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Techniques for brainstorming and generating new ideas
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How to recognize and overcome limiting beliefs
Creating a scope for a data problem
We can find structure when we create the scope for a data problem. A scope is the outline of a story of why we are focusing on this problem.
The scope of a project consists of four parts, which is expressed as the mnemonic CoNVO.
- Context
- Needs
- Vision
- Outcome
When a problem is well-scoped, we will be able to talk about the project easily. The story will have context, conflict (the need), a resolution (the vision) and a happy ending (the outcome.) Once we have done the thinking using the CoNVO structure, we can go and collect the data.
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MORE IDEAS ON THIS
First why, then how
Most people approach data the wrong way: They start with a data set, then use their favourite tools and techniques on it. This produces a narrow set of unsurprising results.
When we want to gain knowledge from the data, we should first do some thinking.
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Outcome (O)
The data scientist wants to know how the data and/or insights will be used. How will it be integrated into the organisation? Who will use the data, and why?
An example of outcome: The marketing team needs to be trained in using the model (or so...
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Vision (V)
Vision is when we take a glimpse of what it will look like to meet the need with data. The vision consist of the following:
- A mockup explaining the intended results: It could take the form of reporting the outcome of the analysis in a few sentences, a ...
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Needs (N)
What needs could be fixed by intelligently using data? When we clearly explain a need, we are showing what could be improved by better knowledge.
An example of needs: We want to place our ads in a smart way. What should we be optimising?
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Context (Co)
We find context when we know who we are working with and why they're doing what they are doing. We learn the context when we talk to them about their long-term goals. The context provides a project with larger goals and helps to keep us on track.
An example of c...
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CURATED FROM
IDEAS CURATED BY
Thinking With Data is not about how to do data analysis but about first working out what the problem is that you're trying to solve.
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Related collections
Other curated ideas on this topic:
Components of a good story
- Characters. Every story features at least one character, and this character will be the key to relating your audience back to the story.
- Conflict. The conflict is the lesson of how the character overcomes a challenge.
- Resolution.
Setting goals for a new year
- Setting goals is a motivational technique, and when done correctly, it can be effective to help you solve a particular problem.
- We all have an idea about the importance of setting goals, but there is a science behind setting goals and executing them.
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