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Optimization

As explained in Everyday Data Visualization

An iterative development cycle is a repeated process of developing, evaluating, and refining a product across successive phases.

Optimization is an iterative development cycle: plan, build, get feedback, and repeat. Each pass turns what was learned in the previous one into a better next version, rather than treating research, design, and development as one-way handoffs. section 8.4

Figure 8.7 The three-step iterative development cycle: plan, build, get feedback, do it all again
08-07

The cycle has three deliberately simple steps—plan, build, and get feedback—then loops back. Repetition is the feature, not a sign that something went wrong. section 8.4

Use the cycle at each stage of a visualization project:

  • Plan by gathering questions and requirements, then confirm that they reflect stakeholder needs. section 8.4
  • Build a tangible artifact: requirements document, wireframe, mockup, or development prototype. section 8.4
  • Get feedback from stakeholders and users, then use it to revise the next plan rather than merely defend the current version. section 8.4

A dashboard improves before it looks finished

An early housekeeping dashboard felt unfinished, with problems such as limited space for calendar-view bar labels. Sharing it anyway surfaced ideas for a legend, better use of calendar and line-chart space, and more color and polish. Feedback converted an awkward draft into a clearer final version. section 8.4.2 section 8.4.2

Iteration needs a stopping rule. As changes become smaller and their combined effect no longer justifies the effort, diminishing returns suggest calling the work done. A deadline can impose the same boundary; near it, check the requirements document to verify that the visualization meets its agreed goals. section 8.4.2 section 8.4.2

How Everyday Data Visualization covers it

How deep it goes
Explains the three-step loop and completion criteria, without detailing implementation mechanics.
Examples
Uses a housekeeping dashboard evolving from an uncomfortable draft into a polished version.
What you can do after
Apply it to refine a visualization until requirements are met or further changes yield diminishing returns.
How it connects
Connects requirements, wireframes, mockups, prototypes, stakeholder feedback, and dashboards.

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This explainer was generated by Manning's knowledge graph from the text of Everyday Data Visualization. The section links point to the parts of the book it draws on.