Which Project Management Methodology to Use: Waterfall, Agile, or Both?

February 24, 2025 / Hans van 't Riet / Leave a comment

1. Introduction

In an era of rapid technological change and market disruptions, organizations must execute projects with both precision and adaptability. Digital transformation initiatives, IT modernizations, and enterprise-wide projects require structured governance to ensure alignment with business goals while maintaining agility to respond to evolving needs. However, choosing between Traditional Waterfall (PMBOK) and Agile (Scrum/SAFe) is not always straightforward.

While Waterfall offers predictability, governance, and risk control, Agile provides speed, flexibility, and iterative value delivery. The reality is that many organizations do not need to choose one over the other but rather combine them strategically. This article explores the strengths and weaknesses of both methodologies, when to apply each, and how a hybrid approach can leverage the best of both worlds.

2. Why You Need a Strong Project Management Setup

Project failure rates remain alarmingly high, with studies indicating that up to 70% of digital transformation initiatives fail due to poor execution, misaligned priorities, and resistance to change. A well-structured Project Management (PM) framework is essential to prevent these failures, ensuring that projects are not only delivered on time and within budget but also drive real business value.

At the core of any successful transformation is clear ownership, structured governance, and a balance between control and agility. Large-scale projects often face a paradox—executives and stakeholders demand predictability and structured planning, while operational teams require flexibility to iterate and adapt. Without the right project management setup, organizations risk falling into two extremes: either too rigid, leading to slow execution and missed opportunities, or too unstructured, resulting in chaotic implementations and wasted resources.

Finding the right project management approach is about more than just process—it’s about aligning methodologies with the business context, organizational culture, and project complexity. For some initiatives, a Traditional Waterfall (PMBOK) approach provides the necessary structure and risk mitigation, while for others, Agile (Scrum & SAFe) offers the speed and adaptability required in fast-moving environments. In many cases, a hybrid model that blends both methodologies delivers the optimal balance.

3. Choosing the Right Approach: Traditional Waterfall (PMBOK) vs. Agile (Scrum, SAFe)

A. The Case for Traditional Waterfall (PMBOK)

Some projects demand a highly structured approach with well-defined requirements, strict regulatory compliance, and minimal scope for change. This is where Waterfall methodologies, based on PMI’s PMBOK framework, excel. Waterfall is most effective in industries where predictability, formal approvals, and rigorous documentation are essential, such as large IT infrastructure deployments, ERP implementations, regulatory projects, and government initiatives.

Waterfall project management operates in a linear, sequential process, with clear stages: Initiation, Planning, Execution, Monitoring & Controlling, and Closing. This structure ensures that risk is carefully managed upfront, scope creep is minimized, and accountability is enforced at every stage. Executives often favor Waterfall because it provides detailed planning, resource forecasting, and cost predictability, making it easier to report progress to stakeholders and investors. However, its rigidity can become a drawback in environments where requirements frequently change or when teams need faster iterations.

B. The Case for Agile (Scrum & SAFe)

Unlike Waterfall, Agile methodologies like Scrum and SAFe are designed for projects with evolving requirements, high collaboration needs, and rapid innovation cycles. Agile breaks work into short, iterative cycles (Sprints) where teams continuously deliver value, receive feedback, and adapt.

Agile thrives in environments where customer needs shift rapidly—such as software development, digital product innovation, and emerging technologies. Teams operate in cross-functional units, fostering collaboration between developers, designers, business leaders, and end-users. The key advantage of Agile is its ability to respond to change quickly, ensuring that projects deliver what users actually need, rather than what was initially planned months ago.

For enterprises managing multiple Agile teams, SAFe (Scaled Agile Framework) provides a structured way to scale Agile across large organizations, ensuring alignment across teams while maintaining flexibility at the execution level.

4. Why Not Both? Leveraging a Hybrid Approach

Many organizations struggle with a pure Waterfall or Agile approach because no single methodology fits every project. The solution? A hybrid model that blends both methodologies strategically. This allows businesses to maintain the structured governance of Waterfall while embedding Agile’s flexibility where it matters most.

A. When to Combine Waterfall & Agile

Enterprise Digital Transformation – Waterfall for strategic planning, Agile for implementation.
IT Modernization – Waterfall for infrastructure, Agile for application development.
Mergers & Acquisitions – Waterfall for integration planning, Agile for transition teams.
Regulated Industries – Waterfall for compliance, Agile for innovation efforts.

B. Structuring a Hybrid Approach

Aspect	Traditional Waterfall (PMBOK)	Agile (Scrum/SAFe)
Planning	Long-term roadmap & milestones	Iterative backlog prioritization
Execution	Sequential phases (Design → Build → Test)	Continuous delivery in sprints
Governance	Strong documentation & risk control	Agile leadership & adaptive governance
Measurement	Scope, cost, time adherence	Value delivery, customer feedback

By combining Waterfall’s governance with Agile’s iterative execution, organizations can reduce risk, optimize delivery speed, and improve project outcomes.

5. Key Takeaways for Executives

No single methodology is universally best—Waterfall excels in structured, risk-heavy environments, while Agile thrives in fast-changing ones.
For predictable, well-defined projects, PMBOK (Waterfall) ensures control.
For innovation-driven or fast-moving projects, Scrum/SAFe enable adaptability.
Hybrid models offer the best of both worlds, integrating structure with agility.
Project governance should be tailored to business needs rather than rigidly following a single methodology.

By adopting a balanced approach, organizations can drive digital transformation efficiently while mitigating risks.

Future of Work: Insights from Human + Machine

February 6, 2025 / Hans van 't Riet / Leave a comment

Human + Machine: Reimagining Work in the Age of AI, written by Paul R. Daugherty and H. James Wilson, has garnered widespread acclaim for its insightful and practical approach to integrating artificial intelligence into business operations. Readers have praised its clear analysis and inspiring examples of AI applications across various industries.

The book is recognized as a thought-provoking and essential resource for understanding the future of work, emphasizing the symbiotic relationship between humans and machines. It makes complex AI concepts approachable, providing a compelling roadmap for leaders aiming to harness AI’s full potential while navigating its ethical and operational complexities.

More than just a technical guide, Human + Machine serves as a strategic playbook for executives seeking to lead AI-driven transformation effectively.

The Core Premise: Collaborative Intelligence

At the heart of Human + Machine is the concept of collaborative intelligence—the idea that AI is not a replacement for human talent but a powerful complement that enhances human capabilities. The book challenges the traditional view of automation as a job eliminator and instead presents a more optimistic, structured framework where AI and humans work symbiotically to create exponential value.

Daugherty and Wilson introduce the MELDS Framework, which identifies five crucial shifts in how businesses can approach AI transformation:

Mindset Shift – Moving from a technology-first approach to a human-centered AI adoption strategy.
Experimentation – Encouraging a culture of iterative learning and agile AI deployments.
Leadership – Ensuring executives play a hands-on role in AI integration and ethics.
Data – Harnessing the right data in ethical, transparent, and responsible ways.
Skills – Investing in upskilling and reskilling employees to thrive in AI-driven environments.

This review captures the key insights from each chapter and provides actionable takeaways for leaders looking to embrace AI effectively.

Chapter Summaries and Leadership Actions

Chapter 1: The AI Work Redesign Imperative

AI does not simply replace jobs; it transforms them by reshaping roles and responsibilities.
Leadership Action: Conduct workforce planning to identify roles that AI will augment rather than replace. Create structured transition plans to help employees adapt.

Chapter 2: The Missing Middle: Humans + AI

Successful AI adoption requires a balance between automation and human judgment.
Leadership Action: Invest in training programs that help employees collaborate with AI, emphasizing decision-making, creativity, and ethics.

Chapter 3: Reimagining Business Processes with AI

AI-driven process redesign should focus on innovation rather than mere efficiency.
Leadership Action: Develop a framework to assess which processes should be augmented, automated, or reinvented entirely using AI.

Chapter 4: AI and Data: The Foundation of Intelligent Workflows

AI’s effectiveness depends on high-quality, structured, and unbiased data.
Leadership Action: Implement strong data governance policies to ensure data integrity, fairness, and transparency in AI applications.

Chapter 5: Scaling AI Across the Enterprise

Many companies struggle to scale AI beyond initial pilot projects.
Leadership Action: Create cross-functional AI implementation teams and define clear metrics to measure AI adoption success.

Chapter 6: AI and the Future of Work

AI will create new job roles while transforming existing ones.
Leadership Action: Establish continuous learning initiatives and reskilling programs to equip employees with AI-relevant competencies.

Chapter 7: The Responsible AI Framework

AI governance should focus on transparency, accountability, and fairness.
Leadership Action: Develop and enforce AI ethics guidelines to ensure responsible deployment and mitigate bias.

Chapter 8: A Leader’s Guide to Reimagining Processes

Leaders must actively drive AI-powered transformation by fostering an experimental and adaptable mindset.
Leadership Action: Encourage a culture of AI-driven experimentation, allowing teams to iterate on AI solutions and adapt based on real-world learnings.

Chapter 9: Eight New Fusion Skills for an AI Workplace

AI-driven work environments require hybrid skill sets that combine human expertise with AI capabilities.
Leadership Action: Create mentorship and coaching programs that help employees develop these fusion skills:
- Intelligent Inquiry – Leveraging AI insights effectively through critical questioning.
- Bot-Based Empowerment – Collaborating with AI tools to enhance productivity.
- Reciprocal Learning – Ensuring continuous feedback between humans and AI systems.
- Relentless Reimagination – Consistently rethinking processes and strategies.
- Holistic Judgment – Balancing AI-generated insights with human intuition.
- Ethical Guardian – Upholding ethical standards in AI development and deployment.
- AI Exponential Thinking – Using AI-driven innovation to scale business impact.
- Constructive Skepticism – Evaluating AI recommendations critically to avoid over-reliance.

Final Thoughts

Human + Machine provides a compelling roadmap for senior executives and transformation leaders seeking to leverage AI as a force multiplier for their businesses. By integrating real-world case studies, actionable frameworks, and the latest AI trends, the updated edition is more relevant than ever for organizations embarking on or refining their AI journeys.

The book’s optimistic yet pragmatic approach distinguishes it from other AI literature, making it an essential read for leaders looking to harness AI’s full potential while navigating its ethical and operational complexities. If you are serious about the future of work and digital transformation, Human + Machine is a must-read that will equip you with the strategies needed to stay ahead in an AI-powered world.

Effective Stakeholder Management in Digital Transformation

February 5, 2025February 5, 2025 / Hans van 't Riet / Leave a comment

Digital transformation is a complex journey that requires strategic stakeholder management to ensure success. Engaging and managing stakeholders effectively across the four key phases—Strategy to Plan, Plan to Execution, Execution to Integration, and Sustainable Adoption to Value Realization—is essential. Below, we explore how to assess and engage key stakeholder groups throughout the transformation, leveraging three industry-proven frameworks I have applied in several different formats.

Using Mendelow’s Power-Interest Matrix for Stakeholder Assessment

To determine which stakeholders to focus on, organizations can use Mendelow’s Power-Interest Matrix, which categorizes stakeholders based on their level of influence (power) and engagement (interest). Stakeholders with high power and high interest should be closely managed, as they are critical to transformation success. Those with high power but low interest should be kept satisfied with updates, while those with low power but high interest should be informed and engaged appropriately. Finally, stakeholders with low power and low interest require only periodic monitoring to ensure alignment.

Applying the ADKAR Model to Assess Stakeholder Participation

The ADKAR model (Awareness, Desire, Knowledge, Ability, Reinforcement) is useful for evaluating where stakeholders stand in terms of engagement. Leaders should assess whether stakeholders are aware of the transformation, desire to participate, have the knowledge and ability to support the changes, and receive reinforcement to sustain engagement. This structured approach helps tailor communication and interventions to move stakeholders through the engagement journey effectively.

Leveraging Kotter’s Change Model for Stakeholder Engagement

Once stakeholders are assessed, Kotter’s 8-Step Change Model provides a roadmap for actively engaging them. This includes creating urgency, building coalitions of support, developing a clear vision, removing obstacles, generating quick wins, and institutionalizing change. By applying these principles, organizations can maintain momentum and ensure stakeholders are aligned and invested throughout the transformation.

In the following section, I will describe how to assess and engage with five main stakeholder groups—Employees, Managers, Executives/Leadership, Board of Management/Shareholders, and Customers/Suppliers/Industry Stakeholders—leveraging the aforementioned models.

1. Employees

Assessing Employees

The ADKAR model provides a structured approach to assessing employees’ engagement in digital transformation. Organizations should evaluate:

Awareness: Do employees understand the need for transformation?
Desire: Are they motivated to participate and embrace change?
Knowledge: Do they have the necessary training and information to contribute?
Ability: Can they effectively apply new skills and technologies?
Reinforcement: Are there mechanisms in place to sustain long-term adoption?

By leveraging this model, leaders can identify gaps and tailor interventions to support employees throughout the transformation journey.

Activities Across the Phases:

Strategy to Plan: Measure awareness, attitudes, and perceived impact on roles.
Plan to Execution: Identify resistance points and skill gaps.
Execution to Integration: Measure adoption levels and operational challenges.
Sustainable Adoption to Value Realization: Track engagement and digital proficiency.

Engaging Employees

Strategy to Plan: Communicate the vision, expected impact, and upskilling opportunities.
Plan to Execution: Involve in pilot programs and provide structured change management support.
Execution to Integration: Celebrate quick wins and reinforce cultural alignment.
Sustainable Adoption to Value Realization: Foster continuous learning and career growth.

2. Managers

Assessing Managers

For managers, the ADKAR approach can also be applied. The activities across the four phases include:

Strategy to Plan: Evaluate readiness to champion change and operational alignment with business plans.
Plan to Execution: Determine their ability and capacity to lead teams through change.
Execution to Integration: Assess change leadership effectiveness.
Sustainable Adoption to Value Realization: Ensure they incorporate the new ways of working into daily practices and sustain leadership in digital culture.

Engaging Managers

Strategy to Plan: Provide training and involve them in shaping implementation roadmaps, ensuring they are part of the guiding coalition as per Kotter’s model.
Plan to Execution: Equip with leadership coaching and transformation frameworks, enabling them to remove barriers and create short-term wins.
Execution to Integration: Ensure ongoing coaching and recognition programs to sustain acceleration and institutionalize changes.
Sustainable Adoption to Value Realization: Embed digital thinking in business processes and continuously reinforce new behaviors.

3. Executives/Leadership

Assessing Executives/Leadership

Executives and leadership play a crucial role in digital transformation due to their high power and interest, as highlighted in Mendelow’s Power-Interest Matrix. Given their influence, continuous engagement is essential to ensure alignment and sustained commitment.

Engaging Executives/Leadership

Strategy to Plan: Secure sponsorship, define measurable transformation goals, and obtain commitment on resources.
Plan to Execution: Maintain active participation in governance structures and involve them early through pilots and demos.
Execution to Integration: Adapt strategies based on real-time insights and ensure transformation adoption is part of leadership reviews.
Sustainable Adoption to Value Realization: Ensure transformation becomes an ongoing capability.

4. Board of Management/Shareholders

Assessing Board of Management/Shareholders

Strategy to Plan: Identify expectations and risk tolerance.
Plan to Execution: Monitor risk perceptions and alignment with corporate goals.
Execution to Integration: Measure financial and strategic outcomes.
Sustainable Adoption to Value Realization: Validate return on investment and future opportunities.

Engaging Board of Management/Shareholders

Strategy to Plan: Present a compelling business case with ROI projections.
Plan to Execution: Provide transparent reporting on progress and early wins.
Execution to Integration: Align transformation metrics with business performance.
Sustainable Adoption to Value Realization: Demonstrate sustained business value and future scalability.

5. Customers, Suppliers, and Industry Stakeholders

Engaging Customers

Strategy to Plan: Communicate potential benefits and involve key customers in feedback loops.
Plan to Execution: Gather feedback through prototype testing and focus groups.
Execution to Integration: Showcase improvements and deepen customer relationships.
Sustainable Adoption to Value Realization: Reinforce engagement through personalization and innovation.

Engaging Suppliers/Partners

Strategy to Plan: Engage in co-innovation discussions and assess digital readiness.
Plan to Execution: Co-develop implementation roadmaps.
Execution to Integration: Strengthen collaboration through integrated systems.
Sustainable Adoption to Value Realization: Strengthen ecosystems with emerging technologies.

Engaging Community & Industry/Competitors

Strategy to Plan: Share thought leadership and collaborate on industry best practices.
Plan to Execution: Establish partnerships for innovation and shared learning.
Execution to Integration: Share success stories and participate in industry forums.
Sustainable Adoption to Value Realization: Lead industry conversations and future transformations.

By structuring stakeholder management through a stakeholder-centric approach across the four phases of digital transformation, organizations can maximize adoption, mitigate risks, and ensure long-term success.

The AI-Savvy Leader: Key Concepts and Actions for Leaders

January 27, 2025January 29, 2025 / Hans van 't Riet / Leave a comment

David De Cremer’s The AI-Savvy Leader: Nine Ways to Take Back Control and Make AI Work has been widely acknowledged by leaders as an essential resource for understanding why AI implementations often fail and, more importantly, how to ensure their success. Among the books I’ve read recently, this stands out as one of the most practical and insightful guides for leaders.

The book provides invaluable insights for navigating the challenges of integrating AI into organizations. Below is a summary, crafted with the assistance of AI (ChatGPT), highlighting the most critical concepts and actionable steps for leaders to take.

1: Learning – Get to Know AI, and Learn to Use It as a Leader

Leaders don’t need to be AI experts, but a foundational understanding of AI’s capabilities and limitations is crucial. This knowledge enables leaders to make informed decisions and oversee AI projects effectively.

Actions for Leaders:

Invest time in learning AI fundamentals through workshops or seminars.
Regularly consult AI experts to remain informed on advancements.
Encourage AI literacy across leadership teams to drive strategic decisions.

2: Purpose – Use Your Purpose to Ask the Right Kind of Questions

AI initiatives should align with the organization’s mission and values. Purpose-driven projects ensure AI is used meaningfully to serve strategic goals.

Actions for Leaders:

Define a clear organizational purpose that guides AI projects.
Evaluate AI initiatives to ensure alignment with long-term goals.
Ask questions like, “How does this AI solution contribute to our mission?”

3: Inclusion – Work in Inclusive Ways to Drive Human-AI Collaborations

Inclusive environments foster better human-AI collaboration by leveraging diverse perspectives. This diversity leads to more innovative and adaptable AI solutions.

Actions for Leaders:

Build cross-functional teams to design and implement AI projects.
Solicit input from employees, customers, and partners to improve AI solutions.
Promote inclusivity to reduce biases in AI systems.

4: Communication – Build a Flat Communication Culture to Drive AI Adoption

Transparent communication accelerates AI adoption and fosters trust. Leaders must ensure open dialogue across all organizational levels.

Actions for Leaders:

Establish regular forums to discuss AI initiatives and progress.
Use clear, non-technical language when communicating about AI.
Encourage feedback loops to address concerns and refine strategies.

5: Vision – Be Visionary in How to Use AI

A strong vision defines how AI will transform the organization and creates a shared sense of purpose. Vision-driven leadership inspires confidence and commitment to change.

Actions for Leaders:

Craft and articulate a clear vision for AI’s role in the next decade.
Link AI efforts to tangible outcomes, such as improved customer experiences.
Share success stories to build enthusiasm and confidence in AI initiatives.

6: Balance – Adopt AI with All Stakeholders in Mind

Balancing stakeholder interests ensures ethical and sustainable AI adoption. This approach builds trust and minimizes resistance to change.

Actions for Leaders:

Conduct impact assessments for all AI initiatives.
Engage stakeholders—employees, customers, and partners—in discussions about AI.
Implement governance frameworks to address ethical challenges.

7: Empathy – Use a Human-Centered Approach to AI Adoption

Adopting a human-centered approach prioritizes user needs, experiences, and trust. This ensures AI enhances rather than disrupts human well-being.

Actions for Leaders:

Gather insights from users to understand how AI impacts them.
Ensure transparency in how AI systems make decisions.
Provide mechanisms for feedback and continuous improvement of AI tools.

8: Mission – Augment (Don’t Automate) to Create Jobs

AI should augment human capabilities rather than replace them. This approach fosters innovation and creates new opportunities.

Actions for Leaders:

Identify processes where AI can enhance productivity without job loss.
Invest in employee reskilling programs for AI-augmented roles.
Communicate how AI can create opportunities for growth and innovation.

9: Emotional Intelligence – Accept That Soft Skills Are the New Hard Skills, and Practice Them

Soft skills like empathy, adaptability, and communication are vital in managing the human side of AI adoption. Emotional intelligence ensures AI serves people effectively.

Actions for Leaders:

Develop emotional intelligence within the leadership team.
Lead by example, showing empathy and adaptability during AI integration.
Address employee concerns with transparency and understanding.

Conclusion: Becoming an AI-Savvy Leader

Leaders play a pivotal role in ensuring AI serves their organization’s purpose while enhancing human capabilities. By following the actionable steps outlined in each chapter of The AI-Savvy Leader, leaders can drive meaningful and ethical AI adoption that aligns with their organization’s values and long-term vision.