TECHNICAL PRODUCT MANAGER • PLATFORM• AWS
Rebuilding order visibility at Nike
From 3-hour manual lookups to real-time answers
As Technical Product Manager for Nike’s internal Order Visibility platform, I led discovery, key architecture decisions, and end-to-end delivery of a new AWS-based order status experience that replaced a failing legacy tool and reduced dependency on analyst-driven investigations.
Outcome: Converted a multi-hour, analyst-dependent lookup process into a self-service, near real-time experience—cutting investigation time by ~99%, saving hundreds of hours per week, and launching with strong internal satisfaction (30+ NPS).
~100x
Latency Improvement
4
Markets
ROLE
Technical Product Manager
SCALE
High-volume “Where is my order?” (WISMO) case load
TEAM & SCOPE
Internal operations, distribution center partners, and consumer service teams across 4 markets
DOMAIN
Order Visibility Platform • AWS
~99%
Lookup Time Reduction
30+
NPS
Hundreds
Hours/Week Saved
Role & Scope
ROLE TITLE
Technical Product Manager – Order Visibility Platform (Nike Technology)
ROLE SUMMARY
I served as TPM and de-facto Product Owner for the MVP and early evolution, owning product strategy, delivery governance, technical decision alignment, and launch/adoption across an 8-person engineering squad (vendor + Nike partners).
DIRECT RESPONSIBILITIES
✔ Problem & solution discovery: Interviews, legacy audit, requirements validation, MVP definition
✔ Product strategy & planning: Vision, roadmap, OKRs, personas, journey maps, value proposition, leadership narratives
✔ Delivery governance: Agile ceremonies, backlog prioritization, sprint execution, stakeholder readouts
✔ Technical & quality decisions: Architecture alignment (event-driven AWS), non-functional requirements (latency, availability, retention), release governance
✔ Launch & adoption: UAT, release notes, internal enablement, onboarding, multi-market rollout planning
CRITICAL IMPACT
When the vendor team under-delivered and key roles were missing, I stepped in as TPM + PO + interim Scrum Master to maintain delivery control and ship within an aggressive ~2.5-month timeline.
PROBLEM & CONTEXT
Limited, Delayed Order Visibility
Nike’s order operations teams were handling high WISMO volume without a reliable self-service way to find accurate status—creating significant operational cost and raising risk ahead of peak season.
Vision
Support “one marketplace” expectations for fast, transparent delivery by enabling internal teams to answer order-status questions quickly and consistently—reducing support burden and protecting consumer trust.
Mission
Replace a failing legacy order-visibility tool and remove dependency on manual analyst lookups. Deliver a reliable, self-service, near real-time order visibility experience within ~2.5 months so operations and support teams could resolve inquiries in minutes—not hours.
1. The User Problem
Internal teams (operations specialists, distribution center partners, consumer service reps) lacked a reliable self-service tool. The legacy experience had hours of data latency, limited search (often single-ID only), inconsistent data, and workflows that forced reliance on a small analyst group with specialized access—turning many WISMO cases into multi-hour investigations.
2. The Business Problem
This was a material cost and peak-season risk. A significant share of support demand was WISMO-related, and teams were spending tens of thousands of hours per year chasing answers—driving higher support cost, slower resolution, and elevated consumer experience risk.
60+ Stakeholder Alignment Matrix
How the PRD readout brought four departments onto the same page
High Impact
Nike Customers
➤ "Where is my order?"
➤ No self-service options
Critical
Support Teams
➤ High WISMO volume
➤ Long investigation cycle
Medium
Operations
➤ Tooling gaps
➤ Inconsistent data timing
High Impact
Business Impact
➤ High support costs
➤ Consumer trust risk
➤ Peak season threat
3. Constraints / Reality
-
Aggressive timeline: leadership request to ship before holiday peak
-
Vendor team already building against incomplete requirements
-
Missing dedicated roles at start (PO/SM/UX/release standards)
-
Legacy data paths with batch delays and inconsistencies
-
Privacy and data-handling requirements surfaced late in the cycle
4. Problem Definition
Nike’s internal operations teams lacked a single, reliable, near real-time view of consumer orders—forcing multi-hour manual investigations and extensive analyst workload at peak risk, impacting cost, speed of resolution, and consumer trust.
APPROACH
Decision-Making & Strategy
How I grounded the product in real problems, made key technical and scope decisions, and reshaped execution to deliver within an aggressive timeline.
Research / Discovery
I anchored the work in real use cases and operational pain—not just “replace the legacy tool".
Legacy Audit
Identified critical gaps: stale data, limited search, inconsistent behaviors, no credible real-time path
User Interviews
Operations, distribution centers, consumer service, analytics, production support
-
Common themes: multi-ID search needs, bulk lookup, and removing analyst bottlenecks
Vendor Validation
Reviewed early wireframes/flows vs. real workflows
-
Found gaps in legacy parity and under-addressed latency/search/reporting needs
Outcome: A fact-based problem frame and a short list of highest-leverage MVP use cases.
Systems or Data Analysis
Core question: How do we deliver accurate, near real-time order data end-to-end?
System Mapping
Mapped order lifecycle with Nike solution architects across:
Order management system
Carrier track-and-trace feeds
Reporting/operational data paths
Fulfillment data stores
Event-stream/messaging pipeline
Options Compared
Time-delay analysis showed only one credible path to near real-time: event-driven streaming + modern indexing/storage (vs. batch-oriented legacy patterns)
❌ OLD
Reuse Pipeline patterns
✅ New
Event-driven AWS pipeline
Storage Strategy
Balanced retention needs vs. cost/performance risk in search indexing (e.g., OpenSearch/Elasticsearch shard strategy)
SOLUTION-PATH DECISION:
Chose an event-driven AWS pipeline: domain microservices (order, fulfillment, shipment) → object storage + search index → API + React UI. This was the only path that met latency and scalability needs, though it required more upfront definition and vendor coaching.
Opportunity Mapping
From interviews, story mapping, and journey analysis, I grouped opportunities into four themes:
WISMO Self-Service
Single and bulk lookup; flexible search inputs (IDs, tracking, product identifiers, date/status)
E2E Visibility
Lifecycle view, time-in-status, “stuck” detection signals
Ops Efficiency
CSV downloads, exception reporting, order health dashboards
Omnichannel Platform
Multi-market rollout readiness, KPI hooks (latency, time saved, satisfaction), future channel expansion
Translated into epics, user stories, and acceptance criteria (search behavior, constraints, error states) and linked to OKRs.
Prioritization & Tradeoffs
Strategic trade-off analysis guided the path selection, which informed ruthless prioritization to deliver within the 2.5-month window
➤ Implementation Path Analysis
Legacy Audit
Incrementally fix legacy tool
Speed
6
Cost
8
Scale
2
Risk
3
19/40
High Tech Debt
Hybrid Approach
New UI on legacy data path
Speed
7
Cost
6
Scale
5
Risk
5
23/40
Bottleneck Risk
Modern Event-Driven
Modern event-driven pipeline
Speed
5
Cost
4
Scale
10
Risk
9
WINNER
28/40
Scalable Foundation
Why Modern Event-Driven Won
It was the only approach that solved the root latency constraint and supported future scale, even if initial delivery required tighter prioritization and sharper execution discipline.
Short-term trade-off
Accept slower build to solve root problem
Long-term value
Scalable foundation for geo expansion
Decision drives phased execution
➤ Phased Delivery Strategy
Phase 1: MVP
Oct 2023 • 2.5 Months
✔ SHIPPED
-
Near real-time order visibility for priority users
-
Multi-input search + bulk lookup
-
Order/fulfillment/shipment views
-
CSV export
-
Scalable AWS foundation (microservices + object storage + search index)
Phase 2: Expand
Q1-Q2 2024
-
Market expansion and operational integrations (case management/ITSM)
-
Exception reporting and baseline analytics
Phase 3: Vision
H2 2024+
-
Broader omnichannel coverage (customer-facing and B2B)
-
Advanced dashboards and predictive insights
Primary MVP tradeoff: Prioritized fast, accurate self-service WISMO resolution over deep analytics and major UX redesign in order to hit the peak-season window.
Path Selection / Strategy
I formalized the plan using a structured set of artifacts to make decisions durable and legible:
Vision & Press-Release
One internal order visibility product to reduce time-to-answer and enable proactive operations
Why
Clear objectives around user adoption, latency, UNPS, geo/channel expansion (extend to 4 markets, integrate Qualtrics for sentiment)
Channel & Geo Strategy
Start with priority user groups and workflows; scale across markets in planned sequence
Data-Retention Strategy
Define primary “hot” retention window for core workflows; plan cost optimization via cold storage over time
System Architecture
L1: Data Sources
L2: Event Stream
L3: Micro Services
L4: Object Storage + Search Index
L5: API + React UI
Near real-time data path
Horizontally Scalable
Resilient Backup Strategy
FEASIBILITY/RISK DECISION:
To manage privacy and release risk, I separated technical readiness from business go-live, enabling a short delay to address late-breaking privacy requirements and ensure stakeholders were available for launch support.
Execution Structure / Roadmapping
Delivery required reshaping how the squad operated to meet the timeline and quality bar.
Stepping in as PO + Scrum Master
After an underwhelming leadership demo, I audited delivery, identified role gaps, and established clear execution ownership and cadence.
Agile Operating Model
I implemented a disciplined cadence:
-
Daily standups + weekly story refinement
-
Sprint planning + retros
-
Kanban boards + Jira for epics/stories
-
Box/Confluence for docs + onboarding
Release Management & Quality
Defined a practical release checklist and quality bar (testing coverage targets, latency SLOs, privacy/security sign-offs)
-
Supported non-functional validation (API/load testing to expected concurrency ranges)
Alignment Decisions
Aligned vendor squad, Nike engineering/architecture, and privacy/security stakeholders on:
-
MVP definition of done and acceptance criteria
-
Event-driven architecture approach
-
Data-handling and privacy requirements
-
Tech readiness vs. business go-live timing
Outcome: Leadership could approve launch with a clear definition of quality, risk posture, and operational readiness.
OUTCOMES
Impact & Results
The platform transformed order visibility from analyst-dependent investigations into near real-time self-service, delivering substantial operational efficiency and peak-season readiness.
Concrete Output
Shipped an internal Order Visibility MVP including:
Platform Architecture
Event-driven AWS foundation (microservices + object storage + search index + API + React UI)
Search Capabilities
Flexible search (multiple identifiers) and bulk lookup support. Order/fulfillment/shipment visibility views. Export and operational workflows to reduce repeat investigations
Strategy & Docs
Full product stack: discovery artifacts, roadmap/OKRs, epics/stories, release governance
Quality Framework
Release management: code coverage, observability, incident tracking, security/privacy checklists
User Impact
Teams finally had a clear, accurate understanding of what to build, when to build it, and how integrations would function. UX, engineering, and business shifted from confusion to clarity, accelerating delivery and reducing churn.
Before: Fragmented
-
Multi-hour investigations per WISMO case
-
Multiple tools + specialized analyst dependency
-
Inconsistent answers, rework, and escalation loops
After: Coordinated
-
Near real-time self-service lookup
-
Faster independent investigation and resolution
-
Reduced analyst bottlenecks and improved onboarding
Enabled operations and support teams to investigate issues by product identifiers, pinpoint where orders were stuck, and resolve cases without specialized access—improving throughput and reducing friction.
Business Impact
✔ Exceeded
99%
Time Saved
Hours → < 2 Minutes
✔ Exceeded
~ 100×
Latency Improvement
Event Driven Architecture
✓ Target
- 40%
WISMO Calls
Reduction in Incidents
80% +
Adoption
Across Geographies
4
Markets
International expansion
+ 30
Internal NPS
Launch satisfaction
As near real-time visibility and operational triggers matured, teams improved bottleneck detection and supported measurable fulfillment throughput improvements (estimated double-digit gains in priority flows), while sustaining high availability during peak demand.
Validation Evidence
UAT with representative operations and support users
Load/performance testing under realistic concurrency
UAT
Performance Testing
Launch feedback surveys indicating strong internal satisfaction (30+ NPS)
Launch Surveys
Ownership
Led end-to-end discovery, product strategy, architectural alignment, backlog prioritization, Agile execution, release governance, and launch of the internal Order Visibility platform—directly driving major time savings, latency improvement, and multi-market adoption.
REFLECTION
Key Learnings
Critical insights from leading the OVD platform that shaped my approach to technical product management
Step Into the Gaps
When key roles are missing or underperforming, stepping in and formalizing ownership can be the difference between drift and a credible MVP.
PRINCIPLE TO CARRY FORWARD
Take ownership of critical gaps early to protect delivery.
Define Quality Standards
Data-sensitive platforms require explicit standards; codifying release governance and non-functional requirements reduces hidden risk and improves confidence in launch readiness.
PRINCIPLE TO CARRY FORWARD
Define quality and compliance gates early—do not assume they exist.
Optimize for Durable Value
Choosing the event-driven path and prioritizing high-leverage MVP workflows created a foundation that could scale across markets and future channels, rather than a one-off peak-season patch.
PRINCIPLE TO CARRY FORWARD
Build for scalability and durability, not just the deadline.