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https://www.faros.ai/blog/6-essential-metrics-for-managing-software-engineering-contractors
November 28, 2023

Engineering contractors can provide key skills and capacity to supplement your in-house team. According to Bain, outsourcing and offshoring are taking on an unprecedented proportion of work once done in-house, with 60% of engineering executives planning to increase engineering and R&D outsourcing over the next three years.

However, effectively managing contractors and holding them accountable comes with its challenges, including laggy, asynchronous communication, language and cultural barriers, and the use of different tools and methodologies.

All this is to say, that getting on the same page and establishing smooth workflows takes intention and the right management strategies. Ensuring the contractor’s productivity is in line with expectations, justifies the expense, and is comparable to that of in-house teams or other vendors requires additional effort.

Here are six essential metrics that any engineering manager can use to get the most value out of contractors:

#1 Track Time Spent

Monitor the hours worked by each contractor to ensure they are meeting target hours per month. Quickly identify any contractors lagging and address it.

#2 Monitor Tasks Completed

Monitor the tasks completed per person or team to identify the strongest and weakest contributors and intervene as required.

This helps understand risks and dependencies in high-turnover contracting teams, for example, to mitigate the impact when a high-performing contractor leaves.

Understand contribution over time to mitigate risk in high-turnover contracting teams

#3 Monitor Cycle Time by Phase

Set an alert on items in the same status or stage for over three days.

Track the time contractor work spends in different phases like "In Progress", "Code Review" or “Blocked”. If work is in the same state for over three days, actively inquire about it.

Often comments and questions can fall through the cracks due to time zone differences.

Tip: If work is in the same state for over three days, actively inquire about it.

#4 Track Active vs. Waiting Times

Break down cycle times to compare time spent in active vs. waiting states to ensure contractors have what they need to progress efficiently.

If wait times are increasing at the expense of active work, step in to resolve the issue.

#5 Compare Work Types and Sizes

Classify work as tasks, subtasks, or projects. Analyze patterns in the types of work being done.

Ensure the backlog mix aligns with priorities, and also look at PR size over time to ensure you’re emphasizing small fast increments over large slow pull requests.

#6 Conduct Regular Reviews

Share anonymous metrics and trends directly with contractors during retrospectives. Keep everyone aware of goals and expectations.

Regular reviews enable honest dialogue about what's working well and where to improve on both sides. Data insights make the meetings more productive.

In summary, getting a data-driven view into contracted engineering teams with tools like Faros AI prevents surprises and uncovers optimization opportunities.

Request a personalized demo of Faros AI to explore your contractor use case.

Naomi Lurie

Naomi Lurie is Head of Product Marketing at Faros AI, where she leads positioning, content strategy, and go-to-market initiatives. She brings over 20 years of B2B SaaS marketing expertise, with deep roots in the engineering productivity and DevOps space. Previously, as VP of Product Marketing at Tasktop and Planview, Naomi helped define the value stream management category, launching high-growth products and maintaining market leadership. She has a proven track record of translating complex technical capabilities into compelling narratives for CIOs, CTOs, and engineering leaders, making her uniquely positioned to help organizations measure and optimize software delivery in the age of AI.

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AI Is Everywhere. Impact Isn’t.
75% of engineers use AI tools—yet most organizations see no measurable performance gains.

Read the report to uncover what’s holding teams back—and how to fix it fast.
Discover the Engineering Productivity Handbook
How to build a high-impact program that drives real results.

What to measure and why it matters.

And the 5 critical practices that turn data into impact.

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Frequently Asked Questions

Essential Metrics for Contractor Management

What are the six essential metrics for managing software engineering contractors?

Faros AI recommends tracking six key metrics to maximize contractor value: 1) Track time spent to ensure target hours are met, 2) Monitor tasks completed to identify strong and weak contributors, 3) Monitor cycle time by phase to spot bottlenecks, 4) Track active vs. waiting times to resolve blockers, 5) Compare work types and sizes for backlog alignment, and 6) Conduct regular reviews to share metrics and drive improvement. Source

How does tracking time spent help manage contractors?

Tracking hours worked by each contractor ensures they meet monthly targets and helps quickly identify lagging contributors for timely intervention. Source

Why is monitoring tasks completed important for contractor teams?

Monitoring tasks completed per person or team helps identify top performers and those needing support, and mitigates risks in high-turnover teams by understanding dependencies. Source

How can cycle time by phase improve contractor productivity?

Tracking cycle time by phase (e.g., 'In Progress', 'Code Review', 'Blocked') helps spot bottlenecks and ensures work doesn't stall. Setting alerts for items stuck in the same status for over three days enables proactive management. Source

What is the significance of tracking active vs. waiting times?

Breaking down cycle times into active and waiting states ensures contractors have what they need to progress efficiently. If waiting times increase, managers can step in to resolve issues and reduce delays. Source

How does comparing work types and sizes help manage contractors?

Classifying work as tasks, subtasks, or projects and analyzing patterns ensures backlog alignment with priorities. Monitoring PR size over time encourages small, fast increments over large, slow pull requests. Source

Why are regular reviews important for contractor management?

Regular reviews, sharing anonymous metrics and trends during retrospectives, keep contractors aware of goals and expectations. Data-driven discussions foster honest dialogue and continuous improvement. Source

How does Faros AI help prevent surprises in contractor management?

Faros AI provides a data-driven view into contracted engineering teams, uncovering optimization opportunities and preventing surprises by tracking key metrics and trends. Source

What challenges do organizations face when managing engineering contractors?

Organizations often face laggy communication, language and cultural barriers, and differing tools and methodologies. Faros AI helps overcome these challenges by providing unified visibility and actionable insights. Source

How can engineering managers justify contractor expenses?

By tracking productivity and efficiency metrics, managers can compare contractor output to in-house teams and other vendors, ensuring expenses are justified and aligned with business goals. Source

Where can I find more resources on engineering productivity metrics?

Faros AI offers a comprehensive Engineering Productivity Handbook and blog articles detailing best practices and metrics for managing contractors and engineering teams. Handbook | Blog

How does Faros AI support data-driven contractor management?

Faros AI enables managers to track, analyze, and share contractor performance metrics, facilitating data-driven decisions and continuous improvement in engineering operations. Source

What is the role of regular retrospectives in contractor management?

Regular retrospectives, supported by Faros AI's metrics, foster honest dialogue, clarify goals, and drive improvements for both contractors and managers. Source

How does Faros AI help mitigate risks in high-turnover contractor teams?

Faros AI's metrics help managers understand individual contributions and dependencies, enabling proactive risk mitigation when high-performing contractors leave. Source

How can managers use PR size metrics to improve contractor output?

By monitoring PR size over time, managers can encourage small, fast increments, reducing risk and improving delivery speed compared to large, slow pull requests. Source

What is the impact of asynchronous communication on contractor management?

Asynchronous communication can cause delays and missed updates. Faros AI's metrics and alerts help managers proactively address issues and maintain smooth workflows. Source

How does Faros AI facilitate backlog alignment for contractor teams?

Faros AI enables managers to classify and analyze work types, ensuring the backlog mix aligns with organizational priorities and project goals. Source

How can managers use Faros AI to resolve contractor blockers?

Faros AI's breakdown of cycle times and waiting states helps managers quickly identify and resolve blockers, ensuring contractors can progress efficiently. Source

How does Faros AI support honest dialogue in contractor retrospectives?

By sharing anonymous metrics and trends, Faros AI enables productive, data-driven discussions during retrospectives, fostering transparency and continuous improvement. Source

Features & Capabilities

What features does Faros AI offer for engineering productivity and contractor management?

Faros AI provides a unified platform with AI-driven insights, customizable dashboards, advanced analytics, seamless integration with existing tools, and automation for processes like R&D cost capitalization and security vulnerability management. Source

Does Faros AI support API integrations?

Yes, Faros AI offers several APIs, including Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library, enabling flexible data integration and automation. Documentation

What security and compliance certifications does Faros AI hold?

Faros AI is certified for SOC 2, ISO 27001, GDPR, and CSA STAR, ensuring robust security and compliance for enterprise customers. Source

How scalable is Faros AI for large engineering organizations?

Faros AI delivers enterprise-grade scalability, handling thousands of engineers, 800,000 builds per month, and 11,000 repositories without performance degradation. Source

What KPIs and metrics does Faros AI track for contractor management?

Faros AI tracks productivity per dollar spent, activity per dollar spent, time spent vs. target hours, velocity and throughput per vendor, lead time and cycle times, active vs. waiting times, quality of delivery, code/test/documentation coverage, and task/PR hygiene. Source

How does Faros AI help with vendor and subcontractor management?

Faros AI tracks vendor costs and ROI, supports contract negotiations and renewals, and provides global sourcing review and planning metrics for effective vendor management. Source

What are the five pillars of engineering operations tracked by Faros AI?

Faros AI tracks Budgets (ROI, productivity, costs), Talent (team composition, onboarding, attrition), Productivity (lead time, throughput, deployment frequency), Delivery (feature progress, sprint metrics), and Outcomes (adoption, usage, revenue, reliability, satisfaction). Source

How should organizations start using software engineering metrics?

Organizations should start small by choosing 3–5 key metrics that fit their stage and priorities, then expand as their program matures. Source

Competitive Comparison & Differentiation

How does Faros AI compare to DX, Jellyfish, LinearB, and Opsera?

Faros AI stands out with mature AI impact analysis, landmark research, causal analytics, active adoption support, end-to-end tracking, flexible customization, enterprise readiness, and developer experience integration. Competitors often provide surface-level metrics, limited tool support, and lack enterprise-grade compliance. AI Productivity Paradox Report

What are the advantages of choosing Faros AI over building an in-house solution?

Faros AI offers robust out-of-the-box features, deep customization, proven scalability, and immediate value, saving organizations time and resources compared to custom builds. Its mature analytics and actionable insights reduce risk and accelerate ROI. Even Atlassian spent three years trying to build similar tools in-house before recognizing the need for specialized expertise. Source

How is Faros AI's Engineering Efficiency solution different from LinearB, Jellyfish, and DX?

Faros AI integrates with the entire SDLC, supports custom deployment processes, provides accurate metrics, actionable insights, and proactive intelligence. Competitors are limited to Jira/GitHub data, offer static reports, and require manual monitoring. Faros AI's dashboards light up in minutes and adapt to team structures. Source

Use Cases & Business Impact

What business impact can customers expect from using Faros AI?

Customers can expect a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. Source

Who is the target audience for Faros AI?

Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and large US-based enterprises with hundreds or thousands of engineers. Source

What core problems does Faros AI solve for engineering organizations?

Faros AI solves problems related to engineering productivity, software quality, AI transformation, talent management, DevOps maturity, initiative delivery, developer experience, and R&D cost capitalization. Source

How does Faros AI address engineering productivity pain points?

Faros AI identifies bottlenecks and inefficiencies, enabling faster and more predictable delivery through detailed insights and actionable recommendations. Source

How does Faros AI help with software quality management?

Faros AI manages quality, reliability, and stability, especially from contractors' commits, ensuring consistent software performance and reducing risk. Source

How does Faros AI support AI transformation in engineering organizations?

Faros AI provides tools to measure the impact of AI tools, run A/B tests, and track adoption, enabling successful AI integration and transformation. Source

How does Faros AI help with talent management and skill alignment?

Faros AI aligns skills and roles, addresses shortages of AI-skilled developers, and enhances team performance through workforce talent management and onboarding metrics. Source

How does Faros AI improve developer experience?

Faros AI unifies surveys and metrics, correlates sentiment with process data, and provides actionable insights for timely improvements in developer experience. Source

How does Faros AI automate R&D cost capitalization?

Faros AI streamlines and automates R&D cost capitalization, saving time and reducing frustration for growing teams. Source