Purpose

Rational Aim: To align analytics customers, stakeholders, and practitioners around the needs for Wikimedia Foundation to make better decisions through data

Experiential Aim: To demonstrate a collaborative, cross-functional model of how WMF staff can develop the vision of analytics

Participants

Anasuya Sengupta
Andrew Otto
Dan Andreescu
David Schoonover
Diederik Van Liere
Erik Moeller
Erik Zachte
Frank Schulenburg
Gayle Young
Howie Fung
Jessie Wild
Kraig Parkinson
Rob Lanphier
Stefan Petrea

Process

Proposed Agenda

Introduction
Understanding our Current Capability
- Review Stakeholder Feedback
- Showcase & Feedback of Analytics Offerings
- Setting up an Innovation Pipeline
Defining an Operating Model for Analytics
Moving from Analytics Platform to Analytics-Enabled Leadership
- Ecosystem Map
- Value Proposition Canvas
- Service Blueprinting
Making Change Happen
- Four-Tables Contextualization
- Action Mapping
- Charrettes: Safe-Fail Experiments & Ritual Dissent
- Resourcing Considerations

Actual Agenda

Introduction
Understanding our Current Capability
- Review Stakeholder Feedback
- Showcase & Feedback of Analytics Offerings
- Setting up an Innovation Pipeline
Defining an Operating Model for Analytics
Moving from Analytics Platform to Analytics-Enabled Leadership
- Ecosystem Map
- Value Proposition Canvas
- ~~Service Blueprinting~~
Making Change Happen
- ~~Four-Tables Contextualization~~
- ~~Action Mapping~~
- ~~Charrettes: Safe-Fail Experiments & Ritual Dissent~~
- ~~Resourcing Considerations~~
- Discuss Next Actions

Issues

Differences in opinion about how analytics works at WMF and how it compares to Analytics Lifecycle presented by Ken Collier.
Challenges learning the Operating Model framework as planned. Had to coach groups through how to use it.
Divergent thinking with respect to how to organize analytics. Could be due to previous issue.
Difficult to keep some remote team members engaged, in part due to A/V issues

Meeting Notes & Artifacts

FIX: missing

Product/Next Steps

Setup scheme for prioritization and scheduling of features.
- Considering leveling capacity by stakeholder group (scheduling work along fixed sequence, fixed time)
- Schedule day-to-day work based on classes of service to support day-to-day responsiveness
- Review monthly
Setup routine for investigating opportunities to improve analytics capabilities
- Identifying needs
- Exploring potential solutions
- Validating ideas with stakeholders and customers
Develop a value path toward initial base cluster and share widely with stakeholders
Follow up with analysts to elicit workflow of analytical model development and analysis
Work with individual stakeholder groups to determine upcoming analytics needs