Two keys to successfully collecting data and uncovering valuable insights from your data projects are context and culture. Bringing in data from different sources and connecting more data points will provide more depth to the analysis. Your organizational environment will also affect how the data project proceeds and the results it achieves.
However, your internal team comes with organizational biases. Some employees tend to focus on the issues in front of them rather than the project as a whole. It’s quite common for team members to churn on incremental improvement, where they strive to accomplish that “1% more” threshold, rather than focusing on the overall goal. In doing so, they can inadvertently set back the entire data project.
Get Out of Your Own Way
According to a Gartner survey and a study from the Harvard Business Review, data projects failed most often due to internal roadblocks (e.g., company politics, insufficient organizational alignment, management resistance) rather than external factors. Too many organizations feel the need to compete “on the edge” due to competitive pressures. They look for ways to remain relevant, to stay (or get) ahead of competitors or to make better, more informed decisions. As a result, they drive the organization to pursue more output from the same input, failing to recognize that the data project continues to provide diminishing returns.
This way of thinking can create organizational and cultural habits that impede progress and the pursuit of meaningful results. If leadership is narrowly focused on the current challenges instead of the long-term strategy, they are likely not steering the team toward where they could have the most significant impact. This fire-drill approach frequently compels them to adjust their priorities haphazardly, often causing them to lose sight of truly strategic progress.
Focus on the Primary Goal
How do you remove this type of friction from the process of improving data systems and getting results from projects? Start simple by identifying a primary, identifiable goal. Determine the incremental, demonstrable improvement that you can make in your data project. Whether your team views this as a pilot project or a proof of concept, the goal is demonstrating value-add to the organizational data-insight. Use this primary goal to guide all of your team’s efforts.
The success of your data project depends on stepping back to take an unbiased look at the goal or outcome that can drive improved decision-making, a clearer view. Set your goal to deliver a tangible degree of actionable, useful data. This becomes the foundation for completing the data project and reaching the established outcome.
Avoid trying to engineer the perfect plan at the outset of the project. Trying to reach the ideal starting point could interminably delay your efforts. Also, don’t let your organizational culture interfere with the pursuit of real results. Rather than “boiling the ocean” with your goals, engage in an honest appraisal up front of what is crucial to pursue as the main outcome. Treat other factors as “nice to have” so they don’t prevent you from achieving the desired result – tangible value-add – for your data project. Then continue to build on those early successes.