Decision mapping process

This deep dive shows how we helped a venture studio bring structure to investment diligencebefore any tools, models, or automation.

The goal wasnt to add more process. It was to make decisions:

• Repeatable (the same question gets answered the same way)
• Auditable (why a decision was made is clear weeks later)
• Time-boxed (progress without endless rework)
• Aligned (executives and operators share the same definition of good enough)

If you want the full case context, see the parent case study: Enabling a Venture Studio to Accelerate Capital Allocations.

What we mapped (and why)

In high-velocity venture environments, the failure mode is rarely bad analysis. Its unclear decision rights, inconsistent evidence standards, and shifting goals mid-stream.

Decision mapping gave the client a shared operating system for diligence:

• A single end-to-end view of the investment process
• Clear gates (what gets decided, by whom, using what evidence)
• Explicit loops for revision vs. stop decisions
• Cross-cutting controls (assumptions, evidence, risk, and decision logs)

This is the work that makes later implementation possiblebecause you cannot automate ambiguity.

How we ran the mapping work (methodical, not theoretical)

We ran a structured sequence with the client team:

1. Decision inventory: what decisions recur, what triggers them, and what good looks like.
2. Artifact review: memos, spreadsheets, IC notes, email threadswhat actually drives a decision in practice.
3. Stakeholder walkthroughs: step-by-step replay of recent deals to surface hidden steps and informal criteria.
4. Gate definition: convert opinions into explicit criteria (minimum evidence, owner, and outputs).
5. Exception handling: identify where reality breaks the happy path and define how to respond.
6. Sign-off and adoption: align leadership on the map, then translate it into templates and routines.

Difficulties we had to overcome (and how we handled them)

• Different meanings of fit. Teams used the same word to mean different things (strategic fit, founder fit, timeline fit). We introduced a shared vocabulary and broke fit into explicit gates.
• Inconsistent evidence quality. Some deals had strong data; others relied on narrative momentum. We defined a minimum evidence pack and an assumptions register to separate facts from beliefs.
• Decision rights drift. In fast cycles, decisions were sometimes made by whoever was in the room. We clarified owners per gate and created a decision log so choices had continuity.
• Time pressure vs. diligence depth. We designed revision loops and stop rules to prevent sunk-cost escalation while keeping velocity.

Phase 1  Market and problem framing

Phase 1 ensures the team is answering the right investment questionbefore diligence expands.

flowchart TD
 A["Trigger: new opportunity for DD"] --> B["Intake and qualification"]
 B --> C{"Fit and priority gate"}
 C -- "No or defer" --> C1["Backlog or parked"]
 C -- "Yes" --> D["Frame the investment question"]


 subgraph P1["Phase 1 - Market and problem framing"]
   direction LR
   D --> D1["Thesis hypothesis: why now / why us / why this"]
   D1 --> D2["ICP and personas: roles / pains / willingness to pay"]
   D2 --> D3["Competitors and alternatives market scan"]
   D3 --> D4["Market sizing (ranges): boundaries / sensitivities"]
   D4 --> D5["Evidence pack: sources log / assumptions register"]
 end


 D5 --> E{"Thesis gate"}
 E -- "Revise" --> D1
 E -- "Proceed" --> F["Venture team setup and workplan"]

What this phase changed for leadership: fewer interesting ideas entering diligence, and more clarity on what needs to be true for a deal to earn time.

Phase 2  Commercial diligence

Phase 2 tests whether the opportunity can become a real businesswithout overbuilding a narrative.

flowchart TD

 D5["Evidence pack: sources log / assumptions register"] --> E{"Thesis gate"}
 E -- "Revise" --> D1["Thesis hypothesis: why now / why us / why this"]
 E -- "Proceed" --> F["Venture team setup and workplan"]


 subgraph P2["Phase 2 - Commercial diligence"]
   direction LR
   F --> F1["Stakeholder outreach: stakeholder calls"]
   F1 --> F2["Problem-solution validation: use cases / switching costs / value drivers"]
   F2 --> F3["Business model hypotheses: pricing logic / packaging / channels"]
   F3 --> F4["GTM stress test: pipeline math / sales cycle / CAC drivers"]
   F4 --> F5["Commercial headwinds / tailwinds register: mitigations / leading indicators"]
 end


 F5 --> G{"Commercial gate"}
 G -- "Stop" --> G1["Stop or learnings captured"]
 G -- "Iterate" --> F2
 G -- "Proceed" --> H["Technical and operational diligence"]

Where we were strict: the iterate loop had to result in new evidence, not stronger opinions. This prevented the team from re-litigating the same debate.

Phase 3  Technical and operational diligence

This phase turns a promising commercial case into an executable plan, without drifting into premature architecture.

flowchart TD

 G{"Commercial gate"}
 G -- "Stop" --> G1["Stop or learnings captured"]
 G -- "Iterate" --> F2["Problem-solution validation: use cases / switching costs / value drivers"]
 G -- "Proceed" --> H["Technical and operational diligence"]


 subgraph P3["Phase 3 - Technical and operational diligence"]
   direction LR
   H --> H1["Solution review: selling prop / pitch to validate"]
   H1 --> H2["GTM readiness: profiles to hire / GTM motions"]
   H2 --> H3["Delivery feasibility: roadmap / resourcing / dependencies"]
   H3 --> H4["Prototype: success criteria / MVP milestones"]
   H4 --> H5["Ops and scalability: hypothesis to validate / progress monitoring"]
 end


 H5 --> I{"Feasibility gate"}
 I -- "Revise scope" --> H3
 I -- "Proceed" --> J["Financial model and value creation plan"]

Exception case we handled explicitly: when feasibility risk was high but strategic upside was real, we created a scoped learn-fast path (revise scope) instead of forcing an approve/reject decision too early.

Phase 4  Investment case and structuring (with controls that persist post-investment)

Phase 4 is where leadership needs confidence: the case is coherent, the risks are visible, and the execution path is owned.

flowchart TD

 H5["Ops and scalability: hypothesis to validate / progress monitoring"] --> I{"Feasibility gate"}
 I -- "Revise scope" --> H3["Delivery feasibility: roadmap / resourcing / dependencies"]
 I -- "Proceed" --> J["Financial model and value creation plan"]


 subgraph P4["Phase 4 - Investment case and structuring"]
   direction LR
   J --> J1["Unit economics model: scenarios / sensitivities"]
   J1 --> J2["Value creation plan: day 100 / month 12 / month 24"]
   J2 --> J3["Governance and cadence: KPIs / decision rights"]
   J3 --> J4["MVP kill switches: protections / levers"]
   J4 --> J5["IC memo: narrative / top risks / mitigations / kill criteria"]
 end


 J5 --> K{"Approval gate"}
 K -- "Reject" --> K1["Reject and rationale archived"]
 K -- "Defer" --> C1["Backlog or parked"]
 K -- "Approve" --> L["Execute: close / onboard / activate plan"]


 subgraph P5["Phase 5 - Post-investment execution"]
   direction LR
   L --> L1["Follow up: results vs KPI"]
   L1 --> L2["Value creation delivery: initiatives / owners / timelines"]
   L2 --> L3["Pivot scale or exit gate"]
   L3 -- "Pivot" --> L2
   L3 -- "Scale" --> L2
   L3 -- "Exit readiness" --> M["Exit prep and outcomes narrative"]
 end


 subgraph X["Cross-cutting controls"]
   direction TB
   X1["Evidence log and citations"]
   X2["Assumptions register"]
   X3["Decision log and audit trail"]
   X4["Stakeholder comms tracker"]
   X5["Risk register and mitigations"]
 end


 D5["Evidence pack: sources log / assumptions register"] -.-> X1
 D1["Thesis hypothesis: why now / why us / why this"] -.-> X2
 F1["Stakeholder outreach: stakeholder calls"] -.-> X4
 F5["Commercial headwinds / tailwinds register: mitigations / leading indicators"] -.-> X5
 J5 -.-> X3
 L3 -.-> X3


 M --> N["Lessons learned to playbook updates"]
 N -.-> B["Intake and qualification"]

Why the controls matter: the client didnt just need a better decision in the momentthey needed a way to explain decisions internally, learn from them, and improve the system over time.

What leadership got out of this

• Clarity: what the process is, where it loops, and what done means at each gate
• Confidence: decisions are grounded in an explicit evidence standard and captured rationale
• Speed without chaos: time-boxed phases, revision loops, and clear stop criteria
• A foundation for execution: the map becomes the reference for templates, routines, and any future tooling

If youd like to see how this mapping work supported the broader engagement, return to the parent case: Enabling a Venture Studio to Accelerate Capital Allocations.

Note on scope

This page intentionally focuses on process and decision design. We avoided detailed technical architecture until the decision criteria and evidence standards were stable.