Project Management Process
Evolution from Agile, to scaled agile
From team to enterprise management
Evolution from Agile, to scaled agile
From team to enterprise management
Due to the increase of team size, project size, and project complexity, the scaled agile model takes place, with additional advantages in the following areas:
Team responsibilities: We have a product manager team, and DevOps teams
Agile practices: Agile release train(ART) as different teams are working together
DevOps: As we have to deliver smoothly and in higher traffic, we need to have DevOps practices
Team Building: Tribes, Squads
Due to the change from applying traditional agile to SAFe, new terminologies has take place:
SQUAD: the scrum team
Chapter: Same function team members, like mobile team, QC team
Tribes: multiple SQUADS
Guild: Team with the same interests, like innovation team, which may be selected team members from different SQUADs
And the rise of the scaled agile framework takes place to meet the large enterprises' growth, to move from team level to:
Program level: Multiple teams for the same product, feature-based model
Solution level: larger team, capability-based model
Portfolio level: organization strategic point of view.
Alignment: Ensures all teams are moving in the same strategic direction.
Built-in Quality: Quality is not negotiable—applies at every step and level.
Transparency: Honest visibility into progress, risks, and issues.
Program Execution: Deliver reliably and continuously with Agile Release Trains (ARTs).
Analysis of values
Focus: Aligning multiple teams and the entire enterprise, instead of Individual teams and collaboration
Key Values: Alignment, Transparency, Program execution and Built-in quality
Scope: Large-scale, multiple teams, ARTs, and portfolio levels, instead of Small, cross-functional teams
Purpose: Deliver continuous value across large, complex organizations, instead of delivering value incrementally and iteratively
Governance & Planning: Structured cadence, PI Planning, Lean Portfolio Management instead of Lightweight, adaptive planning
Take an economic view: Optimize value delivery using cost of delay & trade-off decisions.
Meaning: Prioritize value delivery and ROI.
Steps:
Use WSJF (Weighted Shortest Job First) for backlog prioritization.
Analyze the cost of delay.
Best Practices:
Establish budgets aligned to value streams
Visualize flow efficiency and rework cost.
2. Apply systems thinking: Consider whole systems (people, workflow, value streams).
Meaning: Optimize the system as a whole, not just parts.
Steps:
Identify all stakeholders and system dependencies.
Address root causes, not symptoms.
Best Practices:
Map value streams.
Avoid local optimizations that harm the system
Think of the overall system, not isolated SQUADs and related components or modules to prevent impacting the system, which will require the product management and solution architecture teams.
Apply trade-off architecture
TL Alignment Meetings
SME/POs Alignment Meeting
Product Management
Solution architecture
3. Assume variability; preserve options: Use Set-Based Design to keep flexibility early.
Meaning: Keep design and requirements flexible early on.
Steps:
Use set-based design (explore multiple options).
Delay decisions until economically sound.
Apply configuration design patterns for business and UX
Increase reusable components within the solution to adapt and accept changes on the solution
Best Practices:
Avoid premature commitment.
Use empirical data to converge on best solution:
Calculate infrastructure and potential growth to apply HPA
Calculate database size and potential growth to apply proper sizing and required storage
4. Build incrementally with fast, integrated learning cycles: Reduce risk through small, validated steps.
Meaning: Use short cycles to learn and adapt, which is the mindset of agile, to reduce the change requests, and achieve values for customers.
Steps:
Deliver MVPs.
Run system demos each iteration/PI.
Best Practices:
Automate testing.
Promote continuous integration.
5. Base milestones on objective evaluation of working systems: Use functioning software as proof, not documents.
Meaning: Progress is validated through working software.
Steps:
Use system and PI demos.
Tie milestones to functionality, not plans.
Best Practices:
Engage stakeholders in demo feedback.
Replace documentation-based reviews with working code reviews.
6. Visualize and limit WIP, reduce batch sizes, and manage queue lengths: Enable Lean flow.
Meaning: Flow improves by reducing overload and optimizing batch size.
Steps:
Use Kanban.
Limit work-in-progress.
Best Practices:
Track cycle time.
Maintain small, prioritized backlogs.
7. Apply cadence, synchronize with cross-domain planning: Balance variability and coordination.
Meaning: Align teams using common rhythms and timeboxes.
Steps:
Use fixed iterations and PIs.
Plan and demo together.
Move to process-based practices in engineering and management
Best Practices:
Align all teams with PI Planning.
Apply ART sync and Scrum of Scrums.
8. Unlock the intrinsic motivation of knowledge workers: Empower people, don't micromanage.
Meaning: Empower people, don’t micromanage.
Steps:
Give autonomy and purpose.
Encourage mastery
Best Practices:
Use servant leadership.
Involve teams in decision-making.
9. Decentralize decision-making: Push decisions to the lowest responsible level.
Meaning: Push decisions to the lowest responsible level.
Steps:
Define decision types: frequent vs. infrequent.
Empower teams with decision rights.
Best Practices:
Clarify governance boundaries.
Use decision matrices when needed.
Decentralize decisions that are:
Frequent
Time-critical
Low cost of failure
Centralize decisions that:
Are strategic
Have long-term impact
Involve significant risk
10. Organize around value: Structure teams around value delivery instead of function.
Meaning: Structure teams based on delivering customer value.
Steps:
Design Value Streams.
Form Agile Release Trains (ARTs).
Best Practices:
Align org structure to product flow.
Use Value Stream Mapping to remove delays.
In the SAFe (Scaled Agile Framework), agility is achieved at two complementary levels: Team-Level Agility and Enterprise Agility. Understanding the difference is essential for successful scaling.
At the team level, agility is embodied by Agile Teams using Scrum, Kanban, or XP, delivering working software in short iterations (typically 2 weeks). These teams operate within an Agile Release Train (ART) and focus on delivering user stories and features from the team backlog. Core practices include daily standups, iteration planning, backlog refinement, demo, and retrospective.
Involved Roles:
Scrum Master: Facilitates Agile practices.
Product Owner (PO): Manages team backlog and defines stories.
Agile Team Members: Developers, testers, designers, etc.
Best Practices:
Adopt a clear Definition of Done (DoD).
Encourage continuous integration and test automation.
Use team metrics (e.g., velocity, story completion rate) to improve performance.
Enterprise agility focuses on aligning strategy, governance, architecture, and funding across multiple ARTs, enabling the business to respond rapidly at scale. It includes managing multiple teams-of-teams through ARTs, Solution Trains, and Lean Portfolio Management (LPM). The goal is end-to-end business agility, from idea to delivery, across all value streams.
Involved Roles:
Release Train Engineer (RTE): Facilitates ART-level execution.
Product Management: Owns program backlog and feature prioritization.
System Architect: Ensures technical coherence across teams.\
Solution Train Engineer (STE), Solution Architect, Solution Management: Coordinate multiple ARTs in large solutions.
Lean Portfolio Management (LPM): Aligns strategy, investment, and execution.
Enterprise Architect: Ensures enterprise-wide architectural integrity.
Best Practices:
Use Program Increment (PI) Planning for alignment across ARTs.
Implement Value Stream Mapping to optimize flow.
Apply Lean Budgeting to fund value streams instead of projects.
Leverage metrics dashboards (e.g., SAFe DevOps Radar, Flow Metrics, OKRs).
Promote a Lean-Agile Center of Excellence (LACE) to guide transformation.
Key Differences:
Scope: While Agile focuses on Individual teams, SAFE focuses on Multiple teams, ARTs, and business units
Planning Horizon: While Agile focuses on 1–2 week iterations, SAFE focuses on 8–12 week Program Increments (PIs), roadmaps
Governance: While Agile focuses on Informal, team-driven,SAFE focuses on formalized via LPM, ART sync, and solution reviews
Metrics: While Agile focuses on Velocity, story points, team burndown, SAFE focuses on PI predictability, business value, and OKRs
Funding: While it's Not applicable in agile, SAFE focuses on Lean Portfolio Funding
Alignment: While Agile focuses on PO for alignment, SAFE focuses on Via Strategic Themes, Portfolio Kanban
Definition:
DevOps in Agile at Scale (e.g., SAFe) ensures continuous delivery of value by integrating development and operations across multiple Agile teams. It automates the flow from code to deployment, enabling faster, reliable releases.
Establish a DevOps Culture:
Shared responsibility across Dev, QA, Ops.
Emphasize automation, collaboration, and continuous feedback.
Create a Continuous Delivery Pipeline (CDP):
Stages:
Continuous Exploration (CE): Align on features & backlog.
Continuous Integration (CI): Automate build, test, and merge.
Continuous Deployment (CD): Deliver to staging/production-like environments.
Release on Demand: Release based on business need.
Implement Toolchain Automation:
CI/CD tools, Infrastructure as Code (IaC), testing automation.
Embed DevOps in PI Planning & Execution:
Plan enablers (e.g., test environments, pipelines).
Ensure cross-team dependencies are handled.
Use Metrics for Feedback & Improvement:
Lead time, change failure rate, deployment frequency.
Dr. Ghoniem Lawaty
Tech Evangelist