Book Review: Digital Transformation – Survive and Thrive in an Era of Mass Extinction

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

Although already published in 2019 (more than 5 years ago), this book points several concepts still very relevant in the fast changing world of Digital Transformation. Below a summary of these concepts and recommended actions

In Digital Transformation, technology visionary Thomas Siebel offers a compelling and pragmatic guide for business leaders confronting the rapidly converging forces of cloud computing, big data, artificial intelligence (AI), and the Internet of Things (IoT). These technologies are creating an extinction-level event for legacy business models. Siebel contends that digital transformation is not optional—it is a matter of survival.

Drawing on his experience as founder of C3.ai, Siebel presents a clear strategic playbook and numerous real-world examples that demonstrate how companies across sectors can reinvent themselves using digital technologies. His message is direct: act now, or risk irrelevance.

Key Concepts

1. The Four Technology Pillars

Cloud Computing – On-demand computing infrastructure enabling scalability and speed
Big Data – Massive, diverse datasets that can be analyzed in real-time
Artificial Intelligence (AI) – Predictive, adaptive algorithms that learn from data
Internet of Things (IoT) – Billions of connected devices generating actionable data

2. A Mass Extinction Event for Legacy Businesses

Over half of Fortune 500 companies have disappeared since 2000
Disruption is hitting all industries—not just tech
Traditional business models are no longer sustainable

3. Digital Transformation Is a Strategic Reinvention

Not about marginal gains—requires full-scale operating model redesign
Core focus on operational efficiency, customer experience, and new value creation

4. Data as the Foundation for AI

Success with AI requires clean, integrated, and governed enterprise data
Enterprises must break down data silos and standardize architecture

5. Speed and Scale as Differentiators

Companies must move fast, think big, and deliver value quickly
Long, drawn-out transformations are no longer viable

6. Real-World Case Studies

Enel – Predictive maintenance across its global energy grid
Royal Dutch Shell – AI for well safety, energy trading, and asset optimization
U.S. Department of Defense – AI and IoT for battlefield awareness

Implementation Recommendations

1. Modernize Your Tech Stack

Shift from legacy systems to modern, elastic cloud infrastructure

2. Centralize and Unify Data

Build a data integration layer across all business units
Ensure governance and real-time accessibility

3. Deploy High-Value AI Use Cases First

Focus on predictive maintenance, customer churn, fraud detection, etc.

4. Adopt Agile and DevOps at Scale

Encourage continuous delivery and rapid iterations

5. Re-skill and Upskill the Workforce

Provide training in AI, data science, and cloud technologies

6. Build a Cross-Functional Operating Model

Blend business, IT, and data science in unified delivery teams

7. Create a Transformation Office

Establish a dedicated team with budget, authority, and board-level visibility

Siebel’s 10-Point CEO Action Plan

Declare Digital Transformation a Strategic Priority
Establish a Digital Transformation Office (DTO)
Unify Enterprise Data Architecture
Identify High-Impact Use Cases
Deploy Agile Methodologies
Form Cross-Functional Teams
Invest in AI and IoT Capabilities
Lead Cultural Change from the Top
Develop Digital Talent and Skills
Track Progress and Iterate Continuously

Final Thoughts

Digital Transformation by Thomas Siebel is a must-read for executives seeking to lead their organizations through an era of exponential change. The convergence of cloud, big data, AI, and IoT isn’t just a tech revolution—it’s a business survival imperative. With practical insights, a strong strategic framework, and a CEO-focused action plan, this book is a blueprint for industrial-scale reinvention.

Highly recommended for leaders ready to move from intention to impact.

Master Impactful Communication in Digital Transformation

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

Why Communication Is the Lifeblood of Transformation Communication is more than a soft skill—it’s a strategic lever. Miscommunication or a lack of timely information can erode trust, stall progress, and sow confusion. According to McKinsey, 70% of transformation programs fail, and poor communication is often a silent contributor. Impactful communication aligns stakeholders, drives engagement, mitigates resistance, and reinforces progress. It is how leadership earns trust, how teams stay focused, and how change becomes real.

1. Why Communicate: Purpose, Alignment, and Momentum At every stage of a transformation, communication serves a purpose:

Clarify Purpose: Explain the “why” of the transformation—the vision, strategic drivers, and burning platform.
Create Alignment: Ensure all stakeholders understand their role in the broader narrative.
Build Momentum: Regular communication reinforces progress and sustains engagement.

Example: Continuously link messages to how the topic supports the overall strategy and purpose of the transformation.

2. What to Communicate: The Three Strategic Narratives

Purpose: Why are we doing this? Lay out the rationale, desired future state, and expected benefits.
Progress: What’s happening now? Share timelines, milestones, and any course corrections.
Proof: What’s working? Highlight quick wins, user stories, and lessons learned. Success stories inspire belief.

Example: A transformation dashboard updated monthly with progress visuals and a rotating spotlight on team success stories creates transparency and boosts morale.

3. How to Communicate: Channels, Formats, and Tone

Stakeholder-Focused: Tailor content to audience needs. Executives need strategic updates, while frontline teams need clarity on operational impacts.
Formats: Mix videos, infographics, text updates, and live events. Use storytelling, visuals, and humor where appropriate.
Tools: Combine traditional (emails, town halls) with digital (Yammer, Teams, digital signage).

Example: A short animated video used to explain a new agile model across the company generates more engagement than a 10-page slide deck.

4. Where to Communicate: Choosing the Right Channels

Channels: Leverage both formal (newsletters, intranet) and informal (team meetings, social platforms).
Internal and External: Don’t forget partners, customers, and external stakeholders when relevant.
Beyond Standard: Use unconventional methods like pop-up booths, floor ambassadors, or interactive kiosks.

Example: Place screens in break rooms with FAQs and video testimonials from users. Often, employees read external communication (e.g. LinkedIn) more attentively than internal channels.

5. Who Should Communicate: Roles and Responsibilities

Leadership: Sets the tone and provides credibility.
Program Teams: Share updates and own the transformation story.
End Users: Involve them in co-creation and let their stories become advocacy.
Champions/Change Agents: Act as trusted messengers within the organization.

Example: (Team) Leaders deliver tailored talking points to their teams after town halls to reinforce key messages locally.

6. When to Communicate: Cadence with Purpose

Routine Rhythm: Weekly newsletters, monthly video messages, quarterly town halls.
Event-Driven: Go-live updates, milestone achievements, leadership transitions.
Embedded Moments: Integrate into standups, one-on-ones, and performance reviews.

Example: A transformation team sends a short Friday note every week with “Top 3 things to know” – brief, consistent, and effective.

7. Making Communication Two-Way

Feedback Loops: Open Q&A forums, feedback forms, sentiment pulse checks.
Listening Mechanisms: Focus groups, digital suggestion boxes, skip-level meetings.
Empower Managers: Train and support them to act as translators and listeners.

Example: Run quarterly listening sessions where employees can anonymously submit and vote on questions.

8. Measuring Communication Effectiveness

Quantitative Metrics: Email open rates, intranet views, video play completion, attendance.
Qualitative Feedback: Employee surveys, pulse checks, sentiment analysis.
Behavioral Indicators: Are stakeholders taking desired actions (e.g., using a new tool, adopting a new process)?

Example: Use employee surveys to check communication effectiveness. Include questions on whether the why, who, what, where, and when of the transformation are well understood.

Conclusion: From Messaging to Meaning

Impactful communication is not just about delivering information—it’s about shaping perception, building trust, and enabling action. It’s a leadership discipline that requires intent, empathy, and agility. In digital transformations, where uncertainty is the norm, communication becomes the connective tissue that keeps strategy and execution aligned. For senior leaders, investing in communication is not optional—it’s foundational to transformation success.

AI and Digital Transformation Insights from the GDS CIO Summit

March 22, 2025 / Hans van 't Riet / Leave a comment

Last week, I had the pleasure and privilege of attending and speaking at the GDS CIO Summit – Noordwijk | March 12-13 2025, where I joined around 150 senior leaders from the tech industry. Over two days, we explored some of the most pressing topics shaping our industry today and those that will define the near future. It came as no surprise that 84% of CIOs consider AI a top priority, yet many are still figuring out how to effectively integrate it into their business strategies.

From Vision to Value – IT as a Competitive Advantage

The summit opened with a fantastic panel discussion featuring Angelika Trawinska van Bolhuis ( Dyson), Claudio FINOL (Fyffes), and Cameron van Orman (Planview). A key theme that emerged: IT is no longer just an enabler but a core driver of business strategy—capable of creating either competitive advantage or disadvantage.

Organizations are shifting from project-based ROI thinking to a product and business value-driven approach, requiring agile, dynamic planning and tools like Planview to align IT initiatives with evolving business priorities.

AI’s Growing Impact – The Need for Real-Time Insights

AI was a dominant theme throughout the event, and Kai Waehner (Confluent) led a deep dive into how real-time data fuels AI success. Many infrastructures aren’t designed for this shift, but event-driven architectures and data streaming are emerging as critical enablers.

One standout insight: 2025 is poised to be the year of “Agentic AI”—where autonomous AI agents collaborate in real time to optimize operations. Businesses that prepare for this transformation now will gain a significant competitive edge.

The Future of Work – Productivity, Transparency & AI Integration

How can organizations improve productivity and alignment? Sven Peters (Atlassian) shared fascinating insights into modern Systems of Work. High-performing teams don’t operate in silos; they align around OKRs (Objectives & Key Results) with full transparency.

At Atlassian, they have a simple but highly effective approach: ✅ Weekly 280-character updates to keep work visible ✅ Monthly check-ins to assess progress ✅ Quarterly reviews to refine objectives

AI is deeply embedded in this process, assisting teams in defining OKRs and structuring projects in a smarter way.

AI Regulations, Security & Workforce Evolution

The regulatory landscape around AI is evolving rapidly, particularly in Europe, and Ulrika Billström (OpenText) provided a compelling look at how companies must adapt. AI orchestrators are emerging, capable of managing multiple AI agents to drive large-scale innovation.

A key trend: Instead of moving data to AI, AI is now being deployed closer to where the data resides, fundamentally changing how organizations structure their AI ecosystems.

Day 2 – Real-Time Data & Trust

I had the honor of opening Day 2 alongside Ellen Aartsen ( KPN ), Joshan Meenowa (The KraftHeinz Company), and Ben Thompson ( GDS Group) in a discussion on how data fuels real-time decision-making.

A key question we tackled: How “real-time” does data actually need to be? While not every use case requires real-time data, all use cases require trusted data. Transparency, governance, and reducing reliance on alternative, non-trusted data sources are key to success.

AI Lifecycle Challenges – Managing Rapid Evolution

Kevin K. ( Airia – Enterprise AI Simplified ) shed light on a major challenge: the rapid pace of AI development. With 6,000–8,000 new AI models being created every week, companies struggle to keep up.

The solution? AI orchestration layers—which sit between the data, source systems, and AI models—are becoming essential to manage AI lifecycles efficiently and ensure tangible ROI.

The CIO’s Role is Evolving – Business Leadership is Key

In an insightful discussion with Alan Guthrie ( Calderys) and Alexander Press (Sanofi), we explored how the role of the CIO is undergoing a fundamental shift.

Today’s CIOs must: ✔ Operate at strategic, tactical, and operational levels ✔ Set clear technology guardrails while fostering innovation ✔ Shift IT functions toward product-driven organizations

Technology leadership alone is no longer enough—CIOs must now be business leaders.

Maximizing Tech Investments – Understanding TCO & ROI

To close the summit, @ManishNirmal ( Vimeo) provided a valuable session on how to assess the true Total Cost of Ownership (TCO). Hidden costs—such as training, migration, and operational impact—often make or break the business case for tech investments.

His recommendation? Use frameworks like MEDDIC (Metrics, Economic Buyer, Decision Criteria, Identify Pain, Champion) to map tech solutions based on real business value.

One of the most memorable takeaways: Crawl before you walk, walk before you run—but standing still is not an option.

Final Thoughts

The GDS CIO Summit was a fantastic opportunity to exchange insights with industry leaders and explore where AI and digital transformation are headed. A huge thank you to the GDS Group, especially Sophie Charnaud for her support, and all the brilliant speakers and participants for making it such an insightful event!

Harnessing Lessons Learned for Digital Transformation Success

March 10, 2025 / Hans van 't Riet / Leave a comment

Introduction

Digital transformation is a complex, multi-phase journey that requires continuous learning and adaptation. Organizations that systematically capture and apply lessons learned improve their chances of success, avoid recurring mistakes, and optimize future initiatives. However, many businesses either fail to document insights effectively or struggle to integrate them into future projects. This article explores the importance of lessons learned, effective approaches, implementation strategies, key challenges, and a step-by-step framework to ensure digital transformation efforts benefit from past experiences.

1. Why Lessons Learned Matter in Digital Transformation

Lessons learned play a crucial role in refining digital transformation efforts. Key benefits include:

Preventing Repeated Mistakes – Avoiding common pitfalls saves time, money, and resources.
Enhancing Decision-Making – Informed decisions based on past experiences lead to better outcomes.
Optimizing Processes – Continuous improvement ensures that digital initiatives become more efficient over time.
Strengthening Governance – Ensuring that digital transformation governance evolves based on real-world insights.
Fostering a Learning Culture – Encouraging teams to reflect on successes and failures promotes organizational agility.

By embedding a structured approach to lessons learned, companies can accelerate their digital transformation efforts and increase long-term success.

2. Approaches to Capturing Lessons Learned

Various methodologies exist for systematically gathering insights from digital transformation initiatives. Some of the most effective approaches include:

A. After-Action Review (AAR)

Originally developed by the U.S. Army, the AAR method uses a structured reflection process:

What was supposed to happen?
What actually happened?
What went well and why?
What can be improved and how?

B. Agile Retrospectives

Agile methodologies integrate lessons learned through retrospectives at the end of each sprint. Common questions include:

What worked well?
What didn’t go well?
What can we improve?
What are the action items for the next sprint?

C. Post-Implementation Review (PIR)

A PIR is conducted after a major project phase or the entire transformation effort. It assesses:

Whether objectives were met.
What worked and what didn’t.
How to apply insights to future transformations.

D. Lessons Learned Workshops

Interactive sessions where key stakeholders share insights using structured formats like:

Start, Stop, Continue review.
Root Cause Analysis (Fishbone Diagrams).
Timeline Review with Thematic Grouping of Issues.

E. Knowledge Repositories for Continuous Learning

Organizations can store and share lessons learned using:

Digital transformation playbooks.
Internal knowledge management systems (e.g., Confluence, SharePoint).
AI-driven repositories for searchability.

3. Applying Lessons Learned in Digital Transformation

Capturing lessons is only valuable if they are applied effectively. Here’s how organizations can ensure insights drive real change:

A. Integrate Lessons into Governance Structures

Assign a Lessons Learned Owner or a Transformation Office to track insights.
Make lessons learned a standard agenda item in executive steering committees.
Embed lessons into organizational decision-making and process improvements.

B. Apply Lessons at Different Levels

Sprint/Phase Level – Immediate adjustments based on sprint retrospectives.
Program/Portfolio Level – Aggregate insights to refine digital strategies.
Enterprise Level – Consolidate transformation-wide lessons into strategic planning.

C. Communicate Lessons Effectively

Lessons must reach the right audience to be impactful:

Audience	Communication Approach
Executives	Summary reports, dashboard insights
Project Teams	Workshops, sprint reviews, playbooks
Entire Organization	Newsletters, town halls, digital knowledge hubs

D. Overcoming Common Challenges

Challenge	Solution
Teams don’t document lessons	Use structured templates and automated tools
Lessons aren’t applied	Assign accountability and track implementation
Resistance to discussing failures	Foster a blame-free culture focused on improvement
Insights are scattered across silos	Centralize in a knowledge management system

4. Step-by-Step Framework for Implementing Lessons Learned

Step 1: Capture Lessons at Key Milestones

Conduct lessons learned sessions at the end of sprints, phases, and projects.
Use structured templates and tools to document insights.

Step 2: Analyze and Prioritize Insights

Categorize lessons into successes, challenges, opportunities, and recommendations.
Use analytical tools like Root Cause Analysis to extract meaningful trends.
Prioritize lessons based on strategic impact.

Step 3: Integrate Lessons into Future Projects

Update digital transformation playbooks and methodologies.
Include lessons learned in risk management frameworks.
Modify Standard Operating Procedures (SOPs) based on past experiences.

Step 4: Communicate Lessons Across the Organization

Tailor communication methods for different audiences (executives, teams, entire organization).
Use multiple channels: internal portals, newsletters, videos, and town halls.
Establish a continuous feedback loop for ongoing knowledge sharing.

Step 5: Institutionalize Lessons for Long-Term Impact

Develop a centralized knowledge repository for easy retrieval of past lessons.
Create a Lessons Learned Playbook to guide future teams, e.g. with Do’s and Don’ts
Measure impact through KPIs such as reduced project failures, increased efficiency, and improved adoption rates.

5. Final Thoughts

Applying lessons learned in digital transformation is essential for continuous improvement and long-term success. By embedding a structured process into governance, decision-making, and cultural practices, organizations can avoid repeating mistakes, optimize their digital initiatives, and drive better outcomes.

Successful digital transformations are not just about implementing new technologies—they are about learning, adapting, and evolving. Organizations that prioritize lessons learned as a strategic capability will lead the way in digital excellence.

Effective Risk Management in Digital Transformation

February 28, 2025February 28, 2025 / Hans van 't Riet / Leave a comment

1. Introduction

Organizational transformations represent some of the most complex undertakings in business. According to research by McKinsey & Company (2019), nearly 70% of transformations fail to achieve their stated objectives, with inadequate risk management frequently cited as a contributing factor.

Effective risk management requires a structured approach where risks are identified, assessed, and mitigated at the appropriate levels:

Portfolio Risks – Strategic risks impacting the entire transformation, requiring executive oversight. Examples include: resource allocation, organizational capacity for change, external (market/regulatory) and financial sustainability risks.
Program Risks – Cross-project risks affecting multiple initiatives, managed at the program level. Examples include: interdependencies/resource conflicts between projects, timeline/milestone risks, development, technical integration, adoption, and benefit realization risks.
Project Risks – Operational and execution risks handled by project teams. Examples include: scope/requirements, schedule, budget, resource, quality, performance, team capability/capacity, and stakeholder acceptance risks.

A clear governance structure ensures that risks are escalated to the right level—whether the Executive Steering Committee, Program Leadership, or Project Management—for timely decision-making and intervention.

2. Risk Management in Transformation Governance

To embed risk management into transformation governance effectively, organizations must:

Define risk ownership at different levels (executive, program, project).
Establish governance bodies with clear escalation mechanisms.
Integrate risk reviews into decision-making forums.
Ensure risk reporting is transparent, structured, and aligned with transformation objectives.

3. Risk Assessment & Mapping Tools

Several proven tools can help organizations systematically assess and map risks:

Risk Matrix (Probability vs. Impact): Prioritizes risks based on likelihood and severity.
Risk Breakdown Structure (RBS): Categorizes risks by type (strategic, organizational, operational, financial, technical, change management, etc.).
Bow-Tie Analysis: For high-priority risks, visualizes potential causes, consequences, and controls for a given risk.
Monte Carlo Simulations: Provides probabilistic forecasting for risk impact on budgets and timelines.
SWIFT (Structured What-If Technique): Facilitates structured brainstorming on potential risks.

Each of these tools helps organizations gain visibility into risks and prepare for effective mitigation.

4. Mitigation Planning & Execution

Risk mitigation involves defining structured responses based on the nature and severity of risks:

Avoid: Eliminating the risk by altering the transformation approach.
Mitigate: Reducing the impact or probability through proactive measures.
Transfer: Shifting the risk to a third party (e.g., insurance, outsourcing).
Accept: Acknowledging the risk with contingency plans in place.

A Risk Register should be maintained to track risks, owners, mitigation actions, timelines, resources, and follow-ups. Additionally, mitigation progress should be reviewed in governance forums to ensure accountability and timely interventions.

5. A Step-by-Step Guide to Implementing Risk Management

Risk Management Framework: Agree on the objectives, structure, policies, and procedures.
Risk Identification: Engage stakeholders and put mechanisms in place across all levels to surface risks early.
Risk Assessment: Use structured tools to break risks down, categorize them, and evaluate the likelihood and impact.
Risk Prioritization: Align risk priorities with transformation goals and organizational risk appetite.
Mitigation Strategy Development: Define risk responses (avoid, transfer, mitigate, accept) and allocate necessary resources.
Governance & Oversight: Integrate risk reviews into transformation governance structures, with dedicated risk review sessions.
Ongoing Monitoring & Communication: Establish reporting mechanisms, including risk trend reporting, and continuous improvement processes.

6. Example – Global Financial Services Transformation

A major financial institution undertaking a digital transformation employed a three-tiered risk management approach:

Portfolio Level (Executive Steering Committee)
The ESC focused on strategic risks including regulatory compliance, competitive disruption, and organizational capacity for change. They established quarterly “risk deep dives” where each transformation workstream presented their top risks and mitigation strategies. The ESC maintained a portfolio-level risk contingency reserve, allocating funds to address emerging risks based on severity and alignment with strategic priorities.

Program Level (Transformation Office)
The Transformation Office implemented a “Risk Guild” comprising risk owners from each workstream who met bi-weekly to identify cross-program dependencies and risks. They employed a sophisticated risk visualization dashboard that highlighted interdependencies between workstreams and potential cascading impacts. The office also maintained a centralized risk register with automated escalation of risks that exceeded defined thresholds.

Project Level (Agile Teams)
Individual teams incorporated risk identification into their sprint planning and retrospectives, with “risk spikes” allocated to investigate high-priority uncertainties. Teams used “risk-adjusted story points” to account for implementation uncertainties in their capacity planning. A “see something, say something” culture encouraged anyone to raise potential risks through a simple digital form.

The results were impressive: while industry benchmarks suggested that 70% of financial services transformations fail to meet objectives, this institution achieved 85% of its targeted benefits within the planned timeframe.

7. Common Pitfalls and How to Avoid Them

Risk Management as Compliance Exercise

Problem: Risk management becomes a bureaucratic checkbox exercise rather than a decision-making tool.
Solution: Focus on decision-relevance by integrating risk discussions directly into key decision points. Emphasize how risk information has influenced specific decisions. Use concrete, specific risk descriptions rather than generic categories.

Overemphasis on Documentation

Problem: Teams spend more time documenting risks than managing them.
Solution: Simplify documentation requirements, focusing on action-oriented information. Implement user-friendly tools that minimize administrative burden. Establish “one source of truth” rather than duplicative risk registers.

Failure to Close the Loop

Problem: Identified risks have mitigation plans, but no one follows up on implementation.
Solution: Implement clear accountability for mitigation actions with regular status reviews. Treat high-priority risk mitigations as projects with defined deliverables, timelines, and resources. Celebrate successful risk mitigation.

Risk Isolation

Problem: Risk management operates in isolation from other management processes.
Solution: Integrate risk considerations into strategic planning, resource allocation, and performance management. Use consistent language and frameworks across processes. Ensure risk owners participate in relevant decision forums.

Static Approach

Problem: Risk register becomes a static document that doesn’t evolve with changing circumstances.
Solution: Implement regular risk refresh cycles. Establish triggers for out-of-cycle risk reviews based on internal or external events. Create mechanisms to identify and assess emerging risks.

8. Conclusion

Risk management in organizational transformation is not a peripheral activity but a central governance function that enables informed decision-making and increases the likelihood of success. By implementing a multi-layered approach that addresses portfolio, program, and project risks, organizations can navigate the inherent uncertainties of transformation with greater confidence.

The tools, frameworks, and step-by-step guide outlined in this article provide a roadmap for implementing robust risk management practices. However, the most important factor is creating a risk-aware culture where identifying and managing risks becomes part of everyone’s responsibility.

Step-by-Step Approach to Building a Performance Management System

February 28, 2025 / Hans van 't Riet / Leave a comment

Introduction

Effective performance management is a cornerstone of successful transformation. As organizations move from execution to integration, measuring progress and ensuring alignment with strategic goals becomes crucial. A well-structured Performance Management System (PMS), leveraging Key Performance Indicators (KPIs) and dashboarding, provides the necessary visibility to track, analyze, and optimize performance.

This article explores how to implement a PMS that combines leading and lagging KPIs with structured dashboarding. It outlines the different types of KPIs—outcome, output, and process—and provides a step-by-step guide to designing a robust performance framework.

Understanding KPIs in Performance Management

KPIs are quantifiable measures used to track progress toward specific objectives. A balanced PMS incorporates different types of KPIs:

Leading KPIs: Predict future performance based on current activities. Example: Number of customer inquiries as an early indicator of future sales.
Lagging KPIs: Measure past performance and final outcomes. Example: Quarterly revenue growth.
Outcome KPIs: Focus on the end results that align with strategic goals. Example: Customer retention rate.
Output KPIs: Measure specific deliverables. Example: Number of product features released per quarter.
Process KPIs: Track efficiency and effectiveness of workflows. Example: Average time to resolve a customer complaint.

A well-designed PMS balances these KPIs to provide comprehensive insights into performance.

Theoretical Foundations of Performance Management

Several management theories and frameworks inform performance measurement and dashboarding:

Balanced Scorecard (Kaplan & Norton): Ensures a holistic view of performance by measuring financial, customer, internal processes, and learning & growth perspectives.
SMART Goals: Emphasizes that KPIs should be Specific, Measurable, Achievable, Relevant, and Time-bound.
Continuous Improvement (Deming Cycle – PDCA): Encourages ongoing measurement and refinement of processes through Plan-Do-Check-Act.

These models provide a structured approach to designing an effective PMS that drives sustainable performance improvements.

Step-by-Step Guide to Implementing a Performance Management System

Step 1: Define Objectives and Align with Strategy

Identify key strategic goals at the organizational and departmental levels.
Translate high-level objectives into 3-5 critical success factors.
Document assumptions about cause-and-effect relationships.
Engage stakeholders to ensure buy-in and relevance.

Step 2: Select the Right KPIs

Select leading and lagging KPIs to ensure both predictive and retrospective insights.
Ensure coverage across outcome, output, and process KPIs.
Balance across four perspectives: financial, customer, internal processes, and learning/growth.
Validate that measures are actionable and can be influenced by those responsible.

Step 3: Design the Dashboard

Choose a visualization tool (Power BI, Tableau, or custom solutions).
Define data sources, ownership, baselines, calculation methods, and thresholds.
Include drill-down capabilities for root cause analysis.
Prioritize usability: Use clear charts, color coding, and minimal clutter.

Step 4: Establish Data Collection and Reporting Mechanisms

Ensure integration with existing systems, automate data extraction where possible to reduce manual effort and errors.
Create dashboard hierarchies (executive, operational, analytical).
Set up regular reporting cycles (daily, weekly, or monthly) based on the decision-making cadence.
Design standard meeting agendas and protocols, integrate with existing governance structures.
Define responsibility for maintaining and validating data accuracy.

Step 5: Analyze and Act on Insights

Train managers and teams in the dashboards and performance analysis.
Use dashboards for real-time monitoring and proactive decision-making.
Identify trends, variances, and root causes of performance gaps.
Implement corrective actions and track their impact over time.

Step 6: Review, Refine, and Evolve

Schedule periodic reviews to evaluate the effectiveness of KPIs and dashboards.
Adjust meeting cadence and formats based on effectiveness.
Adjust and incorporate new metrics as business priorities evolve.
Foster a culture of continuous improvement by refining processes based on insights.

Example KPI Definition Template:

Name: First Contact Resolution Rate
Definition: Percentage of customer inquiries resolved in a single interaction
Formula: (Issues resolved in first contact / Total issues) × 100
Data Source: CRM system ticket data
Collection Frequency: Daily, reported weekly
Owner: Customer Support Manager
Target: 85% (Baseline: 72%)
Intervention Thresholds: <75% requires immediate action plan

Conclusion

Implementing a Performance Management System is essential for navigating the execution to integration phase of transformation. By combining leading and lagging KPIs with dashboarding, organizations gain actionable insights that drive continuous improvement. A well-balanced PMS ensures strategic alignment, operational efficiency, and sustained performance growth.

As management theorist Peter Drucker famously observed, “What gets measured gets managed.” However, the corollary is equally important: what gets measured badly gets managed badly. By investing time in thoughtfully designing your performance management system, you create the foundation for sustainable transformation success.

By following the structured approach outlined in this article, organizations can establish a robust framework for performance management, ensuring they stay on track and achieve their transformation objectives.

Maximizing Digital Success with Strategic Workforce Planning

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

Introduction

In my many years involved in strategy formulation, one of the most undervalued tools, which, when properly used, led to extremely valuable discussions and insight, was Strategic Workforce Planning. When planning a Digital Transformation and aligning with leadership on the expected impact of AI implementations, this can be an extremely valuable tool.

Companies invest heavily in cutting-edge technology, yet many overlook a crucial element: their workforce. Strategic Workforce Planning (SWP) is the bridge between business transformation and workforce readiness. It ensures that organizations have the right talent in place to execute their digital ambitions effectively. Without it, even the most sophisticated technology initiatives risk failure due to skill gaps, resource mismatches, and a lack of strategic alignment.

What is Strategic Workforce Planning?

Strategic Workforce Planning is a structured, forward-looking approach that aligns talent with an organization’s business objectives. It enables companies to proactively address workforce needs, anticipate skill shortages, and develop strategies to build or acquire the necessary capabilities.

SWP is most effective when deployed during periods of transformation—such as digital overhauls, automation initiatives, or AI integration. It follows a structured Four-Step Framework:

Set Strategic Direction – Align workforce planning with business and digital transformation goals, ensuring that talent strategies support overall corporate objectives.
Analyze Current Workforce – Assess existing workforce capabilities, identify skill gaps, and evaluate how well employees are prepared for AI and digital shifts.
Forecast Future Requirements – Predict the skills, roles, and workforce composition required to operate in the future digital environment.
Develop Action Plans – Implement targeted hiring, reskilling, and upskilling initiatives to bridge workforce gaps and ensure operational readiness.

Key Takeaways from Research on SWP & Digital Transformation

Recent research underscores the importance of integrating SWP with digital transformation efforts. Three major reports highlight critical trends:

Skill-Based Workforce Management (Boston Consulting Group): Organizations must anticipate skill shortages in AI, automation, and digital transformation. Proactive upskilling and reskilling initiatives will be key to staying competitive.
The Role of SWP in the Age of AI (McKinsey & Company): AI-driven automation will drastically reshape workforce structures. Companies must integrate AI-driven forecasting tools into workforce planning to manage these shifts effectively.
Mastering Digital Transformation in Workforce Management: The ability to map opportunities and challenges in digital transformation is crucial. SWP helps leaders simulate different workforce scenarios and plan for skill evolution.

The Benefits of a Centralized Workforce Strategy

For executives leading digital transformation, having a single source of truth for workforce planning is a game-changer. A centralized SWP approach provides:

Data-Driven Decision-Making – Leaders gain real-time insights into talent readiness and can make informed staffing decisions.
Scenario Planning – Organizations can model different workforce scenarios to anticipate talent needs and mitigate risks.
Workforce Agility – As digital initiatives evolve, companies can quickly adapt their workforce strategies to align with new priorities.

Linking Digital Transformation to Workforce Utilization

Digital transformation does not just introduce new technologies—it fundamentally changes how work gets done. AI and automation are redefining roles, requiring companies to rethink workforce utilization and occupation structures.

Case Studies in Action:

Google has leveraged AI-powered workforce planning tools to anticipate skill needs and align talent development with business priorities. By using data-driven insights, Google ensures that it continuously hires, upskills, and reallocates employees to projects that drive innovation. Their approach integrates predictive analytics, allowing the company to proactively manage workforce transitions as new technologies emerge, ensuring that employees are always equipped with the most relevant skills.
ProRail, the Dutch railway infrastructure manager, faced the challenge of increasing efficiency through digitization without expanding its workforce. To address this, ProRail implemented a workforce planning initiative focused on reskilling existing employees in automation and data analytics. This strategic approach enabled ProRail to optimize train traffic management, integrate AI-driven decision-making, and prepare its workforce for a future where digital operations play a central role in rail infrastructure management.
Microsoft recognized that the future of work required a significant shift in workforce capabilities. To address this, the company launched large-scale reskilling and learning programs designed to prepare employees for AI and digital advancements. Through initiatives like the Microsoft AI Business School and enterprise-wide learning platforms, Microsoft ensures that its workforce remains competitive in an increasingly AI-driven world. Their SWP strategy includes career path modeling, internal mobility programs, and digital literacy initiatives to align talent with the company’s future vision.

Developing a Talent Plan for the Future

To future-proof their organizations, senior executives must take a proactive approach to workforce planning:

Identify future skill requirements based on anticipated digital trends.
Develop recruitment, training, and upskilling strategies to bridge gaps.
Leverage AI-driven workforce planning tools to enhance talent forecasting.

By treating workforce planning as a strategic function rather than an operational necessity, companies can ensure that they have the right talent in place to drive digital success.

The Role of SWP in the Future of Work

The level of automation in jobs is expected to skyrocket in the coming years. Organizations that fail to integrate workforce planning into their digital strategy risk falling behind. Digital and AI solutions must be seamlessly linked to workforce development, ensuring that employees are prepared for the rapid technological shifts ahead.

Conclusion

Strategic Workforce Planning is not just a tactical HR function—it is a core pillar of successful digital transformation. By embedding SWP into the strategic planning process, organizations can future-proof their workforce, optimize resource utilization, and ensure they have the right talent in place to harness the full potential of AI and automation.

For senior executives and transformation leaders, the message is clear: technology alone will not drive digital success. A well-planned, strategically aligned workforce is the key to turning digital aspirations into operational reality.

6 Lean Concepts for Successful Digital Transformation

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

Introduction

Many digital transformations fail not because of technology, but because new ways of working don’t stick. Lean Thinking provides a structured approach to ensure transformation is effectively executed and fully integrated into daily operations. This article explores six key Lean concepts—five foundational tools plus Leader Standard Work—to create lasting impact.

1. Value Stream Mapping (VSM) – Creating Clarity on “As-Is” vs. “To-Be”

Why It Matters

Before launching any digital initiative, organizations need a clear understanding of current inefficiencies and how digital solutions will improve them. Value Stream Mapping (VSM) provides a structured approach to visualize workflows, eliminate waste, and define the future state.

Example: Bosch’s ERP Optimization

Bosch implemented a new digital ERP system but faced slow adoption and workflow inefficiencies. By applying VSM, they mapped the As-Is state, identified bottlenecks, and redesigned the To-Be process with simplified digital interfaces, leading to a 25% productivity increase.

Approach: VSM Mapping Framework

Step 1: Identify key processes and stakeholders.
Step 2: Map the As-Is state (manual steps, delays, inefficiencies).
Step 3: Define the To-Be state with digital solutions.
Step 4: Identify improvement actions and implementation roadmap.

2. Standard Work – Defining the New Way of Working

Why It Matters

Even after successful digital transformation, employees often revert to old habits unless new processes are clearly documented and reinforced. Standard Work ensures consistent execution and prevents variation.

Example: Danaher’s Digital Compliance

Danaher struggled with process inconsistencies post-digital transformation. By implementing Standard Work documents, they aligned global teams on digital best practices and saw a significant reduction in process variability.

Approach: Standard Work Document Structure

Process Name & Purpose
Step-by-Step Instructions (with screenshots where needed)
Roles & Responsibilities
Success Metrics
Review & Continuous Improvement Plan

3. Daily Management – Sustaining the Transformation

Why It Matters

Sustained digital transformation requires continuous monitoring and adjustment. Daily Management ensures teams review progress, discuss obstacles, and reinforce digital processes in short, structured meetings.

Example: Amazon’s AI-Driven Operations

Amazon implemented daily huddles to monitor its AI-driven supply chain. By reviewing key performance indicators (KPIs) daily, teams proactively resolved adoption issues, improving fulfillment speed while reducing errors.

Approach: Daily Management Meeting Agenda

Review Key Metrics (digital adoption, process performance)
Identify Issues & Roadblocks
Escalate Unresolved Problems
Celebrate Successes & Recognize Contributions

4. Visual Management – Making Gaps & Performance Visible

Why It Matters

Without clear visibility, employees and leaders struggle to measure progress. Visual Management (dashboards, Kanban boards) helps teams quickly identify gaps, monitor KPIs, and drive accountability.

Example: Toyota’s Digital Maintenance Dashboards

Toyota faced adoption resistance for a new digital maintenance system. By introducing real-time dashboards, operators could instantly see performance gaps, leading to a higher engagement rate.

Approach: Visual Management Board Setup

Objective & Metrics Displayed (efficiency, downtime, compliance)
Real-Time Data Updates
Clear Color-Coding for Performance Trends
Actionable Insights Section for Teams

5. Problem Solving – Addressing Gaps Systematically

Why It Matters

Digital transformations introduce new challenges. Instead of temporary fixes, structured problem-solving methods like PDCA (Plan-Do-Check-Act) or A3 thinking ensure issues are resolved at the root cause level.

Example: Ford’s Digital Production Line Improvements

Ford faced efficiency issues after implementing digital production tracking. By using PDCA cycles, they systematically identified and eliminated process gaps, improving production flow and reducing defects.

Approach: A3 Problem-Solving Approach

Define the Problem
Analyze Root Causes
Develop & Test Countermeasures
Implement & Sustain Improvements

6. Leader Standard Work – Driving & Sustaining Transformation

Why It Matters

Leaders play a crucial role in ensuring digital transformation is reinforced daily. Without active leadership engagement, employees revert to familiar processes, undermining long-term success.

Example: GE’s Lean Leadership Coaching

GE implemented Leader Standard Work (LSW) to ensure leaders consistently reinforced digital adoption. By embedding digital coaching into daily and weekly routines, they sustained digital engagement long after rollout.

Approach: Leader Standard Work Checklist

Daily: Attend team huddles, review dashboards, coach employees.
Weekly: Conduct structured digital adoption reviews, address problem-solving needs.
Monthly: Assess long-term impact, adjust Standard Work where needed.

Conclusion

Digital transformation is not just about technology—it’s about sustained operational change. By embedding these six Lean concepts, organizations can move from execution to full integration, ensuring digital initiatives drive long-term value.

Call to Action:

Which of these Lean concepts resonates most with your transformation journey?
How are you ensuring that digital changes truly stick in your organization?

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.

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.