95 lines
4.1 KiB
Markdown
95 lines
4.1 KiB
Markdown
# Evidence model
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## Research basis
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Treat the popular `0→1`, `1→10`, and `10→100` language as a practical stage
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metaphor, not a validated personality taxonomy.
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- Peter Thiel popularized `0→1` for creating something new versus copying an
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existing model. The later three-stage extension is practitioner language.
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- March's exploration/exploitation model supports a real distinction between
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searching for new possibilities and refining existing capabilities.
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- D'Acunto, Tate, and Yang found that startups with more diverse collective
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industry skillsets grew faster; a one-standard-deviation increase in skill
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diversity was associated with 16% higher five-year employment growth and
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10% higher sales growth from the mean.
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- A systematic review of entrepreneurial-team diversity describes diversity as
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a double-edged sword: knowledge breadth can help while disparity, separation,
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and conflict can hurt.
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- De Cooman et al. found the best team outcomes when members perceived both
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supplementary fit (important similarities) and complementary fit (different
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useful capabilities), mediated by cohesion.
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- Lewis's transactive-memory research supports making expertise legible:
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effective teams know who knows what and can coordinate that expertise.
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Sources:
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- March, *Exploration and Exploitation in Organizational Learning*:
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https://doi.org/10.1287/orsc.2.1.71
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- D'Acunto, Tate, and Yang, *Entrepreneurial Teams: Diversity of Skills and
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Early-Stage Growth*: https://doi.org/10.2139/ssrn.3750982
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- Klotz et al., *Entrepreneurial team diversity — A systematic review and
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research agenda*: https://doi.org/10.1016/j.emj.2022.10.004
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- De Cooman et al., *Creating Inclusive Teams Through Perceptions of
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Supplementary and Complementary Person–Team Fit*:
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https://doi.org/10.1177/1059601115586910
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- Lewis, *Measuring Transactive Memory Systems in the Field*:
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https://doi.org/10.1037/0021-9010.88.4.587
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## Operational model
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Assess two independent axes.
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### Startup-stage contribution
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| Vector | Observable evidence |
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| --- | --- |
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| `zero_to_one` | frames unmet needs; runs discovery; invents; prototypes under ambiguity; creates a first working artifact |
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| `one_to_ten` | interviews users; iterates from evidence; wins early customers; establishes a repeatable product/GTM loop |
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| `ten_to_hundred` | designs reliable systems; delegates; hires; manages quality and economics; scales repeatable operations |
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### Functional contribution
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| Vector | Observable evidence |
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| --- | --- |
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| `problem_discovery` | finds important unmet needs and tests assumptions |
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| `product` | chooses scope, sequences value, and integrates feedback |
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| `engineering` | builds and operates technical systems |
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| `design` | creates understandable, usable experiences |
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| `go_to_market` | positions, sells, distributes, and learns from the market |
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| `operations` | creates repeatable delivery and reliable processes |
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| `people_leadership` | recruits, aligns, coaches, and resolves conflict |
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| `capital_partnerships` | secures resources and durable external alliances |
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Do not equate a job title with evidence. One outcome may support several
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vectors, but state the linkage explicitly.
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## Evidence hierarchy
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Weight evidence in this order:
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1. verified customer or operational outcome;
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2. shipped public artifact with clear ownership;
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3. repeated responsibility with a concrete result;
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4. specific peer or collaborator feedback;
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5. self-reported preference.
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Preference indicates energy and desired role, not demonstrated capability.
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Require at least two independent strong evidence items for a high-confidence
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`strong` label. Use `unknown` when evidence is absent.
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## Matching rule
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Maximize:
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1. coverage of explicit stage and functional gaps;
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2. overlap in project purpose, collaboration mode, and operating principles;
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3. credible, current evidence;
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4. reciprocal usefulness.
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Check separately for commitment, decision rights, risk tolerance, pace,
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communication norms, and conflict handling. These are not "soft extras";
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complementary skills without operating compatibility can make a worse team.
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Never infer compatibility from demographics or sensitive traits.
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