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Faros AI Doppler Release: ROI and Value Signals

Tech organizations can now interpret value and ROI signals across engineering operations to improve resource allocation and navigate the adoption of AI coding assistants.

Naomi Lurie

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Communicating the ROI of engineering investments for better business alignment

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July 31, 2024

Communicating the ROI of engineering investments for better business alignment

Engineering is one of the most expensive corporate functions. Yet its leaders often cannot easily articulate its impact on key initiatives, justify its resources, or demonstrate productivity improvements gained from new investments.

That puts a heavy strain on the relationship between the CFO, the CTO, and Heads of Engineering. And at this moment of AI transformation, it’s also hindering the effective application of AI to improve financial outcomes.

The latest release from Faros AI, Doppler, enables engineering leaders to gain valuable insights into the overall effectiveness and productivity of their software teams, as well as the specific impact of AI coding assistants like GitHub Copilot. These insights help transform the partnership between Engineering and Finance to ensure better resource allocation and value realization for the organization.

An image shows the highlights of the Faros AI Doppler release, including Investment Strategy module, AI Copilot Evaluation features, and Performance and admin enhancements.

Christian Doppler (1803–1853) makes a fitting namesake for this release due to its core principle of detecting and analyzing signals over time. With our new Investment Strategy intelligence module and enhanced AI Copilot Evaluation module, Faros AI helps organizations understand the true value and efficiency gains from their teams and technological investments, much like how Doppler radar helps meteorologists predict and respond to changing weather conditions.

A new intelligence module: Investment Strategy

The new Investment Strategy module from Faros AI answers three questions CFOs are constantly asking engineering leaders:

  • What is Engineering doing? Confirm that key initiatives are progressing.
  • How does it tie back to corporate strategy and objectives? Demonstrate that Engineering is working on the right things to achieve business outcomes.
  • Do we have the right resource allocation? Calculate the return on investment from FTEs, contractors, locations, and technology.

Faros AI provides a structured picture to answer these questions in periodic reviews, as well as data to support additional ad-hoc and impromptu analysis by fusing together data that is normally disconnected and reported on separately. Faros AI combines financial data (revenue, costs, etc.), employee HR data (contract type, role, seniority, location, average compensation per role, etc.), and productivity data (primarily from task management and version control systems) to provide these insights.

Infographic made of four quadrants for optimizing investment strategy with Faros A: Efficiency, Composition, Effectiveness and Allocation.

Key benefits of the Investment Strategy module:

  • Assess the efficiency and financial impact of your engineering initiatives by comparing their costs against revenue contributions, highlighting areas for potential optimization or concern.
  • Benchmark your engineering overhead and team ratios against industry standards, identifying outliers in team composition that may require attention to optimize efficiency and performance.
  • Evaluate the effectiveness of your talent mix and offshoring strategy by comparing developer productivity across different contract types and geographic locations, enabling you to balance cost and outcomes in terms of productivity, quality, and security.
  • Monitor the allocation of resources and time spent on critical company initiatives with a breakdown by geography and contract type, helping you to understand the distribution of innovation versus maintenance work and ensure your most expensive resources are utilized effectively.

To watch a 4-minute demo of the module, click here.

The industry’s most advanced copilot evaluation framework just got better

Engineering leaders are deploying AI coding assistants like GitHub Copilot, Amazon Q, and Gemini Code Assist under the watchful eyes of executives who anticipate significant productivity gains.

The AI Copilot Evaluation intelligence module provides a complete value framework for answering these top of mind questions:

  • How do I measure and communicate the impact?
  • How do I ensure we’ve given our teams the tools to adopt it successfully?
  • What is changing as a result of that adoption in terms of velocity, quality, security, and satisfaction?

The Doppler release introduces several essential new features to help with setting up your evaluation program, increasing adoption and usage, and measuring the impact.

Infographic showing the new AI Copilot Evaluation features in three buckets - Getting Started, Tracking Adoption, and Measuring Impact.

Quickly launch a strategic measurement program

Get started for free on the GitHub Marketplace. The first step to understanding the impact of GitHub Copilot is getting a measurement program off the ground. Well, now that’s easier than ever. Faros AI has a free app you can download from the GitHub Marketplace.

Faros AI provides analytics that go far beyond the basics available from the GitHub Copilot API, including:

  • Adoption metrics per developer and team (DAU, WAU, MAU)
  • Full Copilot usage data history
  • Team and Power User filters
  • A/B testing and Before/After analysis
  • GitHub data correlated with task, deployment, quality, incident, security, and sentiment data from 100+ tools
  • Out-of-the-box dashboards for tracking adoption, impact, risk, and value

Plus, we have good news for Power BI users. The AI Copilot Evaluation dashboards are now available natively in Power BI, where you’ll get the exact same experience as in Faros AI's built-in BI layer.

Track Copilot Adoption and Maximize License Usage

Turn your best users into mentors with Power User identification. No one is better positioned to train, mentor, and coach your teams on how to use copilots effectively than your power users. That’s why we’re helping you figure out who they are! Faros AI identifies your power users, so you can partner with them to enable team members. Power users have the credibility, context, and insider knowledge to help drive high-quality usage and minimize unused licenses.

Understanding usage of chat. Curious how your developers are benefiting from GitHub Copilot as its functionality evolves beyond code completion? You should be! In addition to lines of code and acceptance rate, Faros AI is now measuring usage of GitHub Copilot Chat, a conversational AI tool within the IDE.

GitHub just announced mixed licensing, where companies can now select Business or Enterprise plans at the organization level (instead of at the Enterprise level). That's a great use case for our A/B testing feature. Compare the impact of the different licensing options and make a data-driven choice.

Measure the impact and ROI of coding assistants

Benchmark how your results compare. Are you an outlier or on par with peers? What kind of results are others seeing? As you roll out any new technology, it's natural to seek this type of insight from peers. Leveraging our experience accompanying rollouts for the better part of a year, we now provide benchmarks for a range of metrics like PR Merge Rate, Cycle Time, Test Coverage, Code Smells, and more.

Capture the voice of the developer. Developer surveys complement system telemetry to help further understand your teams’ experience with coding assistants. Two new survey dashboards are now available to analyze and trend their feedback over time, supporting surveys run on a cadence or within the flow of work.

Faros AI also provides templated surveys to understand which tasks are being augmented by AI, quantify the time savings, understand how the time savings were reinvested, and gauge overall satisfaction with the coding assistant.

To watch a demo video of the complete AI Copilot Evaluation module, click here.

Platform enhancements for easier administration and better performance

The Faros AI platform is designed for the enterprise, handling data sets from tens of thousands of engineers. Every release, we make sure to include features that ease administration and improve platform performance.

Infographic of five new platform features in the Faros AI Doppler release: Improved connector performance, faster dashboard loading, streamlined administration, centralized account provisioning and Databricks Delta Sharing.

Here are the new features available in Doppler:

  • Improved performance for our most popular connectors. Jira and GitHub are the most popular data sources for engineering productivity insights. We’ve made it a whole lot easier to ingest large amounts of data, pull even more historical data, and select the specific data sets you want to backfill. Faros AI also supports webhooks for both these sources.
  • Faster dashboard load times. Users will now experience exponentially faster load times, now that we’ve completed the migration of our PostgreSQL analytics database to DuckDB. DuckDB is an embedded OLAP database, often referred to as the "SQLite for analytics".
  • Simplify user management with SCIM provisioning. As organizations grow and adopt more cloud-based applications, manual account management becomes increasingly complex and time-consuming. Many companies adopt centralized identity management solutions, like Okta, Microsoft Azure Active Directory, or Ping Identity. In addition to previously supported single sign-on through these services, Faros AI supports SCIM, short for System for Cross-domain Identity Management, for user account provisioning, deletion, and suspension.
  • Streamlined administration and empowered teams. We've overhauled our admin pages to make managing your organization's resources a breeze, including improved search, streamlined workflows for assigning teams and updating asset status, and a brand new team quick view with all your team's info at a glance. Plus, new permissions allow teams to create and manage themselves, boosting their autonomy and efficiency.
  • Now in Alpha: Securely share Faros AI data with Databricks data using Delta Sharing. Do you want to view Faros AI reporting data within Databricks to analyze it alongside other business data stores? That’s now possible with Databricks Delta Sharing, the industry’s first open protocol for secure data sharing. Contact us to learn more.

To learn more about these capabilities or speak to sales, reach out to our team.

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