Change management is a critical discipline for organizations navigating today’s fast-paced and complex business environment. At its core, change management refers to the structured approach and set of processes that organizations use to transition individuals, teams, and entire organizations from a current state to a desired future state. The ultimate goal is to drive adoption of new processes, technologies, or strategies while minimizing resistance and disruption.
The Enduring Influence of Classic Change Management Models
For decades, organizations have relied on a handful of classic change management models to guide their transformation efforts. These foundational frameworks have shaped the way leaders think about change, offering structured methodologies to manage the human and operational challenges that accompany organizational shifts.
Some of the most widely recognized traditional models include:
Lewin’s 3-Stage Model of Change: Developed in the 1950s, Kurt Lewin’s model breaks change into three simple steps: Unfreeze, Change, and Refreeze. The unfreezing stage involves preparing the organization for change by challenging the status quo. The change stage is the implementation phase, where new processes or behaviors are introduced. Finally, the refreezing stage aims to solidify these changes as the new norm, embedding them into the organization’s culture and operations.
McKinsey 7S Model: This model emphasizes the importance of aligning seven key elements—Strategy, Structure, Systems, Shared Values, Style, Staff, and Skills—to achieve successful change. The 7S framework highlights the interconnectedness of organizational components and the need for holistic alignment during transformation.
Bridge’s Transition Model: Unlike models focused primarily on processes and systems, Bridge’s model centers on the psychological and emotional transitions individuals experience during change. It outlines three phases: Letting Go, The Neutral Zone, and The New Beginning, recognizing that emotional responses can be a major source of resistance.
ADKAR Model: While slightly more contemporary, the ADKAR model remains a staple in many organizations. It focuses on five building blocks for successful change: Awareness, Desire, Knowledge, Ability, and Reinforcement.
These classic models have provided organizations with blueprints for managing change, helping leaders anticipate challenges, structure their communications, and guide employees through transitions. They have been especially valuable in large, hierarchical organizations where clear, step-by-step processes are necessary to coordinate efforts across multiple teams and layers of management.
Limitations of Traditional Change Models
Despite their enduring popularity, research has increasingly shown that many of these traditional models have limited efficacy in today’s dynamic business world. The pace of change has accelerated, and organizations now face more complex, interconnected, and unpredictable challenges than ever before. As a result, the linear, stepwise approaches of older models can struggle to keep up with:
Rapid technological advancements that require agile and iterative approaches.
Cross-functional collaboration that blurs traditional organizational boundaries.
Continuous transformation, rather than discrete, one-off change initiatives.
Employee expectations for transparency, empowerment, and participation in the change process.
Many of these models were developed in an era when change was infrequent and could be managed as a discrete event. Today, change is constant, and organizations must be able to adapt quickly and continuously. This has led to a growing recognition that newer, more flexible and evidence-based change management models are needed to address the realities of modern business.
The Shift Toward Modern Change Management Approaches
In response to these limitations, new change management models have emerged, informed by recent research and the evolving needs of organizations. These models tend to emphasize:
Behavioral science and data-driven insights to understand and influence employee behavior more effectively.
Agility and adaptability, allowing organizations to respond rapidly to change and iterate their approaches as needed.
Employee engagement and co-creation, recognizing that successful change depends on active participation and buy-in from those affected.
Continuous measurement and feedback, using real-time data to assess progress and adjust strategies on the fly.
Here are some examples of modern models:
Fogg Behavior Model: Applies behavioral science principles to drive sustainable change by focusing on motivation, ability, and prompts.
Agile Change Management: Uses iterative planning, rapid feedback, and cross-functional collaboration to enable organizations to adapt quickly.
Self-Determination Theory (SDT): Emphasizes the importance of intrinsic motivation by fostering autonomy, competence, and relatedness among employees. Change initiatives grounded in SDT encourage choice, participation, and personal relevance, leading to more sustainable and meaningful change.
User-Centric Design: Focuses on designing change interventions around the needs, preferences, and experiences of end users. By deeply understanding what motivates and frustrates employees, organizations can co-create solutions that drive engagement and adoption.
A lot of popular change management models are old models, many of which have been shown by research to have limited efficacy in the business world. Nevertheless, some of these models are still referred to as the core ‘pillars’ of change management. What are newer change management models that have been shown by research to have better validity?
Comparing Classic and Modern Change Management Models
The landscape of change management has evolved significantly, with organizations increasingly recognizing the need to move beyond traditional frameworks. Below is a detailed comparison of classic and modern change management models, highlighting their core characteristics, strengths, and limitations.
Classic Change Management Models
Classic models, such as Lewin’s 3-Stage Model, McKinsey 7S, and ADKAR, have long served as the foundation for organizational change initiatives. These models share several defining features:
Linear, Stepwise Approach Classic models typically follow a sequential process. For example, Lewin’s model moves from Unfreeze to Change to Refreeze, while ADKAR progresses through Awareness, Desire, Knowledge, Ability, and Reinforcement.
Top-Down Implementation Change is often driven by leadership, with plans and communications cascading down through the organization. This structure assumes that senior leaders set the direction and employees follow.
Focus on Process and Structure Traditional models emphasize formal processes, organizational structures, and systems alignment. The McKinsey 7S model, for instance, stresses the importance of aligning strategy, structure, and systems to achieve successful change.
One-Off Initiatives These models are designed for discrete change projects—such as a merger, system upgrade, or restructuring—rather than ongoing transformation.
Strengths of Classic Models:
Provide clear, step-by-step guidance, making them easy to communicate and implement.
Useful for large, hierarchical organizations with established chains of command.
Effective for managing straightforward, well-defined changes.
Limitations of Classic Models:
Can be rigid and slow to adapt to unexpected developments.
Often overlook the emotional and behavioral aspects of change.
May struggle in environments where change is continuous and unpredictable.
Modern Change Management Models
Modern models have emerged in response to the increasing complexity and speed of change in today’s business environment. These frameworks are characterized by:
Agility and Iteration Modern models embrace flexibility, allowing organizations to adapt quickly as circumstances evolve. Change is seen as an ongoing process rather than a linear journey.
Behavioral Science and Data-Driven Insights Newer models use research from psychology and behavioral economics to understand how people respond to change. Techniques such as nudging, habit formation, and real-time feedback are integrated to drive sustainable adoption.
Employee Engagement and Co-Creation Rather than being imposed from the top down, change is co-created with employees. This approach values transparency, open communication, and active participation, fostering a sense of ownership and reducing resistance.
Continuous Measurement and Feedback Modern models leverage digital tools and analytics to monitor progress, gather feedback, and adjust strategies in real time. This ensures that change initiatives remain relevant and effective.
Examples of Modern Models:
Fogg Behavior Model: Focuses on the interplay of motivation, ability, and prompts to drive behavior change.
Agile Change Management: Applies agile principles—such as iterative planning, cross-functional collaboration, and rapid prototyping—to change initiatives.
Digital-First Frameworks: Use technology and automation to streamline change processes and provide actionable insights.
Strengths of Modern Models:
Highly adaptable to fast-changing environments.
Address both the rational and emotional dimensions of change.
Foster a culture of continuous improvement and innovation.
Limitations of Modern Models:
May be challenging to implement in organizations with deeply entrenched hierarchies or resistance to new ways of working.
Require a higher level of change management capability and digital literacy.
Classic vs. Modern Change Management Models
Aspect
Classic Models
Modern Models
Approach
Linear, stepwise
Iterative, agile
Leadership Style
Top-down
Collaborative, participatory
Focus
Process, structure
Behavior, engagement, data
Change Type
Discrete, one-off
Continuous, ongoing
Tools & Techniques
Templates, checklists
Digital tools, analytics, nudges
Employee Role
Recipients of change
Co-creators of change
Measurement
Periodic, post-implementation
Real-time, continuous
When to Use Each Approach
While modern models offer clear advantages in today’s environment, classic frameworks still have their place—particularly for well-defined, large-scale projects with clear objectives and timelines. In contrast, modern models are better suited to organizations facing ongoing transformation, rapid innovation, or the need for cultural change.
The most effective change leaders often blend elements from both approaches, tailoring their strategies to the unique needs of their organization and the specific challenges at hand.
Applying Modern Change Management Models—Practical Steps for Success
Adopting modern change management models requires organizations to rethink traditional approaches and embrace new ways of driving transformation. Below are practical, action-oriented steps for effectively applying contemporary change management principles, ensuring that change is not only implemented but also sustained.
1. Start with a Clear Vision and Purpose
Define the “Why”: Articulate the underlying purpose of the change. Employees are more likely to support transformation when they understand its rationale and how it aligns with organizational values and goals.
Connect to Strategy: Ensure the change initiative is directly linked to broader business objectives. This alignment helps prioritize resources and maintains focus.
2. Engage Stakeholders Early and Often
Co-Create Solutions: Involve employees, customers, and key stakeholders in designing the change. Use workshops, focus groups, and digital platforms to gather input and foster ownership.
Transparent Communication: Maintain open, two-way communication channels. Share progress, setbacks, and successes honestly to build trust and reduce uncertainty.
3. Leverage Behavioral Science and Data
Map Behaviors: Identify specific behaviors that need to change. Use behavioral mapping to clarify what actions drive desired outcomes.
Apply Nudges and Prompts: Introduce subtle cues, reminders, or incentives that make it easier for people to adopt new behaviors. For example, digital prompts or recognition programs can reinforce positive actions.
Monitor with Analytics: Use digital tools to track adoption rates, engagement, and feedback in real time. Adjust strategies based on what the data reveals.
4. Build Agility into the Change Process
Iterative Implementation: Break the change into manageable phases or sprints. Test solutions on a small scale, gather feedback, and refine before rolling out more broadly.
Empower Local Teams: Give teams the autonomy to adapt change initiatives to their unique context. Encourage experimentation and learning from both successes and failures.
5. Foster a Culture of Continuous Improvement
Encourage Feedback Loops: Regularly solicit feedback from all levels of the organization. Use quick surveys, digital suggestion boxes, or team retrospectives to surface insights.
Celebrate Small Wins: Recognize and reward progress, not just final outcomes. Celebrating incremental achievements helps sustain momentum and reinforces positive change.
Adapt and Evolve: Be prepared to pivot strategies as new information emerges. Continuous improvement means viewing change as an ongoing journey, not a one-time event.
6. Equip Leaders and Employees for Success
Upskill Change Leaders: Provide training in agile methodologies, data analytics, and behavioral science. Modern change leaders need a diverse toolkit to navigate complexity.
Support Employees: Offer resources such as coaching, peer networks, and digital learning modules to help employees build confidence and competence during transitions.
7. Sustain Change with Reinforcement and Measurement
Embed Change in Systems: Update policies, processes, and technologies to reflect new ways of working. This institutionalizes change and reduces the risk of reverting to old habits.
Continuous Measurement: Use dashboards and key performance indicators (KPIs) to track progress. Share results openly and use them to guide ongoing adjustments.
Practical Example: A large financial services firm sought to implement a digital-first customer service model. Instead of mandating the change from the top, leaders formed cross-functional teams to co-design new workflows. Behavioral nudges—such as digital prompts and peer recognition—encouraged adoption. Real-time analytics tracked customer satisfaction and employee engagement, allowing for rapid adjustments. Regular feedback sessions and visible celebration of milestones helped embed the new model as “the way we work.”
Final Thoughts
Organizations that thrive in today’s environment are those that treat change as a continuous, collaborative, and data-informed process. By applying modern change management models—grounded in behavioral science, agility, and real-time measurement—leaders can drive transformation that is not only effective but also enduring. The key is to blend clear vision, stakeholder engagement, and adaptive execution, ensuring that change becomes a core organizational capability rather than a disruptive event.
Analytics capability is emerging to be one of the most critical capabilities for companies in the digital world. How effective a company is able to use data to drive efficiency, effectiveness and overall business improvement is the ultimate competitive advantage. Through the ability to use data companies can improve decision making and greater ability to execute on its strategies.
In the same manner how effective a company is in building change analytics capability is emerging to be a critical capability in implementing change.
Download our infographic to understand more about the key elements in building change analytics capability in your organisation.
Change management data is the lifeblood of effective organizational transformation. Its collection and analysis provide the evidence needed to guide decisions, measure impact, and ensure that change initiatives deliver real value. By focusing on the extraction of actionable insights from this data, organizations can move beyond intuition and anecdote, and instead rely on objective, evidence-based strategies.
Change management data is the lifeblood of effective organizational transformation. Its collection and analysis provide the evidence needed to guide decisions, measure impact, and ensure that change initiatives deliver real value. By focusing on the extraction of actionable insights from this data, organizations can move beyond intuition and anecdote, and instead rely on objective, evidence-based strategies.
Why Change Management Data Matters
Change management data refers to the information collected throughout the change process – before, during, and after implementation. It includes quantitative metrics such as productivity, turnover rates, and customer satisfaction, as well as qualitative feedback from surveys, interviews, and focus groups. Process data – tracking training completion, adherence to timelines, and communication effectiveness – also plays a critical role. Financial data, such as cost savings and ROI, further rounds out the picture.
This data is essential for:
Assessing the current state of the organization and identifying gaps or opportunities for improvement.
Measuring the effectiveness of change initiatives and comparing outcomes to expected goals.
Identifying risks and resistance, allowing organizations to proactively address challenges.
Providing evidence-based recommendations for continuous improvement and future initiatives.
Collecting the Right Data
The process of extracting meaningful insights begins with identifying the right data to collect, paying attention to the type of raw data collected that informed decisions. Organizations should start by defining their objectives and determining which key performance indicators (KPIs) will best measure success. By following a few key steps, organizations can effectively analyze their data. Questions to consider include:
What outcomes do we want to measure?
Which data sources and methods are most appropriate?
How frequently should we gather data?
For example, quantitative data can be gathered through workforce analytics software, while qualitative insights often come from employee surveys or interviews, customer feedback, observation of customer behaviour, etc. Process types of data may require a mix of manual and automated methods to derive valuable insights, depending on the complexity of the change initiative.
Analyzing Change Management Data for Insight
Once data is collected, robust data analytics techniques are needed to extract actionable results. Common approaches include:
Descriptive analytics: Summarizing historical data to understand trends and patterns.
Predictive analytics: Using past data to forecast future outcomes, such as the likelihood of resistance or adoption rates.
Sentiment analysis: Analyzing feedback and communication to gauge employee emotions and attitudes.
Network analysis: Mapping relationships and influence within the organization to identify key stakeholders and influencers.
These techniques help organizations answer critical questions:
How effective are our change initiatives?
Where are the main sources of resistance?
How can we tailor communication and support to increase adoption?
What are the financial and operational impacts of change?
Leveraging Data for Change Impact Analysis
Change impact analysis is a structured approach to understanding how change affects people, processes, and technology. Data plays a central role in this process, enabling organizations to:
Assess the scope and magnitude of change across different areas.
Identify dependencies and potential ripple effects.
Tools like interviews, workshops, and surveys provide rich data for impact analysis, while dashboards and visualizations help communicate findings to stakeholders.
Applying Data Insights to Optimise Change Strategies
With robust data collection and analysis in place, organizations are equipped to move beyond merely understanding change dynamics – they can now actively shape and optimize their transformation efforts by utilizing actionable data insights. The next critical step is translating data insights into effective, adaptive strategies that drive real and lasting results.
Adapting Change Strategies Based on Data
The real power of change management data lies in its ability to inform ongoing strategy adjustments for business decisions. By continuously monitoring key metrics, organizations can identify what’s working and what’s not, enabling swift, evidence-based course corrections. For example:
Enhancing Communication: If survey data reveals confusion or disengagement among employees, organizations can modify messaging, increase transparency, or experiment with new communication channels to improve clarity and buy-in.
Refining Training Programs: Performance metrics may highlight gaps in employee skills or knowledge. Data-driven insights allow for the development of targeted training sessions or e-learning modules to address specific needs.
Adjusting Timelines and Rollouts: If adoption rates lag behind expectations, organizations can extend implementation timelines or introduce changes in phases, allowing for incremental learning and adaptation.
Addressing Resistance: Sentiment analysis can pinpoint where resistance is strongest. Organizations can then develop tailored interventions – such as additional support, open forums, or leadership engagement – to address concerns and build trust.
Optimizing Resource Allocation: Data can reveal which teams or departments are struggling most, enabling organizations to redirect resources or leadership support where it’s needed most.
Demonstrating Value and Building Buy-In
One of the most persuasive uses of change management data is in demonstrating the value of transformation initiatives to stakeholders. When backed by data, success stories become far more compelling. For example, organizations can share concrete evidence – such as a 20% reduction in customer complaints or a 15% increase in employee satisfaction – to build buy-in and momentum for ongoing change efforts. This transparency fosters trust and encourages a culture of continuous improvement.
Leveraging Technology for Real-Time Insights
Modern change management is increasingly supported by digital tools and platforms that provide real-time data and visual dashboards for decision making. These technologies enable organizations to:
Monitor Progress Instantly: Digital assessment tools offer real-time “temperature checks” on how change is being received across teams and geographies, allowing for rapid response to emerging issues.
Share Insights Widely: Dashboards make it easy to distribute data and insights to all stakeholders, ensuring everyone is aligned and informed.
Automate Routine Tasks: Data science techniques can automate repetitive processes like data collection and analysis, freeing up resources for more strategic activities.
Building a Sustainable, Data-Driven Change Culture
To truly embed a data-driven approach, organizations must foster a culture that values evidence-based decision-making and continuous learning. This involves:
Investing in Data Literacy: Providing training and hands-on experience with data analysis for change teams, and encouraging collaboration with data scientists or analysts.
Promoting Knowledge Sharing: Regular sessions where teams share insights, case studies, and lessons learned help build collective expertise and drive ongoing improvement.
Celebrating Successes: When data shows positive results, sharing those successes widely reinforces positive behaviors and encourages continued adoption of change.
Extracting and applying insights from change management data transforms how organizations approach transformation. By continuously analyzing data, adapting strategies, and leveraging technology, organizations can ensure their change initiatives are more effective, agile, and sustainable – ultimately allowing team members to achieve their transformation goals with greater confidence and impact. This then becomes a key competitive advantage.
As a next step to understand further, we you can check out this infographic on how data can be transformed into actionable insights. Click on the link below to download the infographic:
Ever wondered how an effective senior leader drives cultural change? What are some of the mechanisms and steps in which to truly influence and materialise targeted cultural behaviours over time?
Watch our exclusive interview with the CEO of Manulife Philippines Richard Bates as he talks about driving change at Manulife.
Change Management outcome is the holy grail, and virtually all organisations are undergoing change. Now more than ever, companies are challenged with multiple layers of driving change simultaneously. What is applicable in this situation is not about a particular methodology of implementing a change program. It is all about implementing simultaneous changes, at the same time. There is no luxury of just focusing on one change at a time, the result of competitive, industry, and environmental challenges.
As change practitioners we work closely with our colleagues in Operations to get ready for, implement, and fully embed changes. So how do our colleagues in operations view and manage change initiatives?
Operations as a function is focused on managing performance and delivery to ensure that the business runs smoothly, with little disruptions, and that performance measures are achieved. Operations is focused on resource management, efficiency, and achieving the various operational indicators whether it’s customer satisfaction, turn-around time, average handling time, or cost target.
When times are hectic and a lot is going on with multiple change initiatives, the key focus for Operations is on managing people’s capacity. Key questions would be “Do we have sufficient time to cater for the various changes?”, and “Will we exceed our change saturation level?”. This is a critical question to answer since the business still needs to run and deliver services without negative change disruptions.
From an Operations planning perspective ‘change capacity‘ is often reduced to the time element, especially those impacting frontline staff.
For example:
What are the times required to reschedule the call centre consultants off the phone to attend training?
How much time is required in the team meeting agenda to outline the changes that are being rolled out?
What is the time involvement of change champions?
Though these are all critical questions clear answers will help Operations plan better to face multiple changes. However, this is not adequate. There is more to planning for multiple changes than just focusing on the time element.
Using the lego analogy to manage multiple changes
We all know LEGO as kids. To build a car we start one brick at a time and see how we go. We experiment with different colours, shapes, and sizes. We make do with the bricks we have and use our imagination to come up with what a car would look like. Sometimes we get stuck and we may need to tweak our bricks a little, or sometimes start from scratch.
It is the same as implementing change initiatives. In order to take people along the journey, we implement a series of activities and interventions so that our impacted stakeholders are aware, ready, committed, and embed the change. The design on the change journey is the process of determining what LEGO bricks to choose. There is no shortcut. It is not possible to build a building without each necessary brick to raise the building up. In implementing change, we also need to lay out each step in engaging our stakeholders.
McKinsey studies over decades have told us that one of the most critical factors to focus on in ensuring change outcome success is clear organisation-wide ownership and commitment to change across all levels. This means that when we design each change brick we need to ensure we target every level of impacted stakeholders.
For example:
Team Leaders: How often do we want Team Leaders to talk about the changes to their teams before the rollout? What content do we want them to use? Do they know how to translate the message in a way that resonates? Do we want them to tell compelling stories that talk to the what, why, and how of the change?
Managers: How are managers made accountable? What metrics are they accountable for? What mediums do we want them to use to engage their teams? What are the consequences of not achieving the outcomes?
Senior Managers: Through what mediums do we expect senior managers to engage their teams about the changes? How do we ensure that they are personally accountable for the success of the change? How are they involved to ensure they own the change?
Looking at the above you can see that for complex change there may need to be a lot of bricks in place to ensure the change outcome is successful!
Going back to the issue of facing into multiple changes, how do we play around with the bricks to ensure that multiple changes are successful? The same way that we play with LEGO bricks!
Look at the colours of the bricks. Do certain colours belong together? When we look across different initiatives, are there similar or common behaviours that can be better linked together to tell a compelling story? Do they support the same strategy? Can there be a joint campaign for these changes?
Is the overall LEGO structure going to be intact? What are the impacts of the various changes happening at the same time in terms of focus, performance and change outcome? Have we exceeded the likely ‘mental capacity’ for people to stay focused on a core set of changes at any one time? Will the pieced-together structure collapse due to having too many elements?
Look at the sizes of the LEGO structures. During implementation when we have both larger and smaller initiatives being executed at the same time, will the larger ones overshadow the smaller ones? If so what are the risks if any?
Re-jig or re-build parts of the LEGO structure as needed to see what it looks like. In a situation where we want to see what the changes look like before we action it, it makes sense to visualise what would happen if we move timelines or change implementation tactics
Example of data visualisation of ‘re-jigging’ change implementation timeline with The Change Compass using different scenarios.
Just like in building LEGO, for change initiatives we need to be agile and be flexible enough to play with and visualise what the change outcome could look like before pulling the trigger. We also need to be able to tweak as we go and adjust our change approaches as needed. In facing the multitude of changes that the organisation needs to be successful, we also need to be able to play with different implementation scenarios to picture how things will look like. Each brick needs to be carefully laid to reach the overall outcome.
Careful consideration also needs to be how all the bricks connect together – the analogy that the change outcomes across initiatives can be determined by how we’ve pieced together various pieces of LEGO for them to make sense, and result in the ownership and commitment of stakeholders.
