Your research team is divided on data interpretations. How can you ensure everyone is on the same page?

It's easy to get lost with all the multitasking/distractions, and sometimes we forget why we started. It's helpful to go about it in certain ways. E.g. starting with a good chat with your client partner to figure out the Central question. I find this the most fun. Once you’ve nailed down that central question, it guides everything else you do, from coming up with the right questions for your survey, to crafting an analysis plan that really digs into the information that helps answer the central question/all things associated with it. Ultimately enabling you to build a powerful narrative that has the central question at it's heart. The result; A focused, engaging, interactive, team driven education in Brand! Something I learnt at Kantar.

Heterogeneous views on Data interpretation within a team is not necessarily a bad thing. It brings in varied perspective and helps in plugging gap areas and reducing positive outcome biases. The larger direction for data interpretation should include: ?? Data analysis is done with the specific goals and research #questions ?? Research #objectives are equally important and data interpretation should be able to provide answers to one of the research objectives ( Positive or negative) ?? All interpretations (and resources) which provides unintended outcomes should be devalued / deprioritised ?? All interpreted data should be checked for #validity and #reliability, in addition to sample size and possible outliers and #biases.

To ensure alignment among the research team on data interpretations, we can: - Bring the team together to discuss the different interpretations openly & review the data collectively. - Define Clear Objectives as to what questions the data is meant to answer & what business goals it aligns with. - Discuss and agree on a standardized approach or framework for analyzing and interpreting data (e.g., hypothesis-driven analysis). - Focus on data-backed arguments rather than opinions, ensuring interpretations are based on solid evidence. - Summarize and document the agreed-upon interpretations and conclusions for future reference and clarity. - If needed, bring in a neutral expert to provide an unbiased perspective.

Goals don't determine outcomes and vice versa. It is good at the start of every research to have a strong hypothesis as well as several action standards to guide the team in making relevant next steps, especially when the fieldwork is time consuming and expensive. Test it against your hypothesis and not to support your goals.

As a project manager, it's crucial to keep your team aligned and focused on the original research objectives. By revisiting these objectives and restating them when interpretations diverge, you can refocus discussions and ensure that everyone is working towards the same goals. Encourage your team to constantly ask themselves if their analysis is helping to answer the core research questions or if it's veering off track. This will help keep interpretations grounded in the intended outcomes of the research, ultimately leading to more successful and impactful results. #projectmanagement #researchobjectives #teamalignment #focusonoutcomes

Creating a culture of open dialogue within your team is key to resolving differences in data interpretation. By establishing a safe space where all team members feel empowered to voice their opinions without judgment, you can harness the power of diverse viewpoints. Emphasize the importance of discussing these differences to gain a more nuanced understanding of the data. When team members actively listen to one another and collaborate to build upon each other's insights, it can lead to a more comprehensive interpretation that everyone can stand behind. #teamcollaboration #opencommunication #diverseviewpoints #datainterpretation

Visual aids can be incredibly effective in clarifying complex data. When your team is divided, presenting data visually can help in identifying where interpretations differ. Use charts, graphs, and infographics to make abstract data more concrete and easier to grasp. Visuals can highlight trends and patterns that might be missed in spreadsheets, helping your team to see the data from a new angle and potentially reconcile differing viewpoints.

Dentro de los criterios, además de los objetivos, es importante considerar la metodología que orientará el análisis, así como limitar las fuentes. Puede tomarse como un rompecabezas: ?qué estamos buscando? si se trata de influencia, correlación, consecuencia, etc., se deben identificar las variables dependientes e independientes. Una vez iniciado, podemos comenzar a sumar las piezas a través de nuestras categorías de análisis e indicadores. Finalmente, es de mucho valor construir información desde la interculturalidad e interseccionalidad.