Data is more available than ever before, and is used by government, civil society, and the private sector to improve processes, products, and services. Data presents an incredible opportunity for innovators to track and analyze progress and results in near-real time. To conduct data-driven design:

  • Focus on measurable outcomes that reasonably define changes from the status quo.
  • Monitor progress and, whenever possible, use counterfactuals to determine if what you are testing is responsible for success or failure.
  • Track costs and quantify benefits to evaluate return on investment.
  • Give important context to quantitative results by using qualitative data to describe the problem you are trying to solve and tell the story of implementing the innovation.
  • Don't be afraid to fail but continue to test and measure results.
  • Questions to Ask

  • How are you defining success (and failure) at the beginning of the project?
  • Which data points are indicative of overall success? Failure?
  • Are changes to the data the result of innovation? Or external factors?
  • What are the benefits and costs of the evidenced changes?
  • Do the changes evidence success or failure? Tell the story.
  • Which solutions could be implemented to facilitate greater success?
  • Checklist

  • Consider the quality and relevance of potential data sources.
  • Hypothesize about which data points should change to achieve success.
  • Develop methods to measure the changes to those data points over time.
  • Determine whether the changes to the data are the result of innovation or external factors. Repeat this process while considering previous results.
  • Determine whether the changes to the data evidence success or failure.
  • Consider which solutions could be implemented to facilitate greater success and implement those changes.