Developer journeys and engineering practices
Product and platform operating model
Application simplification and decoupling
Not exhaustive
Developer journeys and engineering practices
Application patterns
No application archetypes are defined; greenfield development is started from scratch
Software delivery process
Mostly manual; different teams have their own accommodations for routine tasks
Preferred delivery methodology
Higher profitability
80% or more of delivery in IT follows waterfall delivery methodology
Modern engineering practices
Higher profitability
Fully reliant on requirement specification and quality assurance in product delivery
Less developed
Select maturity level:
McKinsey & Company
Application patterns
Teams define their own templates that cover basic code structure and functionality
Software delivery process
Around 50% of applications onboarded to CI/CD pipelines, enabling deployment automation; limited integration of automated guardrails, stage gates, or controls
Preferred delivery methodology
Higher profitability
A mix of waterfall and iterative delivery methodologies, with some areas preferring one over the other
Modern engineering practices
Higher profitability
Limited use of development practices such as feature flagging or A/B tests to reduce risk and better validate product changes
Advancing
Application patterns
Automatically generated boilerplates use enterprise application patterns with
logging/monitoring
Software delivery process
Automated code deployment from development to production (with embedded testing/cyber controls); more than 80% of applications onboarded to subversion software and target pipelines
Preferred delivery methodology
Higher profitability
80% or more of delivery in IT follows iterative delivery methodology
Modern engineering practices
Higher profitability
Wide use of development practices (eg, feature flagging,
A/B tests, blue-green and canary deployments) for product changes
Mature
Developer journeys and engineering practices
Select maturity level:
Mature
Advancing
Less developed
Not exhaustive
Product and platform operating model
Product and platform operating model
Cross-functional delivery teams
Higher profitability
Most delivery teams are functional with only technology capabilities (eg, developers, quality assurance)
Vendor dependency
Higher profitability
More than 80% of applications are delivered by vendors/contract development
Number of reporting levels
Higher profitability
Typically 5 or more levels of hierarchy between a developer and the CEO
AI use case delivery teams
Higher profitability
Opportunistic AI exploration in select domains (eg, workforce management, risk)
Cross-functional delivery teams
Higher profitability
50–60% of the delivery teams possess business, technology, and operations capabilities enabling them to deliver and maintain products
Vendor dependency
Higher profitability
30–50% of applications are delivered by vendors/contract development
Number of reporting levels
Higher profitability
Typically 4 levels of hierarchy between a developer and the CEO
AI use case delivery teams
Higher profitability
Centralized AI pipeline or funnel in place but not fully linked with the business strategy; 20–50 AI use cases in production
Cross-functional delivery teams
Higher profitability
80% or more of the delivery teams include full BizDevSecOps capabilities and are able to deliver and maintain their product end to end
Vendor dependency
Higher profitability
Less than 10% of applications are delivered by vendors/contract development
Number of reporting levels
Higher profitability
Typically 3 or fewer levels of hierarchy between a developer and the CEO
AI use case delivery teams
Higher profitability
AI-enabled use cases embedded in business processes/operational improvements, with defined performance metrics; first proofs of concept on gen AI; more than 100 use cases in production
Select maturity level:
Mature
Advancing
Less developed
Not exhaustive
Application simplification and decoupling
Application simplification and decoupling
Decoupling and service independence
80% or more of teams depend on other teams during releases; there are known monolith systems that are clear bottlenecks in scalability
Capability/
application duplication
Higher profitability
More than 30% of applications in the application portfolio have overlaps in functionality
Omnichannel capabilities
Higher profitability
Products/services for different channels are implemented in separate systems, with no shared code base; business logic is specific to a channel
Public cloud workloads
Higher profitability
Less than 10% of workloads on public cloud
Decoupling and service independence
Around 50% of teams depend on other teams during releases; there are not more than 1–2 monolith systems that are bottlenecks in scalability
Capability/
application duplication
Higher profitability
10–20% of applications in the application portfolio have overlaps in functionality
Omnichannel capabilities
Higher profitability
Notable effort toward delivering products/services across different channels, with limited code reusability
Public cloud workloads
Higher profitability
30–40% of workloads on hybrid cloud; unified control plain across on-premises and public cloud
Decoupling and service independence
95% or more of teams can make releases independently from other teams; each service scaled independently subject to actual loads
Capability/
application duplication
Higher profitability
There are no applications with overlapping functionalities; all applications are aligned with business capabilities
Omnichannel capabilities
Higher profitability
Business logic and process orchestration are largely reused between different channels
Public cloud workloads
Higher profitability
60% or more of workloads on hybrid or multicloud