# Navigating the Data Profession: The Three-Way Tug-of-War
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Chapter 1: The Data Landscape
As a data executive reflecting on the field, I often ponder the most critical aspect every leader in the data space should understand. The answer invariably leads me to the concept of the three-way tug-of-war that data professionals currently navigate. If you're unfamiliar with this notion, it encompasses three distinct approaches: The Dinosaur Way, the Wanted It Yesterday (WIY) Way, and the Fear of Missing Out (FOMO) Way.
Let’s delve deeper into each of these approaches.
Section 1.1: The Dinosaur Way
In nearly every established organization, legacy systems are prevalent, and data professionals often find themselves dedicating countless hours to manage these outdated systems. Much like the dinosaurs of Jurassic Park, these legacy technologies stubbornly persist within the operational framework of the organization. Completely eliminating them is akin to achieving a meteoric extinction event, primarily because the organizational culture is deeply intertwined with these systems.
These legacy platforms have proven their worth over time, and data professionals are tasked with keeping them functional. However, the underlying technology of these systems is often unfamiliar to current data practitioners, and there is minimal support available both internally and externally. Furthermore, these systems were likely constructed by personnel who have long since departed, making maintenance a significant challenge. Despite this, data professionals often find value in certain aspects of these "dinosaurs."
Section 1.2: The Wanted It Yesterday (WIY) Way
Another challenge faced by data professionals is the relentless demand for data from business units. A data team’s existence hinges on the business's need for information. Consequently, data professionals must juggle a myriad of requests from various business sectors, ranging from analyzing historical trends to evaluating current performance and forecasting future outcomes.
In a data-centric organization, data professionals are crucial to its operations. They should be inundated with requests aimed at enhancing every aspect of the organization. However, it often happens that data teams are only consulted in the latter stages of a project when issues arise. In these situations, the data professional's role shifts dramatically, akin to a paramedic responding to an overturned truck on a busy highway, attempting to salvage a poorly conceived initiative.
It's essential for executives to recognize that the necessary data for a project may not be collected or readily available. Relying on proxy data gathered from casual sources, like a conference tagline or an announcement from a sister company, carries significant risk. This piecemeal approach can lead to incorrect conclusions and ultimately increase the chances of failure. To mitigate these risks, organizations should involve data teams early in project planning, requesting feasibility studies and ensuring a data-driven strategy is in place.
Section 1.3: The Fear of Missing Out (FOMO) Way
Looking ahead to the data profession in 2033, I suspect many data professionals will reflect on how much time was spent learning technologies that were never utilized. The allure of new and shiny tools promising ease of use and enhanced productivity can be irresistible. This often leads data professionals to explore and promote these technologies, driven by an underlying fear of missing out.
While the FOMO phenomenon encourages curiosity and staying updated, it's worth noting that a significant majority of these technologies may not endure the test of time. Forecasting which technologies will prevail is challenging, as it depends on various factors aligning perfectly to capture the interest of data professionals.
Chapter 2: Finding the Right Balance
So, how should one navigate these competing demands? It’s a thought-provoking question. Each of the three ways will vie for your attention throughout your career. Focusing solely on the FOMO approach may lead to acquiring skills that go unused in mainstream enterprise settings, while concentrating only on the WIY perspective may result in missing out on emerging technologies that could enhance your work. Conversely, dedicating time to the Dinosaur Way might limit career advancement opportunities.
The ideal solution may seem to involve establishing three distinct teams to focus on each area. However, attracting and retaining talent across all three paths can be quite challenging. Young professionals may be drawn to the excitement of FOMO, while seasoned experts might gravitate toward WIY for career development, leaving the Dinosaur Way struggling to find interest.
Therefore, a balanced approach is necessary, devoting time to all three areas. A suggested guideline for time allocation might look like this:
- Dinosaur Way: 25%
- WIY Way: 50%
- FOMO Way: 25%
These figures are not rigid rules but rather loose guidelines. Understanding the history of past methodologies is crucial for shaping the future. Ignoring historical knowledge can lead to repeating previous mistakes.
Additionally, the pace of technological change can influence how time should be allocated. Rapid technological advancements may necessitate a shift toward the FOMO approach, whereas gradual changes could allow for more balanced time distribution.
Do you resonate with this three-way tug-of-war in the data profession? I invite you to share your thoughts on how you would allocate your time among these paths. Until next time, happy learning!
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