Financial Scenarios: Modeling Talent Strategy

Executive summary#

• Financial scenarios compare total cost, timeline, and risk across build, buy, and partner options for closing capability gaps
• Three core models: Build (hire and develop), Buy (hire experienced), Partner (contractors/agencies)
• Total cost includes cost rate, time-to-billable, opportunity cost, and exit flexibility
• Scenario modeling prevents the common trap: choosing "lowest hourly rate" but ignoring total economics
• Use multi-scenario analysis when demand is uncertain or capability is new to the organization

Definitions#

Financial Scenarios: Comparative economic models showing total cost, timeline, risk, and ROI for different talent strategies (build vs. buy vs. partner) over a specific time horizon.

What's included: Direct costs (salaries, contractor fees), indirect costs (recruiting, onboarding, overhead), opportunity costs (revenue delay from ramp time), exit costs (severance, contract termination), and risk premiums.

What's NOT included: Sunk costs (past investments), non-financial factors in isolation (culture fit, team morale)—though these should inform the final decision after economics are clear.

Key distinction: Financial scenarios are forward-looking decision models (which option to choose) vs. cost accounting which is backward-looking (what did we spend).

Why this matters#

Business impact#

Scenario modeling prevents expensive mistakes:

Problem: Firms default to "build" (hire full-time) or "buy" (contractors) based on habit, not economics.

Consequence: Over-investment in permanent headcount when demand is uncertain, or over-reliance on contractors when building capability would be cheaper long-term.

Example decision without scenarios:

• Sales: "We need 3 cloud architects"
• Hiring: "Okay, posting job reqs"
• Result: 6 months later, $450K invested, still not staffed, missed $2M in opportunities

Example decision with scenarios:

• Sales: "We need 3 cloud architects for 18-month initiative"
• Finance: "Let me model 3 scenarios" (see below)
• Result: Chose hybrid approach (1 hire + 2 contractors), fully staffed in 4 weeks, captured $1.6M revenue

Types of scenarios to model:

1. Build: Hire FTEs, 8-12 week ramp, permanent cost structure
2. Buy (experienced hire): Hire senior FTEs, 4-6 week ramp, higher cost but faster
3. Partner: Contractors or agencies, 1-2 week ramp, higher hourly rate but flexible
4. Hybrid: Combination (e.g., 1 FTE + 2 contractors)

How it works#

The scenario modeling framework#

For each option, calculate Total Economic Cost over decision horizon:

Total Economic Cost = Direct Cost + Opportunity Cost + Exit Cost - Flexibility Value

Where:
  Direct Cost = (Cost Rate × Hours) + Recruiting + Onboarding
  Opportunity Cost = (Revenue Lost × Margin%) during ramp period
  Exit Cost = Severance, notice period, contract termination fees
  Flexibility Value = Option value of scaling up/down based on demand

Step 1: Define the decision parameters#

Required inputs:

• Capability needed: Specific competency (e.g., "AWS cloud architecture, Technical 3+")
• Volume needed: FTE count (e.g., "3 FTE")
• Time horizon: Planning period (e.g., "18 months")
• Demand certainty: Probability this need persists (e.g., "80% confident")
• Revenue at risk: What's lost if we can't staff (e.g., "$2M pipeline")

Step 2: Model each scenario#

Scenario A: Build (Hire Junior, Develop)

Characteristics:

• Hire Level 2 talent, develop to Level 3
• 8-12 week time-to-billable
• Lower cost rate, higher development investment
• Permanent cost structure

Cost model:

Direct Cost per FTE:
  Annual cost rate: $140K (junior + development time)
  Recruiting cost: $15K (agency fee or internal time)
  Onboarding cost: $8K (training, ramp time)

Time-to-billable: 10 weeks average
  Opportunity cost: 10 weeks × $3K/week × 3 FTE = $90K

Total 18-month cost:
  ($140K × 1.5 years × 3 FTE) + $69K recruiting/onboarding + $90K opportunity
  = $630K + $69K + $90K = $789K

Exit cost (if demand drops):
  3 months severance × 3 FTE = $105K

Pros: Lowest long-term cost, builds internal capability, better cultural fit Cons: Slowest time-to-billable, higher risk if demand uncertain, exit costs

Scenario B: Buy (Hire Senior)

Characteristics:

• Hire Level 3+ experienced talent
• 4-6 week time-to-billable
• Higher cost rate, minimal development needed
• Permanent cost structure

Cost model:

Direct Cost per FTE:
  Annual cost rate: $200K (senior, immediately productive)
  Recruiting cost: $25K (competitive market, agency fees)
  Onboarding cost: $6K (minimal ramp)

Time-to-billable: 5 weeks average
  Opportunity cost: 5 weeks × $3K/week × 3 FTE = $45K

Total 18-month cost:
  ($200K × 1.5 years × 3 FTE) + $93K recruiting/onboarding + $45K opportunity
  = $900K + $93K + $45K = $1,038K

Exit cost (if demand drops):
  3 months severance × 3 FTE = $150K

Pros: Fast time-to-billable, immediate productivity, less risk Cons: Higher cost, competitive hiring market, still permanent structure

Scenario C: Partner (Contractors)

Characteristics:

• Engage contractors at $180/hour
• 1-2 week time-to-billable
• No overhead, benefits, or recruiting costs
• Flexible engagement (scale up/down easily)

Cost model:

Direct Cost per FTE:
  Hourly rate: $180/hour
  Annual hours: 1,800 billable (90% utilization, no internal overhead)
  Annual cost per FTE: $324K
  Recruiting cost: $0 (agency provides)
  Onboarding cost: $2K (minimal integration)

Time-to-billable: 1.5 weeks average
  Opportunity cost: 1.5 weeks × $3K/week × 3 FTE = $13.5K

Total 18-month cost:
  ($324K × 1.5 years × 3 FTE) + $6K onboarding + $13.5K opportunity
  = $1,458K + $6K + $13.5K = $1,477.5K

Exit cost (if demand drops):
  $0 (terminate contract with 2-week notice, no severance)

Pros: Fastest time-to-billable, zero exit cost, flexible scaling Cons: Highest hourly cost, no capability building, less control

Scenario D: Hybrid (1 FTE + 2 Contractors)

Characteristics:

• Hire 1 senior FTE (team lead)
• Engage 2 contractors (delivery team)
• Balances speed, cost, and capability development

Cost model:

Direct Cost:
  1 Senior FTE: $200K × 1.5 years = $300K
    + $25K recruiting + $6K onboarding = $331K
  2 Contractors: $324K × 1.5 years × 2 = $972K
    + $4K onboarding = $976K

Time-to-billable:
  FTE: 5 weeks (but team partially staffed week 2 with contractors)
  Contractors: 1.5 weeks
  Blended opportunity cost: $25K (less impact due to partial staffing)

Total 18-month cost:
  $331K (FTE) + $976K (contractors) + $25K opportunity = $1,332K

Exit cost (if demand drops):
  FTE severance: $50K (3 months)
  Contractor termination: $0
  Total: $50K

Pros: Fast partial staffing, builds 1 FTE capability, flexible scaling Cons: Higher complexity, managing mixed workforce

Step 3: Compare scenarios#

Step 4: Factor in demand scenarios#

If demand is uncertain, model multiple demand scenarios:

Scenario 1: Demand persists 18 months (70% probability)

• Build wins: Lowest total cost ($789K)

Scenario 2: Demand drops after 6 months (20% probability)

• Partner wins: No exit cost, only $492K spent vs. $263K (Build) + $105K exit = $368K
• But Build is still cheaper in this scenario

Scenario 3: Demand extends beyond 18 months (10% probability)

• Build wins big: Cost advantage compounds over time

Expected value calculation:

EV(Build) = (0.70 × $789K) + (0.20 × $368K) + (0.10 × $789K) = $704K
EV(Buy) = (0.70 × $1,038K) + (0.20 × $496K) + (0.10 × $1,038K) = $930K
EV(Partner) = (0.70 × $1,477K) + (0.20 × $492K) + (0.10 × $1,477K) = $1,329K
EV(Hybrid) = (0.70 × $1,332K) + (0.20 × $494K) + (0.10 × $1,332K) = $1,165K

Decision: Build has lowest expected value even with 20% risk of early exit.

Example: CaseCo Mid#

{
  "canonical_block": "example",
  "version": "1.0.0",
  "case_ref": "caseco.mid.v1",
  "updated_date": "2026-02-16",

  "scenario_title": "Cloud Capability Build vs. Buy vs. Partner Analysis",
  "scenario_description": "CaseCo Mid needed to build cloud migration capability to pursue $3M pipeline. CFO required scenario analysis before approving talent investment.",

  "decision_context": {
    "capability_needed": "AWS cloud migration (Technical 3-4, Business 2-3)",
    "volume_needed": "3 FTE",
    "time_horizon": "18 months (initial contracts)",
    "demand_certainty": "75% confident demand persists",
    "revenue_at_risk": "$3M pipeline with 45% target margin = $1.35M margin at risk"
  },

  "scenarios_modeled": [
    {
      "scenario": "A: Build (Hire Level 2, Develop to Level 3)",
      "time_to_billable_weeks": 12,
      "cost_rate_per_fte": 145000,
      "recruiting_cost_per_fte": 15000,
      "onboarding_cost_per_fte": 10000,
      "opportunity_cost_total": 108000,
      "total_18_month_cost": 805500,
      "exit_cost_if_fails": 108750,
      "capability_building": "High",
      "flexibility": "Low"
    },
    {
      "scenario": "B: Buy (Hire Level 3 Experienced)",
      "time_to_billable_weeks": 6,
      "cost_rate_per_fte": 205000,
      "recruiting_cost_per_fte": 25000,
      "onboarding_cost_per_fte": 8000,
      "opportunity_cost_total": 54000,
      "total_18_month_cost": 1053000,
      "exit_cost_if_fails": 153750,
      "capability_building": "Medium",
      "flexibility": "Low"
    },
    {
      "scenario": "C: Partner (3 Contractors at $175/hr)",
      "time_to_billable_weeks": 2,
      "cost_rate_per_fte": 315000,
      "recruiting_cost_per_fte": 0,
      "onboarding_cost_per_fte": 2000,
      "opportunity_cost_total": 18000,
      "total_18_month_cost": 1441500,
      "exit_cost_if_fails": 0,
      "capability_building": "None",
      "flexibility": "High"
    },
    {
      "scenario": "D: Hybrid (1 Senior FTE + 2 Contractors)",
      "time_to_billable_weeks": 4,
      "breakdown": {
        "fte_cost": 332500,
        "contractor_cost": 945000,
        "opportunity_cost": 36000
      },
      "total_18_month_cost": 1313500,
      "exit_cost_if_fails": 51250,
      "capability_building": "Medium",
      "flexibility": "Medium"
    }
  ],

  "demand_scenario_analysis": {
    "scenario_1_full_18_months": {
      "probability": 0.75,
      "winner": "Scenario A (Build)",
      "cost": 805500
    },
    "scenario_2_demand_drops_month_6": {
      "probability": 0.20,
      "winner": "Scenario C (Partner)",
      "build_cost_6_months": 376250,
      "partner_cost_6_months": 480500
    },
    "scenario_3_demand_extends_beyond": {
      "probability": 0.05,
      "winner": "Scenario A (Build)",
      "note": "Cost advantage compounds over time"
    }
  },

  "expected_value_analysis": {
    "ev_build": 774000,
    "ev_buy": 993000,
    "ev_partner": 1345000,
    "ev_hybrid": 1221000,
    "recommendation": "Scenario A (Build)",
    "rationale": "Lowest expected value even with 20% risk of early exit. Builds long-term capability for repeat cloud business."
  },

  "cfo_decision": "Approved Scenario A with contingency: If demand drops before month 9, convert 1-2 FTEs to other projects rather than exit. This reduces actual exit risk further.",

  "actual_outcome_12_months_later": {
    "demand_reality": "Demand persisted and grew—now 4 FTE needed",
    "total_cost_actual": 798000,
    "revenue_captured": 2400000,
    "margin_captured": 1080000,
    "net_benefit": 282000,
    "key_learning": "Scenario modeling gave CFO confidence to invest. Without it, would have defaulted to contractors at $1.4M cost, losing $600K+ over 18 months and building zero internal capability."
  }
}

Action: Scenario Comparison Worksheet#

Use this framework to compare build vs. buy vs. partner options:

Scenario Modeling Template#

Decision Context:

• Capability needed: _______________________
• Volume needed: _______ FTE
• Time horizon: _______ months
• Demand certainty: _______% confident
• Revenue at risk: $_______

Scenario A: Build (Hire Junior, Develop)

Pros: _______________________ Cons: _______________________ Best if: _______________________

Scenario B: Buy (Hire Senior)

Pros: _______________________ Cons: _______________________ Best if: _______________________

Scenario C: Partner (Contractors)

Pros: _______________________ Cons: _______________________ Best if: _______________________

Scenario D: Hybrid (__ FTE + __ Contractors)

Pros: _______________________ Cons: _______________________ Best if: _______________________

Decision Matrix#

Recommended scenario: _______________________ Rationale: _______________________

Pitfalls#

Pitfall 1: Comparing hourly rates instead of total economic cost#

Early warning: Decision defaults to "cheapest hourly rate" without considering ramp time, exit costs, or flexibility value.

Why this happens: Hourly rates are visible and easy to compare. Total economic cost requires calculation and assumptions.

Example: FTE at $100/hour "looks" cheaper than contractor at $175/hour, but after factoring in:

• 12-week ramp vs. 2-week ramp (10 weeks × $3K opportunity cost = $30K)
• Overhead allocation ($40K/year not in contractor rate)
• Exit cost ($25K severance if demand drops)

True comparison: FTE = $140K total, Contractor = $315K for 18 months. FTE wins if demand certain, contractor wins if uncertain.

Fix: Always calculate total economic cost over the decision time horizon. Use the worksheet above.

Pitfall 2: Ignoring opportunity cost of slow time-to-billable#

Early warning: "Building" is chosen because lower cost rate, but 10-week delay costs $200K in lost revenue that's never recovered.

Why this happens: Opportunity cost is invisible—it's revenue that never appears in reports. Time-to-billable feels like "ramp time" not "lost revenue."

Example: CaseCo Mid debated hiring 2 junior consultants (12-week ramp, $140K cost rate) vs. 2 contractors ($315K, 2-week ramp) for a $1M engagement with 45% margin.

• Junior hire delay: 10 weeks × $9,600/week lost margin = $96K opportunity cost
• Total cost (juniors): $210K (6 months) + $96K opportunity = $306K
• Total cost (contractors): $315K (6 months) + $9,600 opportunity = $324.6K

Difference: $18.6K. Chose contractors for speed, captured full revenue.

Fix: Calculate opportunity cost as (Weeks delayed) × (Weekly revenue × Margin %) and include in total cost comparison.

Pitfall 3: Not modeling demand uncertainty with scenario analysis#

Early warning: Single scenario analysis assumes demand certainty when it's actually 50-70% probable.

Why this happens: Easier to model one scenario than multiple. Sales team overstates demand certainty to get resources.

Example: CaseCo Mid faced 60% confident demand for data engineering capability.

• Build scenario: $750K total cost, $120K exit cost if demand drops
• Partner scenario: $1.2M total cost, $0 exit cost

Single-scenario analysis: Build wins ($450K cheaper) Multi-scenario analysis:

• 60% demand persists: Build cost = $750K
• 40% demand drops month 6: Build cost = $375K + $120K exit = $495K
• Expected value (Build): (0.6 × $750K) + (0.4 × $495K) = $648K
• Expected value (Partner): (0.6 × $1.2M) + (0.4 × $400K) = $880K

Build still wins, but margin is smaller ($232K vs. $450K). If demand certainty drops to 50%, Partner wins.

Fix: Model 2-3 demand scenarios (full period, early exit, extended) and calculate expected value. If demand certainty <70%, weight flexibility more heavily.

Pitfall 4: Forgetting to include recruiting and onboarding costs in "build" scenarios#

Early warning: Build scenario uses only annual salary/cost rate without adding $15-25K per hire for recruiting, onboarding, training.

Why this happens: Recruiting feels like a "one-time" expense, not part of the hire cost. Onboarding time is invisible.

Example: "Hire costs $150K/year" vs. true first-year cost:

• Annual cost rate: $150K
• Recruiting (agency or internal recruiter time): $18K
• Onboarding (ramp time, training, low productivity): $12K
• True first-year cost: $180K (20% higher than assumed)

For 3-person team over 18 months:

• Assumed cost: $150K × 1.5 × 3 = $675K
• True cost: $180K (year 1) + $75K (6 months year 2) × 3 = $765K
• Difference: $90K (13% underestimate)

Fix: Add recruiting ($10-25K per hire) and onboarding costs ($5-15K per hire) to build and buy scenarios. Include in total cost calculation.

Next#

• Cost of Talent — Calculate cost rate for scenarios
• Cost of Risk — Quantify opportunity cost of delays
• Build-Buy-Partner — Decision framework for sourcing
• Demand Planning — Forecast demand certainty for scenarios

FAQs#

Q: How far out should I model scenarios—6 months, 12 months, 24 months?

A: Match your demand certainty horizon:

• High certainty (>80%): 18-24 months
• Moderate certainty (60-80%): 12-18 months
• Low certainty (<60%): 6-12 months

Beyond the certainty horizon, add scenario branches (demand extends vs. drops) rather than assuming continuation.

Q: Should I use "fully-loaded cost rate" or "cash cost" in scenario modeling?

A: Use fully-loaded cost rate for apples-to-apples comparison:

• FTEs: Salary + benefits + overhead allocation
• Contractors: Hourly rate × hours (no overhead allocation needed)

This makes contractor rates look higher but captures true economics. If you only compare salaries to contractor rates, you'll systematically underestimate FTE costs by 30-50%.

Q: What's a typical "time-to-billable" for each scenario?

A: Rough benchmarks:

• Build (junior hire): 8-12 weeks (recruiting 4-6 weeks + onboarding/training 4-6 weeks)
• Buy (senior hire): 4-6 weeks (recruiting 3-4 weeks + onboarding 1-2 weeks)
• Partner (contractor): 1-2 weeks (sourcing 3-5 days + onboarding 3-5 days)
• Hybrid: Depends on mix, typically 3-6 weeks blended

Faster time-to-billable is worth paying for when revenue is at risk.

Q: How do I calculate "opportunity cost" of delayed staffing?

A: Formula:

Opportunity Cost = (Weeks Delayed) × (Weekly Revenue Lost) × (Target Margin %)

Where:
  Weeks Delayed = Time-to-billable (Scenario A) - Time-to-billable (Scenario B)
  Weekly Revenue Lost = Revenue at risk / Engagement duration in weeks
  Target Margin % = Gross margin % (typically 40-50%)

Example: 8-week delay on $500K engagement (20 weeks), 45% margin:

• Weekly revenue: $500K / 20 = $25K/week
• Opportunity cost: 8 weeks × $25K × 0.45 = $90K

Q: When should I choose "Hybrid" (mix of FTE + contractors) over pure build or partner?

A: Hybrid works best when:

• Demand is moderately certain (60-75%): Too uncertain for full FTE team, too certain for all contractors
• Capability is new to the org: 1 FTE provides knowledge retention, contractors provide immediate capacity
• Demand is lumpy: FTE provides base capacity, contractors handle peaks
• Need team lead + delivery team: Senior FTE leads, contractors execute

Avoid hybrid if managing mixed workforce is complex (small team, first time hiring contractors, no experience managing contingent labor).

Q: What if my scenario analysis shows "Partner" is cheapest but we want to build capability?

A: Three options:

1. Accept the cost premium: If building capability is strategic, pay the premium. Document it as "capability investment" not "staffing cost."
2. Hybrid approach: Start with contractors (capture immediate revenue), hire 1-2 FTEs in parallel (build capability), phase out contractors over 6-12 months.
3. Improve build economics: Reduce time-to-billable (better onboarding, pre-training), hire more senior (faster ramp), or find talent at lower cost rate.

Don't ignore the economics—make capability building an explicit, funded choice.

Q: How often should I re-run scenario analysis?

A: Triggers for re-running:

• Demand changes significantly (>20% up/down from forecast)
• Market rates shift (competitor pricing, talent costs change >10%)
• Quarterly planning cycles (validate assumptions)
• Major hire decisions (>3 FTE or >$500K investment)

Don't re-run continuously—use scenarios for decisions, then commit and execute. Revisit when conditions change materially.

Q: What's a "good" cost difference between scenarios to change the decision?

A: If cost difference is:

• <10%: Choose based on strategic factors (capability building, flexibility, speed)
• 10-25%: Cost matters but consider risk—if demand uncertain, pay 15% premium for flexibility
• >25%: Cost should drive decision unless strategic factors are compelling (e.g., paying 30% premium to build core competency)

Don't agonize over $20K differences on $800K decisions. Focus on scenarios with materially different economics (>$100K or >15% difference).

Q: Should exit costs include "opportunity cost of low morale" from layoffs?

A: No—keep exit costs quantitative:

• Severance pay (3-6 months)
• Benefits continuation (COBRA, etc.)
• Recruiting cost to replace if you exit too early then need to re-hire

Morale impact, employer brand damage, etc. are real but hard to quantify. Document them separately as "strategic considerations" rather than adding arbitrary costs to the scenario.