1️⃣ Align on Data Definitions – Standardize key metrics and terminologies to eliminate confusion among stakeholders. 2️⃣ Establish a Single Source of Truth – Use centralized dashboards or repositories to ensure consistency in data access and interpretation. 3️⃣ Validate and Cross-Check Data – Implement data quality checks and involve multiple perspectives to verify accuracy before making decisions. 4️⃣ Leverage Visual Representation – Use graphs, charts and dashboards to make complex data easily understandable and reduce misinterpretations. 5️⃣ Foster Collaboration & Clear Communication – Regularly engage cross-functional teams to align insights, clarify assumptions and drive informed decision-making.

When facing data interpretation discrepancies, I'd first facilitate a meeting with all involved parties to openly discuss the differing interpretations, focusing on the underlying assumptions and methodologies used. Visualizations and clear documentation of the analysis process can help clarify where interpretations diverge. If necessary, revisit the original project goals and analysis plan to ensure everyone is aligned. If the discrepancies stem from data quality issues, we'd address those before proceeding. Throughout this process, maintaining open communication and documenting all decisions made is crucial to keep the project on track.