How Faros AI Strengthens McKinsey’s Agile360 Methodology

We Go Together like Tacos & Tuesdays‍

Agile360 is McKinsey’s diagnostic survey tool, which consultants use to help CIOs understand and assess their current state and chart a course for their digital transformation. Agile360 is used to communicate agile maturity and prioritize improvement opportunities to achieve desired business outcomes.

Faros AI is a software engineering intelligence platform, founded and designed by the engineering team behind Salesforce Einstein, the world’s most successful enterprise machine learning platform.

Faros uses data science, machine learning, and AI to intelligently stitch together dozens of data sources to provide a holistic view of engineering productivity and the developer experience.

Like McKinsey, Faros AI meets the needs of large enterprises and holding companies, with highly heterogeneous, bespoke, and complex environments. Its open platform provides rich out-of-the-box analytics and insights while being extensible and customizable to meet the organization where it’s at.

Read on to understand how we create a winning combination to:

• Augment self-reported answers with objective data
• Reduce the manual effort to produce the assessment
• Continuously assess and track the impact on business outcomes
• Uncover new opportunities to create value

Augment Self-Reported Answers with Objective Data

Agile360 utilizes surveys and interviews to construct an assessment of the organization’s agile maturity today, along four dimensions: structure, people, processes, and technology.

Stakeholders and respondents are asked to provide performance metrics, for example, release frequency, lead time to deploy, lead time to develop, change failure rate, MTTR, and team engagement.

Faros AI has prebuilt analytics libraries that can crunch these metrics rapidly directly from their data sources, even when homegrown tools, customized pipelines, or spreadsheets are involved. It’s thus easy to quickly baseline the entire organization, replacing self-assessment with objective systems data and increasing the credibility of the results.

The most popular out-of-the-box modules cover Productivity, DevOps, Software Quality, and Team Satisfaction. Furthermore, due to the extensible and customizable nature of Faros AI, your are not confined to what comes off the shelf. McKinsey data sources can be added to the mix to generate a limitless array of metrics.

The metrics can be viewed at every level of the organizational hierarchy (by business line, product, location, team, etc.), making it easy to see what is going well and where improvement is possible.

Key Faros AI Benefits

Frictionless: There is no need to rearchitect tools or processes to achieve this level of visibility. Faros’s domain expertise applies data science to understand how your systems work today, so you generate intelligence without prematurely changing tools, practices, or processes.

Transparent: Every aspect of the Faros platform is transparent, including how the metrics are computed, the data used to compute them, and the source of the data.

Extensible: Faros is an API-first platform, extensible to any data source, use case, and application that serves or intersects with Engineering, e.g. HR, Finance, OKRs, Product, Customer Experience, and Compliance.

Reduce the Manual Effort to Produce the Assessment

Once the Agile360 responses are collected, McKinsey consultants process the output and convert it into outcome scores for deploying Agile at scale. Those outcome scores are then evaluated against benchmarks.

Faros can be configured with the benchmark values McKinsey applies and thus reduce the manual effort to translate assessment data into outcome scores. The benchmarks can be based on:

• The DevOps Research and Assessment (DORA) Report (already exist in Faros)
• McKinsey’s survey and expert view on best-in-class practices in top software and cloud companies
• Industry and peer benchmarks
• Organizational targets (if known)

Armed with these live benchmarks, the organization can clearly see its gaps, its blindspots, and its opportunities to achieve more for the business and for its customers.

Key Faros AI Benefits

Locate problem areas with surgical precision: For any use case, Faros provides trending, benchmarks, progress towards goals and targets, breakdowns by stages, and the ability to slice-and-dice by any dimension — like HR structure, location, product, or service.

Continuous Assessment and Progress Tracking

The Agile360 assessment helps identify improvement opportunities along multiple dimensions. Once the assessment metrics have been instrumented in Faros AI, it becomes easy for McKinsey to track the impact of the changes as the organization enacts these recommendations.

With Faros AI constantly measuring and trending the Agile360 metrics and outcomes over time, it becomes easier to:

• Make the case for change
• Demonstrate ROI with ‘before and after’ metrics
• Track progress over time
• Diagnose emerging issues and new hotspots and tackle them proactively

Key Faros AI Benefits

Customizable metrics: As an organization undertakes improvement measures, new metrics and customized dashboards can closely track many important measures. For example, if the organization understands it must upskill its talent in specific areas, existing Faros AI modules or custom dashboards can be used for a closer analysis of the relevant workforce. Productivity metrics can be viewed in conjunction with information like seniority, tenure, location, and satisfaction.

Programmable: Faros automations leverage all the engineering data sources to remove friction and toil in day-to-day engineering operations. Automations can send alerts and reminders, enforce policies, and optimize workflows, to instill McKinsey best-in-class practices and recommendations for ways of working.

Uncover New Opportunities to Create Value

With Faros AI in place throughout a McKinsey engagement, consultants can uncover new opportunities to create value for clients.

Optimally architected for machine learning and AI, Faros is able to sift through vast amounts of data to direct attention to trends, correlations, anomalies, and outliers. Embedded LLMs remove the barriers to understanding and probing the data further.

For example, Faros AI can calculate each product’s cloud cost per customer and rank the client’s portfolio based on ROI. This insight can help McKinsey advise its clients on where to increase investment or reduce budget allocations.

Key Faros AI Benefits

AI-Native: Faros harnesses AI to connect dozens of disparate systems and serve up insights and recommendations that help excellent engineering organizations make better decisions. Faros co-founder and Chief Scientist, Shubha Nabar, was named one of Forbes’ top women in AI.

Transforming to Data-Driven Engineering — Together

The synergy between McKinsey’s Agile360 methodology and Faros AI’s software engineering intelligence is strong, and the benefit to our mutual clients is boundless.

Reach out to us to explore opportunities to collaborate at faros.ai/partners