Innovation Programs Lead · Singapore / APJ
Turn an ambiguous AI ambition into a customer-backed path to production.
A working case showing how I would facilitate an executive innovation engagement: frame the real customer problem, compare pathways, prototype the smallest credible intervention, and leave with measurable next steps.
Independent application artifact using synthetic information. Not affiliated with or commissioned by AWS.
01 · Customer-backward framing
Do not start with “Where can we put GenAI?”
Start with the customer and the business outcome. In this synthetic case, executives arrive with a broad ambition to “use generative AI in service operations.” The workshop turns that ambition into a testable problem.
Resolve complex service cases faster without asking frontline teams to trade trust for speed.
Success means less time searching fragmented knowledge, fewer avoidable escalations, and clearer next actions — while keeping consequential decisions explainable and human-owned.
Observed frictionKnowledge is fragmented across manuals, bulletins and resolved cases.
Business consequenceSenior specialists become the routing layer for repeatable questions.
First-principles questionWhich part of the resolution loop is both valuable and safe enough to change first?
UnknownWhether faster answers translate into better resolution outcomes and adoption.
Synthetic baseline for the workshop — used to create trade-offs, not to imply customer facts.
12kmonthly service cases
38 minmedian knowledge search
21%cases escalated
6major knowledge sources
02 · Executive discovery
A workshop should convert opinions into explicit decision inputs.
Where is the experience breaking?
Map the moments that create repeat contacts, escalations or loss of trust.
What outcome is worth paying for?
Agree the metric hierarchy before discussing architecture.
What can be grounded and measured?
Test data availability, workflow stability and integration boundaries.
Who must trust the new workflow?
Surface adoption incentives, authority boundaries and change load.
Where can the system be wrong?
Define unacceptable outcomes, escalation triggers and audit needs.
What would make this reusable?
Capture a mechanism that other markets and account teams can repeat.
03 · Opportunity prioritisation
Change the executive constraint. Change the recommendation.
The scoring is deterministic. This is the facilitation mechanism: make assumptions visible, let leaders change the weights, and see how the innovation pathway moves.
Recommended innovation pathwayClear lead under current assumptions
84/100
Guided Resolution Workflow
04 · Make it tangible
Prototype the decision, not the entire destination.
Lightweight conceptHuman-in-the-loop service assistant
Incoming case
“Intermittent pressure loss after firmware update. Restart did not resolve.”
Grounded assistant
Three relevant service bulletins found. Highest-confidence next step: verify sensor calibration before rollback.
Evidence: Bulletin SB-218 · Resolved case pattern RC-44 · Confidence 0.88Proposed action
Prepare calibration checklist and pre-fill the diagnostic work order.
05 · From workshop to production
Leave with owners, evidence and a 30/60/90-day path.
Prove the problem
- Validate the top service journey with frontline teams.
- Define quality, handling-time and trust baselines.
- Confirm the minimum grounded data set.
- Build the narrow interactive prototype.
Prove the workflow
- Pilot one high-volume case type.
- Instrument answer acceptance and escalation.
- Test human approval and auditability.
- Review adoption friction weekly.
Earn the next investment
- Compare pilot outcomes with baseline.
- Decide whether to broaden, change or stop.
- Package reusable workshop + prototype assets.
- Define the next authority boundary.
90-day decisionPilot one high-volume case type, instrument acceptance and quality, then widen only when the workflow earns trust.
The output is not “launch GenAI.” It is a measurable decision: scale, reshape or stop.
Reusable APJ mechanisms
One customer engagement should make the next one faster.
Codify the process, not just the slide deck. Every sprint should leave behind reusable inputs for account teams, specialists and other markets.
Why this is relevant to my background
Product leadership, regional operating complexity and hands-on AI adoption.
Led consumer product portfolios operating at tens of millions of monthly active users with material recurring revenue and multi-market complexity.
Owned product, portfolio and P&L decisions across acquisition, activation, retention, monetisation and live operations.
Worked across Korea, Japan and Southeast Asia, translating regional behaviour into product and operating decisions rather than generic localisation.
Built internal agent frameworks and led practical AI adoption across product, production, design and creative workflows.
This artifact is designed to demonstrate the operating approach: customer-backward framing, executive facilitation, practical AI judgement, measurable activation and reusable mechanisms.