This document discusses piloting data applications and lessons learned. It introduces the author and provides reasons for piloting applications, such as getting stakeholder buy-in and ensuring usability. A case study example describes a project that focused on documentation and user feedback over complex data science. Finally, it emphasizes the importance of user-centered design principles like understanding users and validating designs with them.

1. Piloting Advanced
Data Applications

2. Hello!
I am Glen Ryman
Consulting Data Scientist
You can find me at:
glen.ryman@gmail.com
linkedin.com/in/glenryman

3. 1.
Why pilot data
applications?

4. “Any powerful idea is absolutely fascinating and
absolutely useless until we choose to use it”
- Richard Bach

5. 2.
Poor return on
analytics
investment

6. ➜ C-level commitment
➜ Culture of experimentation
➜ Politics and inability to change
➜ Not enough stakeholder
engagement
FOUR REASONS WHY ORGANISATIONS FAIL AT
ANALYTICS
Reference: The 5As of Analytics Transformation (Accenture), 2016

7. 3.
Case Study

8. ➜ Required to report on research
“impact”
➜ Large body of textual information
➜ Good data science, but complex
and difficult to explain
➜ Lots of experimentation but:
○ not much documentation
○ minimal application
DATA SCIENCE PROJECT IN HIATUS

9. Agree “good enough”
measures
THE SOLUTION
Focus on usability over
the best possible data
science
Fast prototyping with
regular feedback
Documentation!
Apply user centred
design principles

10. USER CENTRED DESIGN PRINCIPLES
Innovate
Understand
Users
Define
Use Cases
Design UI
Validate
with Users
Reference: www.usability.gov

11. 3.
Lessons learned

12. Don’t take the human out of the
equation

13. Thanks!
Any questions?
You can find me at:
glen.ryman@gmail.com
linkedin.com/in/glenryman
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