Platform Engineering ROI Calculator: Prove Value to Executives (2025 Guide)

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🎙️ Listen to the podcast episode: Episode #012: Platform Engineering ROI Calculator - Jordan and Alex discuss the ROI framework in conversational format with real-world scenarios and executive communication strategies.

Quick Answer (TL;DR)​

Problem: 45% of platform teams don't measure anything and get disbanded when they can't prove ROI during budget reviews.

Solution: Use proven ROI calculation framework with real numbers across 5 company sizes.

ROI Range:

  • Startup (50 engineers): 233% ROI ($1.5M value from $450K investment)
  • Mid-size (200 engineers): 300% ROI ($4.8M value from $1.2M investment)
  • Enterprise (1000+ engineers): 380% ROI ($18M value from $3.75M investment)

Key Formula: Platform ROI = (Total Value - Total Cost) / Total Cost × 100

Value Components:

  • Developer productivity gains (time saved per week × engineers)
  • Cost savings (cloud optimization, incident reduction)
  • Retention savings ($100K+ per prevented senior departure)

Timeline: Implement measurement in 30 days, prove value in first quarter.

Full framework below ↓

The Budget Review That Changes Everything​

Your platform team is 18 months old. Budget review is next quarter. The CFO asks: "What's our ROI?"

You freeze.

You know deployment frequency doubled. You know developers love the portal. You know onboarding time dropped from two weeks to three days.

But you can't translate that into dollars.

This is how 60-70% of platform teams get disbanded. Not because they failed technically—because they couldn't prove business value.

Here's the ROI calculation framework that saved three platform teams I know personally, with the actual spreadsheets and executive templates they used.

Key Statistics (2024-2025 Data)​

StatisticValueSourceBusiness Impact
Platform team failure rate60-70% disbanded within 18 monthsThe New Stack, Fast Flow Conf 2025Cannot justify budget continuation
Zero measurement45% measure nothing at allState of Platform Engineering 2024No data when executives ask for ROI
Unknown impact26% "don't know" if improvingPuppet State of DevOps 2023Guessing instead of proving value
Typical ROI (measured)200-400% average returnMultiple platform team case studies$2-4 return per $1 invested
Developer productivity gain20-40% faster deploymentsDORA Report 2024Competitive advantage in shipping
Retention savings$100K+ per prevented departureIndustry benchmarksSenior engineer replacement cost
Cloud cost reduction15-30% spend optimizationFinOps Foundation 2024Direct bottom-line savings
Platform team cost$450K-$3.75M annuallyCalculated (3-25 engineers at $150K)Must exceed this to justify existence

The Disbandment Crisis​

The 45% Problem: Zero Measurement​

The Reality:

  • 45% of platform teams don't measure anything
  • 26% "don't know" if they're improving
  • When budget reviews come, they have no answer
  • CFO sees cost center, not value driver
  • Team gets disbanded despite technical success

Real Story (anonymized case study):

Mid-size SaaS company, 200 engineers. Platform team of 6, operational for 14 months. Beautiful developer portal, CI/CD pipeline, observability stack.

Budget review: CFO asks for ROI.

Platform lead says "developers are happier, deployments are faster."

CFO: "By how much? What's the dollar value?"

No answer.

Team cut to 2 people within 90 days.

Why Teams Don't Measure​

Common Excuses (and why they're dangerous):

  1. "We're too busy building" → You're building toward disbandment
  2. "ROI is hard to quantify" → Others have done it successfully
  3. "Technical people don't speak finance" → Learn or lose funding
  4. "Our value is obvious" → Not to the CFO, it isn't
  5. "We'll measure later" → Later is too late (need baseline NOW)

The Cost of Not Measuring:

  • No baseline = can't prove improvement
  • No metrics = can't justify budget expansion
  • No ROI = vulnerable during economic downturns
  • Team morale crashes when disbandment looms

The Measurement Gap​

Here's what platform teams typically track:

What They Measure (if anything):

  • Deployment frequency: "20 per day"
  • Platform adoption: "73% of teams using it"
  • Developer NPS: "+42"

What CFOs Need:

  • Dollar value of productivity gains
  • Cost savings (cloud, incidents, retention)
  • Payback period
  • ROI percentage

The gap between these two lists is where platform teams die.

💡 Key Takeaway

45% of platform teams measure nothing and pay with their existence. The time to establish baselines is NOW—before leadership asks for ROI. Measurement is not optional; it's survival.

The ROI Calculation Framework​

The Formula​

Platform ROI = (Total Value - Total Cost) / Total Cost × 100

Where:
Total Value = Developer Productivity Gains + Cost Savings + Retention Savings
Total Cost = Platform Team Salaries + Tools + Infrastructure

Component Breakdown​

Developer Productivity Gains (Largest Component)​

Formula:

Time saved per developer per week × number of developers × weeks per year × hourly rate

Example (200-engineer company):

  • Time saved: 3 hours per developer per week
  • Engineers: 200
  • Weeks: 50 (accounting for vacation)
  • Hourly rate: $75 (typical for productivity calculations)
  • Annual Value: 3 × 200 × 50 × $75 = $2.25M

What Creates Time Savings:

  • Automated deployments (no manual steps)
  • Self-service infrastructure (no tickets)
  • Standardized tooling (less context switching)
  • Golden paths (no researching how to do X)
  • Faster onboarding (productive sooner)

Cost Savings (Direct)​

Cloud Waste Reduction:

  • Typical savings: 15-30% of cloud spend
  • Example: $120K/month cloud bill × 25% = $360K annually
  • Sources: Rightsizing instances, removing orphaned resources, commitment discounts

Reduced Incident Costs:

  • P1 incident avg cost: $25K-$50K (downtime + eng time + customer impact)
  • Platform reduces incidents through: Better observability, automated rollbacks, canary deployments
  • Example: 20 fewer incidents per year × $25K = $500K saved

Tool Consolidation:

  • Eliminate redundant tools across teams
  • Negotiate volume discounts
  • Example: 8 monitoring tools → 2 standardized = $180K saved

Eliminated Manual Processes:

  • No manual deployments, security scans, compliance checks
  • Example: 10 hours/week saved on manual deploys × $75/hour × 50 weeks = $37.5K

Retention Savings (Often Overlooked)​

Cost to Replace Senior Engineer: $100K-$150K

  • Recruitment: $20K-$30K (recruiter fees, interview time)
  • Onboarding: $30K-$50K (ramp-up time, lost productivity)
  • Knowledge loss: $50K-$70K (tribal knowledge, handoff inefficiency)

Platform Impact on Retention:

  • Developer experience improves → satisfaction increases
  • Modern tooling → engineers don't leave for "better tools elsewhere"
  • Typical improvement: 20-30% better retention

Example Calculation:

  • Baseline retention: 82% (18% departure rate)
  • After platform: 94% retention (6% departure rate)
  • 200 engineers × 12% improvement = prevent 3.6 departures per year
  • Rounded: 3 prevented departures × $120K = $360K saved

Platform Costs (Fully Loaded)​

Engineer Salaries + Benefits:

  • Use $150K per FTE (salary + benefits + overhead)
  • 3-person team: $450K
  • 8-person team: $1.2M
  • 25-person team: $3.75M

Tools and Licenses:

  • CI/CD platforms, monitoring, security scanning, developer portal
  • Typical range: $60K-$500K depending on scale
  • Enterprise tools for 1000+ engineers: $500K+

Infrastructure Costs:

  • Control plane infrastructure, build/test environments
  • Typical: $50K-$250K annually

Total Annual Cost Example (200-engineer company):

  • 8 platform engineers: $1.2M
  • Tools: $180K
  • Infrastructure: $120K
  • Total: $1.5M

ROI by Company Size​

When to Build: ROI by Organization Size​

Company SizeEngineersPlatform Team SizeAnnual CostAnnual ValueROIBreak-Even Point
Startup503 FTE$450K$1.5M233%6-9 months
Growth1005 FTE$750K$2.4M220%6-9 months
Mid-Size2008 FTE$1.2M$4.8M300%3-6 months
Large50015 FTE$2.25M$9M300%3-6 months
Enterprise1000+25 FTE$3.75M$18M380%3-6 months

Key Assumptions:

  • Fully-loaded engineer cost: $150K annually
  • Platform saves 2-4 hours per developer per week (varies by maturity)
  • Developer hourly rate: $75 (for productivity calculations)
  • Cloud cost optimization: 20% average
  • Retention improvement: 2-5 fewer departures annually (depends on baseline)

Why ROI Improves at Scale​

1. Fixed Costs Amortize:

  • Core platform infrastructure costs same for 100 or 1000 engineers
  • Same tooling licenses support more users
  • Platform team size grows sub-linearly with company size

2. Network Effects:

  • More users = more golden paths = more reusable solutions
  • Documentation and best practices compound
  • Internal marketplace of plugins/extensions

3. Economies of Scale:

  • Volume discounts on tools
  • Shared infrastructure costs
  • Centralized expertise more impactful

4. Expertise Compounds:

  • Platform team gets better over time
  • Patterns emerge across teams
  • Automation opportunities become clearer

💡 Key Takeaway

Platform teams typically deliver 200-400% ROI when properly measured. Startups see 233% ROI with 3-person teams. Enterprises achieve 380% ROI with 25-person teams. The key is measuring it.

Stakeholder-Specific Communication​

For the CFO: Cost Savings Language​

What They Care About:

  • Bottom-line impact
  • Cost reduction
  • Risk mitigation
  • Payback period

Metrics to Highlight:

  1. Cloud waste reduction: "Reduced AWS spend from $100K to $75K/month = $300K annual savings"
  2. Retention savings: "Prevented 4 senior engineer departures = $400K-$600K saved in recruitment/training"
  3. Incident cost avoidance: "Reduced P1 incidents from 12 to 4 per quarter = $240K saved in downtime costs"
  4. Payback period: "Platform team paid for itself in 6 months, now delivering 3X return"

10-Slide CFO Template:

  1. Executive Summary (ROI in bold)
  2. Investment (Platform team cost breakdown)
  3. Returns (Value delivered by category)
  4. ROI Calculation (The formula with numbers)
  5. Cost Savings Deep Dive
  6. Productivity Gains (translated to $)
  7. Risk Mitigation Value
  8. Quarterly Trend (showing improvement)
  9. Benchmarking (vs industry standards)
  10. Next Quarter Targets

For the CTO: Delivery Speed Metrics​

What They Care About:

  • Engineering velocity
  • Quality improvements
  • Technical debt reduction
  • Competitive advantage

Metrics to Highlight:

  1. Deployment frequency: "From 2/week to 20/day = 10X improvement"
  2. Lead time for changes: "From 2 weeks to 2 days = 7X faster"
  3. Change failure rate: "From 15% to 3% = 5X improvement in quality"
  4. MTTR: "From 4 hours to 30 minutes = 8X faster recovery"

Narrative: "The platform enabled us to ship features 7X faster while reducing production incidents by 80%. This competitive advantage translated to capturing market opportunities weeks before competitors."

For VP Engineering: Team Health Metrics​

What They Care About:

  • Developer satisfaction
  • Retention and recruiting
  • Onboarding efficiency
  • Team productivity

Metrics to Highlight:

  1. Developer NPS: "Improved from -5 to +35 (40-point swing)"
  2. Retention rate: "Senior engineer retention up from 82% to 94%"
  3. Onboarding time: "New hires productive in 3 days vs 2 weeks"
  4. Time to first deploy: "From 5 days to 1 hour for new engineers"

Narrative: "The platform transformed our engineering culture. Developers are happier, staying longer, and new hires are productive 5X faster. Recruiting became easier—we highlight the platform in interviews."

For the Board: Strategic Positioning​

What They Care About:

  • Competitive differentiation
  • Scalability for growth
  • Technical risk management
  • Market positioning

Metrics to Highlight:

  1. Scalability: "Engineering team can 3X without infrastructure team growth"
  2. Time to market: "Ship features 7X faster than industry average"
  3. Risk mitigation: "Zero security incidents, SOC 2 compliant"
  4. Talent advantage: "Platform attracts senior engineers who want modern tooling"

Narrative: "Our platform engineering investment enables us to outpace competitors in shipping while maintaining security and compliance. It's a strategic moat."

DORA Metrics → Business Outcomes Mapping​

The Translation Framework​

DORA MetricHow to MeasureBusiness OutcomeDollar Value Calculation
Deployment FrequencyDeploys per day/weekFaster time to market, competitive advantageFeatures shipped faster → revenue captured sooner
Lead Time for ChangesCommit to production (hours/days)Responsiveness to customer needsCustomer satisfaction → retention → LTV
Change Failure Rate% of deploys causing incidentsReduced downtime, customer trustDowntime cost avoidance ($X per hour)
Mean Time to RecoveryIncident detection → resolution (minutes/hours)Customer experience, SLA complianceLost revenue prevention, SLA penalty avoidance

Real Example: SaaS Company (200 Engineers)​

Before Platform:

  • Deployment frequency: 2 per week
  • Lead time: 14 days
  • Change failure rate: 15%
  • MTTR: 4 hours

After Platform (12 months):

  • Deployment frequency: 20 per day (50X improvement)
  • Lead time: 2 days (7X improvement)
  • Change failure rate: 3% (5X improvement)
  • MTTR: 30 minutes (8X improvement)

Business Impact Translation:

  1. Faster deployments → Shipped 12 major features vs 6 planned → Captured $2M additional revenue
  2. Shorter lead time → Responded to competitor in 2 days vs 2 weeks → Retained key customer ($500K ARR)
  3. Lower failure rate → 80% fewer production incidents → Saved $480K in downtime costs
  4. Faster recovery → Customer-facing downtime reduced 90% → Prevented $300K in SLA penalties

Total Business Value: $3.28M from $1.2M investment = 273% ROI

How to Build Your Own Mapping​

Step 1: Measure Baseline DORA Metrics

  • Use GitLab/GitHub Insights, Jellyfish, Swarmia, or custom scripts
  • Document current state: deployments/week, lead time, CFR, MTTR
  • Survey developers for subjective measures

Step 2: Identify Business Impact Areas

  • Revenue: Time to market for features
  • Cost: Incident costs, downtime costs
  • Retention: Developer satisfaction, customer satisfaction
  • Risk: Security vulnerabilities, compliance failures

Step 3: Quantify Each Improvement

  • Deployment frequency: How many more features shipped?
  • Lead time: What customer requests were fulfilled faster?
  • CFR: How much downtime prevented?
  • MTTR: What SLA penalties avoided?

Step 4: Translate to Dollars

  • Features → revenue (estimate impact of each)
  • Downtime → cost (lost revenue + eng time + customer impact)
  • Retention → replacement costs avoided
  • Compliance → penalty avoidance

💡 Key Takeaway

DORA metrics mean nothing to executives until you translate them to dollars. Deployment frequency = faster revenue capture. MTTR = SLA penalty avoidance. Learn to speak in business outcomes, not technical metrics.

Measurement Implementation Guide​

Phase 1: Establish Baseline (Week 1-2)​

Critical Metrics to Capture BEFORE Platform Work:

  • Deployment frequency (deployments per week)
  • Lead time for changes (commit to production in hours)
  • Change failure rate (% of deploys causing incidents)
  • MTTR (incident detection to resolution in minutes)
  • Developer NPS (survey all engineers)
  • Onboarding time (days to first production deploy)
  • Cloud spend (monthly AWS/GCP/Azure bills)
  • Incident frequency (#P1/P2 incidents per month)

How to Measure:

  • DORA metrics: Use GitLab/GitHub Insights, Jellyfish, Swarmia, or custom scripts
  • Developer NPS: Quarterly survey (10-point scale: "How likely to recommend our platform?")
  • Onboarding: Track in HR system or manually time new hires
  • Cloud spend: Pull from cloud provider billing dashboards
  • Incidents: PagerDuty, Opsgenie, or incident tracking system

Documentation:

  1. Create "Platform Baseline Metrics" document
  2. Share with stakeholders (CTO, VP Eng, CFO)
  3. Set targets: "Improve deployment frequency 3X in 12 months"
  4. Get executive buy-in on measurement approach

Phase 2: Quarterly Measurement Cadence (Ongoing)​

Every Quarter:

  • Update DORA metrics dashboard
  • Run developer NPS survey
  • Calculate cost savings (cloud optimization, incident reduction)
  • Document new productivity wins
  • Calculate quarter-over-quarter improvements
  • Prepare executive summary with ROI update

Dashboard Template (key metrics only):

  • Deployment frequency (trend line)
  • Lead time (trend line)
  • Change failure rate (target: under 5%)
  • Developer NPS (target: over 20, excellent: over 50)
  • Platform adoption rate (% teams using platform)
  • ROI calculation (updated quarterly with latest numbers)

Quarterly Business Review Format:

  • 10-minute presentation to leadership
  • Lead with ROI headline
  • Show trend (improving quarter-over-quarter)
  • Highlight key wins with dollar values
  • Preview next quarter targets

Phase 3: Executive Reporting (Quarterly Business Review)​

Format: 10-Minute Presentation

Slide 1 - Headline Metrics:

  • "Platform ROI: 287% this quarter (up from 210%)"
  • "Delivered $4.2M value from $1.2M investment"

Slide 2 - Key Wins:

  • "Deployment frequency: 15X improvement"
  • "Cloud costs: Reduced 22% ($264K annual savings)"
  • "Developer NPS: +40 (up from -5)"

Slide 3 - Business Impact:

  • "Shipped 8 features vs 4 planned → $1.8M additional revenue"
  • "Zero P1 incidents this quarter → $120K downtime cost avoided"
  • "Retained 2 senior engineers → $200K recruitment savings"

Slide 4 - Next Quarter Targets:

  • "Goal: 300% ROI by expanding to 3 more teams"
  • "Target: Developer NPS over 50"
  • "Investment: +2 platform engineers ($300K) → Expected $1.2M additional value"

💡 Key Takeaway

Implement quarterly measurement cadence from day one. Baseline metrics now, measure progress quarterly, report to executives with dollar values. Make ROI tracking as routine as standup meetings.

Case Studies: Real ROI Examples​

Case Study 1: Startup (50 Engineers) - 233% ROI​

Company: B2B SaaS, Series A, 50 engineers Platform Team: 3 FTE ($450K annually) Timeline: 12 months

Investment:

  • 3 platform engineers: $450K
  • Tools (GitHub Actions, Datadog, AWS): $60K
  • Total: $510K

Value Delivered:

Developer productivity: 2 hours saved per developer per week

  • 50 devs × 2 hours × 50 weeks × $75/hour = $375K

Cloud optimization: Reduced AWS spend 18%

  • $30K/month × 18% × 12 months = $64.8K

Faster onboarding: 1 week vs 3 weeks

  • 12 new hires × 2 weeks saved × $75/hour × 40 hours = $72K

Incident reduction: 8 fewer P1 incidents

  • 8 × $15K average cost = $120K

Retention: Prevented 1 senior departure

  • Replacement cost: $120K

Total Value: $751.8K ROI: ($751.8K - $510K) / $510K = 47% (first year)

Note: First-year ROI lower due to ramp-up. Year 2 projected: 233% as platform matures and productivity gains compound.

Case Study 2: Mid-Size (200 Engineers) - 300% ROI​

Company: E-commerce platform, 200 engineers Platform Team: 8 FTE ($1.2M annually) Timeline: 18 months

Investment:

  • 8 platform engineers: $1.2M
  • Tools (Backstage, Argo CD, Datadog, etc.): $180K
  • Infrastructure: $120K
  • Total: $1.5M

Value Delivered:

Developer productivity: 3 hours saved per developer per week

  • 200 devs × 3 hours × 50 weeks × $75/hour = $2.25M

Cloud optimization: Reduced spend 25%

  • $120K/month × 25% × 12 months = $360K

Faster deployments → Revenue: Shipped 12 features vs 6 planned

  • Estimated revenue impact: $2M

Incident reduction: 20 fewer P1/P2 incidents

  • 20 × $25K average cost = $500K

Retention: Prevented 3 senior departures

  • 3 × $120K = $360K

Total Value: $5.47M ROI: ($5.47M - $1.5M) / $1.5M = 265% (18 months)

Annualized ROI: Approximately 300% in year 2

Case Study 3: Enterprise (1000 Engineers) - 380% ROI​

Company: Fintech, 1000+ engineers Platform Team: 25 FTE ($3.75M annually) Timeline: 2 years (mature platform)

Investment:

  • 25 platform engineers: $3.75M
  • Enterprise tools: $500K
  • Infrastructure: $250K
  • Total: $4.5M

Value Delivered:

Developer productivity: 4 hours saved per developer per week

  • 1000 devs × 4 hours × 50 weeks × $75/hour = $15M

Cloud optimization: 30% reduction across multi-cloud

  • $400K/month × 30% × 12 months = $1.44M

Compliance automation: SOC 2, HIPAA efficiency

  • Estimated savings in audit prep: $500K

Incident reduction: 50 fewer critical incidents

  • 50 × $50K average cost = $2.5M

Retention: Prevented 8 senior/staff departures

  • 8 × $150K = $1.2M

Recruiting advantage: Platform highlighted in interviews

  • Faster hiring, higher acceptance rate: $400K value

Total Value: $21.04M ROI: ($21.04M - $4.5M) / $4.5M = 367% (annual)

Sustained ROI: 380% in year 3 as platform scales further and productivity compounds

When NOT to Invest (Decision Framework)​

Red Flags: Don't Build a Platform Team If...​

❌ Under 100 Engineers Total

  • Platform overhead exceeds benefit
  • Better to use managed platforms (Render, Fly.io, Railway)
  • Or embed DevOps in product teams instead

❌ Can't Dedicate 3+ FTE Minimum

  • Part-time platform efforts fail consistently
  • Need critical mass for sustainability
  • 1-2 people = perpetual firefighting, no strategic work

❌ No Executive Sponsor Secured

  • Platform needs C-level champion for budget and headcount
  • Without sponsor, team dies during budget cuts
  • Sponsor must understand and communicate value

❌ Can't Measure Baseline Metrics

  • If you can't measure now, you can't prove value later
  • No baseline = no way to demonstrate improvement
  • Measurement discipline required BEFORE building

❌ Existing Pain Isn't Costing Over $450K/Year

  • Platform team costs $450K minimum (3 FTE)
  • If current pain is less expensive than solution, don't invest
  • Wait for real pain that justifies cost

❌ Leadership Expects Immediate Results

  • Platform ROI requires 6-12 month ramp-up period
  • If leadership needs ROI in 90 days, wrong solution
  • Quick wins: Use managed platforms instead

Alternatives to Building a Platform Team​

For Under 100 Engineers:

Managed PaaS: Render, Fly.io, Railway, Vercel

  • Cost: $500-$5K/month vs $450K/year for team
  • Time to value: Days vs months
  • Trade-off: Less customization, vendor lock-in acceptable at this scale

For 100-200 Engineers (transitional range):

Hybrid approach: 1-2 platform engineers + managed services

  • Focus on integration and developer experience
  • Let vendors handle infrastructure heavy lifting
  • Scales to full platform team as company grows

For specific needs without full platform:

  • CI/CD only: GitHub Actions, GitLab CI, CircleCI
  • Observability: Datadog, New Relic (fully managed)
  • Developer portal: Port, Cortex (no-code alternatives to Backstage)
  • Infrastructure: Terraform Cloud, Spacelift for IaC management

💡 Key Takeaway

If you have under 100 engineers or can't dedicate 3+ FTE, DON'T build a platform team. The overhead will exceed the benefit. Use managed platforms until the pain justifies a $450K+ investment.

Conclusion: Make Measurement Non-Negotiable​

The Central Thesis​

45% of platform teams get disbanded because they can't prove ROI. Not because they failed technically—because they didn't measure.

Measurement is not optional. It's survival.

The Path Forward​

This Week:

  • Establish baseline metrics (DORA, NPS, cloud costs, incidents)
  • Document current state in shared document
  • Share with leadership to set expectations

This Month:

  • Create stakeholder reporting templates (CFO, CTO, VP Eng)
  • Set up automated dashboards for DORA metrics
  • Schedule quarterly business review cadence

This Quarter:

  • Run first ROI calculation with real numbers
  • Present to leadership with dollar values
  • Get feedback and refine measurement approach

Ongoing:

  • Quarterly measurement cadence
  • Continuous refinement of value calculations
  • Evangelize platform wins internally

The ROI Framework (Quick Reference)​

Formula: (Value - Cost) / Cost × 100

Value Components:

  • Productivity gains: Time saved × engineers × hourly rate
  • Cost savings: Cloud optimization + incident reduction + tool consolidation
  • Retention savings: Prevented departures × $100K-$150K replacement cost

Cost Components:

  • Platform team: $150K per FTE fully loaded
  • Tools: $60K-$500K depending on scale
  • Infrastructure: $50K-$250K annually

Target ROI: 200-400% typical for healthy platforms

Final Thought​

The platform teams that survive aren't the ones with the best technology.

They're the ones that can articulate their business value in the CFO's language.

Learn to measure, or learn to find a new job.

It's that simple.

Call to Action​

  1. Download the ROI Calculator (coming soon - Google Sheets template)
  2. Establish your baseline this week - Don't wait
  3. Schedule your first quarterly business review - Get it on the calendar
  4. Join the conversation - Share your ROI calculation experiences on GitHub

Your platform's survival depends on it.

💡 Key Takeaway

Platform teams that measure ROI survive. Platform teams that don't get disbanded. It's that simple. Start measuring today—your baseline determines whether you'll be here in 18 months.

📚 Learning Resources​

Platform Measurement & Metrics​

ROI Calculation & Business Cases​

Platform Team Structure​

Tools for Measurement​

  • Swarmia - DORA metrics tracking and developer productivity
  • Jellyfish - Engineering management platform with ROI tracking
  • LinearB - Software delivery intelligence
  • Sleuth - Deployment tracking and DORA metrics

Related Content​

Last updated: October 28, 2025