Skill: aniebyl/olo-deal-screening (version 1.0.0)

--- name: olo-deal-screening version: 1.0.0 description: Target company evaluation and deal qualification for PE and strategic buyers author: ololand.ai author_url: https://ololand.ai license: MIT triggers: - deal screening - target evaluation - investment criteria - acquisition criteria - deal qualification - deal fit - buyer criteria - deal scoring tags: - finance - screening - m-and-a - due-diligence - private-equity --- # Deal Screening for M&A Score and qualify acquisition targets against buyer investment criteria. ## Screening Framework Evaluate targets across five dimensions, each scored 0-100: ### 1. Strategic Fit (25% weight) - Industry/sector alignment with buyer portfolio - Geographic fit (markets, operations, customer base) - Product/service complementarity - Technology or capability gap fill - Brand and market position value ### 2. Financial Profile (25% weight) - Revenue scale (minimum threshold check) - Revenue growth trajectory (3-year trend) - EBITDA margin vs. industry benchmark - Revenue quality (recurring vs. one-time, customer concentration) - Working capital efficiency ### 3. Valuation Attractiveness (20% weight) - EV/EBITDA vs. comparable transactions - EV/Revenue vs. sector median - Implied IRR at estimated purchase price - Multiple arbitrage potential (buy low, exit higher) ### 4. Risk Profile (15% weight) - Customer concentration (top 10 customers as % of revenue) - Key-person dependency - Regulatory exposure - Technology obsolescence risk - Litigation or compliance issues ### 5. Execution Feasibility (15% weight) - Management team quality and retention likelihood - Integration complexity estimate - Competitive auction dynamics - Seller motivation and timeline - Financing availability ## Scoring Output ``` Overall Fit Score: 78/100 — PROCEED TO DD Strategic Fit: 85/100 ████████░░ Financial Profile: 72/100 ███████░░░ Valuation: 80/100 ████████░░ Risk Profile: 68/100 ██████░░░░ Execution: 82/100 ████████░░ Recommendation: PROCEED TO DD Key Strengths: [top 3] Key Concerns: [top 3] Suggested Next Steps: [prioritized actions] ``` ## Thresholds | Score Range | Recommendation | |-------------|----------------| | 80-100 | Strong fit — prioritize for DD | | 65-79 | Good fit — proceed with caution | | 50-64 | Marginal — requires strategic justification | | Below 50 | Poor fit — pass unless compelling thesis | ## Deal-Breaker Checks (Auto-Fail) Before scoring, check for absolute disqualifiers: - Revenue below buyer's minimum threshold - Negative EBITDA (unless growth-stage thesis) - Active material litigation exceeding 20% of EV - Sanctioned entities in ownership chain - Industry explicitly excluded by buyer mandate ## PE-Specific Criteria For financial sponsor buyers, additionally evaluate: - **LBO feasibility**: Can the deal be levered 3-5x EBITDA? - **Value creation levers**: Revenue growth, margin expansion, add-ons, multiple expansion - **Exit path**: IPO viability, strategic buyer universe, sponsor-to-sponsor - **Hold period returns**: Target 20-25% gross IRR over 3-5 years - **Fund fit**: Check size, vintage, sector focus, geographic mandate ## Output Format Provide structured JSON-compatible output with: - `overall_score`: 0-100 - `recommendation`: proceed_to_dd | proceed_with_caution | pass - `dimension_scores`: object with each dimension - `deal_breakers`: list of any auto-fail conditions triggered - `strengths`: top 3 positive factors - `concerns`: top 3 risk factors - `next_steps`: prioritized action items


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