DISC and Predictive Index Weren't Built for This

This isn't a hit piece on DISC or Predictive Index. I want to get that out of the way upfront, because the moment you write anything that could be read as "your tool is bad," people stop listening.

DISC and PI are amazing tools. I've always been a big fan of them and will continue to be. For many of you, they're exactly what you need. For everyone else, you might find the answer to your questions by continuing to read farther.

What DISC and PI Do Well

These tools are well-validated, widely adopted, and genuinely useful for what they were designed to do. DISC helps people understand communication styles. Predictive Index helps organizations map behavioral drives and cognitive ability to job requirements. Millions of people have taken these assessments. HR departments have built entire talent strategies around them. They work.

If you're a 500-person company trying to understand why your sales team keeps clashing with your engineering team, DISC will give you useful insight. If you're hiring a VP of Marketing and you want to know whether their behavioral profile fits the role, PI will help you think about that more rigorously.

That's real value. I'm not dismissing it.

The Question They Weren't Designed to Answer

Here's the problem: a venture studio isn't asking "What's this founder's communication style?" A studio is asking something much more specific and much harder:

That's a team-level question. DISC and PI are individual-level tools. They'll tell you that Founder A is a high-D and Founder B is a high-S. They won't tell you what happens when those two profiles collide over a product decision at 11pm on a Sunday before a Monday investor pitch. They won't tell you that this specific combination, in this specific market context, with this specific goal, creates a predictable execution risk around shipping speed or financial diligence.

I talked to a studio founder who's launched over a thousand companies. He uses three different assessments on every founder: the Big Five personality model, Clifton Strengths, and something called the Saboteurs test. Three separate tools, none of which talk to each other, none of which model the team as a unit. He's essentially stitching together a patchwork of individual profiles and using his own judgment to interpret how they interact. And he's been doing this long enough to be pretty good at it — but he also admitted he hasn't been rigorous about tracking whether his interpretations were right.

That's not a criticism of him. He's doing more than 90% of studios. But it illustrates the gap: even the most sophisticated operators are assembling team insights manually from tools that were never designed to produce them.

I've heard variations of this from almost every studio I've talked to. One accelerator director told me he had both cofounders take a Gallup assessment, then threw the results into ChatGPT to see if they'd work well together. Another studio's partners are self-described "assessment nerds" who swear by Working Genius and were immediately comparing our approach to what they'd seen from Lencioni's framework. A psychologist I spoke with pointed out something subtle but important: most of these assessments measure theoretical behavior — "what would you do in this situation?" — rather than how someone actually operates under real conditions. There's a gap between what people say they'd do and what they actually do when the pressure is on.

Everyone's trying to solve this problem. Nobody has a purpose-built tool for it.

What Team-Level Analysis Looks Like Instead

The shift isn't incremental. It's not "DISC but better." It's a fundamentally different unit of analysis.

Individual assessment asks: who is this person? What are their strengths? What's their communication style?

Team-level analysis asks: what happens when you put these specific people together? Where will they amplify each other? Where will they create friction? What capability is missing from this combination that will become a problem at the next stage of growth?

That means you need context. Not just personality scores — but what the company is trying to accomplish, what stage it's at, what the market looks like, what the team's work history tells you about how they've operated before. A high-independence score means something very different for a solo founder building an MVP than it does for a cofounder who needs to collaborate daily with a consensus-driven partner.

When we simulate a team, we're not just stacking individual profiles side by side. We're modeling the interaction — the places where two people's natural tendencies will create productive tension, and the places where those same tendencies will create gridlock, resentment, or blind spots. We identify the team's archetype, its primary strength, its most likely execution risk, and what kind of person would best complement what's already there.

None of that is possible if you're starting from an individual assessment framework. You can't get to team-level insight by adding up individual scores. The whole is genuinely different from the sum of its parts.

The Compounding Data Advantage

Here's the other thing that separates a team diligence platform from a traditional assessment: DISC gives you a report. You read it, you maybe have a conversation about it, and then it goes in a drawer. It's episodic. You pull it out when something is at stake — an interview, a conflict, a team offsite — and then it goes away until the next time.

That's the core difference. A team diligence platform doesn't just assess — it tracks. Did the risk we flagged actually show up? Did the hire we recommended work out? Did the cofounder pair we analyzed stay together or fall apart? Every answer feeds back into the model.

For a venture studio making the same kind of decision over and over — founder pairing, cohort selection, first key hire — that feedback loop changes everything. Your fifth team decision is informed by the outcomes of your first four. Your twentieth is informed by nineteen. Over time, you're not relying on a generic personality framework built from a research sample of corporate employees. You're relying on your own data, from your own portfolio, calibrated to what actually works at your specific studio.

That's a dataset nobody else can replicate. And it's one that gets more valuable the longer you use it — which is exactly the opposite of a one-time assessment that sits in a drawer.

The Bottom Line

DISC and Predictive Index have earned their place. They're good tools for the problems they were designed to solve.

But venture studios aren't solving those problems. They're not asking "who is this person?" They're asking "will this team work?" And for that question, you need a different kind of tool — one that models the team as a unit, accounts for context, predicts specific risks, and learns from real outcomes over time.

The studios that figure this out early will have a structural advantage that compounds with every decision they make. The ones that keep borrowing tools from corporate HR will keep getting corporate HR-quality answers to venture-grade questions.

That gap is going to matter more, not less, as the stakes of every people decision keep rising.