Que faites-vous si vos décisions de coordination de projet manquent de données et d’analyses ?

Gather project data from past projects, team feedback, or industry benchmarks. Analyze this data to identify trends and potential risks. Use these insights to inform your decisions and improve future project planning.

It's crucial to adopt a proactive approach. This involves gathering relevant data where possible, utilizing expert judgment and benchmarking, scenario planning, qualitative analysis, risk assessment, and iterative decision-making. By employing these strategies, teams can make informed decisions despite data limitations, while also laying the groundwork for improving data-driven practices in the future.

When project coordination decisions lack data and analytics, one can: - Gather relevant data. - Leverage expertise within the team. - Make informed assumptions. - Establish monitoring mechanisms. - Adapt and iterate as needed.

Quando não existem dados suficientes para embasar a decisão, é necessário buscar nas experiências passadas fundamentos que possam embasar uma gestão de riscos incial. A partir dessa definição de riscos e premissas, é possível continuar com o planejamento do projeto

When project coordination lacks data and analytics, it poses risks such as uncertainty, bias, reactive decision-making, and missed opportunities. To mitigate these risks, it's crucial to identify, assess, and develop strategies for each risk. This includes seeking alternative sources of information, involving experts, and implementing decision-making frameworks. Continuous monitoring, review, and transparent communication with stakeholders are essential for managing these risks effectively.

Na ausuência de dados, uma ótima forma de se realizar o planejamento é buscando as experiências passadas da equipe. É necessário sempre que possível envolver membros que já tenham uma bagagem anterior para que eles possam contribuir com suas lições aprendidas e ajudar em um planejamento mais preciso

It's an Ideal decision to engage key stakeholders if this kind of scenario occurs. As per previous knowledge and experience, the project manager can take proper actions in this regard.

I'd caveat this more heavily. Intuition is often based in experience (and emotion), so can lead down the wrong path if the situation is truly unique. Maybe: A. Break down the project and any challenges to their core components. Write them out if helpful. See if any of these have parellels to past projects you or your team have worked on, and if you can apply that experience. B. Above all, use logic and 'common sense' in your decision making. You probably already understand the unspoken norms of your industry. Very often that behavior won't change across projects and is a powerful determinant of outcome.

The initial step is to carry out risk analysis in order to identify the problem and various option to solve. Secondly ensure you communicate with relevant stakeholder and brainstorm various recommendation on how to go about that is define the problem to come up with ideal scenario of the required analysis. Once you identify the problem select and understand what data needs to be analysed to improve the baseline situation. Identify also what data needs to be collected to solve the problem. Carrying out data processing and prepare them for further analysis. In this stage it is important to do data cleansing. Finally carry out data analysis to generate knowledge to investigate the problem and find possible solutions &communicate the findings.