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ProjectVelocity: Historical Estimation Benchmarking Service

A boutique consulting service that audits a PM's past 12-24 months of projects, extracts actual velocity data (tasks completed per person-week, accounting for task type, team composition, and dependencies), and builds a calibrated estimation model specific to that organization's context. The service delivers a custom estimation playbook with lookup tables, decision trees, and a trained estimation framework that the PM applies going forward.

SERVICE

19 weeks • 70% confidence

Value Proposition

Unlike generic estimation frameworks (Agile, PRINCE2), this is calibrated to YOUR team's actual productivity patterns, task interdependencies, and resource constraints. PMs get a model that reflects their specific context—not industry averages—so estimates become 40-60% more accurate immediately.

Target Audience

Mid-market tech/product teams (20-200 people) with 2+ years of project history and recurring estimation failures

Key Features

  • Historical project data extraction and normalization (Jira, Azure DevOps, Monday.com APIs)
  • Velocity analysis by task type, team member, and dependency complexity
  • Custom estimation lookup tables (e.g., 'Feature X with 3 devs + 1 QA = 6.2 weeks, not 4')
  • And more, with full implementation detail...

Tech Stack

Python (Pandas, NumPy for data analysis) Jira/Azure DevOps/Monday.com APIs SQL for data warehousing Excel/Google Sheets for playbook delivery
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Original Problem

Project managers cannot accurately predict delivery dates from resource allocation

Project managers struggle to estimate realistic project completion dates when given a fixed number of team members, leading to missed deadlines and broken stakeholder commitments. Current estimation methods fail to account for non-linear productivity, task dependencies, and resource constraints, forcing PMs to either over-promise or constantly revise timelines.

Score: 17.5%