Diagnosing Pain Points to Define a Path for AI
How we helped Data Culture define AI use cases and build a prioritized implementation roadmap in 6 weeks for one of their client’s modernized Data & AI modernization efforts:
Outcomes
Generated dozens of AI and modernized data use cases over 6 weeks
Defined
5 evidence-backed priority AI use cases
to be implemented
Surfaced 5-6 additional ideas for expansion beyond original scope for project
Generated notable buy-in from financial services client for ongoing modernization
Context
Data Culture is a boutique data consultancy that sought our help to support a data modernization project they were engaged with for a legacy brokerage in the financial services industry.
This client of theirs was facing a lack of a long-term data & AI strategy, and no concrete plan to understand their current state capabilities.
Objectives
Defining 4-5 AI use cases based on client’s current state and industry context
Prioritizing existing client pain points and needs around pre-existing efforts
Building roadmap to facilitate transition to implementation phase for project
Client Perspective
“Superposition helped us come up with a repeatable way to cut through complexity with this particular client, so we could align across all their different teams and focus on what really mattered for making this project succesful!”
Brittany Bafandeh, CEO - Data Culture
How We Did It
Completed 1-on-1 discovery sessions with 6 different key leaders to determine pain points
Compiled an initial list of use cases per leader and defined potential obstacles to educate prioritization process
Built and socialized a structure for an upcoming prioritization workshop after 4 weeks
Phase 1: Discovery & Education
Phase 2: Prioritization Workshop
Completed 4-hour workshop (with participation from all 6 leaders) to understand the impact/effort of potential use cases
Defined cross-workstream priorities based on workshop activities
Broke down priority use cases to generate starting points for implementation efforts
Phase 3: Implementation Prep Outputs
Used outputs from sessions and workshops to generate 3 outputs for Data Culture’s implementation team:
Full list of modernized data use cases (incl. AI ideation)
Prioritized list of Use Cases
Tactical roadmap of business value per use case to implement
