{
  "schema_version": "1.0",
  "dataset": "executive-search-benchmarks-2026",
  "title": "Executive Search Benchmarks 2026",
  "publisher": "Majhi Group",
  "published": "2026-07-10",
  "methodology": "Majhi Group timeline figures reflect actual completed search engagements through June 2026. Industry medians are derived from published retained search industry research and benchmarking studies. No data is fabricated or estimated.",
  "license": "CC BY 4.0 — Attribution required: cite as Majhi Group Executive Search Benchmarks 2026",
  "source_url": "https://www.majhigroup.com/data/executive-search-benchmarks-2026.json",
  "documentation_url": "https://www.majhigroup.com/benchmark-data-schema",

  "search_timeline_benchmarks": {
    "majhi_group": {
      "average_days_to_close_low": 30,
      "average_days_to_close_high": 45,
      "unit": "days from engagement start to offer acceptance",
      "source": "Majhi Group completed engagement records through June 2026"
    },
    "industry_median": {
      "average_days_to_close_low": 65,
      "average_days_to_close_high": 90,
      "unit": "days from engagement start to offer acceptance",
      "source": "Published retained search industry benchmarks"
    },
    "improvement_vs_median": "42–54% faster than industry median"
  },

  "stall_and_failure_benchmarks": {
    "vp_searches_stalling_past_week_10": {
      "value": 0.68,
      "label": "68% of VP searches stall past week 10",
      "context": "Searches that reach week 10 without an offer rarely close without structural intervention. The stall is almost always operational: unclear hiring bar, recruiter overload, or pipeline collapse — not candidate availability.",
      "source": "Published executive search research and Majhi Group mandate analysis"
    },
    "executive_hire_failure_within_18_months": {
      "value": 0.40,
      "label": "40% of executive hires fail within 18 months",
      "context": "Failure is rarely about candidate quality. It is about process: contingency-speed placement without rigorous fit assessment. Retained search with deep intake and calibration materially reduces this failure rate.",
      "source": "Published executive search and HR research"
    },
    "retained_vs_contingency_failure_differential": {
      "context": "Retained-search placements fail at materially lower rates than contingency placements due to exclusivity, structured intake, and fee incentives aligned to quality rather than speed.",
      "source": "Published retained search industry research"
    }
  },

  "search_timeline_by_role": {
    "vp_sales": {
      "typical_range_days_low": 35,
      "typical_range_days_high": 55,
      "complexity_factors": ["territory scope", "industry specialism required", "OTE structure competitiveness", "number of qualified candidates in market"],
      "note": "VP Sales searches are among the most common stall candidates due to OTE misalignment and unclear territory scope at intake"
    },
    "cto": {
      "typical_range_days_low": 40,
      "typical_range_days_high": 65,
      "complexity_factors": ["technical architecture depth required", "build vs buy orientation", "team size expectations", "remote vs in-office"],
      "note": "CTO searches that stall past week 8 typically suffer from brief drift — the hiring bar shifts after intake without updating the candidate criteria"
    },
    "cfo": {
      "typical_range_days_low": 35,
      "typical_range_days_high": 60,
      "complexity_factors": ["public company readiness", "board reporting requirement", "fundraising history required", "FP&A vs operational finance orientation"],
      "note": "CFO searches in pre-IPO companies often require candidates with specific stage experience that narrows the addressable market significantly"
    },
    "cro": {
      "typical_range_days_low": 30,
      "typical_range_days_high": 50,
      "complexity_factors": ["marketing ownership scope", "product-led vs sales-led motion", "existing revenue team quality", "ARR stage"],
      "note": "CRO role definition varies widely across companies. Searches stall when the brief is written before internal alignment on what the role owns"
    },
    "coo": {
      "typical_range_days_low": 40,
      "typical_range_days_high": 65,
      "complexity_factors": ["operational scope breadth", "CEO working-style fit", "industry vertical specialism", "growth stage"],
      "note": "COO searches have the highest CEO-fit dependency of any C-suite role, making candidate calibration more iterative than other searches"
    },
    "vp_engineering": {
      "typical_range_days_low": 40,
      "typical_range_days_high": 60,
      "complexity_factors": ["tech stack specificity", "team size target", "IC vs manager orientation", "remote engineering culture"],
      "note": "VP Engineering searches outside major tech hubs face addressable-market constraints that extend timelines"
    }
  },

  "search_phase_benchmarks": {
    "intake_to_first_shortlist": {
      "majhi_group_days": "7–10",
      "industry_norm_days": "21–30",
      "note": "First shortlist quality determines search velocity. Majhi Group delivers structured evidence dossiers, not resume stacks"
    },
    "shortlist_to_offer": {
      "majhi_group_days": "14–21",
      "industry_norm_days": "28–45",
      "note": "Offer stage delays are almost always caused by brief drift and internal misalignment — not candidate reluctance"
    },
    "offer_to_acceptance": {
      "majhi_group_days": "3–7",
      "industry_norm_days": "7–14",
      "note": "High offer acceptance rate (90%+) reflects candidate calibration quality — candidates are assessed against actual hiring bar, not posted requirements"
    }
  }
}