The Ultimate Guide to Managing Change Post Covid

The Ultimate Guide to Managing Change Post Covid

by | Guides

Leading change as we know it will no longer be the same. Our audience has changed. Our industries have changed. The way people work is changing. The way to engage people is changing. And change has to change as well. I recently spoke with a manager from a government department who said that their organisation has been thrusted into a digital workforce by a 10-year leap. What they had thought unimaginable has literally occurred overnight. Even against a culture and workforce that had resisted virtual ways of working for many years, this is suddenly the current reality. How shall change management keep up with the post-Covid world? How might we as change leaders lead differently?

In this guide we will be dissecting each section of what has changed around us and how change management approach needs to change going forward.

Theme 1: Increased speed of digitisation, automation and robotics

Given the challenges of social distancing and virtual ways of working, many companies are leveraging this opportunity to speed up the implementation of digitisation. Call centres workforce offshore has been constantly disrupted due to Covid. As a result, companies have implemented working from home for call centre consultants. Others have invested deeply in automation and robotics to better cope with oncoming customer call volumes.

Even today, there are already several AI-enabled robot call centre agents who are able to handle a range of common customer enquires and tasks. Many are designed to speak just like humans are are at times almost indistinguishable from a real human voice. We may not be there just yet in terms of dealing with more complex customer enquires. However, given the significant pace of technical development, we are not far from this.

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This is an AI call centre agent from ‘Amelia’

Chinese companies have been fast-reacting in response to Covid given widespread business impacts on their operating models. For example, JD.com Is a Chinese e-commerce company that has been removing human touchpoints in its operation through process automation and robotics. JD.com has invested in high tech and AI delivery through drones and, autonomous technology and robots and has one of the largest drone delivery system capabilities in the world. During Covid they ramped up their network to supply household goods to those who are in lockdown.

What does this mean for change management? Change management also needs to catch up and gear-up for the digital organisation. Just as digital call centre agents become the workforce of the company, digital engagement and data centricity should be the focus for the change practice. Key focus areas for the change practice should be:

A) Automation and digitisation – A standard, repeatable and effective way of engaging with stakeholders must be a key focus area. This includes:

  1. Surveying, pulsing and measuring stakeholder readiness in a way that is standardised, scale-able and repeatable with effective reporting. Examples could be Microsoft Forms, Survey Monkey or Google Forms that are setup to continuously track stakeholder readiness
  2. Engagement tools to support co-design and involvement of employees. There is a myriad of digital tools already available such as Yammer, Trello, Microsoft 365 tools such as Teams, and Slack.
  3. Change impact assessment and portfolio management. Leverage digital ways of capturing, sharing and reporting on change impacts of a range of stakeholders such as customers, partners and employees. With the speed of change iterations across initiatives and increasing numbers of changes emerging, this is a core capability for the future agile organisation. Tools such as The Change Compass may assist.

TCC Data Graphic

 

 

A sample report from The Change Compass

Use of robotics in engaging with a virtual workforce. Projects and initiatives drivers have still relied on traditional ways of engaging with stakeholders and employees such as emails and newsletters.

To be more engaging, dynamic, and scalable, it may also make sense for the larger and more complex initiatives to leverage bots in engaging with and addressing stakeholder concerns. With a range of providers available, bots may be designed with minimal effort required. Standard FAQs may be combined with prompting questions. Surveys may also be incorporated within bots as well.

The best part of all of these digital tools is that analytics and reporting are designed into the tool and therefore saving change leaders significant time and effort in using data to report on progress. In the digital and virtual organisation, data needs to be constantly nurtured, measured and updated. Opinions and assertions will no longer be tolerated. Agile teams base decisions on updated data and trends.

As change leaders we have the opportunity to measure and foresee changing perceptions, readiness and needs of stakeholders. In traditional organisations, leaders would walk the floor or physically approach staff to gauge concerns. The new organisation needs to be geared for constant, data-based sources of stakeholder sentiments, using not just lagging indicators (e.g. employee satisfaction, and readiness surveys) but leading indicators such as sentiment analysis.

Theme 2: Increasingly frequent business disruptions

With what seems to be increasingly frequent business disruptions such as natural disasters, epidemics, and business models, companies need to be agile, resilient and flexible. What would have been typical corporate practices of 3 or 5 year long-range planning can now be thrown out the door. It doesn’t mean that companies no longer need to do long-range planning, but that plans need to flexible enough to take into account constant disruptions and industry changes.

This also needs to be supported by an organisation that is capable of flexing up, down and across. This means, upsizing and downsizing as required to better cater for customer volumes. Flexing across to other supplementary or complementary products or services as required to discover and benefit from new revenue sources.

What does this mean for change leaders?

With Covid, most organisations have experienced the criticality of having an effective business continuity plan. To execute this, it requires the ability to suddenly change directions within a short period of time. Leaders need to be able to effectively engage with and establish trust with their teams during these tumultuous times.

Business disruptions can bring out the best or the worse in the existing capability of the organisation. Without existing trust between the leadership and employees, any changes in the course of the company may lead to confusion, greater distrust, stress and therefore significant dip in performance.

Some may argue that this seems natural since during the change process it is normal to expect a dip into the ‘valley of despair’ during the initial period of the change, prior to confidence being established. However, several McKinsey studies have disproved this and that companies do not necessarily need to go through a significant dip in performance in order to rise up to ‘normal’ performance levels.

Change-Curve

 

 

This well known ‘Change Curve’ has been proven to be false in a lot of situations

Building change agility

To deal with constant and unexpected disruptions organisations must build agility. What is agility and how does one build it?

  • McKinsey (2015, Aghina & De Smet) proposed that agility is about driving speed with stability. This is the balance between stability (resilience, reliability and efficiency) as well dynamism (fast, nimble and adaptive). This means having a relatively stable set of design structures, governance arrangements and processes within a relatively unchanging set of core elements, or a fixed backbone. To match this, a set of loose, dynamic elements that can be adapted quickly to new challenges and opportunities.
  • The Project Management Institute (PMI) outlined that change agility is about increasing the likelihood that its strategies will be realised, through effective portfolio, program, project and change management. This includes:
    • Establishing a common understanding of sponsor behaviours and expectations
    • Modify reward systems to favour team collaboration over individual contributions
    • Establish decision authorities at the lowest possible level, eliminate layers of governance structures

So what should change leaders do?

Build transparency and trust through constant engagement and involvement. One-way talk is not going to cut it if the goal is to achieve a deeper level of organisational engagement. Employees need to be involved in understanding organisational challenges and have the opportunities to be involved in contributing to and shaping how the organisation is addressing business risks and challenges.

This requires discipline and ongoing commitment, starting with small micro-habits such as communications styles, leveraging the right communication mediums and instil ongoing assessment of these channels and employee sentiments toward engagement effectiveness.

Digitally, what this can look like is a leader who uses several mediums such as Yammer, intranet, email and regular town hall to engage in 2-way dialogue with employees. For organisations that do not yet have leadership trust, there may be initial reluctance to speak openly and candidly. Openness to share opinions and feeling safe to do so needs to be gradually cultivated and cannot be forced. Trust can only come with authenticity. The leader also needs to demonstrate that feedback, opinions and recommendations have been listened to.

How do change managers support change agility within initiatives?

Whilst most change managers are focused on supporting one particular initiative, there is a critical role that change managers can play to support change agility.

  1. Designing change releases into smaller pockets of ongoing releases

By designing smaller, and more digestible releases into the organisation, the initiative is supporting the ongoing development of change capability for small, ongoing changes. Over time, the continuous experience of small changes will help to shape the organisation to get used to small changes are the new norm. Change becomes business as usual.

Small changes are also more likely to be successful as the quantum of change is much easier to adopt than larger changes. The perception of the difficulty to adopt the change is mitigated. The actual process of change is also a smaller step to take.

2. Setting the pace of change

Just as the design of change releases can shape the organisation, so can the pace of change. Change managers should work with their initiative(s) to design the speed of change so that it enhances organisational learning for greater speeds of change over time. Just like running, one starts training by doing shorter runs within shorter distances. Over time, distances and pace can be increased to build overall running speed.

Organisations that are experienced in concurrent and ongoing weekly changes are used to having to get ready for and adjust to changes as the norm. They know where to go for information and help. They are also confident that the support mechanisms are there so there is good trust in their leaders and in the support system for change (whether digital channels or particular initiative roles).

Previous experiences from a faster pace of change means that they are used to knowing what to go through in terms of change. They are familiar with what questions to ask, what support is required and even how to support one another.

3. Design effective engagement routines that support deep engagement

Most organisations have standard business as usual communication routines such as monthly newsletters, town halls, team meetings, etc. The usual practice is to leverage these channels to let impacted stakeholders group know about impending changes.

What’s the problem with this? The problem comes when there is lots of changes impacting the same stakeholder group and the existing communication routines don’t seem to have enough time to go through everything. For example, using team meetings to communicate changes to impacted customer facing staff could be a standard practice. If the team time becomes overwhelmed with various announcements of changes with limited time for other BAU activities such as development, general communications and engagement then there lies the problem.

How do we get around this? Build the expectation to leverage existing digital platforms and promote a ‘self help’ culture whereby teams regularly visit intranet pages, Yammer, read emails or newsletters to find out what is happening. If the only time an impacted customer facing staff finds out about the change is through a team meeting then this is not the most effective use of meeting time.

A more effective engagement mix might be a combination of multiple mediums, using emails, yammer, other digital channels such as intranet pages to communicate the message. If the expectation is set with customer facing staff and there is existing practice of proactive seeking of information, then this decreases the risk of reliance on one particular channel.

The act of proactively seeking information also by itself enhances the engagement of the impacted customer facing staff who would then seek information mediums that they are familiar with and are comfortable using. Any team meetings or town halls could then be used for Q&A and interactions versus information download.

 

 

Leverage the power of digital engagement channels

4. Incorporate the emphasis on agility within learning interventions

Learning agility is the “propensity to continually learn, unlearn and relearn mental patterns and applications from various sources” (Mercer). Learning agility supports and promotes agility mindsets and behaviours.

An employee who is agile in learning is willing and able to learn new things fast, is open-minded, inquisitive and has the patience and drive to learn new areas. To achieve this, employees need supportive leaders who emphasise the importance of continuous learning and also role model this behaviour.

They also need a learning environment where there is time allocated to learn on the job. Leaders take into account failures as a part of learning and establish a culture that is safe to fail. Many organisations such as Google, Intel and Microsoft in fact celebrate failure when the right steps are taken as a part of the learning process.

When you are designing learning interventions as a part of your initiative, design interventions that support learning agility. For example, as a part of learning content, encourage learners to try practicing the new behaviours as exercises. Provide online feedback loops to support continuous learning. Leader learning should promote the above-mentioned behaviours of supporting employees to try different behaviours and any failures that may occur.

Initiative-based learning should also support broader organisational agility through emphasising on the role of innovation and implementing test-and-learn or experiments. For example, content exercise could include asking the learner to come up with ways of arriving at the desired outcome. If the outcome is to follow particular process steps, ask the employee to come up with ways to proactively support and champion this new process across the team.

5. Build an effective narrative around the need for agility

To build or support an agile organisation, communication is key. A compelling narrative or story must be built and implemented that tells the ‘why’ of agility. What is agility important for the organisation? Why not? What does this mean? How to achieve agility? These are common elements of a clear narrative.

A clear and compelling narrative should be developed and linked with various initiatives. Through this, multiple communications from different initiatives are supporting the same message. With each change, the impacted employees are receiving the message about the importance and need for having an agile mindset.

Each leader should also be encouraged to tell their own stories to support the narrative. Nothing is more powerful than an authentic story told by a leader. Ideally the story should be personal and reflects an experience that the leader has been through that shares the theme of agility. Stories loose their power and effectiveness if they are just read out and full of ‘corporate speak’.

Juggling a multitude of continuous agile changes

In the VUCA (volatile, uncertain, complex and ambiguous) world where things are constantly evolving and where agile practices are the norm, how change management is set up should also change.

Imagine you’re spinning 30 plates at the same time. Some plates are smaller some are bigger. Some are spinning at a faster rate than others. Some need to finish spinning earlier than others. There are new plates that need to be added to be spun. To add to the complexity, the plates are constantly evolving. Some are changing colours, others are changing sizes. As a result, how you spin each will need to change as well based on how they are evolving. This is what a lot of organisations are facing right now.

So how should one deal with this situation?

  1. Change management vision and strategy

A clear and logical change management vision and strategy is required to support where the organisation is heading towards. With the various changes mentioned previously, the role of change management is to realise the strategy through a successfully delivered business plan, including various initiatives.

Understanding where the organisation is heading towards, the end state and the roadmap to get there, the change management function needs to identify key strategies to enable successful change. Is the strategy focused on driving agility through leadership and agile practices? Should change management focus primarily on initiative delivery, capability development or governance and reporting?

Is there a clear translation of how each change strategy or tactic will support the realisation of each part of the business plan?

2. Resourcing

To support the various initiatives as a change management function we need to look strategically at the skills required and the volume of work upcoming. What are the emerging change skills required to support the initiatives? Is there a large volume of regulatory changes? What about digital projects? Depending on the nature of projects emerging a strategic workforce planning exercise is required to plan forward. Develop scenarios of volume of projects and change support requirements to develop likely resourcing demands.

A mapping of various change skills should be carried out to flesh out key skills required to support upcoming initiatives. Learning and development skills, stakeholder engagement, sponsorship coaching, communications, organisational design, impact assessment, etc. may be common change skills to map out.

After the workforce planning exercise is completed there should also be a quick quarterly review process to assess to what extent the plan should still remain the same or that it needs to alter based on what has changed. In this way, the change function can regularly keep tab on any evolvement in resourcing needs.

3. Managing the portfolio of changes

With multiple constant changes that are being iterated constantly, a portfolio approach to managing changes is required. A portfolio approach to managing change requires a view of the change initiatives across the board. With a view of all initiatives, one can then better make decisions about prioritisation, change capacity, capability required, operational implications and change maturity required.

To read more about managing a portfolio of changes visit The Ultimate Guide to Change Portfolio Management.

4. Data and change management

Data has become and will continue to become a critical enabler for change management, just like most other disciplines. With data, change professionals can make significant impact on business effectiveness and drive benefit realisation.

  • Real time data can help support fast and agile decision making and allow the business to move with speed
  • With sufficient historical data organisations can also make predictive analysis to understand what the future may hold using data
  • Audience data can allow change professionals to address specific stakeholder needs based on data such as preferences, readiness and engagement levels
  • Portfolio level impact and readiness data can help leaders zoom in on high risk initiatives
  • Drive data-based decision making versus stakeholder opinions and assertions
  • Digitisation of change data to manage the increasing complexity of measuring change across initiatives

To read more about developing change analytics maturity please visit the following article.

Turn change data into actionable insights.

5. Structure of change management

Instead of being structured around individual projects, to support evolving initiatives from a scale and effectiveness perspectives change practices need to re-think the best structural options.

Another popular way is for change practices to be structured around change functions such as learning and development and communications. However, to be more adaptable and flexible to support emerging initiatives it may make sense to adopt an ‘agile team’ structure where teams are organised around portfolios and impacted business units, rather than disciplines.

The advantage of these options will be that change will be better positions to scale up or down as required depending on resource requirements. Focus around business units will ensure a more business-centric approach to change that takes into account multiple initiatives that impact the same stakeholder group.

Theme 3: Evolving virtual ways of working post Covid

Post Covid organisations will examine their ways of working and re-assess what is possible to manage any residual Covid risks as well as leveraging virtual working capabilities developed during Covid. Organisations will leverage virtual working as much as possible as it reduces cost of operating, however, balancing this with face to face office time to maximise productivity and effectiveness.

Organisations also need to take virtual working to the next level by building greater organisational capability. For example, previously most brain storming sessions could only be done via face to face. Now companies need to buckle down and truly leverage various digital tools to enable team discussions, collaboration and idea sharing, 100% virtually. With some working in the office and others at home or other locations, this will be critical.

For change practitioners a key element of the new ways of working is engagement approaches. Truly engaging employees and stakeholders in the post Covid world will be challenging. We all know that face to face communication trumps other forms of communication in terms of impact. However, when this option is not available, clear practices need to be established to maximise engagement effectiveness.

  • Meeting practices. Organisations should establish clear meeting practices that are effective virtually, such as ‘round the grounds’ checking on how each participant is feeling or thinking, pausing for feedback, asking questions to check understanding, using video to show body language, etc.

  • Strengthen organisational culture of employees proactively using particular digital channels for communication. A significant effort needs to be placed on enabling employees to habitually check and participate in digital channels such as Yammer or Microsoft Teams to exchange ideas and keep up with changes. With the pace of change increasing, reliance on email and intranet pages is no longer sufficient and also because these are largely 1-way communication vehicles. With a culture where employees are proactively engaged in digital engagement channels, driving change will be more effective as an outcome

  • Diversity of audience. Organisations are now realising that if they are able to have most of their employees work virtually, this means they are not restricted to hiring talent from particular locations. This means the talent pool can be national or even international. With a greater diversity of physical locale of employees and even cultures, come challenges with engagement and communications. Particular cultural or regional references may need curbing to ensure there is an inclusive working environment. Strategies may also need to be developed when implementing change initiatives to this in multiple physical locations.

  • Performance management. Managing performance virtually will be more complex for managers who cannot ‘see’ the employee. A degree of trust and outcome based management needs to occur. For the change practitioner, the focus is on how to measure and track performance within a mixed working environment both physically and virtually. For digital changes it may be easier to measure change virtually, but for other changes there may be challenges in sensing behaviour change in a virtual environment.

  • Health and safety management. With more employees working from home there are risks such as ‘digital stress’ (from too many video meetings for example) and environmental risks such as children or other family disruptions. During Covid the working day seems to have expanded, by 2 hours in Britain, France and Spain and 3 hours longer in America (The Economist). Change practitioners need to be sensitive to this when there are multiple changes happening, likely leading to risks in health and safety of employees.

The post Covid world presents challenges for organisations and therefore the change practitioner. With challenge comes opportunities. The environment is ripe for the change discipline to take the bull by the horn and transform into a strategic and value adding service to the organisation. One that is critical to its ongoing transformation and one that is evolving with the times.

To read more about project planning post Covid click here.

Is it useful to label change as positive or negative?

Is it useful to label change as positive or negative?

by | Change Measurement, Portfolio management

You may have been asked to rate change into either a positive or negative change to classify initiatives and thereby use the classification to aid change implementation.  After all, we all know of initiatives that nearly everyone sees as negative and other initiatives where it’s going to make people’s lives easier, and therefore viewed as mostly positive.  So, is it useful to classify every initiative as either positive or negative?  Let’s examine this closely.

What is the usefulness of classifying change into either positive or negative?

Some managers believe that if we are able to classify change as either positive or negative then we are able to focus on those changes that are perceived as negative since they may require significant managerial effort to drive through the change.  Also, negative changes may face more resistance.  Therefore, knowing this helps to plan for change implementation.

Negative changes could include significant restructures where employees are losing their jobs, and where there are significant cost-cutting outcomes targeted.  On the other hand, a positive change could be a process improvement where the new process makes work easier for impacted employees, requiring less approval and less paperwork. 

However, there are many issues with this assumption.  Let’s break things down….

Differences in individual perception

Every individual has a different perception of the same change initiative.  After all, we are all individuals with different upbringings, personalities, life experiences, and preferences.  In a major restructuring, whilst most impacted employees losing their jobs may see this as negative, there could be those who are eager to receive the redundancy payout, possessing long tenure at the company.  Others may initiative find the change negative, however found that this was a great opportunity to launch a career they had always wanted.

On the other hand, even for a seemingly positive change that could make most employee’s lives easier, not everyone may see it that way.  There are always some that simply do not like changes at all.  It could be that they are so used to the old ways of working that any change and adjustment would be perceived as negative.

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You may recognise this Rubin Vase picture – either an old woman or a young lady.

Different perceptions in stakeholder groups

It is also important to note that not every stakeholder group would perceive the same initiative in the same way.  It depends on various factors.  For example, with a phone upgrade, younger employees or those groups more familiar with technology would welcome the change with open arms.  New phones with new features, exciting functions, faster responses, and better quality cameras – how could anyone view this as negative?

Well, it could be that for those who are not ‘early adopters’ and are used to using the same phone for the long term, this may be a negative change.  They may not even want to use most of the features of the phone and in fact, more features could mean more confusion and more time required to learn the functions of the phone.

There are positives and negatives in most changes

Inherent in every change, there could be both positive or negative aspects of the change for the same stakeholder.  Implementing a new system in order to improve response time and incorporate greater digital features may be initially painful.  The significant work required to understand why the change is required, the long time spend in preparing for the change, only to find that releases often get pushed back. 

Eventually when the system gets launched there is excitement and everyone is saying how much easier the new system is to use.  However, like all systems, there are bugs that need to be ironed out and this could take at least a few months.  So, you can see that it’s not as easy to just label the whole initiative as positive or negative.  It depends on which angle we are viewing the change and at what phase of the initiative.

Changes may be neither positive nor negative

Some changes may be neutral.  Think of the slew of regulatory changes impacting the financial services sector.  Many of these are process changes that are geared to provide more oversight, transparency, and to benefit customers. 

Small process or policy changes may not be difficult to understand nor to implement.  Employees may not find it a difficult change, however, it doesn’t really benefit them in their roles.  However, they do understand why this was implemented and that this is important to abide by or the company may be fined by the regulator.  So, this is an example of how some changes don’t need to be necessarily positive or negative.

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Perception may not be either positive nor negative. Humans are more complex than that.

Perception toward the change could be altered during the implementation

Change management is about influencing stakeholder perceptions.  If perceptions toward change cannot be altered then what is the point of change management you may ask?  Absolutely. 

Stakeholders may initially have a negative perception of the change due to preconceived ideas about the ‘why’ of the change.  Or it could be that managers’ roles are impacted negatively and therefore they then painted a negative image for their teams.  It could also be that insufficient communication and engagement have been in place and therefore the change came as a surprise – leading to negative perceptions, more towards the senior managers that are driving the change, than the change itself. 

Effective change managers are able to skillfully diagnose stakeholder perceptions and anticipate their potential reactions to change.  The change intervention is therefore designed to effectively influence and collaborate with impacted stakeholders to build rapport and consensus toward the change.  What may have started out as a negative change, can be turned around into a neutral or even positive one.

Time it takes to embed the change for positive/negative changes

It is a fallacy to assume that positive changes always take less effort than negative ones.  This is not always the case.  If we go back to our example of the new system, like any new system, whether perceived in a positive or negative light, effort and time are required to learn the new system.  Focus and effort are required to understand why this change is needed, what it is aiming to achieve, and the impacted stakeholder’s role in this.  Therefore, it is not necessarily the case that positive changes require less effort and focus.

But would negative changes face more resistance?  Maybe yes and maybe no.  Again, it depends.  For example, we know from the below involvement and commitment curve that there more someone is involved in crafting the change the more committed they will feel to the outcome of the change.  So, resistance could be the result of insufficient or ineffective engagement, rather than a necessary result of a perceived ‘negative’ change.

So, you can see that it may not be so useful to try and label change as positive or negative in order to aid change planning.  A much more useful angle to look at planning for change is to look at aspects such as impact, stakeholder readiness, behaviour changes required, level of complexity, etc.

To read more about measuring change check out our Ultimate Guide to Measuring Change.

New vs Old Change Management Models: What the Research Actually Shows

New vs Old Change Management Models: What the Research Actually Shows

by | Change approach, Designing change

The Evolution of Change Management Models

 

 

 

 

 

 

 

 

 

 

Change management is a critical discipline for organisations navigating today’s fast-paced and complex business environment. At its core, change management refers to the structured approach and set of processes that organisations use to transition individuals, teams, and entire organisations 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, organisations 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 organisational 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 organisation for change by challenging the status quo. The change stage is the implementation phase, where new processes or behaviours 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 organisational 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 organisations. It focuses on five building blocks for successful change: Awareness, Desire, Knowledge, Ability, and Reinforcement.

 

 

 

 

 

 

 

 

 

 

These classic models have provided organisations 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 organisations 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 organisations 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 organisational 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 organisations 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 organisations. These models tend to emphasize:

 

 

 

 

 

 

 

 

 

 

  • Behavioural science and data-driven insights to understand and influence employee behaviour more effectively.

  • Agility and adaptability, allowing organisations 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 Behaviour Model: Applies behavioural 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 organisations 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, organisations 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 organisations 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 organisational 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 organisation. This structure assumes that senior leaders set the direction and employees follow.

  • Focus on Process and Structure
    Traditional models emphasize formal processes, organisational 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 organisations 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 behavioural 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 organisations to adapt quickly as circumstances evolve. Change is seen as an ongoing process rather than a linear journey.

  • Behavioural Science and Data-Driven Insights
    Newer models use research from psychology and behavioural 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 Behaviour Model: Focuses on the interplay of motivation, ability, and prompts to drive behaviour 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 organisations 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 Behaviour, 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 organisations 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 organisation and the specific challenges at hand.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Applying Modern Change Management Models—Practical Steps for Success

 

 

 

 

 

 

 

 

 

 

Adopting modern change management models requires organisations 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 organisational 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 Behavioural Science and Data

 

 

 

 

 

 

 

 

 

 

  • Map Behaviours: Identify specific behaviours that need to change. Use behavioural 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 behaviours. 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 organisation. 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 behavioural 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. Behavioural 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

 

 

 

 

 

 

 

 

 

 

Organisations 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 behavioural 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 organisational capability rather than a disruptive event.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Frequently asked questions

What are the main old change management models?
The most widely cited traditional change models include Lewin’s three-step model (Unfreeze, Change, Refreeze, developed in the 1940s), Kotter’s 8-Step Model (1996), and the McKinsey 7-S Framework (1980s). These models were designed for an era of slower, more predictable change and treat change as a finite event rather than a continuous process. Research has consistently shown they perform poorly in complex, fast-moving environments.

What are the key differences between old and new change management models?
Traditional models tend to be linear, prescriptive, and leader-driven, assuming change can be planned in full before execution begins. Modern approaches are iterative, stakeholder-centred, and data-informed. They treat resistance as information rather than an obstacle, build feedback loops into the process, and account for the reality that organisational conditions change during implementation.

Does research support modern change management approaches over traditional ones?
Yes, though the evidence base is still developing. Studies comparing iterative change approaches with linear ones have found significantly higher success rates for agile methodologies in complex environments. Prosci research consistently shows that structured, people-centred change management, regardless of which model is used, produces better outcomes than technically-focused project management alone.

Should organisations abandon traditional change models entirely?
Not necessarily. Traditional models still provide useful conceptual anchors. Kotter’s 8 steps, for example, remain a practical communication tool for explaining change to senior leaders unfamiliar with change management. The problem arises when traditional models are applied rigidly as execution frameworks rather than as frameworks for thinking. Many mature change functions use a hybrid approach: classic models for communication and stakeholder engagement, modern approaches for day-to-day change execution.

How to build change analytics capability: a practical guide for 2026

How to build change analytics capability: a practical guide for 2026

by | Change Measurement

Most change functions have opinions. The best ones have data.

There is nothing wrong with experienced judgement in change management. A seasoned practitioner who has run fifty programmes develops pattern recognition that is genuinely valuable. But experienced judgement on its own has a ceiling. It cannot scale across a portfolio of twenty concurrent initiatives. It cannot identify that three separate programmes are about to converge on the same group of employees in the same six-week window. And it cannot make a credible case to a CFO for additional resourcing unless it can translate human risk into numbers.

That is what change analytics capability provides. Not just dashboards and reports, but the organisational capacity to turn change data into decisions , decisions about which programmes need more support, which stakeholder groups are at risk of saturation, where adoption is lagging behind plan, and how to allocate scarce change management resources across a complex portfolio.

This article sets out what change analytics capability looks like in 2026, how to build it systematically, and what separates organisations that get genuine value from their change data from those that produce reports nobody acts on.

Why change analytics capability matters more now than ever

The analytics landscape has shifted profoundly in the past three years. Gartner’s 2025 data and analytics trend research identifies agentic AI and decision intelligence as the defining themes, with organisations moving beyond simply collecting data toward using it to make better decisions faster. Sixty-one percent of organisations are already evolving their data and analytics operating model because of AI’s impact.

This shift matters for change functions because it raises the bar on what “data-driven” means. Organisations that are building sophisticated decision intelligence capabilities in their commercial and operational functions are going to expect the same rigour from their change management function. A heat map with green-amber-red cells and no underlying methodology will not hold up in that environment.

The second driver is the compounding complexity of the change portfolio. Gartner research on change fatigue documented that employees experienced an average of ten simultaneous enterprise changes in 2022. Managing that volume without portfolio-level analytics is like running a hospital without patient records , theoretically possible, but not something you would design intentionally.

The third driver is accountability. Change management has historically struggled to demonstrate its own value in quantitative terms. Analytics capability provides the mechanism to do this: adoption rates by group, time to proficiency, correlation between change management investment and delivery outcomes. These are not vanity metrics , they are the evidence base for sustainable resourcing of the change function.

The four components of change analytics capability

Change analytics capability is not a single tool or a single role. It is an organisational capability with four interdependent components.

Component 1: Data infrastructure

You cannot analyse what you cannot collect. The data infrastructure component covers what change data is collected, in what format, at what frequency, and from what sources.

Common change data sources include:

  • Change impact assessment data (groups affected, severity, change dimensions)
  • Programme timeline and milestone data
  • Stakeholder readiness survey results
  • Adoption metrics (system usage, process completion, self-reported confidence)
  • Sentiment data (pulse surveys, manager feedback, support ticket categories)
  • HR data (headcount, location, reporting lines) for population segmentation

The critical design question is whether this data lives in connected systems or disconnected spreadsheets. A change function that manually compiles data from twelve different programme SharePoint sites every fortnight does not have analytics capability , it has a reporting overhead.

Component 2: Analytical methodology

Data infrastructure provides the raw material. Analytical methodology determines what you do with it. This component covers the frameworks and calculations used to turn raw data into meaningful signals.

Key analytical methodologies for change functions include:

Change load analysis: Calculating the total volume of change being asked of each stakeholder group at any point in time, accounting for all concurrent initiatives. This is the foundation of change saturation management.

Adoption trajectory modelling: Tracking adoption rates against predicted curves to identify groups that are falling behind and require targeted intervention.

Readiness gap analysis: Comparing assessed readiness levels against readiness thresholds required for successful go-live, enabling proactive resourcing decisions before problems materialise.

Impact correlation analysis: Examining the relationship between change impact scores and adoption outcomes to sharpen future impact assessment methodology.

Component 3: Reporting and visualisation

Analytics that cannot be communicated are analytics that do not get acted on. Reporting and visualisation capability covers how change insights are packaged for different audiences.

Executive audiences need portfolio-level summaries: which programmes are on track for adoption, which groups are at risk, what the cumulative change load looks like across the organisation. They need this information in a format that takes two minutes to consume, not twenty.

Programme teams need operational detail: adoption metrics by group, readiness gap analysis by role, intervention recommendations for the next sprint cycle.

Business unit leaders need a group-specific view: what is landing on their people, when, and how that compares to their team’s current capacity.

The mistake many change functions make is producing one standardised report for all audiences. A skilled change analyst designs the visualisation to match the decision the audience needs to make.

Component 4: Decision-making integration

This is the component that separates analytics capability from analytics activity. Decision-making integration refers to whether change data is actually used to make portfolio and programme decisions, or whether it sits in a report that is acknowledged and filed.

The indicators of genuine decision-making integration include:

  • Change analytics data is included as a standard agenda item in programme steering committee meetings
  • Portfolio-level change load data informs programme sequencing and go-live scheduling decisions
  • Adoption metrics trigger formal review and response when they fall below thresholds
  • Change analytics are referenced in investment cases for change management resourcing

Without this integration, even excellent analytics capability produces limited value.

Building the capability: a five-stage maturity model

Change analytics capability does not appear fully formed. It develops in stages, and most organisations are at stage one or two.

Stage 1: Baseline awareness Change data exists in individual programme documents. Impact assessments are completed per programme. No aggregation or portfolio view. Analytics capability = zero.

Stage 2: Programme-level reporting Individual programmes track and report adoption metrics. Change managers produce reports for their specific programme stakeholders. No cross-programme view. Analytics capability = low.

Stage 3: Portfolio aggregation Change data is collected in a consistent format across programmes and aggregated into a portfolio view. The change function can report on cumulative change load and cross-portfolio adoption status. Analytics capability = moderate.

Stage 4: Predictive analytics Historical adoption data informs predictions for new programmes. Readiness gap analysis drives proactive resourcing decisions. Statistical models are applied to portfolio data to identify risk patterns. Analytics capability = high.

Stage 5: Decision intelligence Analytics are embedded into portfolio governance. Scenario modelling tools allow leadership to test sequencing decisions before committing. AI-assisted analysis identifies emerging risks and patterns faster than human review alone. Analytics capability = advanced.

Most large organisations should be targeting Stage 3 or 4. Stage 5 is achievable but requires significant investment in both tooling and analytical capability within the change function.

The AI dimension: what has changed since 2022

The past three years have fundamentally changed what is achievable in change analytics. Large language models can now summarise open-text survey responses at scale, identify sentiment patterns across stakeholder groups, and flag emerging risks in qualitative data that would previously have required hours of manual analysis.

Gartner’s 2024 analytics research identifies “decision intelligence” as the key capability organisations need to develop, moving beyond data collection and visualisation toward using data to actively inform and improve decisions. For change functions, this means building the capacity to ask predictive questions: given this programme’s impact profile, readiness trajectory, and the current portfolio load on this group, what is the probability of achieving adoption targets on schedule?

This is not science fiction. Purpose-built change management platforms are already incorporating these capabilities. The constraint is not the technology , it is whether the change function has built the data infrastructure and analytical methodology to feed the models meaningful inputs.

Practical tools for building change analytics capability

Building change analytics capability does not require a data science team. It requires three things: a commitment to consistent data collection, a methodology for analysis, and a platform that makes aggregation practical.

For organisations at Stage 1 or 2, the starting point is standardising the data that is collected across programmes. A consistent change impact assessment template, a standard adoption survey instrument, and a single place where programme data is stored are the foundations everything else builds on.

For organisations at Stage 3 and above, purpose-built platforms like Change Compass provide the infrastructure to aggregate cross-portfolio data, visualise cumulative change load by stakeholder group, and track adoption metrics in real time without manual compilation. The weekly demo is a practical way to see what portfolio-level change analytics looks like in practice.

The analyst role: who owns change analytics?

As change analytics capability matures, the question of ownership becomes important. In most change functions, analytics work is done by change managers as a secondary responsibility. This works at Stage 2, but breaks down at Stage 3 and above.

Dedicated change analyst roles are increasingly common in large enterprise change functions. The change analyst focuses on data collection, methodology design, reporting, and the translation of data into decision-ready insights. This role sits at the intersection of change management and data analysis , and it is distinctly different from either.

Organisations that are serious about building analytics capability typically find that one dedicated change analyst serving a team of four to six change managers delivers returns that more than justify the investment, in the form of better-targeted change management effort and more credible reporting to leadership.

Where the return comes from

Change analytics capability generates return in three ways.

First, it improves the allocation of change management effort. When you can see which groups face the highest impact and the greatest adoption risk, you can direct scarce practitioner time to where it matters most rather than spreading it evenly across all programmes.

Second, it reduces adoption failures. Early warning signals , declining survey confidence, usage data below threshold, support ticket spikes , allow interventions before adoption problems become adoption failures. The cost of an intervention in week three is a fraction of the cost of a go-live failure in month six.

Third, it builds the case for the change function itself. Prosci research documents that organisations with excellent change management are significantly more likely to meet their objectives. Analytics capability is what turns that generalisation into a specific, defensible claim about your organisation’s change function.

Frequently asked questions

What is change analytics capability?

Change analytics capability is an organisation’s ability to systematically collect, analyse, and act on data about the change it is managing. It spans data infrastructure, analytical methodology, reporting design, and , critically , the integration of change data into actual portfolio and programme decisions. A change function with strong analytics capability can demonstrate adoption trends, flag saturation risks, and make the case for resourcing with evidence.

What data should a change analytics function collect?

The most valuable data sources are change impact assessment data (which groups, how severely, across which dimensions), stakeholder readiness survey results, adoption metrics (system usage, process adherence, self-reported confidence), and programme timeline data. HR population data is also essential for segmenting results by group, geography, or role type.

How does change analytics differ from project reporting?

Project reporting tracks whether activities have been completed: training delivered, communications sent, workshops run. Change analytics tracks whether change is actually happening: adoption rates, readiness levels, cumulative change load, sentiment trends. The first tells you what the change team has done. The second tells you whether it is working.

Do you need specialist tools for change analytics?

You do not need specialist tools to start. A consistent data collection approach and a shared repository are enough to get to Stage 2 or 3. But managing portfolio-level change data across ten or more concurrent programmes without purpose-built tooling quickly becomes unviable. Platforms designed for enterprise change management provide the aggregation, visualisation, and real-time tracking that make higher maturity levels practical.

How long does it take to build change analytics capability?

Moving from Stage 1 to Stage 3 , from no analytics to a functional portfolio view , typically takes six to twelve months of consistent effort, assuming leadership support and access to appropriate tools. The main constraint is not technology but discipline: building the habit of consistent data collection across all programmes, regardless of size or complexity.

References