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---
type: claim
domain: internet-finance
description: "Bursty arrival processes require more safety capacity than Poisson models predict, scaled by variance-to-mean ratio"
confidence: proven
source: "Whitt et al., 'Staffing a Service System with Non-Poisson Non-Stationary Arrivals', Cambridge Core, 2016"
created: 2026-03-11
---
# Square-root staffing formula requires peakedness adjustment for non-Poisson arrivals because bursty processes need proportionally more safety capacity than the Poisson baseline predicts
The standard square-root staffing formula (workers = mean load + safety factor × √mean) assumes Poisson arrivals where variance equals mean. Real-world arrival processes violate this assumption through burstiness (arrivals clustered in time) or smoothness (arrivals more evenly distributed than random).
Whitt et al. extend the square-root staffing rule by introducing **peakedness** — the variance-to-mean ratio of the arrival process — as the key adjustment parameter. For bursty arrivals (peakedness > 1), systems require MORE safety capacity than Poisson models suggest. For smooth arrivals (peakedness < 1), systems need LESS.
The modified staffing formula adjusts the square-root safety margin by multiplying by the square root of peakedness. This correction is critical for non-stationary systems where arrival rates vary over time (daily cycles, seasonal patterns, or event-driven spikes).
## Evidence
- Whitt et al. (2016) prove that peakedness — the variance-to-mean ratio — captures the essential non-Poisson behavior for staffing calculations
- Standard Poisson assumption (variance = mean) fails empirically for bursty workloads like research paper dumps, product launches, or customer service spikes
- Using constant staffing (fixed MAX_WORKERS) regardless of queue state creates dual failure: over-provisioning during quiet periods (wasted compute) and under-provisioning during bursts (queue explosion)
## Relevance to Pipeline Architecture
Teleo's research pipeline exhibits textbook non-Poisson non-stationary arrivals: research dumps arrive in bursts of 15+ sources, futardio launches come in waves of 20+ proposals, while other days see minimal activity. The peakedness parameter quantifies exactly how much extra capacity is needed beyond naive square-root staffing.
This directly informs dynamic worker scaling: measure empirical peakedness from historical arrival data, adjust safety capacity accordingly, and scale workers based on current queue depth rather than using fixed limits.
---
Relevant Notes:
- domains/internet-finance/_map
Topics:
- core/mechanisms/_map

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---
type: claim
domain: internet-finance
description: "Replacing non-stationary arrival rates with constant staffing leads to systematic over- or under-provisioning"
confidence: proven
source: "Whitt et al., 'Staffing a Service System with Non-Poisson Non-Stationary Arrivals', Cambridge Core, 2016"
created: 2026-03-11
---
# Time-varying arrival rates require dynamic staffing not constant MAX_WORKERS because using average or maximum rates as constants creates systematic misallocation across the arrival cycle
Non-stationary arrival processes — where the arrival rate itself changes over time — cannot be efficiently staffed with constant worker counts. Whitt et al. demonstrate that replacing time-varying rates with either the average rate or the maximum rate produces badly mis-staffed systems:
- **Constant = average rate**: Under-staffed during peak periods, leading to queue explosions and service degradation
- **Constant = maximum rate**: Over-staffed during off-peak periods, wasting capacity and compute resources
The optimal approach tracks the arrival rate over time and adjusts staffing dynamically to match the current load plus an appropriate safety margin (scaled by peakedness for non-Poisson processes).
## Evidence
- Whitt et al. (2016) prove that time-varying arrival rates require time-varying staffing levels for efficiency
- Constant staffing at maximum capacity wastes resources during low-traffic periods
- Constant staffing at average capacity fails catastrophically during burst periods
- Dynamic staffing based on current queue state and arrival rate estimates achieves both efficiency (no waste during quiet periods) and reliability (adequate capacity during bursts)
## Application to Teleo Pipeline
Teleo's research processing pipeline exhibits strong non-stationarity: research dumps and futardio launches create burst periods with 15-20+ simultaneous arrivals, while other periods see minimal activity. Using a fixed MAX_WORKERS setting (constant staffing) is the worst of both worlds:
- During bursts: MAX_WORKERS is too low, queue explodes, processing stalls
- During quiet periods: MAX_WORKERS is too high, workers sit idle, compute wasted
Dynamic worker scaling based on current queue depth and estimated arrival rate (with peakedness adjustment) is the theoretically correct solution.
---
Relevant Notes:
- [[square-root-staffing-formula-requires-peakedness-adjustment-for-non-poisson-arrivals]]
- domains/internet-finance/_map
Topics:
- core/mechanisms/_map

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@ -6,8 +6,13 @@ url: https://www.cambridge.org/core/journals/probability-in-the-engineering-and-
date: 2016-01-01
domain: internet-finance
format: paper
status: unprocessed
status: processed
tags: [pipeline-architecture, operations-research, stochastic-modeling, non-stationary-arrivals, capacity-sizing]
processed_by: rio
processed_date: 2026-03-11
claims_extracted: ["square-root-staffing-formula-requires-peakedness-adjustment-for-non-poisson-arrivals.md", "time-varying-arrival-rates-require-dynamic-staffing-not-constant-max-workers.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
extraction_notes: "Operations research paper on staffing under non-Poisson non-stationary arrivals. Extracted two claims on peakedness adjustment and dynamic staffing requirements. Direct application to Teleo pipeline architecture for worker scaling. No entity data (academic paper, no companies/products/decisions). No enrichments (novel theoretical contribution not covered by existing claims)."
---
# Staffing a Service System with Non-Poisson Non-Stationary Arrivals