The Challenge
Fragmentation as the default operating mode
SIG (Sponsor and Investor Group) bankers at JPMorgan are responsible for managing some of the most complex, high-value client relationships in investment banking — covering major private equity firms, sovereign wealth funds, and growth equity investors globally. Yet when it came time to prepare for a client interaction, they were on their own.
Multiple open screens. Manual Excel trackers. Personal workarounds. Calls to colleagues. The information they needed existed somewhere in the firm — but it was scattered across DASH, Deal Logic, separate CRM tools, business manager reports, and institutional memory. There was no single view that told a banker what they needed to know before walking into a room.
Core Problem
SIG bankers are operating in a fragmented technology environment, maintaining multiple open screens and manual trackers to accomplish what should be unified workflows. This fragmentation creates inefficiency, increases the risk of missed opportunities, and makes it difficult to present a cohesive "One JPMorgan" view to clients.
Key Insight
"The most successful outcome will be a tool that experienced bankers recognize as 'how I already think about this but automated' — rather than a new system they must learn. The design should codify institutional knowledge, not replace it."
Research Approach
Seven bankers, four research objectives
Seven in-depth interviews were conducted with SIG coverage bankers to gather requirements for the Investor Profile experience in DASH. Sessions ranged from 30 to 90 minutes, with participants encouraged to share their screens, demonstrate current workflows, and provide candid feedback on pain points and desired functionality — making the research highly observational as well as attitudinal.
The participant mix was deliberately broad — spanning seniority levels from new joiners to 12+ year veterans, geographic markets from New York to London, and coverage specialisms from large PE sponsors to sovereign wealth funds and growth VCs.
Four research objectives anchored every session: identify key SIG process pain points, finalize required data fields for initial launch, align on functional needs (filters, visualizations), and validate the page layout and information hierarchy of proposed widgets.
Jobs to Be Done
Five things bankers actually need to do
The research organized findings around five core jobs — the real tasks bankers were trying to accomplish, regardless of what tool they were using. Each job had a current-state problem and a clear design implication for the Investor Profile.
Prepare for a sponsor interaction quickly
→ Summary-first dashboard, scannable in 30 seconds
Bankers maintain multiple open screens and manual trackers to piece together a picture before every client interaction. There is no single view that gives them full context — who covers the account, recent conversations, where the firm has exposure, what opportunities or risks exist.
"I keep a bunch of screens open now that I think is what you're kind of uniting... I have DASH open, my contacts I have starred are all open." — AS
"I was literally on the phone with the head of American Securities. We're just catching up. And I can't pull up a view quickly. It'd be great if I had a dashboard and say, 'Hey, let me just give you the interaction we're doing across American Securities.'" — AS
Identify where to spend my time
→ Unified asset list, KDM favorites, fund pressure indicators
Bankers manually maintain favorites lists, scrolling through contacts to identify who needs attention. Portfolio companies and exit opportunities are tracked in separate systems with no cross-referencing. There's no system that surfaces what matters most right now.
"You don't cover the key exit, you don't cover the company. You cover the person who controls it. So if you're covering the person, adding value to the person, and they own a company that's in your space, that's going to elevate your profile with that person." — JS
"It is important knowing which portfolio companies are in which funds... We think about, is that a long-in-the-tooth fund? Do we need to CV this thing? Is that the last asset in the fund?" — AS
Coordinate internally across JPM
→ Three-tier coverage widget, "My Partners" shortcut, two-way visibility
Coverage lists in DASH are overwhelming — 50+ names with no indication of relationship depth. Cross-LOB visibility is nonexistent. Bankers make multiple calls to find the right person, and cross-LOB partners flood inboxes with questions that could be self-served.
"When you go on DASH, oftentimes there's a very long list of people — 60 people. If it's somebody who did one phone call and is now somehow in that list, that's not helpful because currently the depth and responsibility of that relationship is in no way dimensionalized." — JS
"If they could go in and just see the answer to that and what the activity has been because they cover that company, it would take that off my plate. I could just say, 'Look at this tool — it has all the information we need. Please never call me again unless you have a very specific question.'" — JS
Understand our business position with the client
→ Balance of trade: ROE → Exposure → Fees, wallet share with ranking
Financial data is scattered across multiple systems and reports. Bankers request data from business managers, wait for manual pulls, and piece together narratives from disconnected sources. Wallet share requires separate Deal Logic lookups and lacks competitive context.
"If we're #3 but ideas generated are 50, and I'm #3 and Goldman only sold you 2 businesses — I'm kind of like, WTF? So I use those financial metrics as more of a balance of trade." — KB
"I want to be able to trust what's in there. I still can't and I still don't. Before we find a way to do that, all the rest is useless." — IT
Spot opportunity and loss signals
→ Dry spell alerts, wallet decline trends, cross-sell gaps, incumbency data
Signal detection is entirely manual. Bankers rely on memory, scrolling through contact lists, and ad hoc data pulls to identify where attention is needed. There are no proactive alerts or pattern recognition — the system waits for the banker to go looking.
"If there was a way to have the system identify: our win on this company sell-side — this looks like these other companies in your client's portfolios — and get that to pop up somewhere... We have invaluable information that nobody else has around how we got this deal done for a very comparable company to yours. That would be the Holy Grail." — JS
Investor Profile — DASH Concept Mockup
Concept mockup of the Investor Profile in DASH — illustrating the summary-first, pre-meeting snapshot validated through research sessions.
Current State vs. Target State
What bankers ask — and what the profile should answer
For each question a banker needs answered before a client interaction, the research mapped the current workaround against the target state the Investor Profile should deliver.
Opportunity & Loss Signals
Six signals the profile should surface proactively
A core finding was that signal detection was entirely manual — bankers had no system that told them when something had changed or when action was needed. The research defined six signal types the Investor Profile should detect and surface automatically.
| Signal | Real example | How the profile helps |
|---|---|---|
| Dry Spell | No one has met with a key partner in 90 days | KDM table with firm-wide dry spell indicators |
| Wallet Decline | JPM dropped from #3 to #7 in M&A | Wallet share trend line with ranking alerts |
| Coverage Gap | High-value portco with no IB relationship | Product penetration matrix (yes/no by product) |
| Competitor Win | Goldman won a sell-side we weren't invited to | Deals done away tracking with context |
| Exit Opportunity | Fund is aging, last 2 assets remaining | Fund vintage + remaining assets indicator |
| Cross-Sell Gap | CB has operating relationship, IB has none | IB ↔ CB mismatch identification |
Design Direction
Three principles that shaped the solution
The research didn't just surface problems — it generated clear, banker-validated design principles that the Investor Profile mockup was built around.
Summary-centric information display
Scannable overview with drill-down on demand
SIG bankers prefer concise overviews with the option to dive deeper — supporting efficient decision-making rather than passive data browsing. The landing view should be scannable in 30 seconds before a call, with financial metrics, recent interactions, and coverage contacts all visible without scrolling.
Efficient meeting preparation
Purpose-built for prep, not passive browsing
The primary use case is preparing for meetings and targeted follow-ups — not exploratory data browsing. Every widget should answer a question a banker has right before they walk into a room. Drill-down should be available but never required for basic meeting prep.
Integrated and trusted workflows
Unified data with transparent sourcing
Unified, integrated workflows are strongly preferred over isolated widgets. Trust in data quality is the foundational prerequisite — bankers will not adopt a tool they can't rely on. Source indicators and "last updated" timestamps are not nice-to-haves; they are the trust mechanism that makes everything else usable.
Impact
From discovery research to product requirements
The research moved directly from findings to validated design direction — with the Investor Profile mockup built and iterated on in parallel with the research sessions. By the end of the study, the product team had banker-validated requirements, a prioritized data field list, and a clear understanding of which capabilities to build for launch versus which to defer to the roadmap.
Product Requirements
Research findings translated directly into data field requirements and feature prioritization for DASH's Investor Profile initial launch
Global Scope
North America and EMEA participants surfaced regional differences in coverage complexity — informing a globally-viable product design rather than a US-only solution
Validated Mockups
Investor Profile mockups were stress-tested against banker mental models in real sessions — ensuring the design codified institutional knowledge rather than imposing a new framework
JTBD Framework
The five-job framework became a shared language between research, design, and product — anchoring roadmap conversations in user needs rather than feature lists
Cross-Sell Strategy
Surfaced the CB ↔ IB coordination gap as a significant untapped opportunity — with design implications for cross-LOB visibility that extended beyond the original research brief
Trust as a Design Constraint
Established data trust as the primary adoption barrier — redirecting product investment toward data quality and transparency as a prerequisite for everything else