Introduction

The Challenge

Accelerators and incubators face a fundamental tension: the most valuable work (one-to-one human connection between experienced coaches and ambitious founders) gets crowded out by administrative burden. Meanwhile, demonstrating impact to funding stakeholders requires evidence that's scattered across meeting notes, spreadsheets, and coach memories. Current methods force organizations to choose between delivering support and measuring it.

The impact OS Approach

impact OS resolves this tension through a founder-centric system of record that automates administrative work while building comprehensive evidence of impact. The system is built on three core principles:

1. Founder Journey Mapping: Organize everything around how founders actually build companies through team development, market traction, and technology evolution (the three dimensions).
2. Being Less Wrong Over Time: Help founders systematically improve their decision-making through leading/lagging indicator tracking, not just hold them accountable to hitting goals.
3. Foundational Data Enables Abstraction: Capture granular data (observations, commitments, metrics, interactions) so you can report at whatever level each audience needs: individual company details for coaches, portfolio patterns for leadership, aggregate outcomes for funders.

What Makes It Work

The system applies atomic research principles, breaking insights into reusable "nuggets" that can be tagged, filtered, and aggregated. When coaches meet with founders:

• Fireflies.ai automatically captures transcripts
• AI extracts observations categorized by dimension (Team/Traction/Technology)
• What would be 30-60 minutes of documentation becomes 5-10 minutes of review
• Coaches focus on conversation quality, not note-taking

Every two months, founders submit delta-based updates (pre-loaded with previous data, only changing what's different). Custom AI agents analyze accumulated data monthly and quarterly, synthesizing hours of manual analysis into minutes of review.

The Performance Framework

At VOLTA, the target is clear: $0 to $1M ARR in 18 months with 20% month-over-month growth. Head coaches balance this quantitative benchmark with qualitative observations about learning velocity and coachability, making informed exceptions for teams showing strong trajectory even if current metrics lag.

Sprint commitments create an objective framework: teams commit to controllable activities (leading indicators), then evaluate whether those activities moved key metrics (lagging indicators). Over multiple sprints, the data shows whether teams are improving their ability to make strategic bets, the real measure of coaching effectiveness.

Who This Is For

This approach is not for organizations satisfied with current impact reporting methods. It requires:

• Leadership genuinely dissatisfied with their ability to demonstrate impact
• Coaches who have lived the founder journey and thrive on accountability
• Cultural commitment to continuous improvement and transparency
• Willingness to invest in building capability over 12-18 months

If your organization values process compliance over outcomes, or prefers logistics-focused delivery over strategic accountability, this approach will struggle.

What Success Looks Like

• 90 days: Foundational data flowing (Fireflies transcripts, bi-monthly updates, interaction records)
• 6 months: Coaches spending 50% less time on documentation, able to answer key questions with data
• 12-18 months: Portfolio-wide patterns visible, stakeholder reports evidence-based, organizational learning accelerating

Most importantly: You're measuring not just whether companies succeed, but whether they're learning faster, and whether your program is learning faster about what actually accelerates company growth.

An Offer to Collaborate

At Volta, we built the impact OS because we needed to know whether our support was actually helping startups succeed. It's been a long evolution involving cultural shifts, coach buy-in, and continuous refinement. The rest of this document outlines how we approached it, the practical steps we took, and what we learned along the way.

If understanding the direct impact of your support is a priority, and you want to leverage what AI makes possible, we hope this is useful. We're learning as we go and would welcome conversations with other organizations working on similar challenges.

1. impact OS Guiding Principles

impact OS is built on a fundamental belief: the most valuable work happens in one-to-one human connection between coaches and founders. The system is designed around the founder journey, organizing impact measurement across the dimensions that matter most to company building, while eliminating the administrative burden that prevents coaches from focusing on what they do best: supporting people.

Design Principles

Founder-Centric Journey Mapping

impact OS organizes everything around understanding and supporting the founder journey. Rather than imposing program structures or administrative frameworks, the system maps to how founders actually build companies through team development, market traction, and technology evolution. This founder-centric lens ensures that every piece of data captured, every observation recorded, and every metric tracked serves to better understand where founders are in their journey and how best to support their next steps.

Designed for Human Connection, Not Administration

We intentionally hire experienced coaches who have been in the shoes of the founders they're supporting. These coaches understand the nuanced challenges of building a company because they've lived them. impact OS exists to maximize the time coaches spend in meaningful one-to-one conversation and minimize the time spent on paperwork. The system captures their work, amplifies their insights, and handles the administrative burden, but never attempts to substitute for the human judgment and connection that drives real impact.

Continuous Intake Over Cohorts

While many accelerators operate on fixed cohort schedules, impact OS is designed for continuous intake programs (though it can accommodate cohort models). Companies enter residency at various points in their journey and progress is assessed for each team the same way. This creates a more natural flow of support where resources can be allocated based on company needs rather than arbitrary timelines. Each company progresses at their own pace through a common framework of market-driven milestones.

Market Milestones as the North Star

At the heart of impact OS is a progression framework based on tangible market validation, not subjective assessments. Companies advance through clearly defined stages:

• Value Baseline: Validated problem-solution fit
• First Paying Customer: Initial market validation
• X Paying Customers: A statistically relevant number of paying customers
• 10X Paying Customers: Sufficient traction to prove a market for an ideal customer profile (ICP)
• $1M ARR: Proven business model
• $10M ARR: Scale-stage company

These milestones provide an objective, universally understood measure of progress. Whether a coach is reviewing a team's journey or a funding organization is evaluating portfolio impact, everyone speaks the same language: market traction.

Administrative Automation Through Intelligence

The system leverages AI not to make decisions, but to handle the tedious work that prevents coaches from being effective. When a coach meets with a company, simply inviting a Fireflies.ai note-taker to the meeting automatically:

• Captures the full transcript
• Generates detailed observations about company progress and challenges
• Creates structured meeting summaries
• Identifies potential support needs
• Tracks commitment follow-through

This transforms what would have been 30 to 60 minutes of post-meeting documentation into an automated process that happens in the background. Coaches review and refine the AI-generated content, ensuring accuracy while reclaiming time for actual coaching.

Bi-Monthly Pulse: Structured Progress Tracking

Every two months, companies receive automated reminders to submit progress updates through dynamic forms. These updates collect crucial metrics across multiple dimensions:

• Financial Health: Monthly recurring revenue, runway, burn rate, cash position
• Growth Metrics: Customer count, revenue trajectory, team size
• Investment Activity: Funding raised, investor relationships, capital structure
• Team Evolution: Full-time staff, part-time contributors, organizational changes

This regular cadence creates a longitudinal dataset that enables pattern recognition. Are companies typically hitting their first customer milestone within three months or six? Do teams with longer runway show better milestone progression? The bi-monthly updates provide the raw material for these insights.

Evidence-Based Impact Measurement

Traditional accelerator reporting often relies on anecdotal success stories or snapshot metrics. impact OS builds a comprehensive evidence trail by connecting:

• Sprint commitments set by companies
• Meeting interactions and coach observations
• Market milestone progression
• Quantitative metrics from bi-monthly updates
• Support engagement outcomes tied to specific OKRs

This creates an auditable chain from support delivery to measurable outcomes. When a company reaches a new milestone, we can trace back through the observations, meetings, and support engagements that contributed to that progress.

Quality Through Peer Review

The head coach role provides a critical quality assurance layer. Rather than relying solely on individual coach judgment, the system supports a structured QA workflow. AI-powered analysis tools help head coaches review quarterly progress across their entire portfolio, identifying:

• Companies making exceptional progress (and the interventions that helped)
• Teams showing warning signs or stagnation
• Coaches who might need additional support or training
• Patterns in what types of support correlate with positive outcomes

This creates organizational learning. Insights from successful interventions can be documented and shared, while struggling companies can be identified early for additional support.

The System of Record Philosophy

impact OS doesn't try to be a CRM, a project management tool, a communication platform, and a reporting system all in one. It focuses on being the definitive system of record for:

1. Who is in your portfolio (companies, founders, team members)
2. What support you're providing (interactions, engagements, observations)
3. Where they are in their journey (milestones, metrics, progress)
4. Why your support matters (correlations between interventions and outcomes)

By maintaining this clear focus, impact OS integrates with (rather than replaces) the tools teams already use. Meeting notes come from Fireflies. Communication happens in Slack or email. But the structured record of what happened and what it means lives in impact OS.

This architectural philosophy means organizations adopting impact OS aren't forced into wholesale workflow changes. Instead, they gain a layer of intelligence and structure on top of their existing practices, capturing institutional knowledge that would otherwise live only in individual coach's memories or scattered documents.

2. Core Entities & Relationships

impact OS is built around a set of interconnected entities that mirror the real-world structure of accelerator operations. Understanding these core building blocks and how they relate to each other is essential for grasping how the system supports the complete founder journey.

The Company: Center of Gravity

Companies are the central entity in impact OS. Each company represents a startup in your portfolio, whether they're in active residency, alumni, or applicants. The system maintains:

• Business Profile: Name, description, industry classification, location, founding date
• Current Status: Operating status (active, graduated, inactive), residency stage, market milestone achieved
• Performance Snapshot: Latest metrics from bi-monthly updates (revenue, customers, runway, team size)
• Journey History: Complete timeline of observations, interactions, and progress

The system can also track other organizations in your ecosystem (service providers, partners, potential investors) while maintaining focus on your core portfolio companies.

People: The Human Network

Contacts represent every individual in your ecosystem: founders, team members, coaches, advisors, investors, and mentors. The system recognizes that individuals often wear multiple hats and their relationships evolve over time:

• Personal Profile: Name, email, phone, LinkedIn profile, bio, photo
• Company Relationships: Individuals can connect to multiple companies with different roles (founder, employee, advisor, investor)
• Interaction History: Every meeting, conversation, and touchpoint
• Observation Trail: Insights captured about their progress, challenges, and growth

People and companies have flexible relationships. A founder might start one company, pivot, and launch another. An advisor might support multiple portfolio companies. The system captures this real-world complexity naturally.

Coaches are designated to provide ongoing support and are assigned to companies, creating the primary coaching connection that drives the residency experience.

Programs & Cohorts: Organizational Structure

While impact OS is designed for continuous intake, it accommodates structured programs through two levels:

Programs represent your high-level offerings, perhaps a "Residency Program," a "Scale Program," or industry-specific tracks. Programs define:

• Eligibility criteria
• Duration and structure
• Associated resources and support models
• Update schedules (e.g., bi-monthly check-ins)

Cohorts group companies within programs, either for true cohort-based programming or for administrative organization (e.g., "Q1 2024 Intake"). This flexibility means you can operate continuous intake while still organizing companies into logical groups for reporting, events, or specific initiatives.

Interactions: Capturing Engagement

Interactions record every meaningful touchpoint between coaches and companies:

• Meeting Type: One-on-one coaching sessions, group workshops, check-ins, advisor consultations
• Participants: Which companies and people attended
• Date & Duration: When the interaction occurred and how long it lasted
• Integration Points: Connection to Fireflies transcripts for automatic capture
• Observation Generation: Source material for AI-generated insights

Interactions create the paper trail of engagement. They answer: How often are we meeting with this company? Who's attending? What types of support are we providing? This quantitative layer sits beneath the qualitative insights captured as observations.

Observations: Qualitative Insights Through Atomic Research

Observations are the heart of impact measurement in impact OS. The system applies the principles of atomic research, a methodology that breaks down insights into their smallest, reusable components called "research nuggets." Rather than burying insights in lengthy reports that get filed away, each observation is a standalone, evidence-backed unit of knowledge that can be searched, filtered, and recombined to reveal patterns across your entire portfolio.

The Atomic Structure of an Observation:

Each observation follows a three-part atomic nugget structure:

1. Observation (Name + Description): What was discovered, a specific, actionable insight about company progress
2. Evidence: The supporting proof: direct quotes from meetings, data points from updates, or specific examples
3. Tags: Multiple layers of categorization for searchability and pattern recognition

Categorization Layers:

• Type/Dimension: Team, Traction, or Technology (the three core dimensions of founder journey)
• Topics: Thematic tags like "fundraising," "product-market fit," "team dynamics," "customer acquisition"
• Date: When the observation was made or evidence gathered
• Source: Link back to the interaction, company update, or external event that generated the insight

How Observations Are Created:

1. AI-Generated: Automatically extracted from meeting transcripts or company update submissions
2. Coach-Authored: Manually recorded insights from conversations or observations
3. System-Generated: Triggered by milestone achievements or metric thresholds

The Power of Atomic Observations

This atomic approach transforms how impact is measured and understood:

• Pattern Recognition: Tags enable you to see trends across multiple companies. Which challenges appear most frequently before companies hit their first paying customer? What team dynamics correlate with successful traction milestones?
• Searchability: Instead of asking "Which report mentioned that insight about pricing?", you can search observations by topic, company, date range, or dimension to instantly surface relevant insights.
• Context Preservation: While each observation stands alone, source links maintain the full context. You can trace from a single insight back to the complete meeting transcript or update submission.
• Reduced Waste: Tangential insights that don't fit the current conversation aren't lost. An observation about co-founder dynamics from a traction-focused meeting remains accessible when reviewing team challenges months later.
• Organizational Learning: Aggregating observations across your portfolio reveals which interventions work, which challenges are universal, and which support patterns correlate with success.

When a company hits a revenue milestone, the metrics show the number. Observations capture why it happened, what challenges they overcame, what support made the difference, and how their experience connects to patterns across your entire portfolio.

Support Engagements: Targeted Interventions

Beyond regular coaching, companies often need focused support on specific challenges. Support Requests formalize this:

• Problem Definition: Clear articulation of what the company needs help with
• Support Team: Assignment of coach, subject matter experts, or advisors
• OKRs & Commitments: Specific, measurable objectives for the engagement
• Progress Updates: Ongoing commentary and status tracking
• Outcomes: Observations and results linked to the support provided

This creates accountability and traceability. When you bring in a specialized advisor to help with go-to-market strategy, the support engagement tracks: What was the original challenge? What did we commit to? What actually happened? What was the impact?

Commitments: Learning to Be Less Wrong Over Time

The system tracks two types of commitments, but they serve a deeper purpose than simple accountability. They create an objective framework for measuring team behavior and helping founders systematically improve their decision-making.

Residency Commitments: Leading and Lagging Indicators

Sprint-based commitments operate on the principle of leading versus lagging indicators:

Leading Indicators are the specific, controllable activities that companies commit to:

• "+5 sales discovery calls"
• "+5 demo calls"
• "+5 customer interviews"
• "Ship feature X to beta users"

These are behaviors the team can directly control and objectively measure. Did they complete 5 discovery calls or not? This binary measurement provides clear insight into team engagement and execution capability.

Lagging Indicators are the outcomes you hope those activities will influence:

• "+5 paying customers"
• "20% month-over-month revenue growth"
• "Achieve product-market fit score of 40+"
• "Reduce churn by 15%"

These are results that emerge from the leading activities, but aren't directly controllable day-to-day.

The Philosophy: Being Less Wrong Over Time

The goal is not to "get it right" on any given sprint. The goal is to systematically improve the founder's ability to make effective bets. Here's how it works:

1. Make a Hypothesis: The team commits to specific activities (leading indicators) based on their hypothesis about what will move their metrics (lagging indicators).
2. Execute and Measure: Over a 2-4 week sprint, the team executes those activities. The system objectively tracks: Did they do what they committed to?
3. Evaluate the Bet: At sprint review, compare what actually happened to the lagging indicators. Did those 5 discovery calls lead to 2 paying customers as hoped? Or zero? Or 10?
4. Adjust and Improve: The team's next sprint commitments reflect what they learned. They're not failing when the bet doesn't pay off. They're learning to make better bets.

Over multiple sprints, this creates a data-driven narrative of founder growth. Are they getting better at predicting which activities will move their metrics? Are they learning to set more realistic targets? Are they identifying leverage points in their business model? And, most importantly, are they able to monetize the value they are delivering to the market in an increasingly predictable way?

Support Commitments: Objectives specific to a support engagement, tied to the OKRs defined when targeted support is initiated. These follow the same leading/lagging framework but are scoped to a specific challenge or opportunity.

Why This Matters for Impact Measurement

When leveraged, this approach has the potential to change how your organization measures impact:

• Objective Behavior Tracking: You're not relying on subjective assessments of "how hard they're working." You have binary data: they completed their commitments or they didn't.
• Learning Velocity: The real measure of coaching effectiveness isn't whether companies hit their goals. It's whether they're improving their ability to make strategic bets and learn from results.
• Pattern Recognition: Across your portfolio, you can identify which types of activities most reliably lead to which outcomes, creating institutional knowledge about what works.
• Coaching Conversations: Sprint reviews become evidence-based discussions: "You committed to X, achieved it, but didn't see movement on Y. What does that tell us about your business model?"

The commitment model doesn't just track what companies are doing. It creates a structured framework for accelerating founder learning and measuring that acceleration over time.

How It All Connects

The power of impact OS comes from how these entities interconnect:

1. Companies enter the Program and are optionally grouped into Cohorts
2. People (founders, team members) connect to Companies with designated roles
3. Coaches are assigned to Companies, creating the primary support relationship
4. Interactions bring together Companies and People (including coaches) to record touchpoints
5. Observations are generated from Interactions or Company Updates, categorized by dimension (Team/Traction/Technology)
6. Support Engagements provide opportunities for skill development through working with subject matter expert advisors measured by OKRs
7. Commitments create forward-looking goals that are validated through subsequent Observations and Updates

This interconnected model means you can answer complex questions:

• Which companies are making progress on team building but struggling with market traction?
• What interactions and observations preceded a company's breakthrough milestone?
• How much advisor support has each company received, and from whom?
• Which coaches are capturing the most observations, indicating deep engagement?
• What topics appear most frequently in observations for companies that successfully reach $1M ARR?

This doesn't just store data. It creates a knowledge graph of your organization's impact, enabling pattern recognition and organizational learning that would be impossible with disconnected spreadsheets or document folders.

3. The Impact Cycle: Plan, Execute, Measure, Report

impact OS doesn't impose a single workflow. It orchestrates multiple rhythms happening simultaneously. Daily conversations generate observations. Sprints create learning cycles. Bi-monthly updates capture trends. Monthly reviews ensure quality. Quarterly evaluations inform decisions. These rhythms interlock like gears, each operating at its natural frequency while keeping the entire system aligned around founder progress and organizational learning.

4. Adopting impact OS: Key Considerations

This represents a significant shift in how support organizations operate. The software is an enabler, but the critical work is ensuring team alignment to tackle the changes needed for successful implementation. It's not a software project, it's an ongoing commitment to understanding and improving your impact. The following sections outline key considerations we've learned from our experience.

A Call to Collaboration

At VOLTA, we know we're only scratching the surface of what's possible. The methods and tools outlined in this document represent our current understanding, but AI is evolving daily, and with it, what's possible for measuring and improving support organization impact.

We believe these capabilities are becoming critical for our organizations to remain relevant, both in the eyes of ambitious founders choosing where to build their companies, and funders deciding where to allocate resources for economic development.

This is a call to action for leaders of incubators and accelerators who see AI as an enabler of understanding impact and want to evolve their organizations accordingly. Whether you're considering adopting these approaches, have built similar systems, or are exploring different methods entirely, we welcome collaboration.

The challenges we face (demonstrating impact, helping founders learn faster, evolving economic development metrics) are shared across our entire ecosystem. We're stronger when we learn together.

If this framework resonates with your organization's direction and you're interested in collaborating on the continuous evolution of these methods and tools, we'd welcome the conversation.

Matt Cooper
CEO @ Volta