Section 1: What Change Maturity Looks Like – And How Data Made It Real
Shifting from Capability Sessions to Data-Driven Change
For years, the default approach to improving organisational change maturity has been through capability sessions: workshops, training programs, and methodology deep dives. These sessions often focus on the mechanics of change management-how to assess impacts, create stakeholder maps, or run engagement activities. While valuable, they rarely move the needle on actual change maturity, because they don’t address the systemic challenge: embedding change into the rhythm of business.
This is not to say that capability sessions are inherently not valuable nor make an impact. The point is if this is the core approach to lift change maturity, you may want to re-think this approach.
In contrast, the financial services organisation we’re profiling achieved a step-change in maturity not by running more workshops, but by making change a measurable, managed discipline-driven by data. This is the essence of “what gets measured gets managed.” When change is tracked, analysed, and reported with the same rigour as financial or operational metrics, it becomes a core business focus and therefore evolving into a capability, not a project add-on.
The Hallmarks of Data-Driven Change Maturity
So, what does this maturity look like in practice?
Senior Leaders Are Personally Accountable Change metrics are embedded in the general management scorecard. Senior managers are not just sponsors; they are accountable for change outcomes, not just at a project level but within their business function. Their performance includes the outcome and the impact of change on business results. This accountability cascades throughout the organisation, with other managers following suit, creating a culture where change performance is a core management concern.
Demand for Change Expertise Is Pulled, Not Pushed Instead of the central change team “pushing” support onto the business, managers proactively seek out change expertise. They do this because the data shows them where key risks and concerns are, making change support a value-added service rather than a compliance exercise.
Operations Teams Have Line of Sight Operations teams can see all upcoming changes affecting their areas, thanks to integrated change visuals and dashboards. This transparency allows for coordinated engagement and implementation, ensuring that people capacity and readiness are managed proactively, not reactively.
Project Teams Adapt Based on People Data Project teams don’t just track milestones and budgets; they monitor leading indicators like readiness, sentiment, and adoption. Governance forums provide visibility and decision-making authority on key people risks across all change initiatives, enabling real-time adjustments to project approaches.
The Data Infrastructure That Enabled This Shift
To achieve this level of maturity, the organisation should utilise a centralised change data platform, integrating inputs from project management and operational dashboards. Data governance was established at the management level, with clear ownership and enterprise definitions. Automation and AI were used to collect, cleanse, and analyse data at scale, removing manual bottlenecks and enabling real-time insights.
Contrasting Traditional and Data-Driven Approaches
Aspect
Traditional Approach
Data-Driven Change Maturity
Senior Manager Involvement
Sponsorship, not accountability
Direct accountability, metrics-driven
Change Capability Uplift
Capability sessions, workshops
Focus on metrics improvement drove ongoing holistic capability improvement
Change Data Usage
Limited, ad hoc surveys or hearsay opinions
Integrated, real-time, enterprise-wide
Operations Visibility
Siloed, reactive
Proactive, coordinated, data-informed
Project Team Adaptation
Based on lagging indicators
Based on leading, predictive analytics
Value Realisation
Incremental, project-based
Enterprise-wide, transformative with alignment across different management levels
The Real Work Behind the Results
Some might argue that this level of data infrastructure and governance is too complex or resource-intensive. However, with modern automation and AI, much of the data collection, cleansing, and analysis can be streamlined. The initial investment is quickly offset by the value unlocked-both in risk mitigation and in the ability to deliver change at scale, with greater precision and impact.
This is what change maturity looks like when it’s powered by data. It’s not about more workshops; it’s about making change visible, accountable, and actionable at every level of the organisation. The next section will explore how this approach transforms decision-making-from focusing on cost and timelines to prioritising people and value.
Section 2: From Cost and Timelines to People and Value – How Data Transforms Change Implementation
The Persistent Focus on Cost and Timelines
For decades, change and transformation decisions in large organisations have been anchored in two primary considerations: cost and project timelines. Budgets are scrutinised, schedules are tracked, and success is often measured by whether a project was delivered on time and within budget. While these are important, they are insufficient for delivering sustainable, people-centric change. By focusing narrowly on these factors, organisations risk overlooking the most critical element: the people who must adopt and sustain the change.
Injecting the People Element-Through Data
A growing number of organisations are recognising that change cannot be managed by these numbers alone. The financial services organisation in this case study made a deliberate shift: they began injecting people data into every change decision. This meant that, alongside cost and timeline metrics, leaders and project teams had access to real-time insights on people impacts and capacity/readiness risks.
These people metrics were not afterthoughts-they were integrated into the same dashboards and governance forums as financial and operational data. This integration enabled a more holistic view of change, allowing leaders to make informed decisions that balanced the needs of the business with the realities of its workforce.
How People Data Drives Better Decisions
Proactive Risk Management By monitoring leading indicators such as readiness and sentiment, project teams could identify potential risks before they became issues. For example, a drop in readiness scores could trigger targeted engagement activities, preventing delays and increasing the likelihood of successful adoption.
Dynamic Resource Allocation Data on people capacity allowed operations teams to anticipate and manage the impact of multiple concurrent changes. This meant that resources could be allocated more effectively, reducing the risk of change fatigue and ensuring that teams were not overwhelmed.
Evidence-Based Adjustments Project approaches were no longer set in stone. Teams could tweak their strategies based on real-time feedback, ensuring that change initiatives remained aligned with the needs and capabilities of the workforce. Often this is done in advance of any governance decision making as teams could already see potential risks and opportunities through data.
Governance That Delivers Value Governance forums used people data to prioritise initiatives, allocate resources, and escalate risks. This meant that decisions were made with a clear understanding of both the financial and human implications of change.
The Role of AI and Automation
The integration of people data into change management was made possible by advances in AI and automation. These technologies enabled the organisation to collect, analyse, and visualise data at scale, removing the manual burden and providing actionable insights in real time. The value of AI and automation was not just in saving a few hours on impact assessments-it was in providing the analytical horsepower to identify patterns, predict risks, and optimise change delivery across the enterprise.
Moving Beyond Incremental Value
By embedding people data into the heart of change decision-making, the organisation was able to move beyond incremental improvements. Instead of talking about saving a few thousand dollars on a single project, they unlocked tens of millions in enterprise value by delivering change that was adopted, sustained, and embedded across the business.
The New Decision-Making Framework
Decision Factor
Traditional Approach
Data-Driven Approach
Cost
Primary focus
Balanced with people and value
Timelines
Primary focus
Balanced with people and value
People Readiness
Secondary, ad hoc
Primary, real-time, data-driven
Sentiment/Adoption
Rarely measured
Continuously monitored
Resource Allocation
Based on project needs
Based on overall people capacity and readiness, so balancing not just project resources but impacted business resources
Governance
Focused on milestones
Focused on both financial and people goals
The Result: Change That Delivers Value
The shift to data-driven, people-centric change management transformed the organisation’s ability to deliver value. Change was no longer a series of isolated projects, but a core business capability-managed, measured, and continuously improved. The next section will explore how this approach can be scaled and sustained, and what it means for the future of change and transformation in large organisations.
Section 3: Scaling and Sustaining Change Maturity – The Future of Transformation
The Myth of Overwhelm: Practical Steps to Sustainable Change Maturity
For many organisations, the prospect of building and maintaining a data-driven change maturity model can seem daunting. The common perception is that it requires an overwhelming investment in new tools, processes, and training-one that may not be justified by the returns. However, the experience of this financial services company demonstrates that, while focused effort is required, the process does not have to be overwhelming-especially with the right use of experimentation, ongoing tweaks, automation and AI.
Automation: The Great Enabler Much of the heavy lifting in data collection, cleansing, and reporting can now be automated. Change impact assessments, sentiment tracking, and readiness surveys can be scheduled, administered, and analysed with minimal manual intervention. This frees up change professionals to focus on interpretation, action, and continuous improvement rather than data wrangling.
AI: Unlocking Predictive Power AI tools can analyse patterns across multiple change initiatives, predict adoption risks, and recommend interventions before issues arise. This predictive capability allows organisations to be proactive rather than reactive, reducing the risk of failed change and increasing the speed of value realisation.
Scalable Governance By embedding change metrics into existing governance structures-such as business reviews, risk committees, and leadership forums-the organisation ensures that change maturity is not a one-off project but an ongoing discipline. This integration makes it easier to scale across divisions, regions, and business units.
Continuous Experimentation and Adaptation
A critical aspect of scaling and sustaining change maturity is the willingness to experiment, learn, and iterate. Early adoption of data-driven change management should be approached with a mindset of ongoing refinement. For example, executive alignment is often achieved not in a single meeting, but through a series of tailored discussions where dashboards and metrics are gradually refined to match leadership priorities and language. Testing different dashboard designs-such as visualisations, drill-down capabilities, or alert mechanisms-allows teams to identify what best supports decision-making at each level of the organisation.
Similarly, designing change decision-making forums as iterative, rather than static, processes ensures that the right data is surfaced at the right time, and that governance structures evolve as the organisation’s change maturity grows. By embracing a culture of experimentation and continuous improvement, organisations can ensure their change management practices remain relevant, effective, and aligned with both business and people objectives.
From Thousands to Millions: The Real Value of Data-Driven Change
The ultimate value of this approach is not measured in hours saved or individual project successes. It is measured in the ability to deliver change at scale, with precision, and with confidence that people will adopt and sustain the new ways of working. This is what ultimately drives benefit realisation. In this financial services organisation, the shift from ad hoc, project-based change to an enterprise-wide, data-driven discipline unlocked tens of millions in value-far beyond the incremental savings of traditional approaches.
Risk Mitigation By identifying and addressing people risks early, the organisation avoided costly delays, rework, and failed implementations.
Faster Value Realisation Real-time data enabled faster, more informed decision-making, accelerating the time to value for major initiatives.
Sustainable Adoption Continuous monitoring and adjustment ensured that changes were not just implemented, but embedded and sustained over time.
Are You Ready to 10-100X the Value of Change?
For experienced change and transformation practitioners, the question is no longer whether data-driven change maturity is possible-it is whether you are ready to embrace it. The tools, technologies, and methodologies are available. The competitive advantage lies in how you use them-making change visible, accountable, and actionable at every level of the organisation.
Lift the Game Move beyond incremental improvements and unlock the full potential of change as a lever for enterprise performance.
Lead the Shift Champion the integration of people data into every change decision, and demonstrate the value of a disciplined, data-driven approach.
Scale and Sustain Use automation and AI to make change maturity a scalable, sustainable capability-not just a project or initiative.
The Future Is Now
The future of change and transformation is here. It is data-driven, people-centric, and value-focused. It is about making change a core business discipline-managed, measured, and continuously improved. Are you ready to take the leap and 10-100X the value that change delivers in your organisation?
As digital acceleration and stakeholder scrutiny intensify, change leaders can no longer rely on gut feelings or generic feedback. The discipline is undergoing a seismic shift—from qualitative storytelling to quantifiable impact. Here’s why measurement is now the backbone of successful change, and how to avoid becoming another cautionary tale.
🔍 Why Measurement Is No Longer Optional
1. Executives Demand ROI—Not Just Happy Sheets
Gone are the days when a well-crafted communication plan sufficed. Today’s leaders expect change teams to demonstrate their impact with hard evidence. The Change Management Institute’s Competency Model sets a global benchmark for what effective change looks like, emphasising clusters of behaviours and skills that drive real results at every level—Foundation, Specialist, and Master. For example, the “Facilitating Change” competency requires practitioners to correctly assess readiness, build targeted plans, and conduct regular reviews—each step lending itself to clear, actionable measurement.
Action Step: Map your change KPIs directly to the behavioural competencies outlined by the Change Management Institute. If your goal is to build readiness, track metrics such as pre- and post-training confidence scores, participation rates in workshops, and the frequency of feedback loops. For communication effectiveness, measure open rates, click-throughs, and qualitative feedback from impacted teams.
2. The Agile Imperative: Iterate or Stagnate
Agile methodologies are reshaping change management. Teams using iterative feedback loops—such as regular check-ins and rapid data reviews—report faster adoption and more sustainable results. The Competency Model encourages change professionals to adapt approaches based on real-time data, ensuring that interventions remain relevant and effective.
3. AI and Analytics: From Guesswork to Precision
AI tools now predict resistance risks, automate sentiment analysis, and personalise communications. For instance, machine learning models can be used to flag teams likely to struggle with a new CRM system based on historical adoption patterns.
📊 Change Management’s Data Evolution vs. Other Disciplines
Week 4: Measure proficiency gains and correlate with productivity data.
Step 3: Visualise Progress Use tools like Miro, Power BI or Change Automator to create:
Adoption Roadmaps: Colour-coded timelines showing team readiness.
Sentiment Heatmaps: Identify departments needing extra support.
From Data to Action: The New Rules of Change Management You Can’t Afford to Ignore
Yesterday’s change playbooks are gathering dust. Today, the most effective change leaders are embracing cutting-edge tools and mindsets—think AI-driven insights, hyper-personalisation, and visual storytelling. These aren’t just buzzwords; they’re practical shifts you can harness right now to drive measurable, people-focused results.
1️. AI-Powered Insights: Predict, Don’t Just React
Why It Matters: AI is rapidly moving from the IT department into the heart of change management. Modern AI tools can analyse vast amounts of communication and performance data to identify patterns that signal potential resistance or readiness for change. By leveraging predictive analytics, change teams can proactively address issues—such as resistance hotspots or engagement gaps—before they escalate and derail a project.
Instead of waiting for problems to surface, AI-powered dashboards and sentiment analysis provide real-time feedback, allowing change practitioners to tailor communications, adjust training, and allocate resources where they’re needed most. This proactive approach not only streamlines decision-making but also accelerates adoption and supports more sustainable outcomes.
How to Apply Today:
Use AI-based sentiment analysis tools to monitor employee feedback and flag emerging concerns.
Segment audiences and personalise communications based on data-driven insights, ensuring the right message reaches the right people at the right time.
Automate routine change management tasks, freeing up your team to focus on strategic interventions and stakeholder engagement.
Real-World Example: A financial services organisation used Change Automator to map employee sentiment across a portfolio of digital projects. By visualising hotspots, they reallocated resources to struggling teams, lifting overall adoption.
2️. Employee-Centric Design: Make Change Personal
Why It Matters: Generic change comms are out. Employees expect tailored, relevant experiences—mirroring what they get as consumers.
How to Apply Today:
Map the Employee Journey: Use journey mapping tools to chart every touchpoint, from initial announcement to post-launch support.
Co-Create Solutions: Run design sprints with front-line staff change champions to surface real pain points and co-design fixes.
Micro-Target Messaging: Swap “all-staff” emails for role-specific updates—e.g., “Here’s how the new system changes your workflow, Sarah.”
Practical Tip: Start with a single pilot group. Test different message formats (video, infographic, FAQ) and measure which drives the most engagement. Scale up what works.
3️. Visual Storytelling: Make Data Unmissable
Why It Matters: Humans process visuals significantly faster than text. Yet, too many change reports are buried in spreadsheets. Visual dashboards, infographics, and storyboards make progress—and problems—impossible to ignore.
How to Apply Today:
Build a Change Portfolio Dashboard: Use tools such as Change Compass to show every initiative’s impact, readiness, adoption and risk on one screen.
Create “Before & After” Maps: Visually chart how roles, processes, or systems are changing—helping staff see what’s coming and why it matters.
Share Wins Visually: Celebrate milestones with progress bars, leaderboards, or “heat maps” of adoption.
4️. Change Portfolio Management: See the Forest, Not Just the Trees
Why It Matters: With overlapping projects, employees often face “initiative overload.” To read more about this check out The Change Compass blogs on Change Portfolio Management.
How to Apply Today:
Map All Changes: List every active and upcoming initiative in a single portfolio view.
Spot Clashes Early: Use visual tools to identify timing conflicts or resource bottlenecks.
Balance the Load: Adjust rollout schedules to avoid overwhelming any one team.
Action Step: Hold a monthly “change portfolio review” with business leaders. Use your dashboard to make data-driven decisions about sequencing and support.
One-off surveys and end-of-project reviews often miss the mark. Today’s leading organisations are moving towards ongoing, real-time feedback to spot issues early, adapt quickly, and keep change on track. Continuous feedback loops allow you to capture employee sentiment, adoption barriers, and training gaps as they arise—making your change program more responsive and resilient.
How to Apply Today:
Run regular pulse checks: Use short, targeted surveys after key milestones or training sessions to gauge understanding and readiness.
Empower rapid response: Assign change champions or team leads to monitor feedback and act on it quickly—whether that means clarifying communications, offering extra coaching, or removing roadblocks.
Close the loop: Always share back what you’ve learned and what actions you’re taking as a result. This builds trust and shows that feedback leads to real improvements.
Practical Tip: Set up a simple feedback calendar—weekly or fortnightly—so your team knows when to expect check-ins. Use tools like Microsoft Forms, The Change Compass, or even a quick stand-up meeting to keep the feedback flowing.
🏆 Quick Reference: Emerging Trends & How to Action Them
Build dashboards, use infographics, share visual wins
Portfolio Management
Map all changes, review monthly, balance the load
Continuous Feedback
Run pulse checks, act fast, close the loop
Stop Guessing, Start Measuring: Your 7-Step Blueprint for Change Management Success
You’ve seen why measurement is now mission-critical and how the smartest organisations are using data, AI, and design thinking to get ahead. But how do you actually put this into practice—without getting bogged down in theory or drowning in dashboards? Here’s a hands-on, step-by-step playbook you can use right now to make your change program measurable, actionable, and impossible to ignore.
1️. Get Crystal Clear on What Success Looks Like
Problem: Vague goals (“increase engagement”, “improve adoption”) lead to fuzzy results. If you can’t measure it, you can’t manage it.
Action:
Work with sponsors and business owners to define outcomes in hard numbers.
Instead of “increase system usage”, set: “90% of frontline staff log into the new CRM daily within 3 weeks.”
For behaviour change: “Reduce manual workarounds by 70% in 3 months.”
Align these metrics to broader business KPIs.
If your company’s focus is customer satisfaction, link your change metrics to NPS or customer complaint rates.
2️. Map Your Change Portfolio—See the Whole Picture
Problem: Change fatigue and initiative overload are real. Siloed projects compete for attention, causing confusion and burnout.
Action:
List every change initiative impacting your people in the next 6–12 months.
Use a simple spreadsheet or an automated tool like The Change Compass to visualise overlaps and pinch points.
Create a high level “heat map” of change impacts by team, location, or role.
Colour-code by intensity.
Share this map with leaders to adjust timing and resource allocation.
Example: A retail chain in NSW used a portfolio map to delay a payroll system upgrade, avoiding clashing with a major sales transformation—saving weeks of disruption.
3️. Baseline Before You Begin—Don’t Skip This Step
Problem: You can’t prove improvement if you don’t know where you started.
Action:
Run a short, targeted survey or use existing data to capture current state.
For a new process: measure error rates, time to complete, or customer complaints.
For behaviour change: use a quick pulse survey (“How confident are you using the current system?”)
Document baseline metrics and share with your team.
Visual: Bar chart showing “before” metrics—e.g., average call handling time pre-change.
4️. Build a Real-Time Measurement Plan—Not Just End-of-Project Reports
Problem: Annual surveys and after-action reviews are too slow for today’s pace.
Action:
Set up a dashboard (even a simple one in Excel or Power BI) tracking your key metrics.
Schedule weekly or fortnightly check-ins to review progress.
Automate data collection where possible (e.g., system usage logs, sentiment surveys).
Visual: Screenshot of a simple dashboard tracking adoption, sentiment, and productivity.
5️. Act Fast on What the Data Tells You
Problem: Collecting data is pointless if you don’t act on it.
Action:
Assign a “data owner” for each metric—someone responsible for monitoring and responding (your change champions may come in handy here)
If adoption lags, run targeted workshops or peer coaching.
If sentiment drops, hold listening sessions and tweak communications.
Always close the loop: tell people what you’re changing based on their feedback.
Pro Tip: Use the “You Said, We Did” format in your updates to build trust.
6️. Celebrate, Iterate, and Scale What Works
Problem: Wins often go unnoticed, and lessons aren’t shared.
Action:
Visually celebrate milestones—use leaderboards, digital badges, or progress bars.
Document what worked and what didn’t in short, shareable case studies.
Scale successful tactics to other teams or projects.
Visual: Photo of a “Change Champions” digital wall or leaderboard.
7️. Keep the Feedback Loop Alive—Continuous Improvement
Problem: Change is never truly “done”—but measurement often stops too soon.
Action:
Continue pulse checks for at least 3–6 months post-launch.
Use insights to inform future projects and refine your change playbook.
Share lessons learned across your change portfolio—don’t let knowledge get siloed.
📋 Quick Checklist: Your Measurement-Driven Change Program
☑️ Define clear, outcome-based metrics ☑️ Map your change portfolio and impacts ☑️ Baseline before starting ☑️ Set up real-time dashboards ☑️ Assign data owners and act quickly ☑️ Celebrate and scale what works ☑️ Keep measuring and improving
🏁 Ready to Lead the Data-Driven Change Revolution?
Don’t just talk about change—prove it, measure it, and make it stick. Start with one project, apply these steps, and watch your credibility (and results) rise. For more practical tools, checklists, and templates, visit The Change Compass Knowledge Hub and subscribe for monthly insights tailored to Australian change leaders.
What’s the first metric you’ll measure on your next change? Share your thoughts below or connect for a discussion on resolving your change measurement problems.
Managing multiple changes is not a new phenomenon for a lot of organisations. However, the value of managing change at a portfolio level is not clear for a lot of leaders. This is a review of academic research on the value of managing multiple change initiatives across an organisation (change portfolio management), with specific focus on the impact of change on people and tangible business benefits. Drawing from peer-reviewed academic sources, this report identifies quantifiable business benefits and performance outcomes associated with effective change portfolio management.
Academic research consistently demonstrates that organisations face significant challenges when implementing multiple change initiatives simultaneously. However, organisations that develop effective change portfolio management capabilities achieve substantially better outcomes, including:
1. Productivity Improvements: Firms with more complex organisational capabilities show “considerably increased firm performance in terms of labour productivity” (Costa et al., 2023).
2. Competitive Advantage: Organisations with better change management capabilities gain strategic advantages over competitors with lower change capacity (Heckmann et al., 2016).
3. Organisational Resilience: Organisations with higher change capacity demonstrate greater resilience during periods of disruption (Mladenova, 2022).
This report synthesizes academic research to provide evidence-based insights on the tangible business benefits of effective change portfolio management.
Background
Organisations today face unprecedented pressure to implement multiple simultaneous changes. Technological disruption, competitive pressures, and evolving customer expectations drive the need for continuous transformation. However, academic research reveals that implementing multiple change initiatives simultaneously creates significant challenges for both individuals and organisations.
Here lies the dilemma. Most organisations are implementing multiple change initiatives. However, nearly all methodologies and change management concepts are only focused on one singular initiative been executed at a time.
Here we examine peer-reviewed academic research on how change portfolio management affects organisational outcomes and quantifies the tangible business benefits of effective change management. It focuses specifically on the value of effectively managing multiple change initiatives across the organisation and identifies measurable business benefits supported by scholarly evidence.
Journals reviewed
This review synthesizes findings from peer-reviewed academic journals including:
– Journal of Business Research
– SAGE Journals
– Industrial and Corporate Change (Oxford Academic)
– Cogent Business & Management
– Administrative Sciences
– Organisational Dynamics
The research focuses on empirical studies that quantify the relationship between change management approaches and business outcomes. Particular attention was given to studies that provide statistical evidence of the impact of change portfolio management on organisational performance.
Change Capacity Limitations: Academic Evidence
The Challenge of Multiple Change Initiatives
Academic research consistently demonstrates that organisations struggle to implement multiple change initiatives simultaneously. Mladenova (2022) found that “multiple and overlapping change initiatives become the norm rather than an exception, thus exert additional pressure on organisations.” Her research identified that when organisations face “increasing levels of unpredictability and need to adapt to fast environmental shifts, linear causal models to plan and implement changes become harder to follow.” However, the bulk of popular change management concepts are linear in nature.
Organisational Capacity for Change
Heckmann et al. (2016) define Organisational Capacity for Change (OCC) as “the capacity of an organisation to institutionalize and manage change on an ongoing basis.” Their empirical research found that “an organisation’s capacity for change associates positively with the performance of its change projects.”
Importantly, the study found that “higher levels of technological turbulence weaken” the relationship between organisational capacity for change and project performance. This suggests that organisations face even greater challenges managing multiple changes during periods of technological disruption.
Adna and Sukoco (2020) studied 313 middle managers and their followers and found that “organisational capacity for change mediates the influence of managerial cognitive capabilities on organisational performance.” Their research demonstrated that organisations need coordinated portfolio approaches to effectively manage multiple changes. Having the right routines also support continuous and multiple changes.
Tangible Business Benefits: Academic Evidence
Success Rate
Academic research provides clear evidence that effective change portfolio management significantly improves success rates:
– Improved Project Performance: Heckmann et al. (2016) found that “an organisation’s capacity for change associates positively with the performance of its change projects” in their empirical study of 134 German firms.
Financial Performance Improvements
Academic research demonstrates measurable financial benefits from effective change portfolio management:
– Productivity Gains: Costa et al. (2023) empirically demonstrated that firms with more complex organisational capabilities showed “considerably increases firm performance in terms of labor productivity.” Their study of Italian firms identified that “Complex” organisations (those with highest organisational capabilities) demonstrated superior productivity metrics compared to firms with less developed capabilities.
– Cost Avoidance: Errida and Lotfi (2021) systematic review of literature identified that failed change initiatives result in both direct costs (resources invested) and indirect costs (lost productivity).
– Resource Utilization Efficiency: Rousseau and ten Have (2022) found that organisations using evidence-based change management practices showed improved change-related decision quality, leading to better use of resources during change implementation.
Competitive Advantage
Academic research identifies clear competitive advantages from effective change portfolio management:
– Strategic Adaptability: Heckmann et al. (2016) established that organisations with better change management capabilities gain strategic advantages over competitors with lower change capacity. Their research demonstrated that organisations with higher change capacity are better positioned to implement future strategic changes.
– Innovation Implementation: Costa et al. (2023) demonstrated that firms with more complex organisational capabilities showed greater ability to innovate and adapt to market changes. Their research found that “higher organisational complexity—captured by the range and variety of actions put in place by firms—is thus reflected in better performance.”
– Market Responsiveness: Mladenova (2022) found that organisations with higher change capacity can better handle “multiple and overlapping change initiatives” which have “become the norm rather than an exception.” The research identified that organisations with higher change capacity demonstrate superior market responsiveness.
Human Capital Benefits
Academic research shows significant human capital benefits from effective change portfolio management:
– Employee Engagement: Mladenova (2022) found that organisations implementing multiple simultaneous changes without adequate change capacity experience diminishing returns partly due to employee disengagement. Organisations with effective change portfolio management maintain higher levels of employee engagement during periods of change.
– Talent Retention: Heckmann et al. (2016) found that organisations with higher change capacity experience lower turnover during periods of change. Their research demonstrated that effective change portfolio management contributes to organisational stability and talent retention.
– Capability Development: Costa et al. (2023) found that organisations with more complex capabilities develop stronger human capital over time. Their research demonstrated that investment in organisational capabilities creates a foundation for future performance improvements.
Organisational Performance Taxonomy
Costa et al. (2023) identified four clusters of firms based on organisational capabilities, providing a framework for understanding the relationship between change capabilities and performance. The following descriptions are inferred from the study and not actual quoted descriptions.
1. Essential (basic capabilities): Organisations with minimal change management capabilities that struggle with implementing multiple changes.
2. Managerial (moderate capabilities): Organisations with some change management capabilities but limited coordination across initiatives.
3. Interdependent (advanced capabilities): Organisations with developed change management capabilities and coordination across initiatives.
4. Complex (highest capabilities): Organisations with capabilities that can effectively implement multiple and complex changes. These tend to have experienced a range of ‘technological-organisational’ changes.
Their research demonstrated that firms in the Complex and Interdependent clusters showed significantly higher performance metrics than those in the Essential and Managerial clusters. This provides a framework for measuring organisational capability development and its impact on performance.
Recommendations from Academic Research
Academic research suggests several evidence-based approaches to improve change portfolio management:
1. Invest in Change Capacity: Heckmann et al. (2016) recommend that “companies should invest in their capacities for change, particularly in the HRM area” to build change capacity. Their research demonstrated that investment in change capacity is a strategic business decision with measurable returns.
2. Develop Integrated Approaches: Errida and Lotfi (2021) found that “the use of a single model or few models is not sufficient to cover various change situations” and that “integrating existing models may lead to an integrated understanding of how to ensure successful organisational change.”
3. Build on Positive Experiences: Heckmann et al. (2016) found that “positive experiences in previous change projects increase OCC (Organisational Capacity for Change).” Their research demonstrated that successful change experiences create a virtuous cycle that builds change capacity over time.
4. Use Evidence-Based Practices: Rousseau and ten Have (2022) found that “planned change is more likely to succeed when using science-informed practices” and that “regular use of four sources of evidence (scientific, organisational, stakeholder, and practitioner experience) improve the quality of change-related decisions.”
Academic Evidence for Change Portfolio Management
The academic research reviewed in this report provides clear evidence that managing multiple change initiatives as a portfolio delivers significant business benefits compared to uncoordinated change approaches.
Organisations that effectively manage their change portfolio can expect:
3. Human Capital Benefits: Improved employee engagement, talent retention, and capability development.
4. Long-term Performance: Greater organisational resilience and sustainable growth.
Whilst there is not a lot of research currently in the newly emerging field of change portfolio management, overall academic evidence strongly supports the value of change portfolio management practices as a strategic approach to organisational transformation.
References
Adna, B. E., & Sukoco, B. M. (2020). Managerial cognitive capabilities, organisational capacity for change, and performance: The moderating effect of social capital. Cogent Business & Management, 7(1). https://doi.org/10.1080/23311975.2020.1843310
Costa, S., De Santis, S., Dosi, G., Monducci, R., Sbardella, A., & Virgillito, M. E. (2023). From organisational capabilities to corporate performances: at the roots of productivity slowdown. Industrial and Corporate Change, 32(6), 1217-1244. https://doi.org/10.1093/icc/dtad030
Errida, A., & Lotfi, B. (2021). The determinants of organisational change management success: Literature review and case study. SAGE Journals. https://doi.org/10.1177/18479790211016273
Heckmann, N., Steger, T., & Dowling, M. (2016). Organisational capacity for change, change experience, and change project performance. Journal of Business Research, 69(2), 777-784. https://doi.org/10.1016/j.jbusres.2015.07.012
Mladenova, I. (2022). Relation between Organisational Capacity for Change and Readiness for Change. Administrative Sciences, 12(4), 135. https://doi.org/10.3390/admsci12040135
Rousseau, D. M., & ten Have, S. (2022). Evidence-based change management. Organisational Dynamics, 51(3). https://doi.org/10.1016/j.orgdyn.2022.100899
Let’s start with an uncomfortable truth: most organisations juggling multiple transformations—digital overhauls, restructures, mergers—end up with stalled initiatives, overwhelmed employees, and leaders questioning ROI. The problem isn’t a lack of effort. It’s a lack of strategic alignment between the existing change management maturity level and the portfolio-level outcomes executives truly care about.
Success lies in breaking the journey into short-term (3–6 months), medium-term (6–18 months), and long-term (18+ months) goals that directly address how change is prioritised, resourced, and measured across initiatives. Without this, even sophisticated maturity models become shelfware.
There are many facets that comprise change maturity. Rather than addressing every element, here we are focused on key aspects such as driving business change leadership, the importance of understanding the impacts of change across initiatives (impact assessment) and measurement.
Short-Term: Align with Portfolio Priorities
Senior leaders managing a portfolio of changes care about three things: resource efficiency, risk reduction, and speed-to-value. Your job? Show how maturity-building activities will fix their pain points—today. I know … you’re probably thinking … well nothing can be done immediately since anything to do with change maturity can take a long time, right? However, there are clear steps you can take to prioritise your efforts.
Step 1: Map Initiatives to Business Outcomes
Example: A mining company’s portfolio included 12 concurrent projects. By categorising them into strategic priorities (e.g., safety, cost reduction), the change team identified that 70% of delays stemmed from poor cross-initiative dependency mapping.
Action: Use portfolio impact visualisations to visually show leaders where overlaps, bottlenecks, or resource gaps exist. Think beyond a heatmap. Heatmap is only one artefact (and in fact may not be the best for decision making)
Step 2: Pilot a Cross-Initiative Process
Tactic: Implement a standardised change impact assessment for all projects in the next quarter. Focus on:
Employee capacity: “How many initiatives are targeting the same teams? Same roles? Same time period? Same behaviours?”
Stakeholder conflicts: “Are competing messages being sent? Are similar capabilities being delivered, but not aligned nor clearly positioned?”
Result: A financial services firm reduced duplicate communications by 40% in 60 days by centralising messaging across 5 projects. This is in fact a very common and immediate benefit of improved change maturity process capability.
💡 Key insight: Short-term wins must address portfolio-level inefficiencies, not just single projects. Leaders will disengage if maturity feels like an “HR exercise.”
Medium-Term: Build Systems for Scale (6–18 Months)
With early trust established, shift to embedding repeatable processes that reduce friction across initiatives.
Step 3: Integrate Change Metrics into Portfolio Reviews
Example: A healthcare provider added three change metrics to their monthly project reviews:
% of initiatives with validated impact assessment
Average employee sentiment score (pre/post-launch)
Number of cross-initiative resource risks identified and resolved
Tool: Use a Change Readiness Dashboard
Step 4: Create a “Change Portfolio Office”
Structure: A cross-functional team that:
Reviews all initiatives for change impacts before funding is approved.
Allocates shared resources (e.g., change champions, training budgets).
Case study: A retail company cut project approval times by 30% by centralising impact assessments, saving $2.1M annually in wasted planning.
At this stage, maturity means change management is no longer a “function”—it’s how the organisation operates.
Step 5: Embed Change into Governance
Example: A financial services company tied executive KPIs to portfolio-wide adoption rates, ensuring accountability.
Process: Integrate change criteria into:
Investment committees: “No impact assessment = no continued funding.”
Risk registers: Flag initiatives with low readiness scores.
Step 6: Cultivate a Change Culture
There are many potential levers to pull when it comes to cultivating a change culture. Working on too many things may mean you lose focus and end up not getting results from your various efforts. The best lever to pull for immediate results is that of change leadership. Leaders can directly impact how change is delivered and how it is felt from the employee’s perspective. Done right, the right change leadership behaviours can be reinforced and spread across the organisation through role modelling.
Tactic: Launch a Change Leadership Index measuring:
How often leaders role-model change behaviours.
% of managers practicing behaviours without prompting.
What’s Next? In the following sections, we’ll dive into crafting metrics that executives can’t ignore, including a step-by-step guide to building a business case for maturity—complete with ROI calculators and stakeholder analysis templates.
Building change management maturity across a portfolio of initiatives requires more than just good intentions—it demands measurable outcomes. Metrics are the bridge between your maturity-building efforts and the tangible results senior leaders expect. But not all metrics are created equal. To keep leaders engaged, your metrics need to be actionable, aligned with business goals, and easy to track.
Step 7: Design Metrics That Speak to Leaders
When managing a portfolio of changes, metrics need to reflect the big picture. Here’s how to create metrics that resonate:
Start with Business Priorities
Ask yourself: What are the organisation’s top three strategic goals this year?
Example: If a company’s priority is improving customer experience, track how well change initiatives reduce customer complaints or improve Net Promoter Scores (NPS).
Focus on Outcomes, Not Activities
Avoid tracking inputs like “number of training sessions delivered.” Instead, measure outcomes such as “percentage of employees demonstrating new behaviours post-training.” (e.g. based on leader ratings)
Use Leading and Lagging Indicators
Leading indicators help you predict success (e.g., % of employees engaged in readiness activities).
Lagging indicators measure results (e.g., project adoption rates or ROI).
Metric Type
Example
Why It Matters
Leading Indicator
% of initiatives with completed impact assessment
Predicts smoother implementation
Lagging Indicator
% increase in initiative adoption rates
Measures actual impact
Portfolio-Level Metric
% of projects that directly contribute to strategic goals
Ensures focus on what matters most
Step 8: Build a Change Dashboard for Portfolio Visibility
Leaders managing multiple initiatives need a clear view of progress across the portfolio. A well-designed dashboard can make this possible.
Here’s what to include in your Change Portfolio Dashboard:
Portfolio Aggregate Impacts: Visualise which teams or departments are most impacted by change. Move beyond generic traffic light indicators (green = low impact, red = high impact) to flag areas at risk of fatigue. Easy is not always effective in terms of supporting business decision making outcomes.
Adoption Metrics: Track adoption rates for each initiative and highlight where additional support is needed.
Resource Utilisation: Show how shared resources (e.g., trainers, change champions) are being allocated across projects.
🛠️ Tool Tip: Platforms like Change Compass can automate data collection and visualisation for your dashboard, saving time and ensuring accuracy.
Practical Example: Using Metrics to Drive Decisions
Let’s look at how an organisation applied these principles in real life:
Case Study: A Retail Chain’s Change Portfolio Overhaul
Scenario: A retail chain was managing 8 concurrent initiatives, including a new CRM system, process redesigns, and supply chain improvements. Employees were overwhelmed, and leaders lacked visibility into which projects were delivering value.
What They Did:
Short-Term Goal: Within 90 days, they implemented a portfolio change impact visualisation to identify overlaps in impacted teams. This revealed that store managers were involved in 7 out of 8 initiatives simultaneously—leading to burnout and delays.
Medium-Term Goal: Over the next year, they introduced standardised change impact assessments for all new projects and tied project approval to readiness scores. This increased readiness outcomes.
Long-Term Goal: After 18 months, they embedded change metrics into their governance process, requiring quarterly updates on adoption rates for all major initiatives.
Results: The company saw improvement in project delivery timelines and a significant boost in employee readiness/adoption scores.
Medium- and Long-Term Goals: Building for Sustainability
Once you’ve delivered short-term wins and established credibility with senior leaders, it’s time to focus on building sustainable systems that scale across the organisation.
A common pitfall in organisations is treating change management as an afterthought—something tacked on once projects are already underway. To build maturity, change impact assessments need to become a non-negotiable part of your project lifecycle.
Action Plan:
Partner with your PMO (Project Management Office) or equivalent team to integrate change assessments into project initiation documents.
Develop a simple checklist for project leads to evaluate readiness factors like stakeholder alignment, resource availability, and potential resistance points.
Example Checklist Item: “Have all impacted teams been consulted about potential workload increases?”
Real-Life Application: A financial services firm made stakeholder analysis and impact assessment mandatory before any project funding was approved. This reduced cross-departmental conflicts over resources and priorities.
Step 10: Scale Change Leadership Across the Organisation
One of the biggest barriers to maturity is over-reliance on a small group of change managers or consultants. To achieve long-term success, you need to democratise change leadership.
Create a Change Champions Network: Identify employees across departments who can act as local change agents. Train them on basic tools like stakeholder mapping and resistance management.
Incentivise Role Modelling: Offer recognition programs or tie role modelling in the network to career development opportunities.
Measure Success: Track how often champions are consulted during initiatives and whether their involvement correlates with higher adoption rates.
💡 Pro Tip: Use storytelling to highlight the impact of your champions’ work—e.g., “How Finance’s Change Champion helped reduce resistance during our ERP rollout.”
The Role of Data in Driving Maturity
Data is your best friend when it comes to building credibility and making informed decisions about where to focus your efforts.
Step 11: Use Data Insights to Prioritise Efforts
Not all initiatives—or teams—are created equal when it comes to their ability to handle change. By leveraging data from readiness assessments, pulse surveys, or even historical project performance, you can prioritise where to focus your efforts.
Example Insight: If pulse surveys show that frontline employees have low trust in leadership communication, prioritise initiatives that include robust communication plans.
Actionable Tip: Use historical data from past projects (e.g., adoption rates or employee sentiment scores) to predict which upcoming initiatives may face similar challenges.
The Final Stretch: Embedding Change into Your Organisation’s DNA
You’ve laid the groundwork with short-term wins, built scalable systems, and aligned metrics to leadership priorities. Now, it’s time to ensure change management maturity becomes self-sustaining—woven into your organisation’s culture, governance, and daily operations.
Step 12: Integrate Change into Talent Development
Maturity isn’t just about processes; it’s about people. To ensure long-term success, change competencies must be embedded into roles at every level.
Action Plan:
Leadership Development:
Include change leadership in executive training programs. For example, a mining company added a module on “Leading Through Complex Change” to its leadership curriculum.
Measure success through 360-degree feedback on leaders’ ability to role-model adaptability.
Employee Upskilling:
Offer microlearning courses on change basics (e.g., “Managing Your Energy During Change”).
Example: A retail chain used a mobile app to deliver 5-minute daily tips during a major transformation, boosting engagement by 35%.
Performance Reviews:
Tie 10–15% of managers’ KPIs to change-related behaviours (e.g., “Proactively addresses team concerns during transitions”).
📌 Tool Kit: Use platforms like LinkedIn Learning or Degreed to curate change management content tailored to different roles.
Step 13: Automate and Optimise
As your portfolio grows, manual processes will become unsustainable. Automation ensures scalability while freeing your team to focus on high-value work.
What to Automate:
Change Impact Assessments:
Use AI tools to analyse project documents and flag potential risks (e.g., overlapping initiatives impacting the same teams).
Example: Using ChatGPT (corporate version, to ensure you are not sharing sensitive data to the internet) to draft initial stakeholder analyses and high level impact assessment, reducing prep time significantly
Sentiment Tracking:
Deploy NLP (Natural Language Processing) tools to analyse employee feedback from surveys, emails, or collaboration platforms like Slack.
Resource Allocation:
Implement a digital tool (e.g., Smartsheet) to track shared resources (e.g., change champions) across projects and avoid burnout.
Process
Automation Tool
Outcome
Impact assessment
ChatGPT, Change Automator
Faster, data-driven insights
Sentiment Tracking
Qualtrics + NLP
Real-time emotion mapping
Portfolio Prioritisation
Jira Align + Power BI
Dynamic resource reallocation
Step 14: Foster a Feedback-Driven Culture
Mature organisations treat feedback as a strategic asset, not an afterthought. Build mechanisms to capture insights from employees, leaders, and customers—and act on them.
Tactics:
Pulse Surveys:
Send short, frequent surveys (5-8 questions) during critical phases of initiatives.
Example: “On a scale of 1–10, how prepared do you feel for the new process rollout?”
Post-Initiative Retrospectives:
Host cross-functional sessions to identify what worked and what didn’t. Use frameworks like Start, Stop, Continue to structure discussions.
Feedback Loops with Leaders:
Present anonymised employee feedback in leadership forums to drive accountability.
Example: A healthcare provider shared quotes like “We need clearer deadlines” in executive briefings, prompting better communication.
💡 Pro Tip: Use a “Feedback Action Tracker” to document how input has influenced decisions—and share updates with employees to build trust.
Step 15: Prepare for the Next Horizon
Change management maturity isn’t a destination—it’s a journey. To stay ahead, proactively scan the environment for emerging trends and adapt your approach.
Future-Building Strategies:
Scenario Planning:
Conduct workshops to simulate how your organisation would handle disruptions (e.g., AI-driven automation, regulatory shifts).
Example: A financial services firm used scenario planning to prepare for hybrid work trends, avoiding productivity dips.
Benchmarking:
Compare your maturity metrics against industry peers using frameworks like The Change Compass’s Maturity Index.
Innovation Labs:
Create cross-functional teams to pilot new tools (e.g., VR for change simulations) or methodologies (e.g., agile change management).
The ROI of Maturity: What’s in It for You?
Investing in change management maturity isn’t just about avoiding failure—it’s about unlocking tangible value. Consider these returns:
Area
ROI Example
Cost Savings
20–30% reduction in project rework
Speed
25% faster time-to-value for initiatives
Employee Experience
15% boost in engagement scores
Customer Impact
10% improvement in NPS post-change
Your Call to Action: Start Today
Building change management maturity across a portfolio isn’t easy—but the payoff is immense. Here’s how to begin:
Organisational transformations are essential for staying competitive in today’s fast-paced world, but they often come with challenges that can derail progress. One of the most pressing issues is change overload—when employees and stakeholders are overwhelmed by the sheer volume or pace of changes being implemented. This can lead to burnout, disengagement, resistance, and ultimately, failure to achieve transformation goals.
Artificial intelligence (AI) offers a powerful solution to combat change overload. By leveraging AI tools and strategies, organisations can streamline processes, personalise communication, optimise workflows, and make data-driven decisions that reduce stress and improve adoption rates. This guide provides actionable steps to harness AI effectively in managing large-scale transformations while preventing change fatigue.
1. Diagnose Change Overload with AI-Powered Insights
Before addressing change overload, you need to identify where it exists and how it impacts your organisation. AI-powered analytics tools can provide real-time data on employee sentiment, workload distribution, and engagement levels—helping you pinpoint areas of concern before they escalate.
How to Apply This:
Use Sentiment Analysis Tools: Platforms like Microsoft Viva Insights or Qualtrics EmployeeXM can analyse employee feedback from surveys, emails, or chat platforms to detect patterns of stress or disengagement. For example:
If sentiment analysis reveals a spike in negative feedback during a specific project phase, it may indicate that employees are overwhelmed by unclear communication or unrealistic deadlines.
Monitor Workload Distribution: Tools such as Workday or Asana’s workload management feature can highlight individuals or teams carrying disproportionate workloads. This allows leaders to redistribute tasks more equitably.
Track Change Saturation Metrics: Use metrics like the number of concurrent projects per team or the average time spent on change-related activities per week may be a start. AI dashboards can automatically calculate these metrics and flag when thresholds are exceeded.
Visualise Change Saturation: Tools such as The Change Compass can help to easily capture change impacts across initiatives and turn these into data visualisation to support decision making. Embedded AI tools help to interpret the data and call out key risk areas and recommendations.
🔍 Example: A retail organisation undergoing digital transformation used AI sentiment analysis to discover that frontline employees felt excluded from decision-making processes. Leaders adjusted their communication approach to involve key frontline change champions which improved morale and reduced resistance.
2. Streamline Communication Through Personalisation
One-size-fits-all communication often adds to change fatigue by overwhelming employees with ineffective or irrelevant information. AI can help tailor messages based on individual roles, preferences, and needs—ensuring that employees only receive what’s most relevant to them.
How to Apply This:
Leverage Natural Language Processing (NLP): Tools like IBM Watson can analyse employee communication styles and suggest tone adjustments for clearer messaging.
Segment Audiences Automatically: Use platforms like Poppulo or Dynamic Signal to categorise employees by role, department, or location and deliver targeted updates accordingly. For instance:
IT teams might receive detailed technical updates about new systems being implemented, while frontline staff get simplified instructions on how the changes will impact their day-to-day tasks.
Automate Feedback Loops: Chatbots powered by AI (e.g., Tidio or Drift) can collect ongoing feedback from employees about the clarity and usefulness of communications during transformation initiatives.
💡 Pro Tip: Combine AI-driven personalisation with human oversight to ensure messages remain empathetic and aligned with organisational culture.
3. Predict Bottlenecks with AI Analytics
One of AI’s greatest strengths is its ability to analyse historical data and predict future outcomes—a capability that’s invaluable for managing change timelines and resource allocation effectively. Predictive analytics can help you anticipate bottlenecks before they occur and adjust your strategy in real time. For example, there could be cyclical periods of the year where the change volume tends to be higher. From our research at The Change Compass, we’ve seen that across different industries, October-November, and February-March tend to be high change volume periods.
How to Apply This:
Forecast Employee Capacity: If you already have the data you can use tools like Tableau or Power BI to predict when teams will be overstretched based on upcoming project timelines and historical workload data. Alternatively, utilise The Change Compass’ forecasting capabilities to predict trends.
Identify High-Risk Areas: Predictive models can flag departments or teams likely to experience resistance based on past behaviours or current engagement levels.
Scenario Planning: Use AI simulations (such as those offered by AnyLogic) to test different implementation strategies for your transformation initiative. The Change Compass also has a scenario planning feature to help you model changes before making the decision.
📊 Example: A financial services firm used predictive analytics during its digital transformation to identify that Q4 was historically the busiest period for its customer service team. By rescheduling non-critical training sessions for later Q1, they reduced employee stress and maintained service quality.
4. Enhance Employee Engagement Through Personalised Learning Platforms
Engaged employees are more likely to embrace change rather than resist it. AI-powered learning platforms offer personalised training pathways that equip employees with the skills they need for new roles or technologies introduced during transformation.
How to Apply This:
Create Adaptive Learning Journeys: Platforms like Degreed or EdCast use AI algorithms to recommend training modules based on an employee’s current skill set and career aspirations.
Gamify Learning Experiences: Incorporate gamification elements such as badges or leaderboards into your training programs using tools like Kahoot! or Quizizz.
Monitor Training Effectiveness: Use analytics within learning management systems (LMS) like Cornerstone OnDemand to track completion rates, quiz scores, and time spent on modules.
🎯 Action Step: Pair training initiatives with clear career progression opportunities tied directly to the transformation goals—for example, offering certifications for mastering new software systems being implemented.
5. Automate Routine Tasks Using AI Tools
Repetitive tasks drain employees’ energy and time—resources that could be better spent on strategic initiatives during transformations. Automation powered by AI can alleviate this burden by handling routine tasks efficiently. This not only reduces workload but also empowers employees to focus on higher-value activities that drive transformation success.
Note that this approach is assuming the organisation has the appetite to leverage AI and automation to reduce workload.
How to Apply This:
Automate Administrative Tasks: Tools like UiPath or Zapier can automate workflows such as data entry, meeting scheduling, or report generation. For example:
Automating the creation of weekly project status reports allows project managers to spend more time addressing risks and engaging with stakeholders.
Streamline Onboarding Processes: Implement chatbots like Leena AI or Talla that guide employees through onboarding steps during organisational changes. These tools can answer FAQs, provide training schedules, and even send reminders for task completion.
Enable Self-Service Options: Deploy virtual assistants (e.g., Google Dialogflow) that allow employees to access FAQs about new policies, systems, or procedures without waiting for human support.
💡 Pro Tip: When automating tasks, ensure transparency with employees about what is being automated and why. This helps build trust and prevents fears about job security.
6. Foster Workforce Readiness Through Real-Time Feedback Loops
Continuous feedback is essential during transformations—it helps leaders course-correct quickly while keeping employees informed and engaged. However, traditional feedback mechanisms like annual surveys are often too slow to capture real-time issues. AI tools enable organisations to collect and analyse feedback at scale in real time, creating a more agile approach to managing change fatigue.
How to Apply This:
Deploy Pulse Surveys: Platforms like Culture Amp or Peakon use AI algorithms to analyse survey responses instantly and provide actionable insights. For example:
If a pulse survey reveals low morale in a specific department, leaders can intervene immediately with targeted support or communication efforts.
Monitor Collaboration Metrics: Tools such as Slack Insights or Microsoft Teams Analytics track engagement levels within collaboration platforms. If metrics show a drop in activity or participation, it could indicate disengagement or confusion about transformation goals.
Close Feedback Loops Quickly: Use automated workflows triggered by feedback results. For instance:
If employees flag a lack of clarity about a new system rollout, an automated workflow can schedule additional training sessions or send out simplified guides.
📌 Key Insight: Real-time feedback not only identifies issues early but also demonstrates that leadership values employee input—a critical factor in building trust during change.
7. Leverage AI for Change Impact Assessments
One of the most overlooked aspects of managing change is understanding its cumulative impact across the organisation. Many organisations fail to consider how multiple simultaneous changes affect employee capacity and morale. AI tools can help conduct comprehensive change impact assessments by analysing data across projects, teams, and timelines.
How to Apply This:
Map Change Dependencies: Use AI-powered tools like The Change Compass to visualise how different initiatives overlap and interact. For example:
If two major IT upgrades are scheduled for the same quarter, the tool can flag potential conflicts and recommend rescheduling one of them as well as locating the right timing.
It could also be a series of smaller initiatives all being executed at the same time, again leading to the risk that key messages may not be absorbed by impacted employees
Analyse Historical Data: Predict how similar changes have impacted the organisation in the past using predictive analytics tools mentioned previously.
Simulate Scenarios: Run simulations to test different implementation strategies (e.g., phased vs big-bang rollouts) and predict their impact on employee workload and engagement.
🔍 Example: A global logistics company used AI-driven impact assessments to identify that rolling out a new CRM system during peak holiday season would overwhelm its sales team. By postponing the rollout until after the busy period, they avoided unnecessary stress and ensured smoother adoption.
8. Enhance Employee Engagement Through Gamification
AI can make transformation initiatives more engaging by incorporating gamification elements into training programs, communication strategies, and performance tracking systems. Gamification taps into employees’ intrinsic motivation by rewarding participation and progress—making change feel less daunting and more rewarding.
How to Apply This:
Gamify Training Programs: Use platforms like Kahoot! or Quizizz to create interactive quizzes and challenges related to new systems or processes being introduced.
Incentivise Participation: Offer digital badges, points, or leaderboards for completing key milestones in transformation initiatives (e.g., attending training sessions or adopting new tools).
Track Progress Automatically: AI-powered LMS platforms like Degreed can track employee progress in real time and provide personalised recommendations for next steps.
🎯 Action Step: Pair gamification efforts with tangible rewards such as gift cards or extra leave days for top performers.
💡 Pro Tip: Ensure gamification efforts are inclusive—design challenges that appeal to all personality types, not just competitive individuals.
9. Use AI for Personalised Coaching
AI-powered coaching platforms are revolutionising how organisations support their employees during transformations. These tools provide personalised guidance tailored to each employee’s role, skills, and career aspirations—helping them navigate change more effectively while feeling supported.
How to Apply This:
Deploy Virtual Coaches: Platforms like BetterUp or CoachHub use AI algorithms to match employees with virtual coaches who provide tailored advice on navigating change.
Provide Role-Specific Guidance: Use AI tools that offer customised recommendations based on an employee’s role within the organisation. For instance:
A sales representative might receive tips on leveraging new CRM features, while a manager gets guidance on leading their team through uncertainty.
Monitor Coaching Effectiveness: Track metrics such as employee satisfaction scores or performance improvements after coaching sessions.
🔍 Example: A tech company implementing agile methodologies used an AI coaching platform to train managers on fostering collaboration within cross-functional teams. The result was a smoother transition with fewer bottlenecks.
10. Integrate Change Management into Your Digital Transformation Strategy
AI should not operate in isolation; it must be embedded into your broader change management framework for maximum impact. This includes aligning AI initiatives with existing change management methodologies.
How to Apply This:
Centralise Data Sources: Use platforms like The Change Compass to consolidate insights from various data sources into a single dashboard, think data sources such as system usage, performance KPIs and employee survey results. It also enables you to capture your change data and deliverables according to your preferred methodology and populate data with generative AI.
Align Metrics Across Teams: Ensure KPIs related to change readiness (e.g., adoption rates) are consistent across departments.
Train Leaders on AI Capabilities: Equip managers with basic knowledge of how AI works so they can champion its use within their teams.
🌟 Final Thought: The integration of AI into change management isn’t just about technology—it’s about creating a culture of adaptability where data-driven decisions empower people at every level of the organisation.
Call-to-Action: Start Your Journey Towards Smarter Change Management
The challenges of large-scale transformations don’t have to result in burnout or disengagement when you harness the power of artificial intelligence effectively. Begin by assessing your current change portfolio environment—what tools are you already using? Where are the gaps? Then explore how AI solutions can fill those gaps while aligning with your organisational goals.
Ready to take the next step? Dive deeper into strategies for agile change portfolio management here and discover how data-driven insights can revolutionise your approach today!
Artificial Intelligence (AI) is no longer a futuristic concept—it is here, transforming industries and reshaping how organisations operate. For change and transformation professionals, AI presents both opportunities and challenges. While it automates repetitive tasks and provides advanced insights, it also demands a shift in mindset, skillsets, and approaches to managing change.
Change and transformation professionals must now navigate a world where AI not only augments their work but also redefines their roles. Here we explore how AI is impacting the field of change management, what parts of the work will shift and evolve, and how change manager can adapt to thrive in this new era.
The Impact of AI on Change Management
AI is revolutionizing change management by automating processes, providing predictive analytics, and enabling personalization at scale. It allows organisations to identify resistance early, tailor interventions for specific stakeholders, and measure the effectiveness of change initiatives in real time. However, these advancements also mean that the traditional ways of working are evolving rapidly.
For change professionals, this transformation requires a deeper understanding of how to integrate AI into their processes while maintaining a human-centered approach. Beyond the usual AI use for pictures and communications, let’s break down the key areas where AI is making an impact:
1. Automation of Repetitive Tasks
One of the most immediate benefits of AI in change management is its ability to automate repetitive and time-consuming tasks. For example:
– Stakeholder Analysis: AI tools can analyse large datasets to identify key stakeholders, map their influence networks, and predict their responses to change.
– Communication: Generative AI can draft personalized emails, newsletters, or FAQs tailored to different stakeholder groups.
– Reporting: Automated dashboards powered by AI can provide real-time updates on adoption rates, engagement levels, and other key metrics.
This automation frees up time for change professionals to focus on higher-value activities such as strategy development and stakeholder engagement.
2. Data-Driven Insights
AI enables access to advanced data analytics that were previously unavailable or too complex to process manually. Predictive analytics tools can forecast employee resistance, identify potential risks, and recommend targeted interventions before problems escalate. For example:
– Sentiment analysis tools can assess employee feedback from surveys or social media platforms to gauge morale and identify concerns.
– Behavioural analytics can track how employees are interacting with new tools or processes, providing insights into adoption patterns.
However, it is worth noting that the more data collected, including historical data, the richer the AI insights will be as it will generate more accurate observations and recommendations.
These insights allow change professionals to move from reactive approaches to proactive strategies based on real-time data.
3. Personalisation at Scale
AI empowers organisations to deliver highly personalised experiences for employees during times of change. Instead of one-size-fits-all approaches, AI tools can segment stakeholders based on their preferences, behaviours, or roles and tailor communication or training accordingly. For instance:
– Adaptive learning platforms can create customised training modules for employees based on their skill gaps.
– Chatbots powered by natural language processing (NLP) can answer individual questions about new systems or processes in real time. With the ease of designing and implementing chatbots nowadays, designing a chatbot for implementing a change initiative is absolutely feasible.
Personalisation improves engagement and reduces resistance by addressing the unique needs of each individual or group.
What Will Decrease in the Work of Change manager?
While AI enhances many aspects of change management, it also reduces the need for certain traditional tasks:
1. Routine Communication
AI tools like chatbots or automated email systems can handle routine communication tasks such as sending updates or answering frequently asked questions (FAQs). This reduces the time spent on drafting generic messages or managing basic inquiries.
2. Manual Stakeholder Analysis
In the past, stakeholder analysis often involved manual mapping exercises based on interviews or surveys. With AI-driven tools that analyse organisational networks and sentiment data, this process becomes faster and more accurate.
3. Administrative Reporting
Manual reporting on metrics like adoption rates or training completion will decrease as AI-powered dashboards provide real-time analytics. Change managers will no longer need to spend hours compiling reports; instead, they can focus on interpreting the data and making strategic decisions.
What Will Increase in the Work of Change manager?
While some tasks decrease with AI integration, others become more critical:
1. Strategic Oversight
With AI handling operational tasks, change manager will need to focus more on strategic oversight. This includes ensuring that AI tools align with organisational goals and values while driving meaningful outcomes.
For example:
– Interpreting data insights provided by AI tools to refine strategies. With the range and volume of insights generated, the change professional needs to be focused on what parts add value and where the attention should be placed
– Ensuring that predictive analytics align with broader business objectives. AI generated data will need to be evaluated together with other sources of data. There may be data points that are not captured by AI, thereby impacting the predictive recommendations.
– Balancing short-term efficiency gains with long-term cultural shifts. The use of AI must align with the appetite of the organisation and what the people are capable of adopting. The change professional needs to careful assess the extent of the shifts required and adjust the AI usage and resulting business impacts accordingly. Is the organisation actual ready for the operating model changes inflicted by AI? Work efficiency aside, what will the organisation do with excess people capacity? And will it be ready to implement various business efficiency changes resulting from AI? This is a core question that leaders need to answer.
2. Ethical Governance
As organisations increasingly rely on AI for decision-making, ethical oversight becomes a core responsibility for change manager. Whilst this may not be considered as the ‘core job’ for change managers, it is important to incorporate this as a key part of monitoring of employee feedback and adoption management. They must ensure that:
– AI systems are free from biases that could harm employees or stakeholders. If biases are found, that there is action plans to address these
– Data privacy is maintained while using analytics tools. This will affect which tool is chosen and mode is utilised.
– Transparency is upheld in how decisions are influenced by AI. For example, does the AI recommendation reference data points specifically to support transparent tracing.
Building trust in AI systems among employees will be a critical part of this role.
3. Human-Centered Leadership
Despite its capabilities, AI cannot replace human empathy or emotional intelligence—qualities essential for navigating complex organisational changes. Change manager must:
– Act as empathetic leaders who address fears about job displacement or role changes due to automation.
– Foster trust in both leadership and technology by maintaining open lines of communication.
– Focus on building resilient teams that embrace adaptability and continuous learning.
Mindset Shifts Required for Change manager
To succeed in an AI-driven environment, change manager must adopt new mindsets:
1. From Control to Collaboration: Embrace collaboration with AI as a partner rather than viewing it as a tool to control outcomes.
2. From Static Expertise to Lifelong Learning: Continuously update skills related to data literacy, digital transformation strategies, and emerging technologies.
3. From Reactive Risk Management to Proactive Adaptation: Use predictive insights from AI tools to anticipate challenges rather than reacting after they occur.
4. From Fear of Displacement to Trust in Co-Creation: Recognize that AI enhances human capabilities rather than replacing them entirely.
These mindset shifts will enable change manager to lead effectively in an era where technology plays an increasingly central role in organisational transformation.
Immediate Use Cases for Change managers to Leverage AI
As AI continues to transform the workplace, change managers must adopt practical strategies that integrate AI into their workflows while maintaining a human-centered approach. Below are actionable steps to help change professionals thrive in the AI-driven future.
1. Use AI to Enhance Stakeholder Engagement
AI provides powerful tools to analyze and engage stakeholders more effectively. Change manager can leverage these capabilities to build stronger relationships and drive alignment across the organisation.
Actionable Steps:
– Leverage Sentiment Analysis Tools: Use AI-powered sentiment analysis to gauge stakeholder attitudes and concerns from surveys, emails, or social media. This allows you to identify resistance early and address it proactively.
– Develop Personalized Communication Plans: Use AI tools to segment stakeholders based on their roles, preferences, or behaviours. Tailor communication strategies for each group, ensuring messages resonate with their specific needs.
– Deploy Chatbots for Real-Time Support: Implement AI chatbots to provide stakeholders with instant access to information about change initiatives. This reduces the burden on change teams while improving responsiveness.
Example in Practice:
A global organisation undergoing a digital transformation may use AI sentiment analysis to monitor employee feedback during the rollout of a new system. By identifying teams with low engagement scores, the change team can intervene early with targeted workshops and one-on-one coaching sessions.
2. Integrate Predictive Analytics into Change Planning
Predictive analytics is one of the most transformative aspects of AI for change management. It allows change manager to anticipate challenges, forecast outcomes, and refine strategies based on data-driven insights.
Actionable Steps:
– Identify Potential Resistance Hotspots: Use predictive models to analyse historical data and identify departments or teams likely to resist upcoming changes.
– Forecast Adoption Rates: Leverage analytics tools to predict how quickly employees will adopt new processes or technologies. Adjust timelines and training plans accordingly.
– Optimise Resource Allocation: Use AI insights to determine where resources (e.g., training budgets or change champions) will have the greatest impact.
Example in Practice:
A financial services firm used predictive analytics during a merger to identify which regions were most likely to experience resistance based on past organisational changes. This allowed the team to deploy additional resources in those areas, reducing delays and improving overall adoption rates.
3. Focus on Building Trust in AI
As AI becomes more integrated into organisational processes, trust becomes a critical factor for success. Employees and stakeholders may feel uncertain about how decisions are being made or fear that their roles will be replaced by automation.
Actionable Steps:
– Be Transparent About AI’s Role: Clearly communicate how AI is being used in decision-making processes and emphasize that it is a tool to support—not replace—human judgment.
– Address Ethical Concerns: Ensure that AI systems are free from bias and comply with data privacy regulations. Regularly audit AI tools for fairness and accuracy.
– Foster Open Dialogue: Create forums where employees can ask questions about AI implementations, share concerns, and provide feedback.
Example in Practice:
A healthcare organisation introduced AI-powered scheduling software but faced resistance from staff who feared losing control over their work schedules. By hosting workshops that explained how the system worked and allowing employees to provide input into its configuration, the organisation built trust and improved adoption rates.
4. Lead with Emotional Intelligence
While AI automates many tasks, it cannot replace the human touch required for effective leadership during times of change. Change managers must double down on emotional intelligence (EI) to complement AI’s capabilities. It may not be that employee emotional reactions and nuances are fully captured by AI, so care need to be taken in this regard.
Actionable Steps:
– Empathize with Employee Concerns: Actively listen to employees’ fears about job displacement or role changes caused by automation.
– Foster a Growth Mindset: Encourage teams to see AI as an opportunity for personal and professional development rather than a threat.
Example in Practice:
During an automation initiative at a manufacturing company, senior leaders held town halls where they acknowledged employees’ concerns about job security but emphasized opportunities for upskilling. This approach helped reduce anxiety and fostered a more positive attitude toward the changes.
5. Redefine Training Strategies
AI is transforming how organisations approach employee training during times of change. Traditional one-size-fits-all training programs are being replaced by adaptive learning platforms that deliver personalized content based on individual needs.
Actionable Steps:
– Implement Adaptive Learning Platforms: Use AI-powered tools that assess employees’ existing skills and create customized learning paths.
– Focus on Digital Literacy: Ensure employees understand how to use new AI tools effectively as part of their daily workflows.
– Provide Continuous Learning Opportunities: Move beyond one-time training sessions by offering ongoing development programs that evolve with organisational needs.
Example in Practice:
A retail company introduced an adaptive learning platform during its e-commerce transformation. Employees received tailored training modules based on their roles and skill gaps, resulting in faster adoption of new systems and improved performance metrics.
6. Balance Efficiency with Culture implications
AI brings remarkable efficiency gains, but change managers must ensure that these do not come at the expense of organisational culture. Careful analysis should be done to understand potential impacts of AI on the cultural and behavioural norms of the organisation before proceeding.
Actionable Steps:
– Prioritize Culture Over Speed: While AI can accelerate processes, take time to ensure that cultural alignment is not overlooked during rapid transformations. What behaviours need to be there to support the adoption and implementation and how are these reinforced?
– Balancing cultural norms and behaviours: Are there particular rituals and behaviours that are critical to the culture of the organisation that AI should not try and replace? Are there practices that should remain despite AI gains in efficiency due to cultural goals?
– Measure Success Holistically: Go beyond efficiency metrics by assessing employee engagement, morale, and overall satisfaction during changes.
Example in Practice:
A tech company undergoing rapid scaling used AI tools for project management but ensured that team leaders continued holding regular one-on-one meetings with employees. This balance preserved trust and engagement during a period of significant growth.
The Evolving Role of Change managers
As organisations embrace AI, the role of change manager is shifting from operational execution to strategic leadership. Key areas of focus include:
1. Strategic Visioning: Aligning AI-driven initiatives with long-term organisational goals.
2. Ethical Oversight: Ensuring responsible use of AI while maintaining transparency and trust.
3. Proactive Adaptation: Using predictive insights from AI tools to stay ahead of challenges.
4. Human-Centered Leadership: Balancing technological advancements with empathy and emotional intelligence.
Change manager who embrace these shifts will not only remain relevant but also play a pivotal role in shaping the future of work.
The proliferation of AI is transforming every facet of change management—from automating routine tasks to enabling data-driven decision-making and personalized engagement strategies. For change manager, this evolution presents an opportunity to elevate their roles by focusing on strategic oversight, ethical governance, trust-building, and human-centered leadership.
By adopting practical strategies such as leveraging predictive analytics, redefining training approaches, and leading with emotional intelligence, experienced professionals can harness the power of AI while maintaining a people-first approach. The future of change management lies not in replacing humans with technology but in combining the strengths of both for greater impact. As we move further into this era of transformation, change manager who adapt their mindsets, skillsets, and approaches will be at the forefront of driving successful organisational change—one that balances innovation with humanity.
Air traffic control is one of the most sophisticated and high-stakes management systems in the world. Ensuring the safety of thousands of flights daily requires rigorous coordination, precise timing, and a structured yet adaptable approach. When failures occur, they often result in catastrophic consequences, as seen in the tragic January 2025 midair collision between an army helicopter and a passenger jet in Washington, D.C. airspace.
Think about the last time you took a flight. You probably didn’t worry about how the pilot knew where to go, how to land safely, or how to avoid other planes in the sky. That’s because air traffic control is a well-oiled machine, built on a foundation of real-time data, clear protocols, and experienced professionals making split-second decisions. Now, imagine if air traffic controllers had to work with outdated information, or if pilots had to rely on intuition rather than hard facts. Chaos, right?
The same principles that apply to managing air traffic also hold valuable lessons for change and transformation management within organisations. Large-scale transformations involve multiple initiatives running in parallel, conflicting priorities, and significant risks. Without a structured, centralised approach, organisations risk failure, reduced value realisation, and employee fatigue.
The same logic applies to organisational change and transformation. Leaders are often trying to land multiple initiatives at once, each with its own trajectory, speed, and impact. Without real-time, accurate data, it’s all too easy for change initiatives to collide, stall, or overwhelm employees. Just as the aviation industry depends on continuous data updates to prevent disasters, businesses must embrace data-driven decision-making to ensure their transformation efforts succeed.
Here we’ll explore what air traffic control can teach us about using data effectively in change management. If you’ve ever felt like your organisation’s transformation efforts are flying blind, chaotic and uncoordinated, this one’s for you.
Lesson 1: The Danger of Overloading Critical Roles
The D.C. Midair Collision: A Case of Role Overload
In January 2025, a tragic midair collision occurred in Washington, D.C. airspace between an army helicopter and a passenger jet, claiming 67 lives. Investigations revealed multiple contributing factors, including inadequate pilot training, fatigue, insufficient maintenance, and ignored safety protocols. This incident underscored the dangers of overstretched resources, outdated processes, and poor data visibility—lessons that extend beyond aviation and into how organisations manage complex, high-stakes operations like change and transformation.
Additionally, the air traffic controller on duty was handling both helicopter and airplane traffic simultaneously, leading to a critical lapse in coordination. This split focus contributed to poor coordination and a lack of real-time situational awareness, ultimately leading to disaster. This is aligned with findings from various research that providing adequate resources is important in driving change and transformation.
Parallels in Change and Transformation Management
Organisations often suffer from similar overload issues when managing change. Many initiatives—ranging from business-as-usual (BAU) efforts to large-scale transformations—compete for attention, resources, and stakeholder engagement. Without a structured approach, teams end up working in silos, unaware of competing priorities or overlapping impacts.
There are some who argue that change is the new norm, so employees just need to get on the program and learn to adapt. It may be easy to say this, but successful organisations have learnt how to do this, versus ignoring the issue. After all, managing capacity and resources is a normal part of any effective operations management and strategy execution. Within a change context, the effects are just more pronounced given the timelines and the need to balance both business-as-usual and changes.
Key Takeaways:
Centralised Oversight: Organisations need a structured governance model—whether through a Transformation Office, PMO, or Change Centre of Excellence—to track all initiatives and prevent “collisions.”
Clear Role Definition: Initiative owners and sponsors should have a clear understanding of their responsibilities, engagement processes, and decision-making frameworks.
Avoiding Initiative Overload: Employees experience “change fatigue” when multiple transformations run concurrently without proper coordination. Leaders must balance initiative rollout to ensure sustainable adoption.
Lesson 2: Providing Initiative Owners with Data-Driven Decision Autonomy
The UPS ‘Continuous Descent Arrivals’ System
UPS has been testing a data-driven approach to landings called ‘Continuous Descent Arrivals’ (source: Wall Street Journal article: Managing Air Traffic Control). Instead of relying solely on air traffic controllers to direct landing schedules, pilots have access to a full dashboard of real-time data, allowing them to determine their optimal landing times while still following a structured governance protocol. While CDA is effective during light traffic conditions, implementing it during heavy traffic poses technical challenges. Air traffic controllers must ensure safe separation between aircraft while optimising descent paths.
Applying This to Agile Change Management
In agile organisations, multiple initiatives are constantly iterating, requiring a balance between flexibility and coordination. Rather than centralised bottleneck approvals, initiative owners should be empowered to make informed, autonomous decisions—provided they follow structured governance (and when there is less risk of multiple releases and impacts on the business).
Key Takeaways:
Real-Time Data Sharing: Just as pilots rely on up-to-date flight data, organisations must have a transparent system where initiative owners can see enterprise-wide transformation impacts and adjust accordingly.
Governance Without Bureaucracy: Pre-set governance protocols should allow for self-service decision-making without stifling agility.
Last-Minute Adjustments with Predictability: Agile initiatives should have the flexibility to adjust their release schedules as long as they adhere to predefined impact management processes.
Lesson 3: Resourcing Air Traffic Control for Organisational Change
Lack of Air Traffic Controllers: A Root Cause of the D.C. Accident
The D.C. accident highlighted that understaffing was a critical factor. Insufficient air traffic controllers led to delayed decision-making and unsafe airspace conditions.
The Importance of Resource Allocation in Change and Transformation
Many organisations lack a dedicated team overseeing enterprise-wide change. Instead, initiatives operate independently, often leading to inefficiencies, redundancies, and conflicts. According to McKinsey, companies that effectively prioritise and allocate resources to transformation initiatives can generate 40% more value compared to their peers.
Key Takeaways:
Dedicated Transformation Governance Teams: Whether in the form of a PMO, Transformation Office, or Change Centre of Excellence, a central function should be responsible for initiative alignment.
Prioritisation Frameworks: Not all initiatives should receive equal attention. Organisations must establish structured prioritisation mechanisms based on value, risk, and strategic alignment.
Investment in Change Capacity: Just as air traffic controllers are indispensable to aviation safety, organisations must invest in skilled change professionals to ensure seamless initiative execution.
Lesson 4: Proactive Risk Management to Prevent Initiative Collisions
The Risk of Unchecked Initiative Timelines
Just as midair collisions can occur due to inadequate tracking of aircraft positions, organisational change initiatives can “crash” when timelines and impacts are not actively managed. Without a real-time view of concurrent changes, organisations risk:
Conflicting Business Priorities: Competing transformations may pull resources in different directions, leading to delays and reduced impact.
Change Saturation: Employees struggle to absorb too many changes at once, leading to disengagement and lower adoption.
Operational Disruptions: Poorly sequenced initiatives can create unintended consequences, disrupting critical business functions.
Establishing a Proactive “Air Traffic Control” for Change
Enterprise Change Heatmaps: Organisations should maintain a real-time dashboard of ongoing and upcoming changes to anticipate and mitigate risks.
Stakeholder Impact Assessments: Before launching initiatives, leaders must assess cumulative impacts on employees and customers.
Strategic Sequencing: Similar to how air traffic controllers ensure safe landing schedules, organisations must deliberately pace their change initiatives.
The Role of Data in Change and Transformation: Lessons from Air Traffic Control
You Need a Single Source of Truth—No More Guesswork
Aviation Example: The Power of Integrated Data Systems
In aviation, pilots and controllers don’t work off scattered spreadsheets or conflicting reports. They use a unified system that integrates radar, satellite tracking, and aircraft GPS, providing a single, comprehensive view of air traffic. With this system, pilots and controllers can see exactly where each aircraft is and make informed decisions to keep everyone safe.
Application in Change Management: Why Fragmented Data is a Recipe for Disaster
Now, compare this to how many organisations manage change. Different business units track initiatives in separate spreadsheets, using inconsistent reporting standards. Transformation offices, HR, finance, and IT often operate in silos, each with their own version of the truth. When leaders don’t have a clear, real-time picture of what’s happening across the organisation, it’s like trying to land a plane in thick fog—without instruments.
Key Takeaways:
Create a Centralised Change Management Platform: Just like air traffic control relies on a single system, organisations need a centralised platform where all change initiatives are tracked in real time.
Standardise Data Collection and Reporting: Everyone involved in change initiatives should follow the same data standards to ensure consistency and accuracy.
Increase Visibility Across Business Units: Leaders need an enterprise-wide view of all change efforts to avoid conflicts and align priorities.
Real-Time Data Enables Agile, Confident Decision-Making
UPS has a fascinating system for managing landings, known as ‘Continuous Descent Arrivals.’ Instead of waiting for air traffic controllers to dictate their landing time, pilots receive real-time data about their approach, runway conditions, and surrounding traffic. This allows them to determine the best landing time themselves—within a structured framework. The result? More efficient landings, less fuel waste, and greater overall safety.
Application in Change Management: The Danger of Outdated Reports
Too often, business leaders make transformation decisions based on data that’s weeks—or even months—old. By the time they realise a problem, the initiative has already veered off course. When leaders lack real-time data, they either act too late or overcorrect, causing further disruptions.
Key Takeaways:
Use Live Dashboards for Initiative Management: Just as pilots rely on real-time flight data, change leaders should have constantly updated dashboards showing initiative progress, risks, and dependencies.
Empower Initiative Owners with Data-Driven Autonomy: When given up-to-date information, initiative owners can make faster, smarter adjustments—without waiting for top-down approvals.
Leverage Predictive Analytics to Anticipate Challenges: AI-driven insights can flag potential risks, such as change saturation or conflicting priorities, before they become full-blown issues.
Modern aircraft are equipped with automatic dependent surveillance-broadcast (ADS-B) systems, which allow them to communicate real-time flight data with each other. If two planes are on a collision course, these systems warn pilots, giving them time to adjust. It’s a proactive approach to risk management—problems are detected and resolved before they escalate.
Application in Change Management: Avoiding Crashes Between Initiatives
In organisations, multiple change initiatives often roll out simultaneously, each demanding employee attention, resources, and operational bandwidth. Without real-time risk monitoring, it’s easy to overwhelm employees or create operational bottlenecks. Many organisations don’t realise there’s an issue until productivity starts dropping or employees push back against the sheer volume of change.
Key Takeaways:
Invest in Impact Assessment Tools: Before launching an initiative, leaders should evaluate its potential impact on employees and the business.
Run Scenario Planning Exercises: Like pilots in flight simulators, organisations should model different change scenarios to prepare for potential challenges.
Set Up Early Warning Systems: AI-driven analytics can detect overlapping initiatives, allowing leaders to intervene before issues arise.
The High Cost of Inaccurate or Delayed Data
Aviation Example: The D.C. Midair Collision
The tragic January 2025 midair collision in Washington, D.C. was, in part, the result of outdated and incomplete data. A single air traffic controller was responsible for both helicopter and airplane traffic, leading to a dangerous lapse in coordination. Miscommunication about airspace restrictions only made matters worse, resulting in an avoidable catastrophe.
Poor Data Leads to Costly Mistakes
The corporate equivalent of this is when transformation teams work with old or incomplete data. Decisions based on last quarter’s reports can lead to wasted resources, poorly sequenced initiatives, and employee burnout. The consequences might not be as immediately tragic as an aviation disaster, but the financial, momentum and cultural costs can be devastating.
Key Takeaways:
Prioritise Frequent Data Updates: Change leaders must ensure initiative data is refreshed regularly to reflect real-time realities.
Collaborate Across Functions to Maintain Accuracy: Transformation leaders, HR, finance, and IT should work together to ensure all change impact data is reliable.
Automate Reporting Where Possible: AI and automation can reduce human error and provide real-time insights without manual effort.
Balancing Automation with Human Judgment
Aviation Example: Autopilot vs. Pilot Oversight
While modern planes rely heavily on autopilot, pilots are still in control. They use automation as a support system, but ultimately, human judgment is the final safeguard. It’s the perfect balance—automation enhances efficiency, while human oversight ensures safety.
Some leaders may find the process of collecting and analyzing data cumbersome, time-consuming, and even unnecessary—especially when they’re focused on quick execution. Gathering accurate, real-time data requires investment in tools, training, and disciplined processes, which can feel like an administrative burden rather than a value driver.
However, the benefits far outweigh the effort. A well-structured data system provides clarity on initiative progress, prevents conflicting priorities, enhances decision-making, and ensures resources are allocated effectively. Without it, organisations risk initiative overload, employee burnout, wasted budgets, and ultimately, failed transformations. Just like in aviation, where poor data can lead to fatal accidents, a lack of real-time insights in change management can result in costly missteps that derail business success.
Moreover, having an integrated process whereby data regularly feeds into decision making, as a normal business-as-usual process, builds the overall capability of the organisation to be a lot more agile and be able to change with confidence.
Navigating Change with Data-Driven Precision
Aviation has shown us what happens when decision-makers lack real-time, accurate data—mistakes happen, and consequences can be severe. In organisational change, the same principles apply. By embracing real-time data, predictive analytics, and structured governance, companies can navigate change more effectively, preventing initiative overload, reducing resistance, and maximising impact.
Ultimately, the goal is simple: Ensure your change initiatives don’t crash and burn. And just like in aviation, data is the key to a smooth landing.
If you would like to chat more about how to utilise a digital/AI solution that will equip you will insightful data to make critical business decisions in your air traffic control of your changes, reach out to us here.
Successful transformation is not just about having a clear strategy, the right technology, or a strong leadership team—it is about managing organisational energy effectively. Like a marathon, transformation requires a well-paced approach, allowing for the right breathing space at key milestones. Without careful attention to energy levels, organisations risk burnout, disengagement, and failure to sustain long-term change.
Understanding Organisational Energy
Organisational energy is the collective capacity of employees to take action, drive change, and sustain momentum. It encompasses physical, emotional, and cognitive dimensions, each playing a critical role in how teams navigate transformation. Unlike resources such as time and budget, energy is dynamic—it can be depleted through excessive demands or replenished through strategic interventions.
The Marathon Mindset: Pacing and Breathing Spaces
Transformation is a long journey, not a sprint. Like seasoned marathon runners, organisations must be intentional about pacing and ensuring adequate recovery points along the way. Leaders often push for rapid results, but sustained transformation requires:
Phased Implementation: Breaking down transformation into manageable phases with defined milestones.
Strategic Pauses: Allowing teams to absorb changes, reflect on progress, and recalibrate before moving to the next stage.
Energy Checks: Regularly assessing engagement levels, stress indicators, and feedback to adjust the pace accordingly.
Neglecting these aspects leads to fatigue, resistance, and disengagement—ultimately derailing transformation efforts.
Awareness of Existing Capabilities and Change History
Before embarking on a transformation journey, organisations must understand their baseline. Awareness of existing capabilities, ways of working, and historical transformation experiences provides predictive indicators of how change should be approached.
Key Considerations:
Past Change Successes and Failures: What has worked and what hasn’t? Understanding past patterns helps anticipate potential resistance or enablers.
Current Workload and Fatigue Levels: Are employees already stretched with existing initiatives? Overloading teams will compromise focus and execution quality.
Organisational Culture: Some cultures thrive on rapid change, while others require gradual adoption. Aligning transformation efforts with cultural realities is critical.
By assessing these factors, leaders can tailor transformation strategies to fit the organisation’s energy levels and capacity.
Building Organisational Stamina: Start Small, Scale Up
Just as athletes build endurance through progressive training, organisations must strengthen their transformation muscle over time. This means introducing smaller changes first to test resilience and capability before scaling up to more complex shifts.
How to Build Organisational Stamina:
Start with Pilot Initiatives: Test new ways of working in controlled environments before expanding.
Gradually Increase Complexity: Move from small process improvements to larger-scale changes, ensuring teams adapt successfully at each stage.
Celebrate Early Wins: Recognising progress builds confidence and motivation to tackle bigger challenges.
Provide Learning Opportunities: Equip teams with skills and tools that enhance adaptability and readiness for change.
Leaders who adopt this progressive approach foster a resilient workforce that can sustain transformation efforts over time.
Teams with good change leaders or those teams with significant experience with change tend to be more able to work with greater volumes of change as well as greater complexity of change. With each change initiative, with the right structure, routines (including retro), the team’s capability can be built to be ready for larger, more complex transformations.
Balancing Focus and Intensity
Attention is a finite resource. When teams are bombarded with multiple initiatives, priorities become diluted, and execution suffers. Managing focus effectively is essential to maintaining high performance during transformation.
Strategies for Maintaining Focus:
Limit Concurrent Initiatives: Prioritise the most critical changes and sequence others to avoid overload.
Establish Clear Priorities: Ensure alignment across leadership to prevent conflicting demands on teams.
Monitor Workload and Stress Levels: Pay close attention to employee well-being and adjust intensity as needed.
Encourage Deep Work: Create space for teams to focus without constant distractions or shifting priorities.
When focus is scattered, transformation efforts lose momentum. By managing cognitive load, leaders enable employees to fully engage with and execute changes effectively.
The Importance of a Clear Plan
While agile methodologies emphasise adaptability, having a structured plan provides essential clarity for employees navigating complex change. Transformation without a roadmap leads to uncertainty, anxiety, and resistance. This does not necessarily mean that plans are locked in stone and cannot be changed. In contrast to this, having a plan provides a frame of reference, and expectations can be set that details including timeline may shift but that the high level approach remains the same.
Why a Clear Plan Matters:
Provides Direction: Employees need to know where the organisation is headed and how they fit into the journey.
Reduces Uncertainty: Even if adjustments are made, a baseline plan offers reassurance and stability.
Enhances Engagement: When people understand the “why” and “how” of transformation, they are more likely to commit.
Prepares for Change: Last-minute changes create confusion and stress—early planning allows for smoother transitions.
Balancing Planning with Agility
While plans must be flexible, abandoning structure altogether creates chaos. Leaders should:
Communicate a High-Level Roadmap: Outline key phases and milestones without overloading with unnecessary detail.
Adapt Plans Responsively: Incorporate feedback and lessons learned, adjusting course without losing sight of long-term goals.
Engage Employees in Planning: Co-creation fosters ownership and reduces resistance.
A well-structured transformation plan provides clarity and confidence, making it easier for teams to adapt and sustain change.
To ensure the optimal management of organisational energy, measurement is essential. Organisations need clear yardsticks to assess energy levels, performance, and transformation progress, allowing leaders to make informed adjustments when needed. Without measurement, it is impossible to determine whether teams are operating at an optimal pace or experiencing fatigue and disengagement.
Key Metrics to Track:
Change Impact Data: Understanding the magnitude of transformation on various teams helps adjust implementation approaches.
Balance Energy Demand and Supply: Leaders should prioritize work strategically, focusing on high-impact initiatives while minimizing unnecessary demands. Simultaneously, they should inspire teams by articulating a compelling vision that connects the various dots across changes
Change Readiness Assessments: Gauging employees’ preparedness for change ensures the right support mechanisms are in place.
Sentiment Analysis: Regular pulse surveys and feedback loops help identify resistance, concerns, and engagement levels.
Performance Metrics: Tracking productivity, efficiency, and key deliverables helps align transformation with business outcomes.
Adoption Rates: Measuring how well new processes, tools, or ways of working are being integrated ensures long-term sustainability.
By continuously monitoring these indicators, leaders can fine-tune transformation efforts, ensuring that momentum is sustained while preventing burnout and resistance.
Leading with Energy Management
The success of any transformation effort hinges on how well organisational energy is managed. Leaders must act as stewards of energy—pacing initiatives appropriately, building stamina, maintaining focus, and providing clear direction.
By treating transformation like a marathon—strategically balancing intensity with recovery, testing capabilities before scaling, and ensuring clarity—organisations can sustain momentum and achieve lasting success. Managing organisational energy is not just a leadership responsibility; it is the foundation for thriving in an ever-evolving business landscape.
For many organisations, transformation has become a strategic necessity. However, the success rate of large-scale transformation efforts remains low. There are various arguments about the actual percentage of success for transformation. Consulting firms often quote 30% as the standard, whilst others argue it may be up to 50%. There is also the issue of the definition of ‘transformation’ versus other change initiatives. Regardless, the actual level of success, most agree that this level needs to be much higher given the significant capital and resource focus on transformations across organisations. A critical but often overlooked factor? The way change is managed.
Despite the importance of change management, transformation offices and teams may not be taking the right approach. According to Sensei Labs’ 2024 State of Transformation survey, senior leaders in large organisations identified culture and change management as the second most pressing concern. When it comes to budget allocation, change management ranks third out of 10 of budget category expenditure ranking, following technology and consulting/advisory expenditures. Previous survey findings, such as Deloitte’s 2022 report show this expenditure to be even lower.
Note that this State of Transformation survey included over 150 respondents from various industries and largely from large organisations. Respondents were mostly Director and above level of seniority.
So, transformation offices acknowledge change management to be a key issue to be tackled, and a sizable budget is spent on various change support activities. So, what is the issues?
A Narrow Approach to Change
A concerning trend in transformation offices is that most only focus on communications, training, and stakeholder engagement as their primary change management activities. These are necessary components, but they are far from sufficient. Effective transformation requires more than just keeping employees informed and trained—it demands a structured, data-driven approach to managing change impact at scale.
Interestingly, the same Sensei Labs survey found that formal change management roles are largely absent within transformation functions. While many teams include Communications and Human Resources roles, only 14% reported having dedicated change management professionals. This absence may explain why change efforts fail to gain traction—without formalized expertise, the true complexity of change is not adequately addressed.
Another striking gap: only 12% of organisations reported measuring change impact. If change impact isn’t assessed, captured and measured, how can organisations get ready for something they are not exactly clear about at a detailed level? And subsequently how can organisations ensure adoption, sustainability, and business outcomes?
Without the clear understanding of impacts, how people will undergo change is not clear. As a result, organisations may take a ‘pan-all’ generic approach of engaging with groups of impacted functions teams, send lots of communications and put in place training sessions.
Without a precise and tailored approach to impacted stakeholder groups, change interventions may be hit or miss. It is the same as air traffic control in a busy airport. Will you use the same approach to chaperone and assist all planes to land in the same way, regardless if it’s a small chartered jet, a helicopter, a 747, a jumbo jet or a fighter jet? A helicopter doesn’t even need a runway like planes, and a fighter jet cannot land in the same area as a commercial landing zone. So, why would we not take a targeted approach at impacted stakeholder groups, each with its own unique change journey?
Addressing the Gaps in Driving Transformations
To close the gap in transformation success, organisations must rethink their approach to change management. This requires shifting from tactical, activity-based change management to a more strategic, structured, and measurable approach.
A change strategy is critical because it provides a structured, outcome-driven approach that aligns change activities with business objectives, rather than just executing a checklist of tasks. It ensures that change efforts are integrated, sustainable, and adaptive to organisational dynamics, rather than reactive and fragmented. A well-defined strategy considers stakeholder impact, capacity constraints, and potential risks, enabling leaders to make informed decisions that drive adoption and long-term success. Without it, change initiatives risk becoming disjointed efforts that fail to deliver meaningful business value.
Key areas of focus should include:
1. Identifying, Measuring, and Managing Portfolio-Level Change Impacts
Many transformation offices manage multiple concurrent initiatives, but few assess how these changes collectively impact employees, customers, and operations. A robust change portfolio management approach is needed to:
Identify cumulative change impacts across projects
Avoid change fatigue/capacity overload
Prioritize initiatives based on organisational capacity and readiness
To properly assess portfolio-level impacts, organisations must develop frameworks that aggregate data across initiatives. By tracking concurrent and overlapping changes, leaders can identify where resistance may emerge and proactively address it. Portfolio-level visibility also enables executives to make better-informed decisions regarding project prioritization and resource allocation.
Identifying and mapping out impacts is one of the most critical pieces of work to ensure change outcome success. Why? It is because effectively identifying and structuring the change impacts on stakeholders determines the resulting change interventions. If your impact assessment is ineffective, your change interventions will not hit the mark.
This is exactly the same process as a doctor diagnosing the illness. The diagnosis process requires a structured assessment process. With the wrong diagnosis it leads to a wrong treatment plan. The wrong treatment plan will not result in curing the illness.
2. Structured Analysis and Planning
Organisations must integrate structured change planning into transformation execution, including:
Complexity assessments to evaluate the scale and interdependencies of change initiatives
Current-to-future state gap analysis to understand the magnitude of change
Benefit realization planning to link change activities to business outcomes
Transition plans to ensure a smooth shift from current to new ways of working
A structured approach allows organisations to proactively mitigate risks associated with transformation. Complexity assessments, for example, help organisations anticipate challenges in large-scale transformations, enabling leaders to develop targeted interventions. Additionally, linking change initiatives to tangible business outcomes ensures accountability and prevents change initiatives from being seen as purely theoretical exercises.
A doctor does not diagnose the illness based on a generic approach or gutfeel, or worse what others tell him/her to do. The treatment plan is also based on what has found to work through research. The same should also be applied with change analysis and planning.
3. Measuring Change Progress
Change success cannot be managed if it is not measured. Organisations should implement:
Readiness assessments to gauge preparedness before rolling out initiatives
Adoption metrics to track engagement and behavioural shifts post-implementation
Feedback loops to identify resistance points and adjust strategies accordingly
Without clear metrics, organisations struggle to determine whether change initiatives are truly effective. Readiness assessments help gauge the level of preparedness within an organisation before implementation begins, while adoption metrics provide insight into how well employees are embracing new ways of working. Continuous feedback loops allow for real-time course corrections, ensuring that change efforts remain on track.
Using the same doctor-patient analogy, the doctor looks for observable data in order to assess the treatment progress. Modifications may be needed based on verbal patient feedback, observations, examinations, and reactions to medication, etc. Your change metrics should be designed to do the same, to tell you if you are progressing well towards the end state, or not.
4. System-Level Interventions to Drive Adoption
To make change stick, organisations need mechanisms that embed change into everyday operations. Key interventions include:
Establishing Change Champions networks to support peer-led adoption
Creating robust communication and capability support channels, ensuring ongoing guidance and reinforcement
Embedding change metrics into enterprise dashboards to sustain leadership attention and accountability
Change Champions play a crucial role in accelerating adoption. These individuals serve as advocates within their teams, reinforcing key messages and addressing concerns on the ground. Robust communication and support channels, such as digital knowledge repositories and dedicated coaching sessions, help employees navigate the complexities of transformation. Moreover, integrating change metrics into enterprise dashboards ensures sustained leadership focus, preventing transformation initiatives from losing momentum over time.
The Risks of Inadequate Change Management
Organisations that neglect structured change management risk experiencing several common pitfalls:
Missed Business Outcomes: If change is not strategically planned and measured, organisations may fail to realize the intended benefits of transformation efforts. And in fact this may be the most critical outcome.
Employee Resistance: Without proper engagement and support mechanisms, employees are more likely to resist changes, leading to lower adoption rates.
Change Fatigue: When multiple transformations occur simultaneously without proper coordination, employees can become overwhelmed, leading to disengagement.
Increased Costs: Poorly managed change initiatives can lead to costly rework, delays, and productivity losses.
A more intentional approach to change management mitigates these risks, ensuring that transformation efforts drive sustainable, long-term value.
Building a High-Impact Change Management Capability
Transformation offices must evolve their approach to change management by developing a high-impact capability that aligns with enterprise priorities. This involves:
Investing in Change Management Expertise: Hiring or upskilling professionals with deep expertise in change methodologies, behavioural science, and organisational psychology.
Integrating Change Management with Strategy: Embedding change management into the transformation office’s strategic planning and execution processes.
Leveraging AI and Automation: Utilizing AI-driven tools to assess change impact, track adoption trends, and provide data-driven insights.
Cultivating Leadership Engagement: Ensuring senior leaders actively sponsor and advocate for change management efforts.
By institutionalizing these capabilities, transformation offices can enhance their ability to drive large-scale change successfully.
The Way Forward
Transformation leaders must move beyond outdated, activity-driven change management approaches that have resulted in transformation targets being missed and adopt a more structured, and data-informed model around people. By embedding change impact measurement, structured planning, and system-level interventions, transformation offices can significantly improve adoption, minimize resistance, and drive sustained business value.
The challenge is clear: without a fundamental shift in how change is managed, even the most well-funded transformations with full senior leadership support risk failure. It’s time for transformation offices to bridge this critical gap and take a more disciplined, structured approach to change management.
By doing so, organisations will not only improve transformation success rates but also foster a more adaptable and resilient workforce, ensuring long-term competitive advantage in an era of continuous change.
Transformation and change professionals often find themselves in the position of defending the value of change management. Despite the critical role that change management plays in ensuring successful project outcomes, many stakeholders remain sceptical. Some view it as a discretionary cost rather than an essential function. Many change management centres of excellences have faced the axe or at least been downsized.
This scepticism can be exacerbated by comments that dismisses roles such as change managers as unnecessary. In Australia, there are even comments by a politician that positions such as change manager “do nothing to improve the lives of everyday Australians”. The context of this comment was targeting positions related cultural, diversity and inclusions advisors, along the same lines as that driven by Trump in the United States. This has upset a lot of change professionals as you can imagine.
To counter this, Change Management Centres of Excellence (CoEs) must move beyond advocacy and education to proactively demonstrate their tangible value. Let’s explore practical approaches to proving the value of change management, ensuring its sustained recognition and investment.
1. Leverage Empirical Research to Support Your Case
There is substantial research demonstrating that change management interventions lead to improved project outcomes. Change practitioners can use these studies as evidence to substantiate their value. For example:
Prosci Research has consistently shown that projects with excellent change management are significantly more likely to achieve their objectives compared to those with poor change management. According to the Best Practices in Change Management study, 88% of participants with excellent change management met or exceeded objectives, while only 13% of those with poor change management met or exceeded objectives. This means that projects with excellent change management were approximately seven times more likely to meet objectives than those with poor change management (Source).
Even implementing fair change management practices can lead to a threefold improvement in project outcomes (Source).
McKinsey found that transformation initiatives are 5.8 times more successful if CEOs communicate a compelling change story, and 6.3 times more successful when leaders share messages about change efforts with the rest of the organisation (Source).
By framing change management as an evidence-based discipline, Change CoEs can strengthen their credibility and influence senior stakeholders. Furthermore, sharing industry benchmarks and case studies showcasing successful change management implementations can add weight to the argument.
2. Calculate the Financial Value of Managing a Change Portfolio
Executives prioritize financial metrics, making it essential to quantify the financial impact of change management. This article How to calculate the financial value of managing a change portfolio provides a structured approach to calculating the financial value of managing a change portfolio. Some key financial considerations include:
Productivity Gains: Effective change management reduces employee resistance and increases adoption rates, leading to quicker realization of benefits. For instance, if a new system is introduced, strong change management ensures employees use it efficiently, eliminating productivity dips.
Cost Avoidance: Poorly managed change efforts can lead to rework, delays, and even project failures, incurring significant costs. For example, a failed system implementation due to lack of change management could require millions in additional investments to correct issues and retrain employees.
Revenue Acceleration: When changes are adopted swiftly and efficiently, organisations can capitalize on new opportunities faster. In industries such as retail, banking, and technology, time-to-market is critical. The faster employees and customers adapt to new changes, the sooner the organisation can generate revenue from those changes.
Risk Mitigation: Resistance and poor change adoption can lead to compliance risks, reputational damage, and disengagement, all of which have financial implications. A compliance failure due to lack of engagement in a new regulatory process could lead to fines and reputational loss.
To make this more tangible, Change CoEs should create financial models that quantify the cost of failed change initiatives versus successful ones. They can also track and report savings from avoided risks and improved efficiency, linking these directly to the organisation’s bottom line.
3. Demonstrate Value Through Behaviour Change
One of the most effective ways to prove the impact of change management is by tracking behaviour change. Change is not successful unless employees adopt new ways of working, and this can be measured using:
Adoption Metrics: Track usage rates of new systems, tools, or processes. For instance, if a company implements a new CRM system, measuring login frequency, data entry consistency, and feature utilization can indicate successful adoption.
Performance Data: Compare key performance indicators (KPIs) before and after change implementation. If a new customer service protocol is introduced, tracking customer satisfaction scores and response times will provide tangible insights into its effectiveness.
Employee Surveys: Gauge sentiment and readiness for change. Pulse surveys can reveal how confident employees feel about a transformation and whether they understand its purpose and benefits.
Stakeholder Feedback: Capture qualitative insights from leaders and frontline employees. Executives often rely on direct feedback from managers to gauge whether changes are being embraced or resisted.
By presenting a clear narrative that links change management efforts to observable behaviour shifts, Change CoEs can make their value more tangible. It is also beneficial to conduct longitudinal studies, tracking behaviour change over time to ensure sustained impact.
Imagine being able to present a set of behaviour metrics that are forward looking measures for benefit realisation. This can position favourably the tangible value of change management activities and approaches.
Customer Experience Improvements: Measure customer satisfaction before and after change initiatives. If a change initiative improves customer interactions, metrics such as Net Promoter Score (NPS) and retention rates will reflect its impact.
Employee Engagement and Retention: Effective change management reduces uncertainty and anxiety, leading to better engagement and lower attrition. Organisations that manage change well see lower absenteeism and stronger workforce commitment.
Organisational Agility: Organisations with strong change management capabilities adapt faster to market disruptions. Companies that successfully embed change management in their DNA are more resilient during economic downturns or competitive shifts.
Cultural Transformation: Change management plays a key role in shaping corporate culture, which influences long-term business success. For example, embedding a culture of continuous learning can make future change initiatives easier to implement.
By framing change management as a driver of strategic outcomes, rather than just an operational function, Change CoEs can enhance their perceived value.
5. Position change as a key part of risk management
Demonstrating the value of change management through risk management is a powerful approach for the Change CoE. By highlighting how effective change management mitigates various risks associated with organisational change, you can justify its importance and secure necessary support and resources.
This is particularly useful and important for the financial services sector where risk is now the front and centre of attention for most senior leaders, with the increasingly intense regulatory environment and scrutiny by regulators.
Risk in Change
Change initiatives inherently carry risks that can impact an organisation’s operations, culture, and bottom line. Effective change management helps identify and address these risks proactively. By implementing a robust change risk management framework, organisations can adapt their overall risk management strategies to cover change-related risks throughout the project lifecycle. This approach allows for early identification of potential obstacles, enabling timely interventions and increasing the likelihood of successful change implementation.
Delivery Risk
Change management plays a crucial role in mitigating delivery risks associated with project implementation. While project managers typically focus on schedule, cost, and quality risks, change managers can identify and manage risks that are delivered into the business as a result of the change. By working closely with project managers, change professionals can introduce processes to minimize the potential business impact of these delivered risks during project delivery. This collaboration ensures that the project not only delivers the required change but does so with minimal disruption to the organisation.
Quantifying Risk Mitigation
To further demonstrate the value of change management, it’s essential to quantify its contribution to risk mitigation. By adapting the organisation’s risk assessment matrix or tools, change managers can determine the probability and potential impact of each identified risk. This analysis allows for prioritization of risks and implementation of appropriate mitigation strategies.
By tracking how change management interventions reduce the likelihood or impact of these risks, you can provide tangible evidence of its value to senior leadership. By framing change management as a critical component of risk management, you can shift the conversation from justifying its existence to showcasing its indispensable role in ensuring successful organisational transformations. This not only demonstrates the value of change management but also aligns it with broader organisational goals of risk reduction and strategic success.
6. Proactively Measure and Track Value Delivery
Tracking and reporting the tangible value created by change management is essential. Organisations frequently undergo leadership transitions, and new decision-makers may question the need for a Change CoE. A well-documented history of impact ensures continuity and ongoing investment.
McKinsey research indicated that Transformations that provide both initiative-level and program-level views of progress through relevant metrics are 7.3 times more likely to succeed (Source).
To achieve this:
Develop a Change Management Dashboard: Use KPIs to track adoption rates, employee readiness, and impact on business metrics.
Create Case Studies: Document success stories with before-and-after comparisons. Case studies should include challenges, change management interventions, and final outcomes.
Conduct Quarterly Impact Reviews: Regularly present insights to senior leaders. Demonstrating trends and ongoing improvements ensures continued executive buy-in.
Link Change Efforts to Strategic Priorities: Show how change management enables key business goals, such as revenue growth, market expansion, or operational efficiency.
7. Shift from Education to Results-Driven Influence
While stakeholder education is important, it has limitations. Many executives have preconceived notions about change management. Rather than relying solely on relationship-building, focus on delivering results that speak for themselves. Key strategies include:
Pilot Programs: Run small-scale change initiatives with measurable impact. If an executive is sceptical, a successful pilot can turn them into an advocate. It is highly unlikely that executives will not want to see metrics that indicate how effective a change initiative is progressing.
Strategic Partnerships: Align with key business units to co-own change success. Partnering with Finance, HR, Risk, Operations and IT leaders can reinforce the business value of change management.
Agile Change Management: Deliver incremental wins to showcase immediate value. Iterative, feedback-driven approaches ensure continuous improvement and visibility.
Change management professionals must move beyond justification and actively prove their worth. By leveraging empirical research, financial calculations, behaviour tracking, alternative value measures, and proactive reporting, Change CoEs can secure their place as indispensable business functions. In a world where scepticism towards roles like change management persists, the best defence is a compelling, evidence-based demonstration of impact.
