The mark moved. And the reasoning was scattered.
Designing a persistent summary and anomaly investigation experience for QVal
Clients needed to review draft valuations and support their conclusions in audit reporting. But when a valuation changed, users often had to work backward from the result—clicking between screens to reconstruct which inputs, assumptions, or judgments influenced it.
- ROLE
- Product Designer; I owned the design end to end
- COLLABORATION
- Product team, with developers involved early in the data groundwork
A valuation is a conclusion. Reviewers needed to follow its reasoning.
Reviewers began with the mark—the valuation at a given point in time—then worked backward through QVal to check the inputs behind it.
Some drivers were numeric. Others involved a methodology change, a shift in the comparable-company set, or a decision carried forward from an earlier period.
The problem wasn’t just spotting an unusual number.
Reviewers needed to understand period-over-period movement: what changed, why it mattered, and where to look next.
A change in total enterprise value (TEV) might relate to financial performance, market assumptions, capital structure, or valuation methodology.
Without persistent context, each trip to an input made the overall comparison harder to hold in view.
Turn a broad idea into a reviewable problem.
Product brought forward the broad idea of “anomaly detection,” along with common user pain points. The brief left important questions unanswered.
I asked targeted questions to understand what a flagged driver meant and what information a reviewer would need to investigate it.
Product and I worked together to identify and organize driver scenarios across valuation methods. Product defines the thresholds for flagging changes. I shaped how reviewers would understand those changes and move from a flag to the underlying input.
Anomaly detection should give reviewers a place to start—not make the valuation judgment for them.
Carry the comparison across the workflow.
The persistent summary keeps the published and draft marks, their difference, unresolved anomaly count, and last recalculation time in view as users move through QVal.
That stable reference responds to the context reviewers were losing each time they moved from the summary into an input.
The comparison stays visible while the reviewer moves through setup, financials, and the rest of the workflow.
Put the movement beside the work it points to.
The investigation panel keeps the valuation bridge and flagged changes alongside the underlying workflow.
It separates financial metric changes from narrative changes and prioritizes review by impact on TEV.
The bridge shows period movement; the queue gives reviewers a place to begin tracing its drivers.
Guide the review. Leave the judgment with the reviewer.
The system supplies an explanation for a flagged change. Reviewers can follow a link to the relevant input, update it, add their own rationale, and mark it resolved.
System explanation: supplied with the flag. Reviewer rationale: the user’s own reasoning, added during investigation.
EARLY SIGNAL, WORK IN PROGRESS
“Yeah, this would help reduce the amount of going back and forth so much.”
Our biggest client said this after seeing the prototype. It was positive feedback on the proposed direction—not measured impact. The design is still in progress and has not been usability tested. Developers are involved early and are beginning the data groundwork.
Prototype figures are illustrative, not production results.
Next project: Stabilized Steps ↗