Skip to content

Latest commit

 

History

History
25 lines (25 loc) · 2.3 KB

How_To_Ask_The_Right_Questions.md

File metadata and controls

25 lines (25 loc) · 2.3 KB
Raw
  1. Goals
  2. Objectives
  3. Question the dataset given (this should be done after scoping)
  4. Have empathy with stakeholder who has pain point and business objective as well as business expertise
  5. What are the requirements of the problem?
  6. What are the assumptions and constraints?
  7. What resources are available? This is in terms of both personnel and capital, such as computer systems (GPU, CPU available), instruments etc.
  8. Risks and benefits of project:
  • What are the main costs associated with this project?
  • What are the potential benefits?
  • What risks are there in pursuing the project?
  • What are the contingencies to potential risks?
  1. Define success criteria to evaluate project
  • what do you hope to achieve by end of project
  1. To illustrate how these different dimensions come together and can help you maneuver strategically through the data, I’d like to use a GPS analogy. You start by understanding the audience’s starting point (their problem or current state), and then you seek to learn what their intended destination is (their desired outcome or future state). You examine their route and mode of transportation (actions or activities), and then evaluate the progress to their goal (measures or key metrics). This simple formula ensures you don’t get lost in the data labyrinth and positions you to ask the right questions of the data.
  2. Be Like a Detective
  • asking series of questions to get to the root problem
  • look for anomalies
  • keep asking questions until hypothesis is formed
  1. Test hypothesis to get evidence to support or refute it
  2. Be Relentless
  • don't follow a forumula - continually be observant, curious and ask questions about what may be missing
  1. Be Iterative
  • We ask a question, discover our first effort to answer is incomplete, reshape our understanding by bringing in new data, rework our hypothesis, adjust our questions and so on. This process, referred to as iterative analysis, is central to answering the undefined questions that sit at the heart of any big business decision. Finally, remain vigilant about staying open to new possibilities as you integrate additional information. Keep going until you reach a reasonable degree of certainty that you have an accurate understanding of the problem and have determined some clear action, or set of actions, to be taken.