You will most likely be questioned about your analytical approach when your findings do not match preconceived expectations. In such cases, clearly demonstrate to stakeholders how your steps best align with the original objectives. I typically include a procedure slide in my deck that summarizes the methodology in layman's terms; sometimes an appendix with further information is also useful. Once, I had to send an addendum outlining the inclusion and exclusion criteria for the dataset. It boils down to helping stakeholders understand the rationale, particularly regarding long-term implications. Be open to feedback and, if necessary, revisit your analysis, exploring ethical alternatives that ensure accuracy and informed decision-making.

In a recent project analyzing patient outcome data for a healthcare provider, I encountered skepticism from stakeholders who questioned the accuracy of my findings. I first walked the stakeholders through the data collection process, explaining the rigor behind the inclusion criteria and the statistical methods used, such as regression analysis to control for confounding factors. I then showcased the tools used, including R and Excel, highlighting their appropriateness for the analysis, and addressed each concern by referencing specific data points, ultimately providing confidence in the validity of my results. This experience highlights the importance of being prepared to defend methodology as it builds trust and confidence.

El escepticismo de colegas o clientes sobre los resultados es una oportunidad para reflexionar sobre la importancia de no solo realizar un análisis sólido, sino también saber comunicarlo y defenderlo. Por eso es fundamental tener una comprensión profunda de la metodología aplicada, estar preparado para explicar las decisiones tomadas y ofrecer evidencia clara que respalde los resultados. Es clave ser transparente con el análisis de datos y mostrar confianza en la rigurosidad del proceso. Además, el uso de ejemplos y visualizaciones puede ayudar a transmitir la validez de los hallazgos de manera más accesible. En resumen , el exito radica en tener habilidades técnicas y comunicativas para defender un análisis de datos.

Depends on the stakeholder. Some stakeholders question it if it's against their expectations, usually asks against the validity of the data (explain how the data was validated), the source of the information (explain sources in previous slides) and expresses "do the numbers feel right". Another tactic for less senior stakeholders who like the deep dive, we do it together, and in some cases purposefully get their input so they don't question that validity of the data in future.

One thing I’ve found helpful is breaking down the analysis in non-technical terms, showing how each step directly ties to the business goals. This makes it easier for stakeholders to see the logic behind the process and its relevance to decision-making. Actually, I disagree with the assumption that alternative methods would lead to different results. The approach I used was carefully selected based on the nature of the data and desired outcomes, following industry benchmarks. An example I’ve seen is when a stakeholder questioned a similar analysis. After explaining the methodology in detail, they recognized its value and ultimately used the insights to drive a key project forward.