks that you are neither experienced in, nor comfortable with.

Raising understanding around how roles are classified in data can help maneuver this situation. Once people fully understand the divergence in skills between, say, a Data Architect and a Data Analyst, they may be less likely to expect one person to perform both those roles. There has even been growth in data role classification to help define the responsibilities associated with the various job titles and areas of expertise. 

An old, brown brick building on a college campus with a steel gate that is half opened.
Creating data solutions is akin to growing a college campus. It requires a diverse collection of expertise working in unison to make it work. Credit: Pixabay via Pexels.

Here’s an analogy that stresses differences between data roles and elucidates the broad ecosystem needs for data development:

A small college in a remote town is in demand and wants to grow, but hasn’t due to structural limitations. To spur growth, the college needs to incorporate more students (data), because an active student body can generate more research (analysis), find interdisciplinary areas of study (data science), and raise awareness about the school and its accomplishments (information design).

To accommodate an influx of students, the college needs to provide for them. The college thinks a student dorm (data structure) is a good first step. So here some of the steps the college must take to get there:

  • Contract a construction firm to develop and build a new dorm (Data Architects)
  • Contract movers to populate the dorm (Data Engineers)
  • Hire a superintendent to manage the dorm (Database Administrators)
  • Hire residence assistants to work with the dorm’s students (Data Analysts)
  • Hire communications staff skilled in telling student stories (Information Designers)
  • Contract with researchers to study the impact of these students (Data Scientists)

With all these experts working in unison, the college is far more likely to succeed than if it attempted to make a single person carry out each phase of the dorm expansion. It is impossible for one person to build a college dorm, populate it, manage it, work with the students, tell their stories, and research the impact. 

It is impossible for one person to build a college dorm, populate it, manage it, work with the students, tell their stories, and research the impact.

As a result of the collaborative nature of the roles, enrollment increases, but, equally important, so does student activity and published research. The cumulative impact is that the college’s brand grows substantially.

This analogy may not resonate with all audiences, but can be adapted. For our C-suite friends, for instance, the analogy could focus on how a developing company used data to increase yearly earnings.

The key to this analogy is explaining the difficulty as well as uniqueness of each role with kindness and sincerity to your audience. For example, many people can construct a shed, but it takes a different type of expertise to construct a dorm. 

The bottom line: Meet people where they are in terms of understanding and language. Developing literacy in data roles is a process that will likely take more than one analogy, meeting, or even training. Remember, these folks hired you because they know data is important and they want more output because they value the things you have already made.

Christopher Laubenthal headshot
Christopher Laubenthal

Christopher Laubenthal focuses on better data use with visualizations in an organizational setting. He has experience in both for-profit and not-for-profit sectors where he increases literacy, grows culture, and builds data visualizations. Christopher is the Data Design Manager at The DeBruce Foundation, a national foundation whose mission is to expand pathways to economic growth and opportunity. Current projects include his public viz and The DeBruce Foundation’s Career Explorer Tools.

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