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Practical Tips for Executing Data-Driven Innovations

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As a part of a larger program put on by the US Chamber of Commerce and its Foundation, I presented some thought-starters (action-starters, really) for people interested in executing their own "data driven innovations".

Having been at the front lines with some of the world's most talented designers, engineers, social scientists, analysts, product managers, economists, history majors, journalists and artists, I've learned a thing or two about how to structure an interdisciplinary team and how to apply the Agile development methodology for successful, innovative outcomes.

Where I innovate: http://madebymany.com/

The full report: http://www.uschamberfoundation.org/future-data-driven-innovation

Veröffentlicht in: Daten & Analysen, Technologie
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Practical Tips for Executing Data-Driven Innovations

  1. 1. how to execute your own DATA-DRIVEN INNOVATIONS (practical tips from the front lines) @LeslieBradshaw of @MadebyMany & @USCCFoundation #Data4Good @uschamber 10.7.14
  2. 2. What: Data Literacy Design by: Jehoaddan Kulakoff Framework by: Simon Steinhardt & Leslie Bradshaw
  3. 3. Mathematicians Sociologists Engineers Journalists English Majors Information Architects Artists Economists Anthropologists Graphic Designers Who: Diverse Team Subject Matter Experts “Doers”
  4. 4. How: Make Test Learn Framework by: Made by Many
  5. 5. How: Make Test Learn Prototype (various fidelity levels) Real Users Actual Customers True Stakeholders Withhold Judgment Analyze Feedback Let the Data Speak Small Batches Simple Features
  6. 6. How: Make Test Learn Prototype (various fidelity levels) Real Users Actual Customers True Stakeholders Withhold Judgment Analyze Feedback Let the Data Speak Small Batches Simple Features “Small Data”
  7. 7. Paper Prototype Written Hypothesis Keynote Prototype Flinto Prototype HTML/CSS Prototype MVP Prototype Validate / Refine Hypothesis Validate / Refine Hypothesis Validate / Refine Hypothesis Validate / Refine Hypothesis Validate / Refine Hypothesis How: Small Batches, Off Domain Before Full Systems Integration (mobile only)
  8. 8. Alpha Version MVP Prototype Beta Version Integrate Systems Mass Market Continue Iterating How: Continuous Innovation Validate Hypothesis Refine Based on Usage Data + Feedback
  9. 9. Related Plug: U.S. Chamber of Commerce Foundation’s Research Report on The Future of Data-Driven Innovation http://www.uschamberfoundation.org/future-data-driven-innovation My Chapter: Full Report: http://www.uschamberfoundation.org/great-data-revolution Design by: Beutler Ink
  10. 10. DO STAY IN TOUCH :) Email: leslie@madebymany.com Twitter: @lesliebradshaw Managing Partner (NYC Office): http://madebymany.com/ Fellow: @USCCFoundation Related Research: http://www.uschamberfoundation.org/great-data-revolution

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