Engineers speak in milliseconds, percentiles, and CPU utilization. Executives speak in conversion, revenue, and customer satisfaction. This disconnect is one of the biggest barriers to performance investments.
This article shows how to translate technical metrics into business language — and why it matters.
Performance only gets priority when it speaks the language of business.
The Disconnection Problem
Typical conversation
Engineer: "We need to invest in optimization. Our p99 latency is at 800ms."
Executive: "What does that mean for the business?"
Engineer: "It's... bad for performance."
Executive: "We have other priorities."
Why this happens
- Different languages: technical vs commercial
- Different priorities: stability vs growth
- Different metrics: technical vs financial
- Different horizons: short term vs long term
Common Technical Metrics
Infrastructure
| Metric | What it measures |
|---|---|
| CPU utilization | Processing usage |
| Memory usage | Memory consumption |
| Disk I/O | Disk operations |
| Network bandwidth | Network usage |
Application
| Metric | What it measures |
|---|---|
| Latency (p50, p95, p99) | Response time |
| Throughput | Requests processed |
| Error rate | Failure rate |
| Availability | Uptime |
Database
| Metric | What it measures |
|---|---|
| Query time | Query duration |
| Connection pool usage | Connection usage |
| Lock wait time | Contention |
| Replication lag | Replica delay |
Business Metrics
Revenue
- GMV (Gross Merchandise Value)
- Revenue per user
- Average order value
- Cart abandonment rate
User
- Conversion rate
- Bounce rate
- Session duration
- User satisfaction (NPS, CSAT)
Operations
- Customer support tickets
- Churn rate
- Cost per transaction
- Time to resolution
Connecting the Worlds
Translation framework
Technical metric
↓
User impact
↓
Business impact
↓
Dollar value
Examples
Latency:
Latency p95: 500ms → 200ms
↓
Page loads faster
↓
Less abandonment, more conversion
↓
+2% conversion × $10M/month = +$200K/month
Availability:
Availability: 99.5% → 99.9%
↓
Less downtime
↓
Fewer lost sales
↓
3.6h/month of avoided downtime × $50K/h = +$180K/month
Errors:
Error rate: 2% → 0.5%
↓
Fewer failing transactions
↓
Fewer support tickets, more sales
↓
1500 avoided errors × $30/ticket = +$45K/month
Case Studies
Amazon
Discovered that each 100ms of additional latency cost 1% in sales.
Latency +100ms = Sales -1%
For Amazon, 1% = billions of dollars
Verified that pages 0.5s slower reduced traffic by 20%.
Latency +500ms = Traffic -20%
Less traffic = Less ad revenue
Walmart
Observed that each 1s of latency improvement increased conversion by 2%.
Latency -1s = Conversion +2%
Building Bridge Metrics
SLIs (Service Level Indicators)
Metrics that reflect user experience.
SLI: Checkout latency < 500ms
- Technical: latency percentile
- Business: impacts sales conversion
Composite metrics
User Experience Score = f(latency, errors, availability)
Where:
- Latency p95 < 200ms: +1
- Error rate < 0.1%: +1
- Availability > 99.9%: +1
Score 3/3 = Excellent
Score 2/3 = Acceptable
Score 1/3 = Problem
Cost per transaction
Monthly infra cost / Monthly transactions = Cost per transaction
January: $50K / 1M = $0.05/tx
February: $45K / 1.2M = $0.0375/tx (improvement!)
Communicating with Executives
What NOT to do
❌ "Our p99 latency went from 200ms to 400ms" ❌ "CPU is at 85%" ❌ "We have 50 timeouts per minute"
What to do
✅ "Our site is 2x slower, which may be causing cart abandonment" ✅ "We're near capacity limits. Without action, we may have outages during the next peak" ✅ "500 customers per hour are seeing errors at checkout, potentially losing $X in sales"
Communication template
SITUATION:
[Technical metric] is at [value], [X]% [above/below] normal.
USER IMPACT:
[What the user experiences]
BUSINESS IMPACT:
[Estimated impact in $ or business metric]
REQUIRED ACTION:
[What we need to do and how much it costs]
ROI:
[Cost of action vs cost of problem]
Example
SITUATION:
Checkout latency is at 800ms, 4x above normal.
USER IMPACT:
Payment page takes too long to load, some users abandon.
BUSINESS IMPACT:
We estimate 15% increase in cart abandonment.
With average ticket of $100 and 10,000 checkouts/day:
Potential loss: $150,000/day
REQUIRED ACTION:
Query optimization and cache addition.
Estimated cost: 2 weeks of 1 engineer (~$10,000)
ROI:
Investment of $10K to avoid $150K/day loss.
Payback in less than 2 hours.
Conclusion
The bridge between technical and business is essential for:
- Prioritization: performance competes with features for resources
- Investment: executives approve spending with clear ROI
- Alignment: everyone understands what matters
To build this bridge:
- Measure business impact alongside technical metrics
- Translate into language executives understand
- Quantify in dollars when possible
- Demonstrate ROI of performance investments
Latency in milliseconds doesn't pay salaries. Revenue does. Connect the two.