How can you make decisions when data is incomplete?

To make decisions when data is incomplete, remind yourself of what's important, the priority, your organization's why and that can provide enough direction where there are loopholes. In actuality, we all make decisions with incomplete data all the time, its not new. But it's also very paramount to question our biases and assumption by discussing openly with people of different perspectives to be sure that decision aligns with the why because at times we make alignment assumptions and we can genuinely be wrong.

Los supuestos son una realidad con y sin datos completos. Lo realmente importante es realizar la suposición en base a experiencias previas, situaciones con variables similares, diversos puntos de vista, comparativas y quizás un plan de acción alterno.

When faced with incomplete data, consider gathering more information if possible, weigh the available evidence, identify key factors, and use logical reasoning to make an informed decision. It can also be helpful to acknowledge uncertainties and be open to adapting your decision as more information becomes available.

Fa?a o melhor uso possível dos dados disponíveis. Analise e interprete os dados existentes de maneira crítica, aproveitando ao máximo as informa??es disponíveis. Utilize métodos estatísticos ou modelos preditivos para preencher lacunas nos dados, quando apropriado. No entanto, é importante reconhecer as limita??es dessas abordagens.

Sometimes people assume having more data will give more insights. Most of the time this is true. However, there is such a thing as too much data. This adds several burdens to the work you are doing (time, cost and scope creep). Be cognisant of what the goals are for your project and assign data thresholds that enable you to get the answers you need.

The key to this issue is to collect more data always if possible. However if that is not possible due to timeline or budget constraints, assess potential alternatives for gathering the missing data or accounting for the data with another variable. For example, perhaps your dataset does not include age of subjects but you have year of birth and month. This would be sufficient to calculate age and attribute this to each subject without collecting more data.

When gathering data it is always best to have a framework in place beforehand. Understanding why you seek to collect the data, don't just begin collecting at random. Garbage in... Garbage out. Categorize the different types of data you seek to collect and try and understand beforehand if you have selected the best data to analyze before beginning. The worst thing possible is to spend 6 months collecting data only to later become aware that it is entirely unusable. I would even go as far to make a test run with fake data inputs to see if you are able to analyze what you would like to do before committing to data collection.

With incomplete data, the analysis can lead to incorrect and biased decisions so I rather to spend more time to have an integrated dataset which covers all the aspects, then we can rely on the story it says.

The cost of Too little data is the potential outcome of the project. The cost of Too much data is the potential time of the project. Finding the balance and making a decision to move forward is better than inaction altogether. Let’s work on Progression over perfection. Action over inaction every single time! The time taken for the gathering “efficient” data can sometimes stifle the growth and progression of projects. I believe it’s important to accept that data, people, machines and experience will continue to grow and evolving over time..

When we don't have adequate data we should gather more related data's which revolve around it. It will help us to build a rough insight about the needs of actual data . Not accurate but, we can get some or the other hint which can help in getting to tackle the situation up to a certain point. So, we should try to get and gather more and more data for a better result and understanding. Hope this helps to get an idea regarding importance of Gathering more data for a good approach.

Una herramienta importante ante situaciones como la escasez de datos es la estimación de la incertidumbre. Por ejemplo, se está desarrollando una campa?a comercial en una zona geográfica nueva que lleva poco tiempo en marcha y hay pocos datos de conversión, pero debido a un imprevisto hay que tomar la decisión inmediata de si es rentable seguir con la campa?a o no. Es este caso, sería posible utilizar los pocos datos de conversión disponibles para, mediante la aplicación de una distribución estadística, estimar la incertidumbre sobre la conversión y en base a eso poder tomar una decisión más informada.

It's possible to use various software programs to compare and gain deeper insights from data. To illustrate, in my recent project on Bank telemarketing strategies, I made use of three different software programs to analyze datasets and compare two ML classifiers. Specifically, I employed Rstudio, SAS software, and Jupyter Notebook for comparison. This approach aided me in making informed decisions and extracting valuable insights from the data.

Scrutinize the gathered data, focusing on key factors the influence the decision. Apply analytical tools, statistical methods, or qualitative approaches to extract meaningful insights from the available information.

Ante el análisis de datos, recomiendo la técnica PESTEL ya que facilita un análisis global al considerar múltiples variables (Político, Económico, Social, Tecnológico, Medioambiental y Legal). Por otro lado, un modelo muy utilizado, que es sencillo y transversal, es el análisis FODA, el cual permite visualizar variables internas y externas (fortalezas, oportunidades, debilidades y amenazas). Marcos como estos facilitan el establecimiento de correlaciones para idear soluciones con una perspectiva más efectiva.

Trend analysis and forecasting methodologies are remarkable tools to analysis data over time. Certain widgets (charts, tables...etc) are appropriate with certain data types. For example, use donuts or pie charts for categorical data while use line charts and scatter graphis for numerical data over time. The degree of detail depends on the audience who you will be presenting to.

In situations where data is incomplete, effective decision-making requires reliance on assumptions, available information, and expert opinions. Logic, intuition, and past experiences become valuable tools. For instance, in a marketing campaign with limited customer data, assumptions about preferences can guide decisions. It's crucial to acknowledge, test, and document assumptions transparently. Seeking insights from diverse perspectives and encouraging brainstorming provide alternative viewpoints. While incomplete data poses challenges, a well-thought-out mix of assumptions, partial information, and collaborative insights can lead to informed decision-making.

In the absence of the complete data, make explicit assumptions based on the available information. Clearly document these assumptions to maintain transparency and guide the decision-making process.

Data will never be 100% complete. Often, market conditions change faster than we can collect the data. Thus, an agile mindset can be useful where appropriate - pilot your decision when possible, check pilot results quickly and amend your next steps accordingly. Repeat.

Personally, the need to some educated guesses or certain assumptions would be a dire requirement. State such assumptions and recognise their potential influence on the decision-making. Communicate openly the limitations and uncertainities in the currently available data.

Making assumptions based on logic, intuition, experience, or expert insights is valuable, provided they are well-reasoned and informed. Relying on past experiences, domain knowledge, or established principles can help in formulating more educated assumptions. It's essential to balance intuition with evidence and expertise to ensure that assumptions are logical and aligned with the context.

There is always a way, if there is a will. You will always have alternatives for the critical decisions you've made. When you make a decision, it is imperative that you will have its positives and negatives. To control the negatives, you need to look out for other alternatives. The best way to look out for alternatives is creating an Action Plan with a mechanism of ISO 9001: PLAN DO CHECK ACT. PLAN your alternatives by interacting with stakes involved in the decision. DO well in advance what is actually needed to correct the expected negatives. CHECK if the risk mitigation that you're applying is doing well or not. ACT before you get the negative output, implement the alternative and check if it compliments your alternate action plan .

Examining several options in light of conclusions and the data analysed would be a good way to begin. Evaluate each option's potential consequences, advantages, and hazards. Include important parties or stakeholders in the assessment process to obtain diverse viewpoints and insights.

Involving stakeholders in the evaluation process helps ensure that diverse perspectives and priorities are considered when assessing alternatives. Understanding stakeholders' concerns, preferences, and objectives allows for a more comprehensive evaluation. Moreover, considering the impact of each alternative on different stakeholders helps in making decisions that align with broader organizational goals and stakeholder expectations.

I systematically evaluate alternative courses of action. This involves considering different scenarios, assessing potential risks and benefits, and determining the most viable options given the available information.

Evaluate Alternatives(A Game of Chess with Uncertainty): Imagine the market as a chessboard, your decisions like strategic moves, and data the whispers of the wind. Each alternative is a potential piece, with its own strengths and weaknesses. Don't fall for the allure of the grand knight charge – analyze each option with cold logic. Consider the risks, the rewards, the data's whispers, and the potential for unexpected twists. Choose wisely, for a single misstep could leave your king vulnerable to the market's ever-shifting tides.

Decision-making doesn't end with implementation. I establish monitoring mechanisms to track the outcomes of the chosen course of action. Regular reviews allow for adjustments if needed, ensuring that decisions remain aligned with organizational goals.

Once you have implemented your decision, you anticipate a positive output. But, possibilities of having an error is inevitable. You need to build up a continuous and effective feedback mechanism to gather systematic and unbiased opinions/feedbacks from the end-users/personnel or departments that are affected due to your decision. Document the feedbacks and check for any breakthrough suggestions that improve your existing system. Make the expected outcome even better by making suitable changes. Develop a monitoring system that ensures your processes need to be validated on repeated intervals or as you amend your decision. This change needs to be implemented and continuously monitored for future improvements.

Decisions based on incomplete data can be challenging. It's crucial to acknowledge the uncertainty and consider potential risks. Employ strategies like sensitivity analysis or seek additional information to mitigate the impact of missing data on decision-making.

In the realm of urban planning, monitoring and reviewing decisions are crucial for long-term success. After implementing a zoning change, an urban planner would use key performance indicators like community satisfaction and economic impact to continuously evaluate outcomes. Adjustments may be made based on feedback, ensuring the plan evolves and remains effective over time.

Navigating decisions with incomplete data? Embrace the challenge, acknowledging the risk. Transform hurdles into stepping stones by adopting a strategic approach. 1.Embrace the Wisdom of Many: Diversity is crucial. Engage diverse minds for collective insight. It's about finding the right answer together, fostering collective wisdom. 2.Lay Your Cards on the Table: Transparency is key. Communicate openly about data limitations to build trust. A shared understanding creates a culture of collective problem-solving. 3.Prepare for Plot Twists: Anticipate the future's unpredictability. Develop contingency plans – Plan B, C, and D. Multiple strategies ensure readiness for life's curveballs, maintaining control in unforeseen circumstances.

The Black Swan Theory. Nassim Nicholas Taleb's concept of the "Black Swan" illustrates the profound impact of highly improbable events. This theory emphasizes the limitations of our knowledge and the importance of expecting the unexpected.

Consider external influences including geopolitical events, legislative changes, and market trends. These outside factors may affect the context of decision making and offer further context of your analysis.

Tomar decisiones con datos incompletos puede ser desafiante, pero es posible abordar este problema siguiendo algunas pautas y consideraciones, como identificar las limitaciones de los datos, utilizar técnicas de análisis adecuadas, evitar sesgos de selección, considerar la posibilidad de sesgos de supervivencia, comunicar las limitaciones de los datos, establecer planes de acción flexibles, y buscar retroalimentación y aprendizaje.

Quando os dados est?o incompletos para a tomada de decis?o, além de todos os passos já mencionados, fundamental retomar os direcionadores estratégicos da empresa. Estar alinhado com a estratégia da empresa deve ser ponto imprescindível para a tomada de decis?o, que muitas vezes supre lacunas de dados. Ter um modelo para tomada de decis?o, com critérios pré definidos de acordo com os objetivos estratégicos da empresa, contribui para acelerar o processo. Direcionamento estratégico juntamente com um modelo de prioriza??o s?o a??es que contribuem para sair do microgerenciamento e suprem, em muitos casos, a lacuna de dados.

A tomada de decis?o se formos ver pelo angulo mais neurocientífico seria a op??o dentre várias analisadas na camadas de raciocínio/ pensamentos ao qual nosso cérebro funciona. A decis?o tomado seria o consciente tomando ciência da analise profunda realizada, lembrando que nosso cérebro evoluiu para categorizar e classificar informa??es. Eu realmente acredito que a ideia de informa??es insuficientes pode ser um mecanismo de defesa caso a decis?o mostre n?o ter sido acertada. Dois bons livros que discutem esse ponto que trago s?o BLINK de Malcolm Gladwell e COMO A MENTE FUNCIONA de Steven Pinker.