Deal Flow Management: Beyond the Spreadsheet Pipeline

Every emerging GP starts the same way: a Google Sheet with company names, a few columns for stage and notes, and maybe some conditional formatting to distinguish "Active" from "Passed." It works. For a while.

The problem emerges somewhere around deal 50-100. Your spreadsheet has become a graveyard of half-updated rows, unclear statuses, and notes that made sense three months ago but are now cryptic. You're scrolling through 200 rows to find the company you met last week. Your "pipeline review" consists of scanning a spreadsheet and trying to remember what happened with each deal.

This is not a deal flow management system. It's a list. And lists don't scale.

Why Spreadsheets Fail for Deal Flow

The fundamental issue is that deal flow is a process, and spreadsheets are built for data storage, not process management. Here's where the mismatch becomes painful:

No Workflow Visualization

A spreadsheet shows you rows. It doesn't show you flow. You can't glance at a spreadsheet and immediately see how many deals are in screening vs. diligence vs. term sheet. You have to filter, sort, or count manually. And when you're in a partner meeting trying to discuss the pipeline, scrolling through a spreadsheet is not an impressive presentation.

No Temporal Context

When did you first meet this company? How long have they been in diligence? When was the last time someone updated this record? Spreadsheets don't track history. Every edit overwrites the previous state, so you lose the narrative of how a deal has progressed.

No Source Attribution

Where did this deal come from? Was it a referral from your LP? A cold inbound? A conference meeting? Source tracking is critical for understanding what's actually generating your best deals, but in a spreadsheet, it's an afterthought column that rarely gets filled in consistently.

No Scoring Standardization

How do you compare Deal A to Deal B? If your evaluation criteria live in your head and your notes are in free-text format, every comparison is subjective and inconsistent. Two deals might both be labeled "interesting" but for completely different reasons with completely different conviction levels.

The Kanban Approach

A kanban board organizes deals into visual columns representing pipeline stages. At a glance, you can see the distribution of your pipeline and identify bottlenecks or gaps.

Standard Pipeline Stages

Here's a pipeline structure that works for most emerging VC funds:

Sourced: Initial entry point. You've heard about the company or received a referral. Minimal information captured — company name, one-line description, source, and initial gut reaction.

Screening: You've done enough initial research to determine whether the company warrants a first meeting. This stage includes reviewing the deck (if available), checking the market, and basic founder research.

First Meeting: You've met the founders. Your notes from the meeting are captured, and you have an initial assessment of team, market, and product.

Deep Diligence: You're serious about this deal. You're conducting reference checks, customer calls, market analysis, financial review, and competitive landscape assessment. This is the most resource-intensive stage.

Investment Committee: The deal has passed diligence and is being presented for a final investment decision. For solo GPs, this might be your own formal review process. For partnerships, it's the IC meeting.

Term Sheet / Closing: You've decided to invest and are in the process of negotiating terms and closing the deal.

Closed / Portfolio: The investment is made. The deal moves from pipeline to portfolio.

Passed: You decided not to proceed. Critically, you record why — this builds institutional knowledge about your decision-making patterns.

Why Kanban Works

The visual structure of a kanban board provides several advantages:

Pipeline balance: If you have 50 deals in "Sourced" and 0 in "Screening," you know you're not processing fast enough. If you have 5 deals in "Deep Diligence" simultaneously, you know you're overcommitted and quality will suffer.

Velocity tracking: How long does the average deal spend in each stage? If deals are sitting in "Screening" for three weeks, you have a bottleneck. If deals move from "First Meeting" to "Passed" in 2 days, your screening is effective.

Stage-appropriate views: When you're in deal-sourcing mode, you focus on the left side of the board. When you're doing diligence, you focus on the middle. Each mode of work has its own visual context.

Deal Scoring Frameworks

Subjective assessment of deals is unavoidable — investing is as much art as science. But a scoring framework adds structure to your evaluation and makes comparisons more rigorous.

Simple Scoring Model

Rate each deal on a 1-10 scale across four dimensions:

• - Team (30% weight): Founder quality, domain expertise, execution capability, team completeness
• - Market (25% weight): Market size, growth rate, timing, competitive dynamics
• - Product (25% weight): Product quality, differentiation, defensibility, customer traction
• - Deal Terms (20% weight): Valuation, round dynamics, governance rights, co-investor quality

A weighted composite score gives you a single number for ranking and comparison. A deal scoring 8+ across all dimensions is a strong candidate. A deal scoring 9 on team but 4 on market tells you something specific about the risk profile.

Scoring Discipline

The key is consistency. Score every deal that reaches the "First Meeting" stage. Do it immediately after the meeting while your impressions are fresh. Review your scores quarterly to calibrate — are your 8s actually performing better than your 6s? If not, your scoring criteria need refinement.

Over time, your scoring data becomes a valuable dataset. You can analyze patterns: "Our best investments all scored 8+ on team and 7+ on market, regardless of product score." This informs your strategy and sharpens your decision-making.

Deal Flow Analytics

Once your deal flow data is structured, you can extract insights that are impossible to derive from a spreadsheet:

Source Analysis

Which sources generate the most deals? Which sources generate the best deals (highest scores, most likely to reach IC)? Common insight: "40% of our deal flow comes from inbound, but 70% of our investments come from referrals." This tells you to invest more in relationship-based sourcing.

Conversion Rates

What percentage of sourced deals make it to first meeting? From first meeting to diligence? From diligence to investment? Typical benchmarks: - Sourced to First Meeting: 20-30% - First Meeting to Diligence: 15-25% - Diligence to Investment: 30-50% - Overall Sourced to Investment: 1-3%

If your conversion rates are significantly different from these benchmarks, it tells you something about your sourcing quality or evaluation rigor.

Sector Distribution

Are you seeing enough deals in your thesis areas? If your fund thesis focuses on healthcare AI but 80% of your pipeline is fintech, you have a sourcing gap in your core thesis.

Time-to-Decision

How long does it take from first meeting to investment decision? Faster isn't always better — rushing diligence creates risk — but if your average time-to-decision is 90 days and competitive deals are closing in 30, you're losing allocations to faster-moving funds.

The Archstone Deal Pipeline

Archstone's deal flow module is a kanban-based pipeline with all of the structure described above, built specifically for VC deal flow:

• - Customizable stages that match your specific workflow
• - Deal scoring with configurable criteria and weights
• - Source tracking with attribution analytics
• - Founder and contact management linked to each deal
• - Diligence checklists with customizable templates
• - Notes and timeline preserving the full history of each deal
• - Analytics dashboard with conversion rates, source analysis, and sector distribution

When a deal closes, it transitions seamlessly from the deal pipeline into the portfolio tracker. The company record carries over, and you start tracking operational metrics from day one.

Archie, our AI assistant, adds another layer. You can ask: "Show me all healthcare deals in diligence with a team score above 7" or "What's our conversion rate from first meeting to investment this quarter?" — and get instant answers without building pivot tables.

Making the Transition

If you're currently using a spreadsheet, here's how to migrate:

1. Export your current spreadsheet as a CSV
2. Map your columns to Archstone's deal fields (company name, stage, sector, notes, score)
3. Import the data — Archstone will create deal cards and place them in the appropriate pipeline stages
4. Start using the kanban for all new deals. Resist the temptation to maintain the spreadsheet in parallel — that defeats the purpose

The migration takes about an hour. The productivity gain starts immediately.

Your deal flow is the lifeblood of your fund. It deserves a system that matches its importance — one that helps you find, evaluate, and close the best deals, not one that makes you scroll through an endless spreadsheet hoping you don't miss something.