This blog is based on Episode 14 of our GovEd Talks Video series: Data Informed? Data Driven? Just help me use my data! by Jamie Champagne, Business Analysis Professional at Champagne Collaborations & Author at LinkedIn and Pluralsight.
In today's dynamic business landscape, the buzzwords "data-informed" and "data-driven" often dominate conversations. The real challenge lies not just in possessing data but in utilizing it effectively to make intelligent decisions. Let's embark on a journey to explore the art of posing meaningful questions and harnessing the potential of data for faster, smarter, and more informed decision-making.
Start with a Clear Goal: Know Your Why
Before delving into the vast realm of data, articulate a clear business goal. Why are you exploring data? What specific outcome are you aiming for? Establishing a goal provides direction and purpose, ensuring that your foray into data analysis is purposeful and aligned with broader business objectives.
Master the Art of Asking Questions
Good decision-making hinges on asking the right questions. In your data exploration, adopt the habit of breaking down business concerns using techniques like functional decomposition and the five whys. Scrutinize the "what, why, which, how, where, and when" to gain a comprehensive understanding of your business needs.
Past vs. Future Focus: The Types of Questions
While exploring data, consider the nature of your questions. Descriptive questions delve into the past, focusing on what happened. Move beyond these to predictive questions, pondering what could happen based on past data. However, the real power lies in prescriptive questions, which propel you into a future-focused mindset. Anticipate and predict, aiming for insights that guide decisions for tomorrow.
Leveraging Data: A Simple Checklist
To effectively leverage data, start with a basic checklist. Identify what data you currently have access to and what your team frequently uses. Then, assess what data you need access to for a more comprehensive understanding. Explore alternative sources and consider substitutes for unavailable data to broaden your perspective.
Asking for Help the Right Way: The Art of Collaboration
When seeking assistance with data, approach it with a structured request. Clearly state what data you need and, crucially, explain why you need it. This approach ensures that data experts can align their support with your business objectives, maximizing the relevance and effectiveness of the insights provided.
Separating Correlation from Causation
In the realm of data analysis, distinguishing between correlation and causation is paramount. While correlation identifies relationships between variables, causation establishes a cause-and-effect link. Always question whether an observed correlation implies causation, ensuring that your data-driven insights lead to actionable and impactful decisions.
The Causation Conundrum: Random Correlation Examples
As a cautionary note, consider seemingly random correlations, such as the neighborhood with the highest delivery pizza orders correlating with the highest crime rate. Challenge such correlations by flipping the perspective. If the relationship can be reversed, it might be mere correlation rather than causation.
Conclusion: Empowering Decision-Makers with Data Wisdom
Navigating the realm of data for informed decision-making involves setting clear goals, asking purposeful questions, and mastering the nuances of data types. Whether exploring the past, predicting the future, or prescribing actions, the strategic use of data requires a thoughtful and goal-oriented approach. By adhering to best practices, collaborating effectively, and understanding the subtleties of correlation and causation, businesses can unlock the true power of data and propel themselves into a future of intelligent decision-making.
If you're interested in learning more about data management, consider enrolling in our upcoming course Data Analytics. Our course will help learners to ensure the integrity of the data, turn data into actionable information, and further use analytics to answer specific questions in a visual or another easy-to-use format.
