Designing Systems at Scale (Alëna Iouguina at DesignOps Summit 2018)
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Alëna Iouguina: "Designing Systems at Scale" DesignOps Summit 2018 • November 7-8, 2018 • New York, NY http://www.designopssummit.com
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Designing Systems at Scale (Alëna Iouguina at DesignOps Summit 2018)
- 1. Act I: Process and play St. Petersburg New York
- 2. The tools and processes allow us to translate our ideas and passions in a way that makes the magic happen.
- 3. “A toy is a vehicle that creates spaces where anything is possible.”
- 4. “Isn’t that why you’re here? To learn how to streamline the process?”
- 7. Creation and distribution of operations must have a transparent process and documentation, but application of operations must be invisible.
- 9. Shopify
- 10. Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9
- 11. Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9
- 12. Information flow Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9
- 13. Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9
- 14. Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9
- 15. Market Insights + Data Science + Support teams Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9 UXR UXR UXR UXR UXR UXR UXR UXR
- 16. Market Insights + Data Science + Support teams Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9 UXR UXR UXR UXR UXR UXR UXR UXR
- 17. Market Insights + Data Science + Support teams Shopify f1 f2 f3 f4 f5 f6 f7 f8 f9 UXR UXR UXR UXR UXR UXR UXR UXR
- 19. knowledge cycle Distribute knowledge Create or improve knowledge Apply knowledge Evaluate knowledge interdisciplinary distribution of knowledge
- 20. 1. Create
- 23. ‘what’ stream Objects Behaviours Sounds People Temporal Emotion ‘where’ stream Surroundings Specific location Relationship between parts Orientation Layout and configuration
- 26. ‘What’ stream ‘Where’ stream object-related data context-related data
- 27. ‘What’ stream ‘Where’ stream Perirhinal cortex Lateral entorhinal area Parahippocampal cortex Medial entorhinal area object-related data context-related data
- 28. ‘What’ stream ‘Where’ stream Perirhinal cortex Lateral entorhinal area Parahippocampal cortex Medial entorhinal area ‘What’ ‘Where’ ‘What’ ‘Where’ data => informationdata => informationdata => information object-related data context-related data Posterior hippocampus Anterior hippocampus data => informationdata => information
- 29. ‘What’ stream ‘Where’ stream Posterior hippocampus Anterior hippocampus Perirhinal cortex Lateral entorhinal area Parahippocampal cortex Medial entorhinal area ‘What’ ‘Where’ ‘What’ ‘Where’ data => informationdata => information object-related data context-related data Anterior hippocampus
- 30. ‘What’ stream ‘Where’ stream Posterior hippocampus Anterior hippocampus Perirhinal cortex Lateral entorhinal area Parahippocampal cortex Medial entorhinal area ‘What’ ‘Where’ ‘What’ ‘Where’ data => information information => knowledge data => information object-related data context-related data Prefrontal cortex (mPFC) Anterior hippocampus
- 31. ‘What’ stream ‘Where’ stream Posterior hippocampus Anterior hippocampus Perirhinal cortex Lateral entorhinal area Parahippocampal cortex Medial entorhinal area ‘What’ ‘Where’ ‘What’ ‘Where’ data => information information => knowledge data => information object-related data context-related data Prefrontal cortex (mPFC) Anterior hippocampus Great decisions
- 32. ‘what’ stream ‘where’ stream What is the comparative effectiveness of Facebook and Instagram for improving customer acquisition among retail merchants? What are merchant experiences with these marketing channels and perceptions of outcomes? Quant stream Qual stream
- 33. What is the comparative effectiveness of Facebook and Instagram for improving customer acquisition among retail merchants? What are merchant experiences with these marketing channels and perceptions of outcomes? ‘what’ stream ‘where’ stream Full picture of merchant experiences with two marketing channels, barriers to adoption, and the ultimate effectiveness of these channels among a specific segment of our population. Quant stream Qual stream
- 34. Closed-ended questions Behavioural data Task analysis data Survey data Statistical analysis and interpretation Open-ended questions Interview data Observational data Text and image analysis Pattern interpretation Quant + Qual = BFFs 👯♀️ Quant stream Qual stream
- 37. knowledge cycle Distribute knowledge Create knowledge interdisciplinary distribution of knowledge
- 38. Shopify UXR UXR UXR UXR UXR UXR UXR UXR
- 39. What Where Shopify Market Insights UXR UXR UXR UXR UXR UXR UXR UXR
- 40. What Where Shopify Data Science DS DS DS DS DS DS DS DS
- 41. Shopify data warehouse Market Insights Data Science + Support teams Embedded (UX Research + Data Science + Support)
- 42. 1. Create 2. Distribute 3. Apply
- 43. data knowledge cycle Distribute knowledge Create knowledge interdisciplinary distribution of knowledge
- 44. data information knowledge cycle Distribute knowledge Create knowledge interdisciplinary distribution of knowledge
- 45. data information knowledge knowledge cycle Distribute knowledge Create knowledge interdisciplinary distribution of knowledge
- 47. 1. Create 2. Distribute 3. Apply 4. Evaluate
- 49. KPIs Wisdom data information knowledge knowledge cycle Distribute knowledge Apply knowledge Create knowledge Evaluate knowledge interdisciplinary distribution of knowledge Create and improve knowledge
- 50. a) Leadership b) Asset visibility c) Knowledge management
- 51. a) Leadership b) Asset visibility c) Knowledge management
- 52. I take research very seriously and value information acquisition as one of the most important traits of Shopify. My hope is that researchers teach people to get better at this while also helping acquire more information for the collective group. The team cannot be an excuse to atrophy this skill. Data doesn't always tell you why people are behaving a certain way and therefore you should have a research team to help you understand the user behaviour.
- 53. a) Leadership b) Asset visibility c) Knowledge management
- 55. a) Leadership b) Asset visibility c) Knowledge management
- 59. Information flows f1 f2 f3 f4 f5 fn