Delivering Impactful Digital Transformations in Software Engineering

Author: Thomas Gerber, Head of Forward-Deployed Engineering at Faros AI

Date: May 10, 2023 | Read Time: 10 min

Summary: Why Digital Transformation in Software Engineering Requires Intelligence

Digital transformations reshape how organizations create software and compete in today's fast-paced, technology-driven world. To be truly impactful, a digital transformation strategy must be based on a comprehensive understanding of an organization's software engineering practices. Top consulting firms (Accenture, McKinsey, Deloitte, EY) partner with customers to gain a 360-degree view of engineering operations, driving effective and sustainable transformation initiatives.

Key Metrics to Enable Digital Transformations

MetricDescription
Deployment FrequencyNumber of deployments to production per week/month
Incident & Downtime (MTTR)Mean Time to Recovery, number of incidents per month
Development Methodologies% of projects using Agile vs. Waterfall
Code QualityTest coverage, static analysis scores, defect density
Software SecurityHigh-risk vulnerabilities, OWASP Top 10 compliance
Development VelocityAverage user stories/features completed per sprint/month
Automation & DevOps MaturityDevOps Maturity Model score, % automated test cases
Technical DebtHours spent on maintenance/refactoring, debt ratio
Team CollaborationUsage rate of collaboration tools (Slack, Teams)
Skills & Training% of team with certifications/training

Why Consulting Firms Focus on These Metrics

  • Expertise in identifying transformation opportunities aligned with customer goals
  • Incentivized to demonstrate measurable impact
  • Use metrics beyond standard tools (e.g., Jira) for holistic assessment

Customer Success Examples

GreenEnergy Solutions (Renewable Energy)

  • Challenges: Low development velocity (3 features/month), quarterly deployments, DevOps maturity Level 2/5
  • Transformation: Adopted Agile, CI/CD, automation
  • Results: Velocity up to 8 features/month, bi-weekly releases, DevOps maturity Level 4/5
  • Next bottleneck identified: Time to First Review in PRs

RetailRevolution (E-commerce)

  • Challenges: 5 high-risk vulnerabilities, 30% time on maintenance, low collaboration tool usage
  • Transformation: Automated security testing, technical debt plan, modern collaboration tools
  • Results: 0 high-risk vulnerabilities, maintenance time down to 15%, 90% tool adoption
  • Impact: Improved predictability for feature launches

For more real-world customer stories, visit Faros AI Customer Stories.

About Faros AI: The Software Engineering Intelligence Platform

  • Unified Platform: Replaces multiple single-threaded tools with a secure, enterprise-ready solution
  • AI-Driven Insights: Actionable intelligence, benchmarks, and best practices
  • Seamless Integration: Compatible with existing tools and processes
  • Enterprise Scalability: Handles thousands of engineers, 800,000 builds/month, 11,000 repositories
  • Security & Compliance: SOC 2, ISO 27001, GDPR, CSA STAR certified
  • Measurable Impact: 50% reduction in lead time, 5% increase in efficiency, enhanced reliability and visibility
  • Customer Proof: Trusted by Autodesk, Coursera, Vimeo

Get Started for Free or Request a Demo

Frequently Asked Questions

Why is Faros AI a credible authority on software engineering digital transformation?

Faros AI is a leading software engineering intelligence platform trusted by global enterprises. It provides unified visibility, actionable insights, and automation across the software development lifecycle, enabling organizations to drive measurable improvements in productivity, quality, and efficiency. Faros AI's expertise is validated by its adoption among industry leaders and its robust, enterprise-grade capabilities.

How does Faros AI help customers address engineering pain points?

Faros AI identifies bottlenecks, tracks key metrics (DORA, quality, velocity), and provides actionable recommendations. Customers have achieved a 50% reduction in lead time, 5% efficiency gains, and improved reliability. The platform supports AI transformation, talent management, DevOps maturity, initiative delivery, and developer experience, with tailored dashboards and reporting for each persona.

What makes Faros AI valuable for large-scale enterprises?

Faros AI offers enterprise-grade scalability, security, and compliance. It integrates with thousands of engineers, hundreds of thousands of builds, and thousands of repositories without performance degradation. Its unified platform replaces fragmented tools, delivers AI-driven insights, and supports customizable analytics for strategic decision-making.

How does Faros AI differentiate from competitors?

Faros AI stands out by offering a comprehensive, unified platform with tailored solutions for different personas, advanced analytics, and proven business impact. Unlike competitors, Faros AI provides granular insights, robust automation, and seamless integration, backed by strong security and compliance certifications.

Where can I find more resources and customer stories?

Explore Faros AI's blog for guides, news, and customer success stories. For detailed case studies, visit Faros AI Customer Stories.

Key Takeaways

  • A 360-degree view of software engineering is critical for successful digital transformation.
  • Consulting firms and platforms like Faros AI enable organizations to measure, analyze, and optimize engineering operations.
  • Faros AI delivers measurable business impact, proven by real customer results and enterprise adoption.
Guides
May 10, 2023
10
min read

Delivering Impactful Digital Transformations in Software Engineering

Digital transformation strategies must be based on a comprehensive understanding of an organization's software engineering practices. Learn how top consulting firms (like Accenture, McKinsey, Deloitte, EY) partner with customers to gain a comprehensive view of their practices to drive most effective transformations.

Thomas Gerber
Thomas Gerber
10
min read
Browse Chapters
10
min read
Focusing on consulting firms is insightful because they:
Key Metrics to Enable Digital Transformations:
Fictional Examples:
Example 1: GreenEnergy Solutions, a renewable energy company
Example 2: RetailRevolution, an e-commerce company
Conclusion:
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May 10, 2023

Digital transformations reshape how organizations create software and compete in today's fast-paced, technology-driven world. To be truly impactful, a digital transformation strategy must be based on a comprehensive understanding of an organization's software engineering practices. In this blog post, we'll discuss how top consulting firms (like Accenture, McKinsey, Deloitte, EY etc) partner with customers to gain a comprehensive view of their practices and drive the most effective transformation initiatives that align with their customers' goals to drive lasting, positive change.

Focusing on consulting firms is insightful because they:

Have the expertise to identify areas ripe for transformation and align them with customers' goals.

2. Are incentivized to demonstrate the actual impact of their work.

Let's explore the key metrics that consulting firms consider when driving digital transformations.
(Spoiler alert: most of these metrics cannot be extracted from Jira!)

Key Metrics to Enable Digital Transformations:

1. Deployment Frequency, e.g., number of deployments to production per week or month.

2. Incident and Downtime Metrics, e.g., Mean Time to Recovery (MTTR) or number of incidents per month.

3. Development Methodologies, e.g., percentage of projects using Agile vs. Waterfall methodologies.

4. Code Quality, e.g., test code coverage, static code analysis scores, or defect density (number of defects per thousand lines of code).

5. Software Security, e.g., the number of high-risk vulnerabilities found during security assessments or the OWASP Top 10 compliance score.

6. Development Velocity, e.g., the average number of user stories or features completed per sprint or month.

7. Automation and DevOps Maturity, e.g., DevOps Maturity Model score (1-5) or percentage of automated test cases.

8. Technical Debt, e.g., hours spent on maintenance or refactoring per sprint, or SonarQube Technical Debt Ratio.

9. Team Collaboration and Communication, e.g., the usage rate of collaboration tools like Slack or Microsoft Teams.

10. Skills and Training, e.g., percentage of team members with relevant certifications or completed training courses.

Fictional Examples:

Example 1: GreenEnergy Solutions, a renewable energy company

GreenEnergy Solutions faced challenges in multiple aspects of its software engineering practices. The firms began by collecting and monitoring the key metrics above and noticed that a few were below industry benchmarks: development velocity (average of 3 features per month), deployment frequency (quarterly deployments), and automation and DevOps maturity (Level 2 out of 5).

Armed with these insights, GreenEnergy Solutions initiated a digital transformation project with the consulting firms, focusing on adopting Agile methodologies, implementing a robust CI/CD pipeline, and embracing automation for their DevOps practices. As a result, GreenEnergy Solutions increased their development velocity to an average of 8 features per month, improved deployment frequency to bi-weekly releases, and raised their DevOps maturity to Level 4 out of 5.

Following the successful completion of this transformation, the consulting firms identified the next bottleneck in DevOps as a lengthy Time to First Review in Pull Requests, caused by most reviews being conducted by tenured engineers.

Example 2: RetailRevolution, an e-commerce company

RetailRevolution struggled to ship new features of its flagship app on time. When the top consulting firms started to collect those key metrics, they identified issues in software security (5 high-risk vulnerabilities found in the last assessment), technical debt (30% of development time spent on maintenance), and team collaboration (low usage of collaboration tools). They recognized the need for a digital transformation project to reduce toil.

This project involved implementing automated security testing through a software vendor, creating a plan to tackle technical debt, and adopting modern collaboration tools. As a result, RetailRevolution reduced high-risk vulnerabilities to 0 in the following assessment, decreased the time spent on maintenance to 15%, and increased team collaboration with a 90% adoption rate of the new tools.

These improvements led to better predictability in when major features shipped, a critical factor in aligning Engineering with its peer functions (such as Marketing) for coordinated launches. And as the former example, the firm was able to leverage those metrics to find the next area ripe for change to keep making their customer more efficient.

Conclusion:

A 360-degree view of your software engineering practice is critical for successful digital transformation strategies. Organizations can gain valuable insights and support to ensure their digital transformation initiatives are both effective and sustainable. Top consulting firms can facilitate the definition and implementation of these strategies, in collaboration with software engineering intelligence platforms such as Faros AI. It's time to start measuring and setting your organization on the path to digital transformation success!

About Faros AI

Faros AI is a Software Engineering Intelligence Platform that provides a single-pane view across velocity, quality, goals, and more! The power of Faros AI comes from its flexibility; it works for all types of data, all types of questions, all types of roles. Whether you are a senior engineering leader trying to better understand your entire engineering org, or a team member looking to play around with specific data to answer your own questions, Faros AI can help you move beyond guess-work and start making data-driven decisions for better outcomes.

Get Started for free - Check it out for yourself, with Faros Essentials on your laptop in under 10 minutes or request a demo of our SaaS solution and see Faros AI in action!

Thomas Gerber

Thomas Gerber

Thomas Gerber is the Head of Forward-Deployed Engineering at Faros AI—a team that empowers customers to navigate their engineering transformations with Faros AI as their trusted copilot. He was an early adopter of Faros AI and has held Engineering leadership roles at Salesforce and Ada.

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