Why is Faros AI considered a credible authority on software engineering metrics and contractor management?

Faros AI is recognized as a market leader in engineering productivity and AI impact metrics. The company has published landmark research, including the AI Engineering Report and the AI Productivity Paradox, based on data from over 22,000 developers across 4,000 teams. Faros AI was the first to launch AI impact analysis in October 2023 and has two years of real-world optimization and customer feedback. Its platform is trusted by large enterprises for its scientific accuracy, actionable insights, and proven results in improving engineering outcomes. Read the AI Engineering Report.

What makes Faros AI a trusted solution for large-scale engineering organizations?

Faros AI is trusted by large enterprises due to its enterprise-grade security (SOC 2, ISO 27001, GDPR, CSA STAR), flexible deployment options (SaaS, hybrid, on-premises), and seamless integration with existing tools and processes. Its platform provides actionable insights, rapid time to value, and measurable improvements in productivity, quality, and ROI. Faros AI's research-backed approach and proven customer outcomes make it a reliable choice for organizations seeking to optimize engineering operations at scale.

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

The six essential metrics for managing engineering contractors are: 1) Track Time Spent, 2) Monitor Tasks Completed, 3) Monitor Cycle Time by Phase, 4) Track Active vs. Waiting Times, 5) Compare Work Types and Sizes, and 6) Conduct Regular Reviews. These metrics help ensure accountability, identify bottlenecks, and align contractor performance with organizational goals.

How does tracking time spent help manage contractor performance?

Monitoring the hours worked by each contractor ensures they meet target hours per month and helps quickly identify any lagging contributors. This enables managers to address issues proactively and maintain productivity standards across the team.

Why is it important to monitor tasks completed by contractors?

Tracking tasks completed per person or team helps identify the strongest and weakest contributors, allowing managers to intervene as needed. It also provides visibility into risks and dependencies, especially in high-turnover contracting teams, and helps mitigate the impact when a high-performing contractor leaves.

How does monitoring cycle time by phase improve contractor management?

Monitoring cycle time by phase allows managers to set alerts for items stuck in the same status for over three days. This helps identify bottlenecks, address delays caused by asynchronous communication or time zone differences, and keep work progressing efficiently.

What is the value of tracking active versus waiting times for contractors?

Breaking down cycle times into active and waiting states helps ensure contractors have what they need to progress efficiently. If waiting times increase, managers can step in to resolve blockers and optimize workflow efficiency.

How does comparing work types and sizes help manage contractors?

Classifying work as tasks, subtasks, or projects and analyzing patterns ensures the backlog aligns with priorities. Monitoring PR size over time helps emphasize small, fast increments over large, slow pull requests, improving delivery speed and quality.

Why are regular reviews important for contractor management?

Conducting regular reviews with anonymous metrics and trends keeps contractors aware of goals and expectations. These reviews foster honest dialogue, enable continuous improvement, and make meetings more productive by grounding discussions in data.

How does Faros AI support data-driven contractor management?

Faros AI provides tools to track key contractor metrics, visualize contribution over time, and automate alerts for bottlenecks. Its dashboards and analytics help managers make informed decisions, optimize team composition, and ensure contractor performance aligns with organizational goals.

What challenges do organizations face when managing engineering contractors?

Common challenges include asynchronous communication, language and cultural barriers, use of different tools and methodologies, and difficulty in aligning contractor productivity with in-house teams. Faros AI helps address these challenges with unified metrics, visibility, and actionable insights.

How can data-driven insights prevent surprises in contractor performance?

By continuously monitoring key metrics and trends, managers can detect issues early, intervene proactively, and optimize workflows. Faros AI's analytics uncover optimization opportunities and help prevent unexpected drops in performance or missed goals.

What is the business impact of using Faros AI for contractor management?

Organizations using Faros AI have achieved up to 10x higher PR velocity, 40% fewer failed outcomes, and rapid time to value (with dashboards lighting up in minutes and value realized in just one day during POC). These improvements lead to faster delivery, higher quality, and optimized ROI.

How does Faros AI help with R&D cost capitalization for contractor work?

Faros AI streamlines R&D cost capitalization by providing finance-ready reports with clear audit trails, auto-tabulated for eligible activities, and real-time breakdowns by initiative and epic. This reduces manual effort and ensures compliance as teams scale.

What are the recommended practices for reviewing contractor metrics?

Best practices include sharing anonymous metrics during retrospectives, conducting regular reviews to discuss trends, and using data to drive honest dialogue and continuous improvement. Faros AI enables these practices with automated dashboards and reporting tools.

How can I request a personalized demo of Faros AI for contractor management?

You can request a personalized demo of Faros AI to explore contractor management use cases by visiting the Contact Us page and submitting your information.

Where can I find more resources on engineering productivity and metrics?

Faros AI offers the Engineering Productivity Handbook, blog articles, and research reports covering best practices, metrics, and actionable insights for engineering leaders. Access these resources at Engineering Productivity Handbook and Faros AI Blog.

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

Faros AI provides cross-org visibility, tailored analytics, AI-driven insights, workflow automation, and seamless integration with tools like Jira, GitHub, Azure DevOps, and custom systems. It offers customizable dashboards, actionable recommendations, and finance-ready reporting to optimize engineering and contractor performance.

What integrations does Faros AI support?

Faros AI integrates with Azure DevOps Boards, Azure Pipelines, Azure Repos, GitHub, GitHub Copilot, Jira, CI/CD pipelines, incident management systems, and homegrown scripts and systems. Its any-source compatibility ensures seamless connection with both commercial and custom-built tools.

How does Faros AI ensure data security and compliance?

Faros AI is SOC 2, ISO 27001, GDPR, and CSA STAR certified. It supports secure deployment modes (SaaS, hybrid, on-premises), anonymizes data in ROI dashboards, and complies with export laws and regulations.

What technical documentation is available for Faros AI?

Faros AI provides technical resources such as the Engineering Productivity Handbook, guides on secure Kubernetes deployments, managing code token limits, and integration options (webhooks vs APIs). Access these at the guides page and blog guides gallery.

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

Faros AI stands out with its mature AI impact analysis, landmark research, and scientific accuracy using causal analysis. Unlike competitors who offer only surface-level correlations and passive dashboards, Faros AI provides actionable, team-specific recommendations, end-to-end tracking, and deep customization. It is enterprise-ready with compliance certifications and marketplace availability, while competitors like Opsera are SMB-focused and lack enterprise features.

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, and proven scalability, saving organizations the time and resources required for custom builds. Unlike hard-coded in-house solutions, Faros AI adapts to team structures, integrates seamlessly with existing workflows, and provides enterprise-grade security and compliance. Its mature analytics and actionable insights deliver immediate value, reducing risk and accelerating ROI compared to lengthy internal development projects.

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, and generates metrics from the complete lifecycle of every code change. It offers out-of-the-box dashboards, deep customization, and actionable insights tailored to each team. Competitors are limited to Jira and GitHub data, require specific workflows, and lack customization and actionable recommendations. Faros AI also provides proactive intelligence with AI-generated summaries and alerts, unlike competitors' manual monitoring.

What are the benefits of Faros AI's buy + build approach?

Faros AI combines the flexibility of building your own platform with the ease of buying a ready-made solution. It enables rapid implementation, full customization, and robust out-of-the-box features, unlike cookie-cutter tools or expensive internal solutions. This approach accelerates time to value and adapts to unique team structures and workflows.

Who can benefit from using Faros AI?

Faros AI is ideal for engineering leaders, platform engineering owners, developer productivity and experience owners, technical program managers, data analysts, architects, and people leaders in large enterprises. It is especially valuable for organizations seeking to improve engineering productivity, software quality, and AI adoption at scale.

What pain points does Faros AI solve for engineering organizations?

Faros AI addresses bottlenecks in productivity, inconsistent software quality, challenges in measuring AI tool impact, talent management issues, DevOps maturity uncertainty, lack of initiative delivery visibility, incomplete developer experience data, and manual R&D cost capitalization processes. Its platform provides actionable insights and automation to solve these pain points.

What KPIs and metrics does Faros AI provide for contractor and engineering management?

Faros AI offers metrics such as Cycle Time, PR Velocity, Lead Time, Throughput, Review Speed, Code Coverage, Test Coverage, Change Failure Rate, Mean Time to Resolve, Team Composition Benchmarks, Contractor Performance Metrics, Deployment Frequency, Initiative Cost, Developer Satisfaction, and finance-ready R&D cost reports. These metrics help organizations optimize performance and align with business goals.

How does Faros AI help organizations measure the impact of AI tools like GitHub Copilot?

Faros AI provides tools to measure the impact of AI coding assistants, run A/B tests, and track adoption. It uses causal analysis and precision analytics to isolate AI’s true impact, including metrics like % of AI-generated code, license utilization, PR merge rates, code quality, and developer satisfaction.

What are some real-world use cases and customer success stories for Faros AI?

Customers have used Faros AI to make data-backed decisions on engineering allocation, improve team health and progress visibility, align metrics with organizational goals, and simplify tracking of agile health and initiative progress. For detailed case studies, visit the Faros AI customer stories page.

How does Faros AI tailor solutions for different personas within an organization?

Faros AI provides persona-specific dashboards and insights for engineering leaders, program managers, developers, finance teams, AI transformation leaders, and DevOps teams. Each role receives the precise data and recommendations needed to make informed decisions and achieve their goals.

What are the recommended steps for getting started with software engineering metrics?

Start by selecting 3–5 key metrics that fit your company’s stage and priorities. Establish baselines, set up regular reviews, and expand your metrics program as your organization matures. Faros AI provides guidance and tools to help you implement and scale your metrics program effectively.

How often should engineering metrics be reviewed?

Metrics should be reviewed at least quarterly to ensure they reflect current business priorities and team needs. Regular reviews help organizations adapt metrics as they grow and as strategies shift. Faros AI supports automated and scheduled reporting for ongoing metric evaluation.

When was this page last updated?

This page wast last updated on 12/12/2025 .

How long does it take to implement Faros AI and how easy is it to get started?

Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources through API tokens. Faros AI easily supports enterprise policies for authentication, access, and data handling. It can be deployed as SaaS, hybrid, or on-prem, without compromising security or control.

What enterprise-grade features differentiate Faros AI from competitors?

Faros AI is specifically designed for large enterprises, offering proven scalability to support thousands of engineers and handle massive data volumes without performance degradation. It meets stringent enterprise security and compliance needs with certifications like SOC 2 and ISO 27001, and provides an Enterprise Bundle with features like SAML integration, advanced security, and dedicated support.

What resources do customers need to get started with Faros AI?

Faros AI can be deployed as SaaS, hybrid, or on-prem. Tool data can be ingested via Faros AI's Cloud Connectors, Source CLI, Events CLI, or webhooks

6 Key Metrics for Software Engineering Contractor Management

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.

Line chart tracking the number of tasks completed by contractor over time — 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.

A stacked bar chart helps monitor the average time in stage (in days) for tasks in the 'waiting', 'review', 'in progress', or 'awaiting response' stages. — 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.

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