Facilitating holistic product decisions with information architecture

Facilitating holistic product decisions

with information architecture

Johanna Kollmann | @johannakoll | IA Summit 2017, Vancouver

CHALLENGES

“Multi-context” product

Website

Command-line tool

Integrations & notifications

Photo by NASA HQ PHOTO, https://flic.kr/p/cxko4u

Mental Model

System Model

Conceptual Model

We ended up designing “from the code layer out” - rather than having product intent drive the system.

HOLISTIC PRODUCT THINKING

CODE HAS IA

1) Concepts and language in the code beat the best diagrams.

Lessons learned

From an IA’s point-of-view:

• How will user journeys change?

• What’s the new hierarchy?

• Does our taxonomy still work?

• What do we call features and product concepts?

• Which words will make sense to users, what have we learned from research?

Scenario: scaling the product

From an engineer’s point-of-view:

• How does the data model need to change to support this?

• How do existing code structures need to change?

• What do we call things in the code?

• What new services and capabilities will be required?

Scenario: scaling the product

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

Lessons learned

• Re-architect the code to match the conceptual model

• Can you use the terms that are user-facing in the code?

• It is what’s in the code that will be used and remembered

Build from the product layer in - not from the code layer out

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

3) Engage with, and inform, the IA of your system architecture.

Lessons learned

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

3) Engage with, and inform, the IA of your system architecture.

Lessons learned

THINKING IN USER JOURNEYS IS HARD

Objectives + metrics

Epics

User stories

Tasks

Customer Needs Business goals

Feature

Discovery phase Feature plan

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

3) Engage with, and inform, the IA of your system architecture.

4)Feature testing can create a shared understanding of high-priority features.

Lessons learned

Example credit: https://github.com/guidance-guarantee-programme/pension_guidance/blob/master/features/customer_booking_request.feature

Feature testing

• Written before you start coding

• Expressed in human language

• Facilitates understanding the feature

across the user journey

• Great for clarifying questions, easy to

collaborate on

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

3) Engage with, and inform, the IA of your system architecture.

4) Feature testing can create a shared understanding of high-priority features.

5) Feature inventories that include engineering capabilities can provide a holistic overview across product and system architecture.

Lessons learned

Feature inventory

• High-value core features

• Map against channels, integrations,

whatever your context requires

• Map system architecture (services,

capabilities) against features

• Will inform API development

TAKE-AWAYS

Semantics matter! The code has IA and drives your engineering colleagues’ conceptual model.

Identify process points and tools that can connect the product and system architecture.

1) Concepts and language in the code beat the best diagrams.

2) Collaborate with system architects and engineers to ensure that concepts in the code match the product intent.

3) Engage with, and inform, the IA of your system architecture.

4) Feature testing can create a shared understanding of high-priority features.

5) Feature inventories that include engineering capabilities can provide a holistic overview across product and system architecture.

Lessons learned

say hi: @johannakoll

THANKS MERCI DANKE