How do you balance data and feedback with your intuition and vision when making decisions?

1 Know your goal

Before you start collecting and analyzing data and feedback, you need to have a clear and specific goal for your decision. What are you trying to achieve? What are the criteria for success? How will you measure the impact and outcome of your decision? Having a well-defined goal will help you focus your data and feedback collection and evaluation, and avoid getting distracted or overwhelmed by irrelevant or conflicting information.

2 Use data and feedback as evidence, not as answers

Data and feedback can provide valuable evidence to support or challenge your intuition and vision, but they cannot give you the final answer. You still need to interpret and contextualize the data and feedback, and consider their limitations and biases. For example, data may be incomplete, outdated, or inaccurate, and feedback may be subjective, biased, or influenced by external factors. Therefore, you need to use data and feedback as inputs, not as outputs, for your decision making process.

3 Trust your intuition and vision, but test them

Your intuition and vision are based on your experience, knowledge, creativity, and values, and they can give you a unique and original perspective on the problem and the solution. However, they are not infallible, and they may be influenced by emotions, assumptions, or blind spots. Therefore, you need to trust your intuition and vision, but also test them against data and feedback. You can use data and feedback to validate, refine, or revise your intuition and vision, and to identify potential risks, gaps, or opportunities.

5 Be flexible and adaptable

One of the key skills for creative problem solving is flexibility and adaptability, meaning that you are open to change and learning from data and feedback, and that you are willing to adjust your intuition and vision accordingly. You need to be flexible and adaptable in your decision making process, and avoid being rigid or attached to your initial ideas or assumptions. You also need to be flexible and adaptable in your implementation and evaluation of your decision, and be ready to iterate and improve based on new data and feedback.