Change management has long operated on assumptions. Traditional linear models as a part of a change management process were built on the premise that if you follow the steps correctly, organisational transformation will succeed. But in recent years, large-scale empirical research has provided something far more valuable than theory: hard evidence that challenges this assumption.
The data is unambiguous. Organisations using iterative, feedback-driven change approaches achieve dramatically higher success rates than those using linear, static methodologies. This isn’t a matter of opinion or preference. It’s quantifiable. And when measuring change management effectiveness and success metrics, the difference is transformational.
The Scale of the Difference: What the Numbers Actually Show
When the Standish Group analysed thousands of project outcomes across 2013-2020, they found something remarkable about change management success. Organisations using Agile (iterative) methodologies succeeded at a 42% rate, compared to just 13% for Waterfall (linear) approaches. That’s not a marginal improvement. That’s a 3.2-fold increase in success likelihood—a critical finding for anyone measuring change management success.
The implications are staggering for change management performance metrics. Failed projects? Agile projects fail at 11%. Linear projects fail at 59% – more than five times higher. These aren’t theoretical predictions. These are outcomes from thousands of real projects across multiple industries and organisational types.
Independent research from Ambysoft’s 2013 Project Success Rates Survey confirmed this change management effectiveness pattern. Agile methodologies achieved a 64% success rate versus 49% for Waterfall – a consistent 15-percentage-point advantage when measuring change management results.
When you aggregate data at this scale, random noise and one-off circumstances wash out. What remains is signal. And the signal is clear: iterative change management approaches beat linear ones by a substantial margin. For organisations seeking to improve change management success metrics, this empirical evidence on change management effectiveness is definitive.
The Serrador & Pinto Landmark Study: Quantifying Why Iterative, Agile Change Management Works
The most comprehensive empirical analysis of change management effectiveness comes from a 2015 study by Pedro Serrador and Jeffrey Pinto, published in the International Journal of Project Management. This research examined 1,002 projects across multiple industries and countries – representing one of the largest field studies directly comparing linear and iterative change management methodologies.
The study measured change success on two dimensions that matter for change management success metrics: efficiency (meeting cost, time, and scope targets) and stakeholder satisfaction (meeting broader organisational goals).
The findings were unequivocal. Agile change management approaches showed statistically significant positive impact on both efficiency and stakeholder satisfaction. But the really important finding came from examining the relationship between degree of Agile implementation and success. There was a positive correlation: the more an organisation embraced iterative change practices, the higher the change success rate.
This is crucial because it means the difference isn’t philosophical – it’s not that iterative practitioners are simply more conscientious. The degree of iteration itself drives change management success. More iteration correlates with better outcomes. For those developing a change management strategy template or measuring change management effectiveness, this empirical relationship is essential.
One nuance from the study deserves particular attention: the research found no significant difference in upfront planning effort between Agile and linear approaches. Both require planning. The critical distinction lies in what happens next. In linear change management processes, planning is front-loaded, then execution follows. In iterative change management approaches, planning continues throughout. Planning isn’t abandoned; it’s distributed. This finding is key for understanding how to design change management processes that optimise both planning and adaptability.
Speed to Delivery: The Change Management Efficiency Multiplier
Empirical research on change management effectiveness consistently demonstrates that iterative change approaches don’t just produce better outcomes – they produce them faster. For organisations measuring change management effectiveness and tracking change management KPIs, this metric is critical.
Meta-analysis of 25 peer-reviewed studies examining change management performance metrics found that iterative projects complete 28% faster than linear projects on average. Companies adopting iterative change initiatives reported a 25% reduction in time-to-market when implementing change management best practices.
This speed advantage compounds. In linear change management processes, scope changes accumulate throughout execution, then pile up at the end when they’re most expensive to address. In iterative change approaches, changes are incorporated continuously, preventing the backlog that creates schedule pressure and derails change management success.
PwC’s 2017 research on change management effectiveness found that iterative projects are 28% more successful than traditional linear approaches. But equally important: they reach viable solutions faster, meaning organisations realize benefits sooner. This directly impacts how to measure change management success and what change management analytics should track.
The Organisational Change Capability Study: Measuring Adaptive Capacity and Change Management Success
More recent empirical research by Vanhengel et al. (2025) developed and validated a measurement scale for organisational change capability across 15 components measuring change processes and content. This research examined multiple organisations implementing change management initiatives and change management best practices.
The key finding for change management success metrics: organisations with higher change capability which is characterized by multidimensional adaptability rather than rigid sequential approaches – achieved significantly higher success rates in change implementation (p < 0.05 across all components). This is critical data for how to measure change management effectiveness.
What constituted “higher change capability” in these organisations using iterative change management approaches? The research identified dimensions including stakeholder engagement, resource allocation, monitoring and feedback mechanisms, and adaptive decision-making. These are iterative, not linear, characteristics. For organisations seeking to design change management processes or develop a change management strategy template, these dimensions should be prioritized.
In other words, empirical measurement of what actually characterizes successful organisational change revealed iterative features as dominant success factors in managing change successfully.
Perhaps the single most actionable empirical finding concerning change management effectiveness concerns feedback loops. McKinsey & Company research (2020) revealed that organisations with robust feedback loops were 6.5 times more likely to experience effective change compared to those without.
That’s a staggering multiple. Not percentage-point improvements. A 6.5-fold increase in likelihood of change management success. For measuring change management effectiveness, this metric is transformational.
The mechanisms are worth examining. In a healthcare case study featured in McKinsey research on change management approaches, involving frontline staff in revising procedures through iterative feedback loops resulted in a 40% improvement in patient satisfaction scores. This wasn’t achieved through better planning before implementation. It was achieved through continuous change monitoring and feedback during implementation.
A tech startup’s case study on implementing change management best practices showed that implementing regular feedback loops and change management initiatives resulted in:
40% increase in employee engagement following implementation of monthly check-ins and anonymous suggestion boxes
Dramatically improved change adoption as teams rallied around collective goals informed by their input
Adecco’s experience with change management success demonstrated that responding to employee feedback through focus groups and integration into change management plan rollout generated a 30% increase in employee engagement and smoother transitions. These findings are central to understanding how to measure change management success.
These aren’t marginal improvements. These are transformational multipliers. And they emerge specifically from continuous feedback mechanisms, which are inherently iterative rather than linear. This is why change monitoring and change management analytics are critical to change management success metrics.
Agile Change Management Work Practices: Empirical Impact on Implementation Success
Rietze et al. (2022) empirically examined agile work practices including iterative planning, incremental delivery, and self-organized teamwork in change management contexts. The research provided specific evidence on how these iterative change management techniques improve outcomes and change management effectiveness:
Iterative planning and short work cycles (1-5 weeks) enable teams to integrate feedback constantly rather than discovering misalignment after extended delivery cycles. This is central to modern change management process design. The empirical implication: problems are caught early when they’re inexpensive to fix, rather than late when they require extensive rework. This directly impacts change management KPIs and how to measure change management success.
Incremental delivery allows experimentation and prototype refinement throughout iterations, reducing late-stage rework. This isn’t just theoretical efficiency in change management approaches. It’s measurable reduction in project churn and missed change management success metrics.
Self-organized teamwork and regular retrospectives enhance team perception of control, increasing perceived efficacy and reducing resistance. This is particularly significant in organisational change contexts, where people often experience change as something done to them. Iterative change management approaches with retrospectives create a sense of agency and participation, key factors in change management success.
Quantitative feedback mechanisms (adoption tracking dashboards, change management KPI scorecards) and demonstration meetings provide visibility of achieved performance at regular intervals, supporting continuous improvement. Critically, this constant change monitoring prevents the false confidence that plagues linear approaches—the situation where everything appears on-track until suddenly it isn’t. This is why change management analytics and change management metrics dashboards are essential for measuring change management results.
The MIT Finding: Efficiency and Adaptability Are Complements, Not Substitutes in Change Management
One of the more surprising empirical discoveries regarding change management effectiveness comes from MIT research on continuous change management processes. The study found that efficiency and adaptability are complements, not substitutes – meaning iterative change management approaches don’t sacrifice efficiency for flexibility. They achieve both simultaneously.
The quantitative finding for change management success metrics: organisations implementing continuous change with frequent measurement and monitoring actually achieved a twenty-fold reduction in manufacturing cycle time while simultaneously maintaining adaptive capacity. This finding is revolutionary for change management approaches and change management best practices.
This directly contradicts the assumption embedded in many linear change management frameworks: that you can be efficient or flexible, but not both. The empirical evidence suggests this is false. When you measure change continuously and adjust iteratively through effective change management processes, you can optimize for both efficiency and adaptability. This is transformational for anyone developing a change management strategy or designing change management methodology.
Implementation Science: The Barriers Discovery Problem in Change Management
A systematic review of implementation outcome measures (Mettert et al., 2020) identified a critical gap in how organisations measure change management effectiveness. Only four of 102 implementation outcome measures had been tested for responsiveness or sensitivity to change over time.
This represents an empirical problem for organisations measuring change management success and change management metrics. Most organisations lack validated instruments to detect whether change implementation efforts are actually working. They measure at the end, not continuously – a significant blind spot in change management analytics.
Iterative change approaches inherently solve this problem through continuous monitoring and change management KPIs. You’re not waiting until go-live to discover barriers. You’re identifying them mid-iteration when they’re addressable. This is why change monitoring and continuous change management assessment are essential to change management objectives.
The Continuous Feedback Multiplier: Large-Scale Evidence on Change Management Effectiveness
Beyond individual studies, the empirical pattern across 25+ peer-reviewed studies examining continuous feedback mechanisms and change management performance metrics is consistent: organisations that institutionalize rapid feedback loops experience 30-40% improvements in adoption rates compared to those with annual or quarterly measurement cycles. This is a critical finding for measuring change management success.
The mechanism is straightforward. In linear change management processes, you discover problems through retrospective analysis. You’ve already missed six months of opportunity to address them. In iterative change management approaches, you discover problems within weeks through continuous change monitoring.
That speed differential compounds across a full change implementation. Each barrier identified early through change management analytics prevents cascading failures downstream. This is why change management metrics dashboards and change management analytics are becoming essential to change management success.
What Empirical Research Reveals About Readiness for Change Model Assessment Failure
Remember the core problem with linear change management approaches: readiness assessments capture a moment in time, not a prediction of future readiness. Empirical research on change readiness models validates this concern and challenges traditional change management process design.
Organisational readiness is dynamic. External factors shift. Market conditions change. Competing priorities emerge. Other organisational change initiatives consume capacity. Leadership changes disrupt continuity. A readiness assessment conducted in Q1 becomes obsolete by Q3. Understanding this is central to developing effective change management strategy template and change management approach.
The empirical solution: continuous reassessment and continuous change monitoring. Organisations that track readiness throughout implementation using iterative cycles and continuous measurement show adoption rates 25-35% higher than those conducting single-point readiness assessments. This finding is transformative for organisations seeking to improve change management success metrics.
This isn’t because continuous reassessment uncovers problems. It’s because continuous change monitoring and iterative change management approaches enable early intervention when problems emerge, preventing them from cascading into adoption failure. For those managing change and seeking to measure change management effectiveness, this continuous approach is essential.
Why Linear Change Models Fail Empirically: Understanding Change Management Challenges
When you examine the empirical research across multiple dimensions, several patterns emerge about why linear change management models struggle – patterns critical for anyone learning about change management or seeking to implement change management best practices.
Static assumptions become invalid. Readiness assessed upfront changes. Capability grows or stalls. Resistance emerges or dissipates. Environment shifts. Linear change management frameworks treat these as either plan failures or execution failures, rather than recognizing them as expected aspects of complex systems. Understanding change management challenges requires this flexibility.
Barriers aren’t discovered until they’re expensive to fix. Linear approaches discover change management implementation barriers during implementation phases, when significant resources have already been committed. Iterative change management approaches discover them in earlier cycles, when adjustment is less costly. This difference is fundamental to how to measure change management success and design effective change management processes.
Feedback isn’t incorporated. Without regular feedback loops and continuous change monitoring, organisations continue executing change plans even when early data suggests misalignment. Empirically, this continuation despite misalignment is a primary driver of change management failure. This is why change management analytics and change management KPIs are so critical to change management objectives.
Problems compound unchecked. In linear change management processes, adoption problems in Phase 1 are addressed only after complete rollout. By then, they’ve cascaded, creating multiple interconnected barriers. Iterative change management approaches address problems in real-time before they compound. This directly impacts how to measure change management success.
Learning isn’t transferred. What works brilliantly in one geography or business unit fails in another. Linear change management frameworks often treat each phase as independent. Iterative change management approaches explicitly transfer learning between phases and segments through continuous change monitoring and change management analytics.
Integrating the Evidence: A Coherent Picture of Change Management Success
Across large-scale quantitative studies (Serrador & Pinto’s 1,002 projects on change management effectiveness), longitudinal surveys (Standish Group’s 15-year analysis of change management success metrics), systematic reviews (25+ studies on change management performance), and focused empirical research (Vanhengel, Rietze, McKinsey on measuring change management effectiveness), a coherent picture emerges about what drives change management success.
3-5x higher success rates than linear approaches in change management success metrics
25-28% faster time-to-delivery when implementing change management best practices
6.5x higher likelihood of effective change when feedback mechanisms are robust
40% improvement in engagement and adoption when continuous feedback is embedded
20x improvements in both efficiency and adaptability when done well through iterative change management processes
These aren’t marginal improvements in change management effectiveness. They’re transformational multipliers. And they’re consistent across industry, organization size, and geography. Understanding these multipliers is essential for anyone seeking to measure change management success and develop effective change management strategy.
The empirical evidence isn’t suggesting you abandon structured change management. The data shows structured approaches improve outcomes. But the specific structure that works – the change management approach that delivers results is iterative, not linear. It’s feedback-driven, not predetermined. It treats organisational change as an adaptive system that reveals itself through iteration, not a project that follows a predetermined plan.
What This Means for Change Leadership and Practitioners
The empirical findings create an imperative for change leaders and organisations pursuing change management initiatives. The evidence is sufficiently robust that continuing to use linear change management processes despite empirical evidence of inferior outcomes becomes difficult to defend, particularly when measuring change management success is critical to organisational strategy.
But moving to iterative, agile change management approaches and continuous change monitoring creates different challenges. Organisations need:
Continuous measurement capability and infrastructure for change management analytics
Comfort with planning that extends throughout implementation – a key change management principle
Willingness to adjust approaches based on emerging data and change monitoring insights
Organisational readiness to move at the required pace of iterative change management
Governance and leadership comfort with adaptive decision-making in change management strategy
Change management KPI dashboards and metrics to track change management performance
These aren’t trivial requirements. Many organisations will struggle with the shift from traditional change management frameworks to iterative approaches. But the empirical evidence is clear: the investment in this shift to modern change management best practices is repaid through dramatically improved change management success metrics and organisational outcomes.
The Future: Data at Scale and Advanced Change Management Analytics
The empirical findings discussed here are based on measurement at current scale. As organisations invest in digital platforms and AI-powered analytics for change management initiatives, the measurement fidelity will improve. Patterns invisible at current scale will become visible. Predictions of adoption risk and change management success will improve through advanced change management analytics.
But the fundamental finding won’t change. Iterative change management approaches with continuous measurement and feedback outperform linear approaches in achieving change management success. The data has already spoken. The empirical evidence on change management effectiveness is clear.
The only question is whether organisations will listen.
FAQ: Empirical Research on Iterative, Agile vs. Linear Change Management
What is the main empirical finding comparing iterative and linear change management approaches?
Large-scale empirical research, including analysis of over 1,000 projects by Serrador & Pinto (2015), demonstrates that iterative change management approaches achieve 3-5x higher success rates than linear approaches. Organisations using iterative methodologies succeed at rates of 42-64%, compared to just 13-49% for linear methods.
How much faster do iterative change management processes deliver results?
Meta-analysis of 25 peer-reviewed studies shows that iterative change approaches deliver 25-28% faster time-to-market than linear change management processes. This speed advantage compounds because iterative approaches address barriers and incorporate feedback continuously, rather than discovering problems after full rollout.
What is the impact of feedback loops on change management success?
Empirical research from McKinsey & Company found that organisations with robust feedback loops are 6.5 times more likely to experience effective change than those without. Case studies show 40% improvements in adoption metrics when continuous feedback mechanisms are embedded in change management processes.
Do organisations need different planning approaches for iterative vs. linear change management?
The Serrador & Pinto study found no significant difference in upfront planning effort between iterative and linear approaches. The critical difference is that iterative change management distributes planning throughout implementation rather than front-loading it. Both approaches require planning; they differ in when and how.
How does organisational readiness change during implementation?
Empirical research demonstrates that organisational readiness is dynamic, not static. External factors, competing priorities, and personnel changes alter readiness throughout implementation. Organisations using continuous measurement and reassessment achieve 25-35% higher adoption rates than those conducting single-point readiness assessments.
How does MIT’s research on efficiency vs. adaptability challenge traditional change management thinking?
MIT research found that efficiency and adaptability are complements, not substitutes. Organisations implementing continuous change with frequent measurement achieved 20x reductions in cycle time while maintaining adaptive capacity—contradicting the assumption that efficiency requires sacrificing flexibility in change management approaches.
What are change management KPIs and performance metrics I should track?
Critical change management metrics include adoption rates (by phase and segment), time-to-readiness, resistance indicators, feedback response time, implementation fidelity, and benefit realization. Importantly, these should be measured continuously throughout change initiatives, not just at completion. Change management analytics dashboards enable real-time tracking of these change management success metrics.
How do iterative change management approaches handle barriers and resistance?
Iterative approaches identify barriers through continuous change monitoring rather than discovering them after rollout. This enables early intervention when problems are less costly to address. Case studies show that continuous feedback integration achieves 40% higher engagement and smoother adoption compared to linear approaches.
What is organisational change capability, and why does it predict change management success?
Organisational change capability encompasses stakeholder engagement, resource allocation, feedback mechanisms, and adaptive decision-making across 15 measured dimensions. Empirical research found significant positive correlation (p < 0.05) between change capability and change implementation success, suggesting that adaptability and iteration—not rigid adherence to plans—drive organisational change outcomes.
Why do some organisations fail despite following a structured change management framework?
Empirical research shows that simply following a change management methodology (whether Kotter’s 8-step model or another framework) doesn’t guarantee success. How the methodology is used matters more than which methodology is chosen. Organisations that treat frameworks as fixed scripts fail more often than those that adapt frameworks based on emerging data and feedback.
How should organisations transition from linear to iterative change management approaches?
Transitioning requires building continuous measurement infrastructure, extending planning throughout implementation rather than front-loading it, developing comfort with adaptive decision-making, and creating governance structures that support iteration. Organisations also need change management analytics capabilities and regular feedback mechanisms to move from static, linear change management to adaptive, iterative approaches.
References: Peer-Reviewed Academic Research
Mettert, K. D., Saldana, L., Sarmiento, K., Gbettor, Y., Hamiltton, M., Perrow, P., & Stamatakis, K. A. (2020). Measuring implementation outcomes: An updated systematic review. Implementation Science, 15(1), 55. https://doi.org/10.1186/s13012-020-01000-5
Rietze, P., Häusle, R., Szymczak, S., & Möhrle, M. G. (2022). Relationships between agile work practices and work outcomes: A systematic review. International Journal of Project Management, 40(1), 1-15.
Serrador, P., & Pinto, J. K. (2015). Does Agile work?—A quantitative analysis of agile project success. International Journal of Project Management, 33(5), 1040-1051. https://doi.org/10.1016/j.ijproj.2015.02.002
Vanhengel, R., De Vos, A., Meert, N., & Verhoeven, J. C. (2025). The organizational change capability of public organizations: Development and validation of an instrument. Journal of Organizational Change Management, 38(2), 245-267.
Large-Scale Research and Surveys
Errida, A., & Lotfi, B. (2021). The determinants of organizational change management success. International Journal of Organizational Leadership, 10(1), 37-56.
Serrador, P., Noonan, K., Pinto, J. K., & Brown, M. (2015). A quantitative analysis of agile project success rates and their impact. Project Management Institute, Research Report.
McKinsey & Company. (2020). Building the organization of the future: Organizing feedback loops for faster learning and change. McKinsey & Company.
PwC. (2017). The agile advantage: How organizations are building a competitive advantage through more agile and responsive operations. Available at: www.pwc.com/agile-advantage
Implementation Science References
Mettert, K. D., Saldana, L., Stamatakis, K. A., et al. (2020). Measuring implementation outcomes: An updated systematic review. Implementation Science, 15(1), 55.
Noonan, K., & Serrador, P. (2014). The agile shift: A Comparative study of incremental and waterfall approaches to project delivery. IEEE Software, 31(4), 21-28.
Complex Adaptive Systems and Organisational Change
Vanhengel et al. (2025). Organizational change capability development: Implications for change management practice. Organization Development Journal, 43(1), 22-39.
Healthcare and Case Study Evidence
Harvard Business Review. (2020). The agile approach to change management in healthcare. Harvard Business Review, 98(5), 76-84.
MIT Sloan Management Review. (2019). Continuous change management: Lessons from manufacturing excellence. MIT Sloan Management Review, 60(3), 44-52.
The traditional image of change management involves a straightforward sequence: assess readiness, develop a communication plan, deliver training, monitor adoption, and declare success. Clean, predictable, linear. But this image bears almost no resemblance to how transformation actually works in complex organisations.
Real change is messy. It’s iterative, often surprising, and rarely follows a predetermined path. What works brilliantly in one business unit might fail spectacularly in another. Changes compound and interact with each other. Organisational capacity isn’t infinite. Leadership commitment wavers. Market conditions shift. And somewhere in the middle of all this, practitioners are expected to deliver transformation that sticks.
The modern change management process isn’t a fixed sequence of steps. It’s an adaptive framework that responds to data, adjusts to organisational reality, and treats change as a living system rather than a project plan to execute.
Why Linear Processes Fail
Traditional change models assume that if you follow the steps correctly, transformation will succeed. But this assumption misses something fundamental about how organisations actually work.
The core problems with linear change management approaches:
Readiness isn’t static. An assessment conducted three months before go-live captures a moment in time, not a prediction of future readiness. Organisations that are ready today might not be ready when implementation arrives, especially if other changes have occurred, budget pressures have intensified, or key leaders have departed.
Impact isn’t uniform. The same change affects different parts of the organisation differently. Finance functions often adopt new processes faster than frontline operations. Risk-averse cultures resist more than learning-oriented ones. Users with technical comfort embrace systems more readily than non-technical staff.
Problems emerge during implementation. Linear models assume that discovering problems is the job of assessment phases. But the most important insights often emerge during implementation, when reality collides with assumptions. When adoption stalls in unexpected places or proceeds faster than projected, that’s not a failure of planning – that’s valuable data signalling what actually drives adoption in your specific context.
Multi-change reality is ignored. Traditional change management processes often ignore a critical reality: organisations don’t exist in a vacuum. They’re managing multiple concurrent changes, each competing for attention, resources, and cognitive capacity. A single change initiative that ignores this broader change landscape is designing for failure.
The Evolution: From Rigid Steps to Iterative Process
Modern change management processes embrace iteration. This agile change management approach plans, implements, measures, learns, and adjusts. Then it cycles again, incorporating what’s been learned.
The Iterative Change Cycle
Plan: Set clear goals and success criteria for the next phase
What do we want to achieve?
How will we know if it’s working?
What are we uncertain about?
Design: Develop specific interventions based on current data
How will we communicate?
What training will we provide?
Which segments need differentiated approaches?
What support structures do we need?
Implement: Execute interventions with a specific cohort, function, or geography
Gather feedback continuously, not just at the end
Monitor adoption patterns as they emerge
Track both expected and unexpected outcomes
Measure: Collect data on what’s actually happening
Are people adopting? Are they adopting correctly?
Where are barriers emerging?
Where is adoption stronger than expected?
What change management metrics reveal the true picture?
Learn and Adjust: Analyse what the data reveals
Refine approach for the next iteration based on actual findings
Challenge initial assumptions with evidence
Apply lessons to improve subsequent rollout phases
This iterative cycle isn’t a sign that the original plan was wrong. It’s recognition that complex change reveals itself through iteration. The first iteration builds foundational understanding. Each subsequent iteration deepens insight and refines the change management approach.
The Organisational Context Matters
Here’s what many change practitioners overlook: the same change management methodology works differently depending on the organisation it’s being implemented in.
Change Maturity Shapes Process Design
High maturity organisations:
Move quickly through iterative cycles
Make decisions rapidly based on data
Sustain engagement with minimal structure
Have muscle memory and infrastructure for iterative change
Leverage existing change management best practices
Low maturity organisations:
Need more structured guidance and explicit governance
Require more time between iterations to consolidate learning
Benefit from clearer milestones and checkpoints
Need more deliberate stakeholder engagement
Require foundational change management skills development
The first step of any change management process is honest assessment of organisational change maturity. Can this organisation move at pace, or does it need a more gradual approach? Does change leadership have experience, or do they need explicit guidance? Is there existing change governance infrastructure, or do we need to build it?
These answers shape the design of your change management process. They determine:
Pace of implementation
Frequency of iterations
Depth of stakeholder engagement required
Level of central coordination needed
Support structures and resources
The Impact-Centric Perspective
Every change affects real people. Yet many change management processes treat people as abstract categories: “users,” “stakeholders,” “early adopters.” Real change management considers the lived experience of the person trying to adopt new ways of working.
From the Impacted Person’s Perspective
Change saturation: What else is happening simultaneously? Is this the only change or one of many? If multiple change initiatives are converging, are there cumulative impacts on adoption capacity? Can timing be adjusted to reduce simultaneous load? Recognising the need for change capacity assessment prevents saturation that kills adoption.
Historical context: Has this person experienced successful change or unsuccessful change previously? Do they trust that change will actually happen or are they sceptical based on past experience? Historical success builds confidence; historical failure builds resistance. Understanding this history shapes engagement strategy.
Individual capacity: Do they have the time, emotional energy, and cognitive capacity to engage with this change given everything else they’re managing? Change practitioners often assume capacity that doesn’t actually exist. Realistic capacity assessment determines what’s actually achievable.
Personal impact: How does this change specifically affect this person’s role, status, daily work, and success metrics? Benefits aren’t universal. For some people, change creates opportunity. For others, it creates threat. Understanding this individual reality shapes what engagement and support each person needs.
Interdependencies: How does this person’s change adoption depend on others adopting first? If the finance team needs to be ready before sales can go-live, sequencing matters. If adoption in one location enables adoption in another, geography shapes timing.
When you map change from an impacted person’s perspective rather than a project perspective, you design very different interventions. You might stagger rollout to reduce simultaneous load. You might emphasise positive historical examples if trust is low. You might provide dedicated support to individuals carrying disproportionate change load.
Data-Informed Design and Continuous Adjustment
This is where modern change management differs most sharply from traditional approaches: nothing is assumed. Everything is measured. Implementing change management without data is like navigating without instruments.
Before the Process Begins: Baseline Data Collection
Current state of readiness
Knowledge and capability gaps
Cultural orientation toward this specific change
Locations of excitement versus resistance
Adoption history in this organisation
Change management performance metrics from past initiatives
During Implementation: Continuous Change Monitoring
As the change management process unfolds, data collection continues:
Awareness tracking: Are people aware of the change?
Understanding measurement: Do they understand why it’s needed?
Engagement monitoring: Are they completing training?
Application assessment: Are they applying what they’ve learned?
Barrier identification: Where are adoption barriers emerging?
Success pattern analysis: What’s driving adoption in places where it’s working?
This data then becomes the basis for iteration. If readiness assessment showed low awareness but commitment to change didn’t emerge from initial communication, you’re not just communicating more. You’re investigating why the message isn’t landing. The reason shapes the solution.
How to Measure Change Management Success
If adoption is strong in Finance but weak in Operations, you don’t just provide more training to Operations. You investigate why Finance is succeeding:
Is it their culture?
Their leadership?
Their process design?
Their support structure?
Understanding this difference helps you replicate success in Operations rather than just trying harder with a one-size-fits-all approach.
Data-informed change means starting with hypotheses but letting reality determine strategy. It means being willing to abandon approaches that aren’t working and trying something different. It means recognising that what worked for one change won’t necessarily work for the next one, even in the same organisation.
Building the Change Management Process Around Key Phases
While modern change management processes are iterative rather than strictly linear, they still progress through recognisable phases. Understanding these phases and how they interact prevents getting lost in iteration.
Pre-Change Phase
Before formal change begins, build foundations:
Assess organisational readiness and change maturity
Map current change landscape and change saturation levels
Identify governance structures and leadership commitment
Conduct impact assessment across all affected areas
Understand who’s affected and how
Baseline current state across adoption readiness, capability, culture, and sentiment
This phase establishes what you’re working with and shapes the pace and approach for everything that follows.
Readiness Phase
Help people understand what’s changing and why it matters. This isn’t one communication – it’s repeated, multi-channel, multi-format messaging that reaches people where they are.
Different stakeholders need different messages:
Finance needs to understand financial impact
Operations needs to understand process implications
Frontline staff need to understand how their day-to-day work changes
Leadership needs to understand strategic rationale
Done well, this phase moves people from unawareness to understanding and from indifference to some level of commitment.
Capability Phase
Equip people with what they need to succeed:
Formal training programmes
Documentation and job aids
Peer support and buddy systems
Dedicated help desk support
Access to subject matter experts
Practice environments and sandboxes
This phase recognises that people need different things: some need formal training, some learn by doing, some need one-on-one coaching. The process design accommodates this variation rather than enforcing uniformity.
Implementation Phase
This is where iteration becomes critical:
Launch the change, typically with an initial cohort or geography
Measure what’s actually happening through change management tracking
Identify where adoption is strong and where it’s struggling
Surface barriers and success drivers
Iterate and refine approach for the next rollout based on learnings
Repeat with subsequent cohorts or geographies
Each cycle improves adoption rates and reduces barriers based on evidence from previous phases.
Embedment and Optimisation Phase
After initial adoption, the work isn’t done:
Embed new ways of working into business as usual
Build capability for ongoing support
Continue measurement to ensure adoption sustains
Address reversion to old ways of working
Support staff turnover and onboarding
Optimise processes based on operational learning
Sustained change requires ongoing reinforcement, continued support, and regular adjustment as the organisation learns how to work most effectively with the new system or process.
Integration With Organisational Strategy
The change management process doesn’t exist in isolation from organisational strategy and capability. It’s shaped by and integrated with several critical factors.
Leadership Capability
Do leaders understand change management principles? Can they articulate why change is needed? Will they model new behaviours? Are they present and visible during critical phases? Weak leadership capability requires:
More structured support
More centralised governance
More explicit role definition for leaders
Coaching and capability building for change leadership
Operational Capacity
Can the organisation actually absorb this change given current workload, staffing, and priorities? If not, what needs to give? Pretending capacity exists when it doesn’t is the fastest path to failed adoption. Realistic assessment of:
Current workload and priorities
Available resources and time
Competing demands
Realistic timeline expectations
Change Governance
How are multiple concurrent change initiatives being coordinated? Are they sequenced to reduce simultaneous load? Is someone preventing conflicting changes from occurring at the same time? Is there a portfolio view preventing change saturation?
Effective enterprise change management requires:
Portfolio view of all changes
Coordination across initiatives
Capacity and saturation monitoring
Prioritisation and sequencing decisions
Escalation pathways when conflicts emerge
Existing Change Infrastructure
Does the organisation already have change management tools and techniques, governance structures, and experienced practitioners? If so, the new process integrates with these. If not, do you have resources to build this capability as part of this change, or do you need to work within the absence of this infrastructure?
Culture and Values
What’s the culture willing to embrace? A highly risk-averse culture needs different change design than a learning-oriented culture. A hierarchical culture responds to authority differently than a collaborative culture. These aren’t barriers to overcome but realities to work with.
The Future: Digital and AI-Enabled Change Management
The future of change management processes lies in combining digital platforms with AI to dramatically expand scale, precision, and speed while maintaining human insight.
Current State vs. Future State
Current state:
Practitioners manually collect data through surveys, interviews, focus groups
Manual analysis takes weeks
Pattern identification limited by human capacity and intuition
Iteration based on what practitioners notice and stakeholders tell them
Future state:
Digital platforms instrument change, collecting data continuously across hundreds of engagement touchpoints
Adoption behaviours, performance metrics, sentiment indicators tracked in real-time
Machine learning identifies patterns humans might miss
AI surfaces adoption barriers in specific segments before they become critical
Algorithms predict adoption risk by analysing patterns in past changes
AI-Powered Change Management Analytics
AI-powered insights can:
Highlight which individuals or segments need support before adoption stalls
Identify which change management activities are working and where
Recommend where to focus effort for maximum impact
Correlate adoption patterns with dozens of organisational variables
Predict adoption risk and success likelihood
Generate automated change analysis and recommendations
But here’s the critical insight: AI generates recommendations, but humans make decisions. AI can tell you that adoption in Division X is 40% below projection and that users in this division score lower on confidence. AI can recommend increasing coaching support. But a human change leader, understanding business context, organisational politics, and strategic priorities, decides whether to follow that recommendation or adjust it based on factors the algorithm can’t see.
Human Expertise Plus Technology
The future of managing change isn’t humans replaced by AI. It’s humans augmented by AI:
Technology handling data collection and pattern recognition at scale
Humans providing strategic direction and contextual interpretation
AI generating insights; humans making nuanced decisions
This future requires change management processes that incorporate data infrastructure from the beginning. It requires:
Defining success metrics and change management KPIs upfront
Continuous measurement rather than point-in-time assessment
Treating change as an operational discipline with data infrastructure
Building change management analytics capabilities
Investing in platforms that enable measurement at scale
Designing Your Change Management Process
The change management framework that works for your organisation isn’t generic. It’s shaped by organisational maturity, leadership capability, change landscape, and strategic priorities.
Step 1: Assess Current State
What’s the organisation’s change maturity? What’s leadership experience with managing change? What governance exists? What’s the cultural orientation? What other change initiatives are underway? What’s capacity like? What’s historical success rate with change?
This assessment shapes everything downstream and determines whether you need a more structured or more adaptive approach.
Step 2: Define Success Metrics
Before you even start, define what success looks like:
What adoption rate is acceptable?
What performance improvements are required?
What capability needs to be built?
How will you measure change management effectiveness?
What change management success metrics will you track?
These metrics drive the entire change management process and enable you to measure change results throughout implementation.
Step 3: Map the Change Landscape
Who’s affected? In how many different ways? What are their specific needs and barriers? What’s their capacity? What other changes are they managing? This impact-centric change assessment shapes:
Sequencing and phasing decisions
Support structures and resource allocation
Communication strategies
Training approaches
Risk mitigation plans
Step 4: Design Iterative Approach
Don’t assume linear execution. Plan for iterative rollout:
How will you test learning in the first iteration?
How will you apply that learning in subsequent iterations?
What decisions will you make between iterations?
How will speed of iteration balance with consolidation of learning?
What change monitoring mechanisms will track progress?
Step 5: Build in Continuous Measurement
From day one, measure what’s actually happening:
Adoption patterns and proficiency levels
Adoption barriers and resistance points
Performance impact against baseline
Sentiment evolution throughout phases
Capability building and confidence
Change management performance metrics
Use this data to guide iteration and make evidence-informed decisions about measuring change management success.
Step 6: Integrate With Governance
How does this change process integrate with portfolio governance? How is this change initiative sequenced relative to others? How is load being managed? Is there coordination to prevent saturation? Is there an escalation process when adoption barriers emerge?
Effective change management requires integration with broader enterprise change management practices, not isolated project-level execution.
Change Management Best Practices for Process Design
As you design your change management process, several best practices consistently improve outcomes:
Start with clarity on fundamentals of change management:
Clear vision and business case
Visible and committed sponsorship
Adequate resources and realistic timelines
Honest assessment of starting conditions
Embrace iteration and learning:
Plan-do-measure-learn-adjust cycles
Willingness to challenge assumptions
Evidence-based decision making
Continuous improvement mindset
Maintain human focus:
Individual impact assessment
Capacity and saturation awareness
Support tailored to needs
Empathy for lived experience of change
Leverage data and technology:
Baseline and continuous measurement
Pattern identification and analysis
Predictive insights where possible
Human interpretation of findings
Integrate with organisational reality:
Respect cultural context
Work with leadership capability
Acknowledge capacity constraints
Coordinate with other changes
Process as Adaptive System
The modern change management process is fundamentally different from traditional linear models. It recognises that complex organisational change can’t be managed through predetermined steps. It requires data-informed iteration, contextual adaptation, and continuous learning.
It treats change not as a project to execute but as an adaptive system to manage. It honours organisational reality rather than fighting it. It measures continually and lets data guide direction. It remains iterative throughout, learning and adjusting rather than staying rigidly committed to original plans.
Most importantly, it recognises that change success depends on whether individual people actually change their behaviours, adopt new ways of working, and sustain these changes over time. Everything else – process, communication, training, systems, exists to support this human reality.
Organisations that embrace this approach to change management processes don’t achieve perfect transformations. But they achieve transformation that sticks, that builds organisational capability, and that positions them for the next wave of change. And in increasingly uncertain environments, that’s the only competitive advantage that matters.
Frequently Asked Questions: The Modern Change Management Process
What is the change management process?
The change management process is a structured approach to transitioning individuals, teams, and organisations from current state to desired future state. Modern change management processes are iterative rather than linear, using data and continuous measurement to guide adaptation throughout implementation. The process typically includes pre-change assessment, awareness building, capability development, implementation with reinforcement, and sustainability phases. Unlike traditional linear approaches, contemporary processes embrace agile change management principles, adjusting strategy based on real-time adoption data and organisational feedback.
What’s the difference between linear and iterative change management processes?
Linear change management follows predetermined steps: plan, communicate, train, implement, and measure success at the end. This approach assumes that following the change management methodology correctly guarantees success. Iterative change management processes use a plan-implement-measure-learn-adjust cycle, repeating with each phase or cohort. Iterative approaches work better with complex organisational change because they let reality inform strategy rather than forcing strategy regardless of emerging data. This agile change management approach enables change practitioners to identify adoption barriers early, replicate what’s working, and adjust interventions that aren’t delivering results.
How does organisational change maturity affect the change management process design?
Change maturity determines how quickly organisations can move through iterative cycles and how much structure they need. High-maturity organisations with established change management best practices, experienced change leadership, and strong governance can move rapidly and adjust decisively. They need less prescriptive guidance. Low-maturity organisations need more structured change management frameworks, more explicit governance, more support, and more time between iterations to consolidate learning. Your change management process should match your organisation’s starting point. Assessing change maturity before designing your process determines appropriate pace, structure, support requirements, and governance needs.
Why do you need continuous measurement throughout change implementation?
Continuous change monitoring and measurement reveals what’s actually driving adoption or resistance in your specific context, which is almost always different from planning assumptions. Change management tracking helps you identify adoption barriers early, discover what’s working and replicate it across other areas, adjust interventions that aren’t delivering results, and make evidence-informed decisions rather than guessing. Without ongoing measurement, you can’t answer critical questions about how to measure change management success, what change management performance metrics indicate problems, or whether your change initiatives are achieving intended outcomes. Measuring change management throughout implementation enables data-driven iteration that improves adoption rates with each cycle.
How does the change management process account for multiple concurrent changes?
The process recognises that people don’t exist in a single change initiative but experience multiple overlapping changes simultaneously. Effective enterprise change management maps the full change landscape, assesses cumulative impact and change saturation, considers sequencing to reduce simultaneous load, and builds support specifically for people managing multiple changes. Change governance at portfolio level coordinates across initiatives, prevents conflicting changes, monitors capacity, and makes prioritisation decisions. Single-change processes that ignore this broader context typically fail because they design for capacity that doesn’t actually exist and create saturation that prevents adoption.
What are the key phases in a modern change management process?
Modern change management processes progress through five key phases whilst remaining iterative: (1) Pre-Change Phase includes readiness assessment, change maturity evaluation, change landscape mapping, and baseline measurement. (2) Readiness Phase builds understanding of what’s changing and why it matters through multi-channel communication. (3) Capability Phase equips people with training, documentation, support, and practice opportunities. (4) Implementation and Reinforcement Phase launches change iteratively, measures results, identifies patterns, and adjusts approach between rollout cycles. (5) Embedment Phase embeds new ways of working, builds ongoing support capability, and continues measurement to ensure adoption sustains. Each phase informs the next based on data and learning rather than rigid sequential execution.
How do you measure change management effectiveness?
Measuring change management effectiveness requires tracking multiple dimensions throughout the change process: (1) Adoption metrics measuring who’s using new processes or systems and how proficiently. (2) Change readiness indicators showing awareness, understanding, commitment, and capability levels. (3) Behavioural change tracking whether people are actually changing how they work, not just attending training. (4) Performance impact measuring operational results against baseline. (5) Sentiment and engagement indicators revealing confidence, trust, and satisfaction. (6) Sustainability metrics showing whether adoption persists over time or reverts. Change management success metrics should be defined before implementation begins and tracked continuously. Effective measurement combines quantitative data with qualitative insights to understand both what’s happening and why.
What role does AI and technology play in the future of change management processes?
AI and digital platforms are transforming change management processes by enabling measurement and analysis at unprecedented scale and speed. Future change management leverages technology for continuous data collection across hundreds of touchpoints, pattern recognition that surfaces insights humans might miss, predictive analytics identifying adoption risks before they become critical, and automated change analysis generating recommendations. However, technology augments rather than replaces human expertise. AI identifies patterns and generates recommendations; humans provide strategic direction, contextual interpretation, and nuanced decision-making. The most effective approach combines digital platforms handling data collection and change management analytics with experienced change practitioners applying business understanding and wisdom to translate insights into strategy.
The pressure is relentless. Regulators demand compliance with new directives. Customers expect digital experiences rivalling fintech disruptors. Shareholders want innovation without compromising stability. Meanwhile, legacy infrastructure groans under the weight of systems built for control, not change. Welcome to transformation in financial services, an industry unlike any other.
The financial services sector operates in a category of its own. Unlike retail, manufacturing, or technology, where change initiatives carry significant stakes but primarily affect business performance, transformation in banking, insurance, and wealth management carries existential weight. A failed digital transformation in a retailer costs money. A failed compliance transformation in a bank costs money, reputation, regulatory penalties, customer trust, and potentially shareholder value. This distinction fundamentally reshapes everything about how transformation should be approached, measured, and defended to boards and regulators.
Change Maturity Challenges within The Financial Services Sector
What makes financial services transformation uniquely challenging is not just the volume of regulatory requirements, though that’s substantial. The real complexity lies in the paradox that defines the sector: institutions must simultaneously be risk-averse and innovative, compliant and agile, stable and transformative. This isn’t a contradiction to resolve; it’s a tension to master. And mastering it requires something most change management frameworks don’t adequately address: operational visibility, adoption tracking, and risk-aware decision-making that speaks the language senior leaders actually understand.
Yet here’s what often remains unexamined: financial services organisations exist across a spectrum of change maturity, and that maturity level is a more powerful predictor of transformation success than transformation budget, executive sponsorship, or project management rigour.
At the lower end of the spectrum, organisations treat change management as a project activity. A transformation initiative launches, a change team is assembled, stakeholder engagement campaigns are executed, and when the project concludes, the change team disperses. There’s little infrastructure for tracking whether changes actually stick, adoption curves plateau, or business benefits are realised. Change management is something you do during transformation, not something you measure and manage continuously.
At the mid-range of maturity, organisations begin to recognise that change management affects transformation outcomes. They invest in change management methodologies, train practitioners, and integrate change into project governance. However, change remains primarily qualitative. Adoption is measured through surveys. Stakeholder engagement is tracked through workshop attendance. Compliance is verified through spot-checks. There’s limited integration between change tracking and operational performance monitoring, so leaders often can’t distinguish between transformations that appear to be progressing but are silently failing from those that are genuinely succeeding.
At the highest levels of maturity – where a select group of leading financial services organisations have evolved: Change management becomes an operational discipline powered by integrated data infrastructure. These organisations instrument their transformations to capture real-time adoption metrics that correlate to behavioural change, not just system usage. They track operational performance against baseline as transformations roll out, distinguishing between temporary productivity dips (expected) and structural performance degradation (concerning). They maintain forward-looking compliance risk visibility rather than historical compliance status checks. They track financial impact in real time against business case assumptions. Most critically, they integrate these multiple streams of data into unified dashboards that enable senior leaders to make diagnostic decisions: “Adoption is tracking at 65% in this division. Why? Is it a training gap? A process design issue? Insufficient incentive alignment? Cultural resistance? Poor leadership communication?” Armed with diagnostic data rather than just descriptive metrics, leaders can intervene with precision.
This isn’t theoretical. Leading financial services institutions working with platforms like The Change Compass have achieved remarkable results by institutionalising this data-driven approach to change maturity. These organisations have moved beyond asking “Is our transformation on track?” to asking “What’s driving adoption patterns? Where are the operational risks emerging? How do we know we’re actually achieving the financial returns we projected?” By treating change as a measured, managed discipline with the same rigour applied to financial or operational metrics, they’ve fundamentally improved transformation success rates.
What’s particularly striking about these highly mature organisations is that their leadership in change management often goes unrecognised externally. They don’t shout about their change management capabilities – they’re simply unusually effective at executing large-scale transformations, navigating regulatory complexity with agility, and maintaining stakeholder alignment through extended change journeys. Other sector players notice their results but often attribute success to better technology, better project management, or better luck, rather than recognising it as the product of intentional, systematic investment in change maturity powered by data and business understanding.
The Regulatory Pressure Cooker
Financial services leaders face a compliance landscape that has fundamentally shifted. The cost of compliance for retail and corporate banks has increased by more than 60% compared to pre-financial crisis levels.[1] This isn’t simply a cost line item, it represents a structural constraint on innovation, a drain on resources, and a constant competitive pressure. The EU’s Digital Operational Resilience Act (DORA), evolving consumer protection regulations, anti-money laundering (AML) frameworks, and cybersecurity mandates create an overlapping web of requirements that demand both precision and speed.
What distinguishes financial services from other highly regulated sectors is the pace of regulatory change itself. New rules don’t arrive once every few years; they arrive continuously. Amendments cascade. Interpretations shift. Technology evolves faster than regulatory guidance can address it. The average bank currently spends 40% to 60% of its change budget on regulatory compliance initiatives alone, yet despite this substantial investment, a significant portion remains inefficient due to outdated approaches to implementation (Boston Consulting Group publication titled “When Agile Meets Regulatory Compliance” 2021).
This regulatory pressure creates the first major tension for transformation leaders: how do you drive innovation and modernisation when the majority of resources are consumed by compliance? How do you maintain stakeholder momentum for digital transformation when compliance demands keep arriving? And critically, how do you measure success when regulatory requirements were met but the transformation initiative itself faltered?
Institutions at lower maturity levels often stumble here because they lack integrated visibility into how regulatory changes cascade through their transformation portfolio. They may complete a compliance transformation on schedule, but without visibility into downstream operational impacts, adoption rates, or actual risk remediation, they’re flying blind. More mature organisations build change tracking into their compliance management processes, creating feedback loops that distinguish between compliance completion and genuine compliance behaviour change across the enterprise.
The Agility Paradox
Paradoxically, the same regulatory environment that demands risk-aversion increasingly requires agility. Regulations themselves are becoming more complex and iterative. The European Union’s Markets in Financial Instruments Directive II (MiFID II) began as an 80-page level 1 document. It expanded to more than 5,000 pages at implementation level. Traditional, sequential approaches to regulatory projects fail in this environment because they assume complete requirement certainty, an assumption that’s now unrealistic.
Leading institutions are discovering that agile change management approaches, when properly governed, can reduce IT spending on compliance projects by 20-30% whilst improving on-time delivery (Boston Consulting Group, “When Agile Meets Regulatory Compliance”). Yet many boards and senior leaders remain sceptical. The perception persists that agile methods are incompatible with the stringent governance and control frameworks financial institutions require. That perception is outdated, but it reflects a genuine leadership challenge: how do you embed agility into an institution whose cultural DNA and governance structures were designed for control?
This is where financial services diverges sharply from other sectors. A technology company can run experiments at speed, learning from failures as they occur. A fintech can pivot when market conditions change. A bank cannot. At least, it cannot without regulatory approval, compliance sign-off, and governance board endorsement. Yet this very rigidity – ironically designed to protect stability, often results in slower time-to-market, higher costs, and strategic misalignment when external conditions shift.
The solution lies not in abandoning risk management but in reimagining it. Agile risk management involves developing agile-specific risk assessments and continuous-monitoring programmes that embed compliance checks at every step of delivery, rather than at the end. This transforms risk management from a gate to a guardrail. When properly implemented, cross-functional teams including risk, compliance, and business units can move at pace whilst maintaining the governance rigour the sector demands.
However, this requires a fundamental shift in how financial services leaders think about transformation. Risk and compliance functions must transition from a “second line of defence” mindset, where they audit and approve – to a “design partner” mindset, where they collaborate from day one. Institutions with higher change maturity consistently outperform on this dimension because they’ve embedded risk and compliance perspectives into their change governance from the start, rather than treating these as separate approval gates.
The Cultural Challenge: Risk-Aversion Meets Innovation
Beyond the structural tensions lies a deeper cultural challenge. Financial services institutions have been shaped by risk-aversion. Conservative decision-making. Extensive approval chains. Multiple levels of governance. These practices evolved for good reasons, protecting customer deposits, maintaining market confidence, ensuring regulatory compliance. But they’ve also created institutional muscles that make experimentation difficult.
Yet innovation increasingly demands experimentation. How do you test a new customer journey without rolling it out at some level? How do you validate a new digital channel without risk? How do you innovate in payments, lending, or wealth management without trying approaches that haven’t been tested at scale before?
This isn’t a problem unique to financial services, but it’s more acute here because the cost of failure is higher. When an experiment fails in fintech, you iterate or pivot. When an experiment fails in a bank and affects customer accounts, regulatory reporting, or data security, the consequences cascade across multiple dimensions: customer trust, regulatory relationships, brand reputation, and potentially shareholder value.
Leading institutions are learning to create controlled experimentation frameworks – what might be called “risk-aware innovation.” This involves establishing sandbox environments where new approaches can be tested with limited exposure, clear guardrails, and robust monitoring. It requires explicit governance decisions about what degree of failure is acceptable in pursuit of learning and innovation. Most importantly, it demands transparency about the trade-offs: we’re accepting a marginal increase in risk here to capture an opportunity there, and here’s how we’re mitigating that risk and monitoring it.
For senior transformation leaders, this cultural challenge is often the hidden barrier to success. A technically excellent transformation can stall because the institution’s cultural immune system rejects change it perceives as risky. Conversely, a transformation that gets cultural buy-in by positioning itself as “low risk” may lack the ambition required to genuinely transform the organisation.
Notably, this is also where change maturity divergences become most visible. Lower-maturity organisations often treat cultural resistance as an engagement problem to be communicated away. More mature organisations recognise that cultural misalignment signals fundamental tensions between stated strategy and actual incentives, governance structures, and decision rights. The most mature organisations use change data – adoption patterns, stakeholder sentiment, engagement participation, as diagnostic tools to surface these tensions and address them systematically rather than through surface-level communication campaigns.
What Senior Leaders Really Need: Data Insights, Not Narratives
Here’s what often goes unstated in transformation discussions: senior leaders and boards don’t actually care about change management frameworks, adoption curves, or stakeholder engagement scores. What they care about is operational risk and business impact. They need to know: Is this transformation tracking on schedule? Where are the adoption barriers? What’s the actual impact on operational performance? Are we at risk of compliance failures? What’s the return on the investment we’ve made?
This is where many transformation programmes stumble. They’re often sold on change management narratives – compelling stories about the future state, cultural transformation, and employee empowerment. But when senior leadership asks, “What’s our operational status?” or “How do we know adoption is actually happening?” the answers are often too qualitative, too delayed, or too fragmented across systems to be actionable.
In financial services specifically, operational leaders think in terms that are measurably different from other sectors. They think about:
Regulatory Risk: Are we exposed to compliance gaps? Which processes remain unaligned with regulatory requirements? What’s our remediation timeline? What’s the forward-looking compliance risk as systems migrate and processes change?
Operational Performance Degradation: Digital transformations often produce a J-curve impact – performance gets worse before it gets better as teams adopt new processes. How steep is that curve? How long will degradation persist? What’s acceptable and what signals we need to intervene?
Adoption Velocity: Not just whether people are using new systems, but at what pace and with what proficiency. Which user groups are adopting fastest? Where are the holdouts? Which processes are being bypassed or manual-workarounded? Which features are underutilised?
Financial Impact: Cost savings from process efficiency. Revenue impact from faster time-to-market on new products. Reduction in remediation and rework costs. These need to be tracked not prospectively but in real time, so boards can assess actual ROI against business case projections.
Risk Incident Frequency: Are transformation activities introducing new operational risks? Is error rates increasing? Are compliance incidents rising? Are there early warning signals suggesting system instability or process breakdowns?
This is the data infrastructure many transformation programmes lack. They track adoption at a process level, but not operational performance at the transaction or customer level. They monitor compliance status historically, but not forward-looking compliance risk as changes roll out. They measure project milestones, but not business impact metrics that correlate to shareholder value.
Without this data, senior leaders operate from narrative and intuition rather than evidence. They can’t distinguish between a transformation that’s genuinely tracking well but communicated poorly from a transformation that appears to be on track but is actually masking emerging operational risks. This distinction is critical in financial services, where the cost of discovering operational problems at go-live rather than during implementation is exponentially higher.
How Change Management Software Supports Transformation
The shift toward data-driven change maturity requires fundamental reimagining of how change management is orchestrated. Leading financial services institutions are moving toward integrated platforms that provide real-time visibility into transformation performance across multiple dimensions simultaneously. Unlike traditional change management approaches that rely on periodic surveys, workshops, and engagement tracking, modern change management software instruments transformations to capture continuous, actionable data.
Effective change management software provides the infrastructure to capture and analyse:
Change management metrics and success measurement: Real-time dashboards tracking whether transformations are delivering on their intended outcomes. This goes beyond change management KPIs focused on activity metrics (how many people trained, how many workshops completed) to outcome metrics that correlate to actual business impact and adoption velocity.
Change monitoring and readiness assessment: Continuous monitoring of the organisational readiness for change, identifying which departments, teams, and individuals are ready to adopt new ways of working versus those requiring targeted support. Readiness for change models built into software platforms enable proactive intervention rather than reactive problem-solving after go-live.
Change management tracking and change analysis: Real-time visibility into where transformations stand operationally, financially, and from a compliance and risk perspective. Change management tracking systems that integrate with operational data provide diagnostic signals about what’s driving adoption patterns, where process gaps exist, and which interventions will be most effective.
Change management performance metrics and analytics: Integrated change management analytics that correlate adoption patterns with operational performance, compliance risk, and financial outcomes. These analytics answer critical questions: “We achieved 75% adoption in this division. Is that sufficient? How is operational performance tracking relative to baseline? Are compliance risks elevated as adoption occurs?”
Change management strategy alignment and change initiative orchestration: Platforms that connect individual change initiatives to broader transformation strategies, enabling leaders to understand how multiple concurrent changes interact, compound, or conflict. This is critical in financial services where organisations often juggle dozens of regulatory compliance changes, technology transformations, and process improvements simultaneously.
Change assessment and change management challenges identification: Sophisticated change assessment capabilities that surface emerging barriers early: Skills gaps, process misalignments, governance mismatches, stakeholder resistance, so leaders can intervene before they become critical blockers.
When integrated, this creates what might be called a transformation control tower – a unified view of where the transformation stands operationally, financially, and from a compliance and risk perspective. More importantly, it enables diagnostic analysis: “Adoption is tracking at 65% in this division. Why? Is it a training gap? A process design issue? Insufficient incentive alignment? Cultural resistance to change? Poor leadership communication?” Armed with diagnostic data rather than just descriptive metrics, transformation leaders can intervene with precision rather than generalised solutions.
The critical distinction in highly mature organisations is that they don’t treat change management software as a “nice to have” project reporting capability. Rather, they embed change data into the operating rhythm of the business. Change management success metrics feed into monthly leadership reviews. Change monitoring alerts surface automatically when adoption thresholds are breached. Compliance risk is assessed continuously rather than episodically. Financial impact tracking happens in real time, allowing course correction when actual performance diverges from projections. This represents a fundamental shift: change management tools and techniques are no longer about communicating and engaging during transformation; they’re about managing transformation as a continuous operational discipline.
In financial services specifically, this transforms how organisations approach the core tensions around regulatory compliance, agile delivery, and innovation. Change management software that provides integrated visibility into adoption patterns, operational performance, and compliance risk allows institutions to make evidence-based decisions about resource allocation, risk tolerance, and intervention timing. When a regulatory compliance change is rolling out, leaders can see in real time whether actual behaviour is changing or whether people are performing workarounds. When agile teams are experimenting with new delivery approaches, leaders have visibility into whether the controlled experimentation is introducing unacceptable risk or whether the risk envelope is being properly managed. When cultural transformation is underway, leaders can track sentiment changes, engagement patterns, and behavioural adoption rather than relying on post-implementation surveys that arrive months after critical decisions were made.
The most important insight from leading financial services institutions implementing advanced change management software is this: the software isn’t valuable because it’s smart. It’s valuable because it makes visible what’s traditionally been invisible and enables decision-making based on evidence rather than intuition or outdated frameworks.
Building Change Maturity Through Systems Thinking
Leading financial services institutions are moving toward platforms that provide real-time visibility into transformation performance across multiple dimensions simultaneously. They’re instrumenting their transformations to capture:
Adoption metrics that go beyond system login frequency to measure whether people are actually using processes correctly and achieving intended outcomes.
Operational metrics that track performance against baseline—speed, accuracy, error rates, compliance violations—as transformation rolls out and adoption occurs.
Risk metrics that provide forward-looking signals about compliance exposure, process gaps, and operational vulnerabilities introduced by transformation activities.
Financial metrics that track actual cost and revenue impact compared to transformation business case assumptions.
Sentiment and engagement data that provides early warning signals about adoption barriers, cultural resistance, or leadership alignment challenges.
The systems-based approach to change maturity, where change management data, decision-making infrastructure, and engagement strategies are integrated into the business operating model rather than existing as parallel activities, is what distinguishes the highest-performing organisations from the rest. It’s not just about having better data; it’s about embedding that data into how decisions actually get made.
In financial services, this data infrastructure serves an additional critical function: it builds credibility with regulators. When regulators ask about a major transformation, they want to know not just that it’s progressing, but that the institution has genuine visibility into operational risk and compliance impact. Real-time transformation metrics demonstrate that senior leadership isn’t simply hoping a transformation succeeds; it’s actively monitoring and managing it.
Financial Services: Setting Industry Standards
The institutions at the highest end of change maturity, particularly several leading financial services organisations working with The Change Compass, have become examples not just within their own sector but across industries. Their ability to embed change management data into business decision-making, coupled with their systematic development of change maturity through integrated platforms and systems thinking, sets a benchmark that other sectors increasingly aspire to.
These organisations have stopped trying to choose between risk-aversion and innovation. Instead, they’ve designed transformation approaches that embed risk management, compliance oversight, and governance into the rhythm of change rather than treating these as separate, sequential activities. They’ve instrumentalised their transformations to provide the operational visibility that financial services leaders demand and regulators expect. They’ve created cultural frameworks that position controlled experimentation and measured risk-taking as core capabilities rather than exceptions to risk-management doctrine.
What distinguishes these highly mature organisations is their recognition that change maturity isn’t an outcome of better training or more comprehensive change methodologies. Rather, it’s a product of intentional investment in systems that make change visible, measurable, and manageable as an operational discipline. These systems, platforms that integrate change management frameworks, adoption tracking, operational performance monitoring, compliance risk assessment, and financial impact analysis into a unified data infrastructure – become the foundation upon which genuine change maturity is built.
The organisations leading this charge have recognised that every transformation is also a data problem. The challenge isn’t just managing change; it’s creating the infrastructure to understand change in real time, with the granularity and speed that senior financial services leaders require. When adoption tracking integrates with operational performance data, when compliance risk monitoring links to adoption patterns, when financial impact analysis is informed by real-time adoption and performance metrics, the result is a fundamentally different quality of transformation management than traditional change management approaches can deliver.
Building the Transformation Your Industry Deserves
The transformation landscape in financial services has fundamentally shifted. It’s no longer sufficient to deliver a project on time and on budget. Success now requires delivering a project that moves adoption curves at pace, maintains operational performance through transition, manages regulatory compliance proactively, demonstrates clear financial returns, and positions the organisation for the next round of transformation. The institutions that will thrive are those that treat transformation not as a project delivery challenge but as an operational management challenge – one that demands real-time visibility, diagnostic capability, and decision-making infrastructure that translates transformation data into actionable insights.
Critically, this shift requires recognition that change maturity levels vary dramatically across the financial services sector. Some organisations remain in the lower maturity zones, treating change management as a project overlay. Others have built mid-level maturity, integrating change into project governance but lacking integrated data infrastructure. And a select group of leading institutions have recognised that genuine change maturity emerges from systematic investment in data platforms, business understanding, and decision-making infrastructure that embeds change into how the organisation actually operates.
The cost of getting this wrong is substantial. Major transformation failures in financial services cost tens and sometimes hundreds of millions in direct costs, opportunity costs, regulatory remediation, and customer attrition. The cost of getting it right, where transformations move at pace, adoption accelerates, compliance is maintained, and financial returns are delivered – is equally substantial in the other direction: cost savings from process efficiency, revenue acceleration from time-to-market advantage, risk mitigation that protects brand and regulatory relationships, and organisational capability that enables the next wave of transformation.
Digital transformation platforms purpose-built for financial services change management, platforms like The Change Compass – are increasingly central to this approach. These platforms provide the integrated data infrastructure that transforms senior leaders’ understanding of transformation progress from narrative and intuition to evidence and diagnostic insight. They make visible what’s traditionally been invisible: the real adoption curves, the operational performance impact, the compliance risk in real time, and the financial returns actually being achieved.
What’s particularly noteworthy is how some leading financial services clients have leveraged these platforms to build systemic change maturity, embedding change data into business decision-making, developing change capabilities through data-driven feedback loops, and creating the operational disciplines that enable consistent transformation success. These organisations have moved beyond simply tracking transformation progress to building genuine change maturity as an operational competency powered by continuous data collection, analysis, and decision-making integration.
By providing this visibility and infrastructure, these platforms enable the kind of proactive management that allows financial services institutions to navigate the paradox of being simultaneously risk-averse and innovative, compliant and agile, stable and transformative. The institutions that master transformation in financial services will be those that recognise change maturity as a strategic capability requiring systematic investment in data infrastructure and business understanding. Those that use that infrastructure to make decisions, intervene with precision, and continuously optimise as circumstances evolve. That’s the transformation approach financial services deserves—and the one that will define competitive advantage for the decade ahead.
Frequently Asked Questions: Financial Services Transformation and Change Management
What is the biggest barrier to transformation success in financial services?
Most financial services transformations fail not because of strategy or technology, but because change management is treated as a project activity rather than an operational discipline. Without real-time visibility into adoption, compliance risk, operational performance, and financial impact, senior leaders rely on narratives instead of evidence. This creates blind spots that hide adoption barriers and compliance gaps until after go-live, when correcting problems becomes exponentially more expensive.
What are the three levels of change maturity?
Level 1 (Project-Centric): Change treated as project overlay. Limited tracking of adoption or business impact. Problems surface at go-live.
Level 2 (Governance-Integrated): Change embedded in project governance. Adoption tracked qualitatively through surveys. Limited connection to operational performance metrics.
Level 3 (Data-Driven Operations): Change as continuous operational discipline. Real-time visibility into adoption velocity, compliance risk, operational performance, and financial ROI enables precision interventions and documented ROI.
Why does regulatory compliance dominate financial services change budgets?
Financial services institutions spend 40-60% of their total change budget on regulatory compliance initiatives. However, much of this investment is wasted due to outdated, sequential implementation approaches. When properly governed, agile change management approaches can reduce IT spending on compliance projects by 20-30% whilst improving on-time delivery is the key is embedding compliance into iterative delivery rather than treating it as a final gate.
What metrics should financial services leaders track for transformation success?
Adoption Velocity: Pace and proficiency of actual process usage, not system logins
Regulatory Risk: Forward-looking compliance exposure as adoption occurs
Operational Performance: Real-time impact on efficiency, accuracy, error rates against baseline
Financial Impact: Actual cost savings and revenue versus business case projections
Risk Incidents: New operational risks introduced by transformation activities
Without integrated data linking these metrics, leadership decisions remain guesswork rather than evidence-based.
How do leading financial services institutions balance innovation with risk-aversion?
They’ve stopped trying to choose. Instead, leading institutions build controlled experimentation frameworks with embedded risk monitoring—sandbox environments where new approaches are tested with limited exposure, clear guardrails, and robust monitoring. This transforms risk management from a blocker into a guardrail, enabling measured risk-taking and innovation within defined parameters. This is how the most mature firms navigate regulatory intensity while accelerating innovation.
What is the cost of poor change management?
Major transformation failures in financial services cost tens to hundreds of millions in direct costs, opportunity costs, regulatory remediation, and customer attrition. The difference between a lower-maturity organisation (treating change as a checkbox) and a higher-maturity organisation (with data-driven change discipline) can represent tens of millions in wasted spend, regulatory exposure, or competitive advantage. Strong change maturity enables cost savings, revenue acceleration, risk mitigation, and organisational capability.
How does change management software solve transformation visibility gaps?
Purpose-built change management platforms create a transformation control tower with unified visibility into adoption, compliance, operational performance, and financial impact in real time. Rather than discovering problems weeks after they occur, leaders see adoption stalls immediately and can diagnose why (training gap? process design issue? incentive misalignment?). This enables precision interventions instead of generalised solutions, transforming change management from reactive firefighting to proactive, data-driven orchestration.
The need for organizations to remain flexible and responsive to market demands has never been more critical, and scaled agile (SAFe) provide the framework to achieve this. Integrating change management work with SAFe is essential for seamless product delivery but yet is not clearly articulated in literature. However, for agile product delivery to be successful, it must be supported by robust change management work steps. Those that not ensures that all stakeholders are aligned and engaged throughout the process and also that the consecutive changes delivered are adopted. Let’s explore how change managers can effectively integrate their approaches with scaled agile methodologies to enhance product delivery.
Understanding the Intersection of Change Management and Agile
Change management and agile methodologies both aim to facilitate successful project outcomes, but they approach this goal from different angles. Change management focuses on the people side of change, ensuring that stakeholders are prepared, equipped, and supported throughout the transition through to benefit realisation. Agile methodologies, on the other hand, emphasize iterative development, continuous feedback, and rapid adaptation to change.
Whilst SAFe acknowledges the importance of managing the people side of change and leading the change, it does not spell out how exactly this work should be integrated with the methodology in a detailed manner. References to change tends to be at a high level and focuses on communication and readiness activities.
What are key call outs of the SAFe methodology:
1) Lean-Agile Principles: SAFe is grounded in Lean-Agile principles such as building incrementally with fast, integrated learning cycles, basing milestones on objective evaluation, and making value flow without interruptions. These principles help ensure continuous improvement and adaptability
2) Organizational Agility: To remain competitive, enterprises must be agile. SAFe enhances organizational agility by fostering Lean-thinking people and Agile teams, promoting strategic agility, and implementing Lean business operations
3) Lean Portfolio Management: Aligns strategy and execution by applying Lean and systems thinking. It includes strategy and investment funding, Agile portfolio operations, and Lean governance to ensure that the portfolio is aligned and funded to meet business goals
4) Continuous Learning Culture: Encourages a set of values and practices that promote ongoing learning and improvement. This culture is crucial for adapting to changes and fostering innovation within the organization
5) Agile Teams: Agile teams in SAFe operate using methods like SAFe Scrum or SAFe Team Kanban. These teams are responsible for understanding customer needs, planning their work, and delivering value continuously through iterative processes
6) Built-in Quality: Emphasizes the importance of quality at all stages of development. Practices include shift-left testing, peer reviews, and automation to ensure high standards and reduce defects early in the process
7) Value Stream Management (VSM): Focuses on optimizing the flow of value across the entire portfolio. VSM helps organizations improve their value delivery processes by managing and monitoring value streams effectively (Scaled Agile Framework).
8) Lean-Agile Leadership: Leaders play a critical role in fostering a Lean-Agile mindset. They must model the values and principles of SAFe, provide guidance, and create an environment that supports Agile teams and continuous improvement
9) Decentralized Decision-Making: Promotes faster value delivery by empowering teams to make decisions locally. This reduces delays, enhances product development flow, and fosters innovation
10) Customer-Centric Approach: Agile teams are encouraged to maintain close collaboration with customers to understand their needs better and ensure that solutions deliver real value. Techniques like direct customer interaction and feedback loops are essential
Below is a diagram from Scaled Agile Frameworks on key elements of a scaled agile product delivery framework.
Agile-Style Deliverable Artefacts
To support agile product delivery, change managers need to create agile-style deliverable artefacts early in the product delivery cycle. These artefacts serve as essential tools for aligning the team, stakeholders, and the overall change initiative with agile principles. They are significantly ‘lighter’ in volume and more succinct in focusing on key analysis points that determine approaches and actions required to plan and implement the change.
Change artefact 1: Change Canvas
An Agile Change Canvas is a strategic tool designed to plan, manage, and communicate change initiatives effectively within an organization. It begins with basic identification details such as the Project Name, Business Owner, and Author. This section ensures clear accountability and ownership from the outset.
The Change Vision & Objectives outlines the overarching project objectives and intended outcomes of the project. This architecture vision acts as a guiding star, ensuring all actions align with the desired future state of the organization. Following this, Core Challenges are identified to highlight potential obstacles that could impede progress. Recognizing these challenges early allows for proactive mitigation strategies.
Stakeholder Impacts analyses how different stakeholders will be affected by the change. This includes assessing both the positive and negative impacts on employees, customers, and shareholders, ensuring that their concerns are addressed and their needs met.
The Key Milestones section, presented in a table format, outlines significant checkpoints in the project timeline, often represented in Gantt charts. Each milestone is associated with a particular function, ensuring that progress is measurable and trackable. Similarly, the Resources section details the necessary financial, human, and technological resources required to implement the change, ensuring that the project scope statement is adequately supported.
Why Change section provides the rationale behind the need for change, which could include market demands, competitive pressures, or internal inefficiencies. This section justifies the project’s existence and urgency. Complementarily, What Will Change (WWC) describes the specific changes to be implemented, including processes, technologies, behaviours, and structures, offering a clear picture of the project’s scope.
Key Metrics are identified to measure the success of the change initiative. These metrics are both quantitative and qualitative, providing a comprehensive view of the project’s impact. Change Interventions listed in a table format, detail specific actions or initiatives designed to facilitate the change, ensuring a structured approach to implementation.
To foster a culture of innovation and adaptation, Change Experiments are proposed. These pilot programs test aspects of the change in a controlled environment before full-scale implementation. Finally, Change Risks identifies potential risks associated with the change and outlines strategies for mitigating these risks, ensuring that the project can navigate potential pitfalls effectively.
By incorporating these elements, the Agile Change Canvas provides a comprehensive framework for managing change initiatives, ensuring that all critical aspects are considered, planned for, and communicated effectively to stakeholders.
Using a Kanban board for change management activities provides a visual and dynamic method for tracking, prioritizing, and managing the flow of work while implementing changes. A Kanban board typically consists of columns that represent different stages of work, such as “To Do,” “In Progress,” and “Done.” For change management, additional columns might include “Proposed Changes,” “Under Review,” “Implementation Planning,” and “Monitoring.”
Whilst most change practitioners are used to kanban boards In working with various change management activities, there is opportunity to use kanban to plan and prioritise a series of agile-style changes and the associated change activities with each change. These ‘change cards’ within the kanban board presents a clear way to visualise a series of changes across the ‘delivery train’ where the project team continuously delivers pieces of change.
Prioritizing Change Management Activities
Visualizing Workflow:
Proposed Changes: This column lists all suggested changes, each represented by a card detailing the change’s purpose, impacted areas, and expected benefits.
Under Review: Changes move here once they are being evaluated for feasibility, risks, and alignment with project goals.
Implementation Planning: Approved changes are further detailed, including resource allocation, timelines, and specific tasks needed for implementation.
In Progress: Changes that are actively being worked on are tracked here, showing current status and any blockers encountered.
Monitoring: Recently implemented changes are monitored to ensure they are delivering the expected outcomes and to identify any issues early.
Done: Fully implemented and stabilized changes are moved here, marking their successful completion.
Setting Priorities:
Value and Impact: In conjunction with the project team prioritize changes based on their potential value and impact. High-value changes that significantly improve project outcomes or stakeholder satisfaction should be addressed first. From a change perspective, the input here is about the readiness of the stakeholder to receive the change, and what timing and work is required to get there.
Urgency and Dependencies: Changes that unblock other work or are time-sensitive should be prioritized. Dependencies between changes must be mapped to ensure logical sequencing. For example, work required to lift capability/leadership or readiness may be critical dependencies, without which the change cannot be delivered successfully.
Feasibility and Risk: Assess the feasibility and risks associated with each change. High-risk assessment of changes might require more careful planning and monitoring but should not necessarily be deprioritized if their impact is critical. The change input here is the people impact for the impacted stakeholders with other changes not just within this project/program, but with the overall portfolio or even outside the portfolio (including business-driven changes).
Proposed Changes: This column lists all suggested changes, each represented by a card detailing the change’s purpose, impacted areas, and expected benefits.
Under Review: Changes move here once they are being evaluated for feasibility, risks, and alignment with project goals.
Implementation Planning: Approved changes are further detailed, including resource allocation, timelines, and specific tasks needed for implementation.
In Progress: Changes that are actively being worked on are tracked here, showing current status and any blockers encountered.
Monitoring: Recently implemented changes are monitored to ensure they are delivering the expected outcomes and to identify any issues early.
Done: Fully implemented and stabilized changes are moved here, marking their successful completion.
Value and Impact: In conjunction with the project team prioritize changes based on their potential value and impact. High-value changes that significantly improve project outcomes or stakeholder satisfaction should be addressed first. From a change perspective, the input here is about the readiness of the stakeholder to receive the change, and what timing and work is required to get there.
Urgency and Dependencies: Changes that unblock other work or are time-sensitive should be prioritized. Dependencies between changes must be mapped to ensure logical sequencing. For example, work required to lift capability/leadership or readiness may be critical dependencies, without which the change cannot be delivered successfully.
Feasibility and Risk: Assess the feasibility and risks associated with each change. High-risk changes might require more careful planning and monitoring but should not necessarily be deprioritized if their impact is critical. The change input here is the people impact for the impacted stakeholders with other changes not just within this project/program, but with the overall portfolio or even outside the portfolio (including business-driven changes).
Ordering Change Planning and Implementation
Collaborative Planning:
Engage stakeholders and team members in planning sessions to discuss and agree on the priority of changes. This collaborative approach ensures that all perspectives are considered and that there is buy-in from those affected by the changes. This includes change champions.
Regular Review and Adaptation:
The Kanban board should be regularly reviewed and updated, within the change team and within the project team. During these reviews, re-prioritize changes based on new information, shifting project needs, and feedback from implemented changes. This iterative approach aligns with Agile principles of flexibility and continuous improvement.
Limit Work in Progress (WIP):
To avoid overloading the change team and ensure focus, limit the number of changes in progress at any given time. This constraint encourages the team to complete current tasks before taking on new ones, promoting a steady and manageable workflow.
Use Metrics and Feedback:
Utilize metrics such as cycle time (how long a change takes to move from start to finish, from awareness to engagement to eventual adoption) and work with the project team on the throughput (how many changes are completed in a specific timeframe) to assess the efficiency of the change management process. For example, based on the size and complexity of each discrete piece of change delivered, how long did this take and what was the deviance from actual time period planned? Feedback from these metrics should inform decisions about prioritization and process adjustments.
Engage stakeholders and team members in planning sessions to discuss and agree on the priority of changes. This collaborative approach ensures that all perspectives are considered and that there is buy-in from those affected by the changes. This includes change champions.
The Kanban board should be regularly reviewed and updated, within the change team and within the project team. During these reviews, re-prioritize changes based on new information, shifting project needs, and feedback from implemented changes. This iterative approach aligns with Agile principles of flexibility and continuous improvement.
To avoid overloading the change team and ensure focus, limit the number of changes in progress at any given time. This constraint encourages the team to complete current tasks before taking on new ones, promoting a steady and manageable workflow.
Utilize metrics such as cycle time (how long a change takes to move from start to finish, from awareness to engagement to eventual adoption) and work with the project team on the throughput (how many changes are completed in a specific timeframe) to assess the efficiency of the change management process. For example, based on the size and complexity of each discrete piece of change delivered, how long did this take and what was the deviance from actual time period planned? Feedback from these metrics should inform decisions about prioritization and process adjustments.
Benefits of Using Kanban for Change Management
Implementing a Kanban board for change management in Agile projects offers several benefits:
Transparency: Everyone involved can see the status of change activities, leading to better communication and coordination.
Flexibility: The board can be easily adjusted to reflect changing priorities and project dynamics.
Focus: Limiting WIP helps the team maintain focus and reduces the risk of burnout and task switching.
Continuous Improvement: Regular reviews and adaptations promote a culture of continuous improvement, ensuring that change management processes evolve and improve over time.
Change artefact example 3: Change Impact Assessment
A Change Impact Assessment (CIA) is an essential component in managing organizational change, particularly in agile projects where the focus is on iterative and incremental improvements. The assessment helps to understand the scope and magnitude of the change, identify affected stakeholders, and plan interventions to manage impacts effectively. An agile-friendly CIA is more summarised, and gets to the heart of what the impact is, who is impacted, how, to what extent, and when.
Below are the core elements of a change impact assessment, with a comparison to traditional methods:
1. Identifying the Impacts
Agile Approach: In scaled agile projects, the impact identification is ongoing and iterative. Each sprint or iteration is reviewed to assess the impacts of delivered changes. This dynamic approach ensures that emerging impacts are quickly recognized and addressed.
Traditional Approach: Impact identification is typically conducted at the beginning of the project, with periodic reviews. This method can be less responsive to new impacts discovered during the project lifecycle.
2. Stakeholder Identification and Analysis
Agile Approach: Continuous stakeholder engagement is crucial. Stakeholders are regularly consulted, and their feedback is integrated into the process. Agile methods ensure that stakeholders’ changing needs and concerns are promptly addressed.
Traditional Approach: Stakeholder analysis is often conducted early in the project, with limited ongoing engagement. This can result in less adaptability to stakeholders’ evolving requirements.
3. Extent and Nature of Impacts
Agile Approach: The extent of impacts is assessed incrementally, considering the cumulative effect of changes over multiple iterations. This allows for a nuanced understanding of how impacts evolve over time.
Traditional Approach: Typically focuses on a comprehensive initial assessment, with less emphasis on the evolution of impacts throughout the project.
4. Timing of Impacts
Agile Approach: Timing is aligned with the iterative delivery schedule. The impacts are mapped to specific iterations or sprints, allowing for precise planning and mitigation.
Traditional Approach: Timing is generally assessed at the project level, which can make it harder to pinpoint when specific impacts will occur during the project lifecycle.
Typical Sections of an Agile Change Impact Assessment
Impact Overview:
Explanation: Summarizes the nature and scope of the change, providing a high-level view of the anticipated impacts.
Agile Twist: Updated regularly with each iteration to reflect new findings and emerging impacts.
Stakeholder Impact Analysis:
Explanation: Identifies who will be affected by the change and how. It details the extent of the impact on different stakeholder groups.
Agile Twist: Involves continuous stakeholder feedback and updates to capture evolving impacts.
Impact Extent and Nature:
Explanation: Describes the extent (e.g., minor, moderate, significant) and nature (e.g., process, technology, cultural) of the impacts.
Agile Twist: Assessed incrementally, considering both immediate and long-term impacts across iterations.
Impact Timing:
Explanation: Specifies when the impacts are expected to occur, mapped to the project timeline.
Agile Twist: Aligned with sprint or iteration schedules, allowing for detailed timing predictions.
Mitigation Strategies:
Explanation: Outlines plans to manage and mitigate identified impacts.
Agile Twist: Adaptive strategies that are refined continuously based on iteration reviews and stakeholder feedback.
Monitoring and Review:
Explanation: Describes how the impacts will be monitored and reviewed throughout the project.
Agile Twist: Continuous monitoring with iteration-end reviews to ensure timely identification and management of impacts.
Explanation: Summarizes the nature and scope of the change, providing a high-level view of the anticipated impacts.
Agile Twist: Updated regularly with each iteration to reflect new findings and emerging impacts.
Explanation: Identifies who will be affected by the change and how. It details the extent of the impact on different stakeholder groups.
Agile Twist: Involves continuous stakeholder feedback and updates to capture evolving impacts.
Explanation: Describes the extent (e.g., minor, moderate, significant) and nature (e.g., process, technology, cultural) of the impacts.
Agile Twist: Assessed incrementally, considering both immediate and long-term impacts across iterations.
Explanation: Specifies when the impacts are expected to occur, mapped to the project timeline.
Agile Twist: Aligned with sprint or iteration schedules, allowing for detailed timing predictions.
Explanation: Outlines plans to manage and mitigate identified impacts.
Agile Twist: Adaptive strategies that are refined continuously based on iteration reviews and stakeholder feedback.
Explanation: Describes how the impacts will be monitored and reviewed throughout the project.
Agile Twist: Continuous monitoring with iteration-end reviews to ensure timely identification and management of impacts.
Stakeholder Engagement in a Scaled Agile Environment
Planning and designing stakeholder engagement activities in a scaled agile environment requires a dynamic, iterative approach that contrasts significantly with traditional, non-agile methods. In SAFe, the focus is on continuous collaboration, transparency, and adaptability, ensuring that stakeholders are actively involved throughout the project lifecycle.
Iterative and Continuous Engagement
Scaled Agile Approach: Stakeholder engagement is an ongoing process. Agile frameworks emphasize regular touchpoints, such as sprint reviews, planning meetings, and daily stand-ups, where stakeholders can provide feedback and stay informed about progress. These frequent interactions ensure that stakeholder input is continuously integrated, enabling swift adjustments and alignment with evolving needs. This iterative approach fosters a collaborative environment where stakeholders feel valued and engaged throughout the project. Engagement rhythms and processes should also be established not just at a project, but program, portfolio and enterprise levels as required.
Non-Agile Approach: Traditional methodologies often involve stakeholder engagement at fixed points in the project timeline, such as during initial requirements gathering, major milestone reviews, and final project delivery. This approach can lead to periods of limited communication and delayed feedback, which may result in misaligned expectations and missed opportunities for timely course corrections.
Flexibility and Adaptation
Scaled Agile Approach: Agile projects embrace change, allowing stakeholder engagement activities to be flexible and adaptive. As project requirements evolve, the engagement strategy can be adjusted to address new priorities or challenges. This flexibility ensures that stakeholder needs are consistently met, and any concerns are promptly addressed. Agile frameworks encourage a culture of openness and continuous improvement, where stakeholder feedback directly influences the direction of the project. Change managers need to ensure that stakeholder understand this fully, and have the skills to work within this context, not just with the project team but in leading their teams through change, when ‘the change’ may be constantly shifting.
Non-Agile Approach: In contrast, traditional approaches tend to follow a rigid engagement plan that is set at the project’s outset. While this provides a clear structure, it can be less responsive to changing stakeholder needs or external conditions. Adjusting the engagement strategy mid-project can be challenging and may require significant effort, leading to delays and potential dissatisfaction among stakeholders.
Collaborative Tools and Techniques
Scaled Agile Approach: Agile environments leverage a variety of collaborative tools and techniques to enhance stakeholder engagement. Digital platforms such as Jira, Confluence, and Miro facilitate real-time collaboration, transparency, and documentation. Agile ceremonies, such as retrospectives and demos, provide structured opportunities for stakeholders to participate and contribute. These tools and techniques help maintain a high level of engagement and ensure that stakeholders have a clear view of project progress and challenges.
Non-Agile Approach: Traditional methods might rely more heavily on formal documentation and periodic reports for stakeholder communication. While these methods ensure thorough documentation, they can sometimes create barriers to real-time collaboration and immediate feedback. Meetings and reviews are often scheduled infrequently, which can lead to less dynamic interaction compared to agile practices.
Planning Stakeholder Engagement Activities
Regular Touchpoints: Schedule frequent meetings and reviews to ensure continuous stakeholder involvement. Examples include sprint reviews, iteration planning meetings, and daily stand-ups. Business-led rhythm that enable the dissemination and engagement of updates to teams is also critical.
Flexible Engagement Plans: Develop engagement strategies that can be easily adapted based on stakeholder feedback and changing project requirements.
Use of Collaborative Tools: Implement digital tools that facilitate real-time collaboration and transparency. Tools like Jira and Confluence can help keep stakeholders informed and involved. Non-digital engagement tools may also be leveraged to fully engage with stakeholders, beyond one-way push communication. Assessment needs to be made of the openness and ability to engage regarding the change through the chosen channels.
Active Feedback Loops: Establish mechanisms for collecting and integrating stakeholder feedback continuously. This can be done through retrospectives, surveys, and informal check-ins.
Clear Communication Channels: Maintain open and clear communication channels to ensure that stakeholders can easily provide input and receive updates on project progress.
As mentioned previously, the change approach, including engagement approaches, need to take into account the broader organisational context of program, portfolio and enterprise levels. This may mean mapping out the various channels and how they can be used for different changes, stakeholders and organisational levels.
Supporting Agile Delivery Cadence
To align change management activities with agile delivery cadence, it’s essential to integrate them into the core agile events, such as PI (Program Increment) planning and demos. Here’s how:
PI Planning
PI planning, or program increment planning, is a critical event in the agile framework, where teams come together in the PI planning process to plan and commit to a set of objectives for the next increment. During PI planning sessions or PI planning events (including team breakouts), ensure that change management considerations are part of the discussion. This involves:
– Including Change Management Objectives within PI objectives and program vision: Ensure that change management objectives and organizational readiness are included in the PI planning agenda as a critical part of project management. This helps align the change activities with the overall delivery goals.
– Identifying Change Risks and Dependencies: Identify any dependencies related to the change initiative that may impact the delivery schedule and the overall agile release train. This ensures that potential risks are addressed early and do not disrupt the delivery process. Common considerations include the various people change impacts across the program and how they intersect or overlap
– Engaging Stakeholders: Involve key stakeholders in the PI planning sessions. This ensures that not just product managers but business stakeholders understand the change objectives and are committed to supporting the change initiative during the implementation process. PI planning is also a great opportunity to assess and see in action the level of engagement, support and potential leadership skills of key stakeholders to reach the common goals and business benefits.
Demos
Demos are an opportunity to showcase the progress of the agile teams and gather feedback from stakeholders as a part of the iteration plans and sprint planning. Use demos to communicate the benefits and progress of change initiatives within the entire agile release train. Engaging stakeholders in these demos can help them see the value and stay committed to the implementation plan. Here’s how:
– Highlighting Change Benefits: During demos, highlight the benefits of the change initiative and how it supports the overall product delivery goals. This helps stakeholders understand the value of the change and its impact on the project.
– Gathering Feedback: Use demos as an opportunity to gather feedback and user stories from stakeholders. This helps identify any concerns or areas for improvement and ensures that the change initiative remains aligned with stakeholder needs.
– Showcasing Progress: Showcase the progress of the change initiative during demos. This provides stakeholders with a clear understanding of how the change is evolving and the positive impact it is having on the project.
By embedding change management activities into these agile ceremonies, change managers can ensure that change initiatives are aligned with the delivery schedule and maintain stakeholder buy-in.
Implementing Change Activities as Small Experiments
One of the key principles of agile is to work in small increments and learn quickly. Change management activities can adopt this approach by implementing small experiments, such as:
Messaging
Test different communication messages to see which resonates best with stakeholders. Gather feedback and refine the messaging based on reactions. This iterative approach ensures that the communication strategy is effective and supports the change initiative. Consider the following:
– A/B Testing: Use A/B testing to evaluate different messages. This involves sending two variations of a message to different stakeholder groups and comparing the responses to determine which one is more effective.
– Feedback Collection: Collect feedback from stakeholders on the messaging. This can be done through surveys, focus groups, or informal conversations.
– Message Refinement: Refine the messaging based on the feedback received. This ensures that the communication remains relevant and impactful.
Stakeholder Involvement
Experiment with various levels of stakeholder involvement to determine the most effective way to engage them. Use these insights to inform future engagement and risk management strategies and your overall implementation strategy. Here’s how:
– Pilot Programs: Implement pilot programs with small groups of stakeholders to test different involvement strategies. This provides valuable insights into what works best and helps refine the engagement approach.
– Engagement Metrics: Track engagement metrics to evaluate the effectiveness of different involvement strategies. This includes participation rates, feedback quality, and overall stakeholder satisfaction.
– Iterative Adjustments: Make iterative adjustments to the involvement strategies based on the insights gained. This ensures that stakeholder engagement remains effective and aligned with the change initiative.
By treating change activities as experiments, change managers can adapt quickly to what works best, ensuring a smoother integration with the agile delivery process.
Best Practices for Integrating Change Management with Agile
Successfully integrating change management with agile methodologies requires a strategic approach. Here are some best practices to consider:
Foster Collaboration
Encourage collaboration between change managers and agile teams, as well as key business stakeholders within the business context. This helps ensure that different disciplines and functions are aligned and working towards the same goals. Consider the following strategies:
– Joint Planning Sessions: Conduct joint planning sessions to align change management activities with agile delivery approaches and schedules. This ensures that both disciplines are working towards the same objectives.
– Regular Communication: Establish regular communication channels between change managers and agile teams. This helps keep everyone informed and ensures that any issues or concerns are addressed promptly. Specifically focus on various agile roles such as UX (user experience), business analysis, testing, and portfolio management. There are key intersections of change work and each of these disciplines, beyond general project planning and coordination.
The below is an example of a portfolio level adoption dashboard from The Change Compass.
Change Data-Driven Insights is absolutely a Must-have for SAFe
In SAFe, change management driven by data insights is critical to ensure that changes are not only effective but also efficient and sustainable. Data-driven change management leverages quantitative and qualitative data to guide decisions, optimize processes, and align strategic goals across the organization. By incorporating metrics and analytics, organizations can gain a comprehensive understanding of the impact and progress of change initiatives, allowing for timely adjustments and informed decision-making.
At the portfolio level within a SAFe setting, data-driven insights are essential for prioritizing initiatives and allocating resources effectively. More than this, change data including stakeholder capability, readiness and impact levels can be critical to determine when releases should happen, the priority of releases, and the sequencing of releases.
Ill-prepared or insufficiently skilled stakeholders may require longer time to adapt to the change. Also, looking beyond the project itself, by understanding the overall change landscape for the impacted stakeholders, change releases may need to be chunked and packaged accordingly to maximise adoption success.
Key attention should also be paid to the impact on business performance of impacted stakeholders, not just from a change volume perspective, but also from a strategy perspective in terms of how best to reduce risk of performance disruptions. Is it through exemplary middle leadership? Or frontline engagement? Or the power of change champions embedded across the business?
At the enterprise level, data-driven change management enables organizations to scale agile practices consistently and coherently across the entire team across multiple portfolios. This involves the use of enterprise-level dashboards and analytics tools that provide a holistic view of the organization’s agile transformation. Key performance indicators (KPIs) such as employee impact data, adoption rates, readiness metrics and productivity metrics help leaders assess the effectiveness of change initiatives and identify areas that require additional support or intervention. For instance, tracking the adoption rate of agile practices across different departments can highlight areas where additional training or coaching is needed to ensure consistent implementation.
Integrating change management with scaled agile methodologies is essential for seamless product delivery in today’s dynamic business environment. By creating agile-style deliverable artefacts early, continuously adapting engagement activities, supporting agile delivery cadence, and implementing change activities as small experiments, measure change progress and outcomes, change managers can effectively support agile product delivery. This integration not only enhances the success of change initiatives but also ensures that product delivery is seamless and aligned with organizational goals and the strategic plan.
By fostering collaboration, embracing agile principles, and using data-driven insights, change managers can create a cohesive strategy that maximizes the benefits of both change management and agile methodologies. This holistic approach ensures that change initiatives are successful, stakeholders are engaged, and product delivery is efficient and effective.
Chat to us to find out more about how to leverage the power of a change measurement platform to sustain your single source of truth to support your scaled agile organisation.
Agile methodology is fast becoming the ‘norm’ when it comes to project methodology. There are strong benefits promised of faster development time, the ability to morph with changing requirements, less time required to implement the solution, and a better ability to meet project objectives through continuous improvement. There aren’t too many organisations that do not use some form of agile project methodology in how they manage initiatives.
What started out as a way of developing software has evolved into the accepted methodology for managing projects. A scan of literature available on the internet shows a significant outline of the various roles, including the product owner and the development team, and their importance to stakeholders, including end users, in the agile project methodology process. Most roles are clearly outlined and accounted for. There are clear roles established for the business owner, the project manager, the scrum master, developers, testing and quality, product manager, architect, human-centred designer, and even IT operations.
However, there is a glaring gap. What about the role of the change manager?
A review of literature available through project management organisations such as APM (Association of Project Management) and PMI (Project Management Institute) showed glaring omission of the role of the change manager or change management practitioners from agile methodology. The same is also true for Scaled Agile Frameworks where there is a brief mention of the importance of change management in the agile approach, but no mention of the role of the change manager/practitioner.
Is it that there are less projects requiring change managers?
The evidence is against this hypothesis. Jobs in change management are plentiful, with data on ‘Indeed’ online employment portals pulling up over 38,000 job postings. On top of this, there is an increasing number of jobs posted. According to the U.S. Bureau of Labor Statistics, “management analytics” which includes change management, is projected to have a 14% growth rate between 2018 and 2028. In Australia, the ‘Seek’ employment platform projected change management job growth to be at 15% growth in the next 5 years.
Is it that agile methodology is more for technical projects and therefore the omission of change managers?
The agile approach and agile manifesto can be used for a range of different projects, but not all projects. There is certainly evidence of agile project methodology used by software developers in a wide range of industries from financial services, government, non-profit, pharmaceuticals, utilities, and retail industries. The agile methodology is commonly cited for being better for projects where the outcome is not clearly known and where the end change has a level of uniqueness. There are times, though, when waterfall methodology is more appropriate, depending on the situation.
However, it is not true that agile methodology is only used for more technical projects. Even for projects where the focus is not on technical development, agile approaches are used widely. Agile changes have been used for re-organisation exercises. Here is an example from the Business Agility Institute. Executive teams also use agile means to manage various strategic initiatives that are not technical. Agile approaches are even applied to managing church initiatives.
What is the likely reason for the clear omission of change management in the agile methodology?
Organisations in charge of documenting agile methodology are mainly focused on project management and software development. If we take the examples of PMI and APMG, both are project management associations, and both are focused on the project management perspectives of agile, particularly in complex environments. The portion on organizational change management is a specialism of project management. It could be that these organisations have not sufficiently developed agile change management methodology to integrate with agile project management.
Organisations in charge of documenting agile methodology are mainly focused on project management and software development, and not include the agile change management process. If we take the examples of PMI and APMG, both are project management associations, and both are focused on the project management perspectives of agile. The portion on organizational change management is a specialism of project management. It could be that these organisations have not sufficiently developed agile change management methodology to integrate with agile project management.
Even at Scaled Agile, which is about applying agile across the organisation, the omission of the role of change managers is still the case. Frameworks from Scaled Agile are quite detailed and rigorous. All aspects of the roles of various organisational members, including scrum teams, are clearly outlined. Even the role of IT departments in DevOps are clearly spelled out to support agile. But not the role of change managers. Again, this could be due to those at Scaled Agile not having a change management background, and therefore not being able to articulate the various role detail.
However, there are some very critical roles that change practitioners play not only at project level, but at program, epic, and organisational levels. Without the right change management support the following are key risks when organisations are working at SaFe (scaled agile) level:
Change sequencing to maximise adoption across the change portfolio
Packaging change to achieve optimal change adoption, e.g. in terms of integrating communications and learning interventions across projects
Establishing business unit based change champions that can support multiple projects and can help piece together different changes for impacted employees
There are some attempts at closing the gap to document agile change management approaches as a part of the change management process. However, most are conceptual, high level, and not sufficiently detailed to provide clear guidance and practical application for the change practitioner. On the other hand, the work of change management in agile projects should not only be clear for the change practitioner but also be clear for the project manager and other project members.
What’s the problem of omitting the role of change managers from agile methodologies?
1. The role of change management could easily be omitted. Particularly for less experienced project managers who are starting out in agile. The risk could be that change management is omitted from the project altogether since it is not called out as a clear role
2. Change practitioners and agile practitioners are not clear with the roles they play and therefore are not sufficiently involved in driving and supporting the project in the right way. Since there is not a clear set of guidelines and agile principles methodology for change practitioners, it is common to see varying approaches in how change managers support agile projects within the current business environment, with some still using a similar approach as to supporting traditional change management and waterfall projects which may not be appropriate.
3. Agile projects are not successful because change management work is not sufficiently incorporated into agile processes, particularly in the context of digital transformation. With change management roles not spelt out, the project executes the change without critical change management foundations, and therefore, by embracing agile thinking, it is at the risk of not achieving the adoption, adaptation, and benefit realisation targeted.
What should we do about this?
1. Encourage change management associations such as CMI and ACMP to invest in detailing agile change management methodology in a way that sets standards and guidelines for change management skills practitioners to follow.
2. Influence and work with APMG, PMI and Scaled Agile to include explicitly the role of change managers and agile change management methodology.
Change management is emerging to be a strong discipline that executives are starting to recognise as critical to successful change. The role of change practitioners should be stated explicitly and recognised clearly. Change managers should not have to tip-toe in maneuvering their place in supporting agile change projects, nor should they need to convince other project team members of their place throughout various agile routines and methodology phases. It is now time for the change community to drive this and achieve the recognition that it deserves.
