S&P Global · Case Study
Empowering organizations to detect and defend supply chain risks
A unified risk intelligence platform that turns fragmented, reactive supplier
monitoring into proactive, evidence-led decisions — across cyber, financial,
geopolitical, and operational threats.
Enterprise
Risk Intelligence
0 → 1 Ownership
6-Month Timeline
Dashboard Preview
[ Product mockup placeholder ]
The Problem
Supply chain threats were multiplying — and the tools couldn't keep up
Enterprises face a widening web of third-party risk: cyber breaches, financial
instability, geopolitical disruption, and operational failures — often surfacing
only after damage is done. Existing tools left analysts stitching signals together
across disconnected systems, with no single framework to detect exposure early or
defend against it decisively.
Our analysts and clients needed a way to move from reactive fire-fighting to
proactive, prioritized action — spotting the risks that matter before they became
incidents.
Business Context
A strategic bet on a net-new intelligence platform
S&P Global set out to build a new supply chain risk intelligence offering — an
opportunity to consolidate its data and expertise into a single product experience,
rather than another siloed module.
The strategic decision
Replace an existing third-party tool with a purpose-built, internally owned
platform — reducing reliance on external vendors while turning S&P Global's
proprietary data into a genuine competitive edge.
My Role
Senior UX Designer — end-to-end ownership, discovery to delivery
I led the design of this product across 6 months, from first framework to
market-ready experience. My core responsibilities spanned:
01
Stakeholder & user research
Interviews, surveys, and contextual observation with analysts and clients to
frame the real problem.
02
Information architecture & interaction design
Structuring a complex, data-dense platform into a coherent, navigable experience.
03
Wireframing through high-fidelity prototypes
Two rounds of usability testing with real users and rapid iteration on findings.
04
Cross-functional collaboration
Partnering across PM, engineering, QA, and SMEs to align on scope, feasibility,
and phased rollout.
05
Design handoff, documentation & UAT support
Detailed specs, design-to-dev handoff, and support through build and acceptance
testing.
Who I Was Designing For
Meet Julie — a risk analyst drowning in fragmented data
J
Julie
Cyber Risk Analyst
Major Enterprise Client
"I spend more time hunting for signals across tools than actually assessing risk."
Julie's core frustrations
Risk data was scattered
No single source of truth — signals lived across disconnected tools and reports.
Planning meant manual spreadsheet work
Scenario analysis was slow, error-prone, and impossible to keep current.
Monitoring was reactive, not proactive
Threats surfaced too late — after they'd already become incidents.
The competing tool was barely usable
The incumbent third-party product created friction instead of clarity.
Her goal
A fast, intuitive interface that surfaces the risks that matter — and gives her the
evidence to defend her recommendations to leadership.
Discovery → Definition
Turning stakeholder input into three design challenges
I ran structured interviews with cybersecurity analysts, procurement leads, and
engineering stakeholders to surface the real problem beneath the surface asks.
Synthesizing findings at scale, three core design challenges emerged.
01
Speed
Analysts spent too long aggregating data before any analysis could begin. The
product had to compress that.
02
Depth
Surface-level dashboards weren't enough — "what if" scenarios and layered
monitoring needed real analytical depth.
03
Trust
Heightened accuracy mode: it had to act with confidence and stand behind the
evidence it surfaced.
Ideation → Architecture
Mapping the platform around one core job
I mapped the platform around the core job-to-be-done: monitor, analyze,
simulate, stay informed, and compare each risk to become a mature, confident
module with its own design system.
Running collaborative sketching sessions with the PM and engineering leads, I
set gap-off, but-to-surface technical constraints before they became late-stage
blockers — locked at least two rounds of design lesson.
Risk Intelligence Platform
Monitor
Analyze
Simulate
Stay Informed
Compare
Key Decisions & Trade-offs
Where I made the hard calls
Ambitious scope met a fixed timeline. These are the decisions that kept the
product honest — and shippable.
Scope
Scope over surface clarity
I prioritized a comprehensive feature set — rather than a pared-down MVP —
because launching with thin coverage would have left analysts without the depth
they needed. The trade-off: more to design and test in the same window.
Real Data
Real data in testing
I pushed to use real supplier data in usability sessions rather than dummy
content. It surfaced tabbed-condition constraints early but made testing setup
slower and harder to coordinate.
Scenario Saving
Saving in the original brief
Scenario saving wasn't in the original scope, but I made the case that it was
fundamental — it changed the value proposition of the simulator from a one-time
calculation tool to an ongoing decision-support system. Engineering confirmed it
was feasible within the timeline.
Design Solutions
Five interconnected modules, each designed to eliminate a specific friction point
– MODULE 01
Dashboard
A real-time command center that surfaces overall risk posture at a glance — severity color-coding, trend graphs, and a global supplier map — so analysts get an immediate read on where attention is needed most, without hunting through reports.
– MODULE 02
Supplier Analysis
Deep dive views with filters by criticality, industry, and risk direction. Customizable metrics let analysts assess incidents, system vulnerabilities, and breach history, then drill into depth without ever committing away from the default view.
– MODULE 03
Scenario Simulator
The platform’s most differentiated feature. Analysts model “what-if” scenarios — natural disasters, geopolitical conflicts, manufacturing disruptions — and instantly see impact across EMEA, APAC, or any defined region. Simulations can be saved and compared over time, turning reactive analysis into proactive planning.
– MODULE 04
News Insights
Real-time curated news tracking tied to specific suppliers. Automated alerts surface major cyber incidents and data breaches as they happen — turning news from a manual task into a managed feed.
– MODULE 05
Comparison
Side-by-side supplier risk comparison with financial impact mapping. Analysts can quantify estimated losses against likelihood scenarios, making risk recommendations defensible to leadership.
Prototyping & Testing
Two rounds of testing that reshaped the experience
I moved from low-fidelity structure to high-fidelity flows, validating each stage
with real users and turning findings into targeted redesigns.
Testing Round 1
Interactive prototype with integrated data
Key feedback
A killer top-N supplier feature offered little — until placed in a real
industry-segment context, where it became a fast, intuitive exploration.
Outcome
Incorporated a "key switch" for functionality, reprioritizing navigation
around targeted exploration.
Testing Round 2
High-fidelity flows with supplier data
Key feedback
Scenario simulation was a green-changer, but it needed to be more
approachable and less anxiety-inducing.
Outcome
Implemented scenario-saving features and comparative analytics to measure
changes over time.
What I Learned
Two lessons that outlasted the project
01
Standardize alignment is a design deliverable
On this project, the most consequential design work happened in conversations —
not Figma. Getting engineering, PM, and leadership looking at the same prototype
at the same time collapsed weeks of misalignment into a single session.
02
The right constraint is a gift
The 6-month timeline forced rigorous prioritization. Every feature had to earn
its place — and that discipline made the final product sharper, not smaller. The
biggest shift in user behavior came not from a cleaner UI, but from confidence:
users trusting the data enough to act on it. That's a design outcome, not just a
cosmetic one.
Impact & Results
Measurable outcomes across time, adoption, and cost
"The visual consistency and clarity are remarkable. It feels intuitive, and I can
customize it exactly the way I need."
— User feedback, usability testing
~70%
Faster time-on-task
Streamlined workflows reduced the average time analysts spent on cyber risk
analysis.
70%
Reduction in lead conversion time
A significant cut in the time it took to move from a desired UX outcome to a
confident-from-users trusting the data enough to act on it.
$100K+
Annual cost savings
Eliminating the third-party subscription paid for the internal build and
delivered ongoing savings.
Julie's Final Verdict
"The dashboard isn't just about viewing data — it's about empowering our team to
make smarter decisions faster. Our cyber risk management capabilities have never
been stronger."
J