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.

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.

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.

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.

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.