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Get Started Free →Apply organizational ambidexterity theory to balance exploration and exploitation activities. Use this skill when the user needs to diagnose whether an organization is over-exploiting or over-exploring, design structures that support both innovation and efficiency, or evaluate the tension between short-term performance and long-term renewal.
.claude/skills/asgard-ai-platform-grad-ambidexterity/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -26% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -35% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 67% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 4% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 33% | 0% |
Organizational ambidexterity refers to a firm's ability to simultaneously pursue exploration (innovation, experimentation, new opportunities) and exploitation (efficiency, refinement, execution of existing capabilities). March (1991) demonstrated that firms favoring one over the other face suboptimal outcomes: over-exploitation leads to competency traps, while over-exploration leads to failure traps.
Trigger conditions:
When NOT to use:
IRON LAW: Over-Exploiting Kills Long-Term Innovation;
Over-Exploring Kills Short-Term Revenue
Exploitation WITHOUT exploration leads to a COMPETENCY TRAP: the firm
becomes excellent at yesterday's business and is blindsided by change.
Exploration WITHOUT exploitation leads to a FAILURE TRAP: the firm
burns resources on experiments that never reach market scale.
There is no stable equilibrium — the balance must be actively managed.Assess the organization's exploration-exploitation ratio:
| Indicator | Exploitation-Heavy | Balanced | Exploration-Heavy | |-----------|-------------------|----------|-------------------| | R&D spend (% revenue) | < 3% | 5-15% | > 20% | | New product revenue (% total) | < 10% | 20-40% | > 50% | | Time horizon of projects | < 1 year | Mixed | > 3 years | | Tolerance for failure | Very low | Moderate | Very high | | Process formalization | Rigid | Adaptive | Chaotic |
Choose the structural approach:
For structural ambidexterity, define:
For contextual ambidexterity, define:
Establish review cycles (quarterly pipeline health, annual market trends) to detect drift toward either trap. Define trigger conditions for rebalancing.
markdown# Ambidexterity Assessment: {Organization} ## Current State Diagnosis - Balance: Exploitation-heavy / Balanced / Exploration-heavy - Evidence: {key indicators} - Risk: Competency trap / Failure trap / None ## Recommended Ambidexterity Mode - Mode: Structural / Contextual / Sequential - Rationale: {why this mode fits} ## Design Recommendations - Exploration unit: {scope, budget, metrics, reporting} - Exploitation unit: {scope, budget, metrics, reporting} - Integration mechanism: {how they connect} ## Rebalancing Triggers - {Condition 1}: shift toward more exploration - {Condition 2}: shift toward more exploitation
references/march-1991-model.mdreferences/structural-ambidexterity-design.md| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-19 | pass→pass | 23,597 | 19,268 | -18% | 1 | 1 | 0% | 3,668 | 3,764 | +3% | 0 | 0 | — |
case-01 | fail→pass | 106,037 | 24,317 | -77% | 1 | 1 | 0% | 5,754 | 4,251 | -26% | 0 | 0 | — |
case-02 | fail→fail | 56,929 | 24,546 | -57% | 1 | 1 | 0% | 6,921 | 4,697 | -32% | 0 | 0 | — |
case-03 | fail→pass | 45,723 | 24,875 | -46% | 1 | 1 | 0% | 7,080 | 4,569 | -35% | 0 | 0 | — |
case-04 | fail→fail | 52,949 | 27,650 | -48% | 1 | 1 | 0% | 7,112 | 4,934 | -31% | 0 | 0 | — |
case-05 | fail→pass | 16,104 | 15,601 | -3% | 1 | 1 | 0% | 2,312 | 3,869 | +67% | 0 | 0 | — |
case-06 | fail→pass | 25,595 | 18,214 | -29% | 1 | 1 | 0% | 3,852 | 4,023 | +4% | 0 | 0 | — |
case-07 | pass→pass | 17,019 | 21,090 | +24% | 1 | 1 | 0% | 2,627 | 4,392 | +67% | 0 | 0 | — |
case-08 | pass→pass | 23,234 | 24,224 | +4% | 1 | 1 | 0% | 3,029 | 3,998 | +32% | 0 | 0 | — |
case-09 | pass→pass | 20,547 | 19,446 | -5% | 1 | 1 | 0% | 2,679 | 3,983 | +49% | 0 | 0 | — |
case-10 | pass→pass | 22,190 | 34,753 | +57% | 1 | 1 | 0% | 3,434 | 3,809 | +11% | 0 | 0 | — |
case-11 | pass→pass | 38,717 | 16,586 | -57% | 1 | 1 | 0% | 2,730 | 3,877 | +42% | 0 | 0 | — |
case-12 | pass→pass | 23,296 | 19,174 | -18% | 1 | 1 | 0% | 2,877 | 4,205 | +46% | 0 | 0 | — |
case-13 | pass→pass | 33,170 | 53,516 | +61% | 1 | 1 | 0% | 4,363 | 4,627 | +6% | 0 | 0 | — |
case-14 | fail→pass | 17,069 | 23,890 | +40% | 1 | 1 | 0% | 2,648 | 3,512 | +33% | 0 | 0 | — |
case-15 | fail→pass | 22,086 | 16,074 | -27% | 1 | 1 | 0% | 2,837 | 3,723 | +31% | 0 | 0 | — |
case-16 | pass→pass | 30,571 | 22,284 | -27% | 1 | 1 | 0% | 3,955 | 4,298 | +9% | 0 | 0 | — |
case-17 | pass→pass | 20,885 | 21,181 | +1% | 1 | 1 | 0% | 3,230 | 3,804 | +18% | 0 | 0 | — |
case-18 | pass→pass | 20,512 | 20,508 | -0% | 1 | 1 | 0% | 2,630 | 3,748 | +43% | 0 | 0 | — |
case-20 | pass→pass | 33,659 | 57,316 | +70% | 1 | 1 | 0% | 4,145 | 5,156 | +24% | 0 | 0 | — |
case-21 | pass→pass | 35,304 | 35,342 | +0% | 1 | 1 | 0% | 4,429 | 5,780 | +31% | 0 | 0 | — |
case-22 | pass→pass | 30,719 | 30,448 | -1% | 1 | 1 | 0% | 4,070 | 4,711 | +16% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +27 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.