How to Change Behaviour in the Workplace: A Complete Guide
In almost every change initiative there is an element of behaviour change. For some initiatives, the behaviour change in adopting a new habit required is large and complex whilst for others it can be as small as pressing different buttons and using a different user interface. Effective behaviour change, including incorporating new procedures, is one of the most critical outcomes that the change practitioner can hope to achieve. With the achievement of desired behaviours come the ultimate benefit associated with an initiative. On the other hand, not achieving the behaviour change targeted means that the change has not succeeded.
Given the importance of behaviour change in every initiative this article aims to cover key aspects of how a change practitioner should approach and design the behaviour change. Yet, successfully designing and implementing behaviour change is one of the most challenging tasks for the change practitioner. It is common place that many change practitioners do not have the experience to know how to achieve successful behaviour change.
The definition of behaviour change
So what is behaviour change?
Behaviour change “refer(s) to any transformation or modification of human behaviour”.
This seems like a fairly general definition that is all-encompassing and can include anything ranging from behaviour change in a psychological context or in a social or workplace context.
However, a key part of behaviour change is to recognise that behaviour, by definition, must be observable in some Shape or form. A behaviour can be verbal, non-verbal, or physical behaviour. However, a behaviour cannot be ‘perception’ or ‘thinking’ since these cannot be observed nor displayed necessarily.
Another feature of behaviour change is that the behaviour is to be changed from the current state to a future state. The quantum of the change determines the complexity of the change required and the extent to which a series of change interventions is required to achieve the desired future state. This means, if the behaviour change is easy from the impacted person’s perspective, then the change approach can be fairly light and does not need to be complex. However, if the quantum of the change is large, then a heavy design of change interventions is expected to achieve the outcome.
Some examples of behaviour change within a change initiative context includes:
Using a different computer program interface with different layout or keystroke steps in performing tasks
Different process steps required in disclosing financial details in business reporting
Proactive coaching employees through feedback to improve sales effectiveness
Reporting on risk incidents that are not compliant with company standards
Actively establishing rapport with the customer to demonstrate empathy by acknowledging their feelings and demonstrating effective listening
Speak up against bullying behaviours amongst colleagues
The importance of focusing on behaviour change
Inexperienced change practitioners will normally just followed the standard cookie-cutter approach of filling out the various change templates such as stakeholder matrix, change impact assessment, and a change plan. And then proceed to develop a communications plan or a learning plan as a part of experiential learning before executing on implementation.
So what is wrong with this?
As called out previously, in almost every change initiative there is a set of desired behaviours required to achieve the end state of the change initiative. The job of the change practitioner is to figure this out and design a change program around the achievement of these behaviours. Just by filling in templates and carrying out standard change approaches will most likely not achieve the targeted behaviours.
For example, in transitioning users from an old ERP system to a new digital system with a new look and feel, it is critical to identify the core behaviours required in the new state. Is it that in using the new digital system the user has access to a lot more timely data and therefore the behaviour change needs to be around 1) proactively checking for data and derive insights and 2) use these insights and data to make better decisions.
This means that if you were to just focus on communicating the change and train employees on how to use the new digital system, the whole project may not be deemed to be successful. This is because it is simply a project of ‘installation’ of a new system. However, the benefits targeted by the new digital system is about employees gaining more insights through the ability to easily access a range of data previously not available. Employees may know how to use the new system but it does not mean that they will automatically exhibit these desired behaviours.
One of the tricky things about behaviours is the ‘knowing’ vs. ‘doing’ conundrum. Just because someone knows how to do something it does not mean they will necessarily do it. Just because there is a pedestrian path, it does not mean that everyone will always use it. In a similar way, just because someone knows that the company wants him/her to document sales activities, it does not equate that all sales people will document all sales activities. In fact, in practice, we know that spending time on ‘admin’ such as documenting and entering sales activities into a system is often the last thing sales people want to do.
In the next section we will cover how to drive behaviour change.
How to achieve behaviour change
BJ Fogg model
Dr BJ Fogg is a Stanford professor who founded the Behavior Design Lab at Stanford University. BJ Fogg also wrote the New York Times bestseller ‘Tiny Habits’. What I love about this is that the Fogg model is incredibly simple and practical. It is grounded and backed up by significant empirical research and not just an ‘opinion’.
The Fogg model highlights 3 key elements that must converge at the same time for a behaviour to occur.
1. Motivation – Different motivators have different impacts on behaviour
2. Ability – This refers to how easy it is to undertake a behaviour. Some characteristics include time, money, physical effort, brain cycles (or ease of understanding and processing the task at hand), social deviance (the extent to which a behaviour is out of the social norm), and non-routine (behaviour that disrupts an existing routine)
3. Prompt/Trigger – These are reminders of events that prompt a particular behaviour. It could be an alarm, an associated image/event/person/scent, etc that reminds the person of the behaviour.
The power of this model is in its simplicity. You can apply this to any change initiative and the model will guide your thinking on how to design effective behaviour change. When something feels easy to do (low ability), then it will not require a lot of motivation to do it. Alternatively, when something is perceived as very hard to do, then it will require very high motivation to understate the behaviour. The key is to aim above the line. So, either focusing on increasing ability or increasing motivation will result in above the curved line, which means the behaviour taking place.
Example of applying the Fogg model
Case: You are implementing a cost cutting exercise due to the impact of Covid on the organisation. As a result of this exercise, the impacted employees will need to pick up parts of the roles of others who have been let go. The behaviour change required is that impacted employees will need to cover a broader set of tasks and at times have a heavier workload as a result.
Application:
Motivation: The impacted employee’s motivation is currently impacted after seeing their fellow colleagues lose their jobs and hence feeling worried that their jobs may be impacted. This is despite reassurances from senior managers that no more jobs will be cut for the time being. The challenge will be to sufficiently motivate these employees by continuously reassuring them of their job safety and working through the transition of having a broader role responsibility. Appealing to the focus on supporting customers and not letting them down may be a theme to reinforce.
Ability: It is critical to assess to what extent impacted employees are able to carry out new tasks assigned from a skill perspective. Training or coaching may be required. The other area to address is workload concerns. The perception that a heavy workload is required will hinder their likelihood of carrying out the additional responsibilities. Workload prioritisation and protocols are key topics to talk through to reassure employees how workload may eventuate during heavy periods.
Trigger: Different triggers may be designed to remind and reinforce the uptake of new accountabilities. These may include manager 1:1s, team reporting, open visual display of performance indicators, email reminders, colleague reinforcement/coaching, etc.
According to the Fogg model if the new accountabilities are significant it would be best to break these down into smaller behaviour increments vs a ‘big bang’ transition. It could be that there is a gradual transition whereby a period of continuous coaching is required after gradually introducing new sets of tasks for the employee to uptake and practice. After the transition period is completed, the employee then formally uptakes on the full accountabilities.
According to research findings, it is much easier to adopt the new behaviours if the discrete behaviours are broken down to small increment behaviours. Fogg has used lots of different examples of this one of which is doing push-ups. He started by doing 10. Then he would add 1 more every day to the push-up exercise, eventually getting to 100 push-ups. Adding a trigger to the new behaviour is also critical. For example, Fogg gave the example of doing sit-ups first thing in the morning as soon as you get up or doing pushups after going to the toilet. The event of getting up or going to the toilet then becomes a trigger for the new behaviour.
Cognitive Behavioural approaches to behaviour change.
Cognitive behavioural therapy is a widely established clinical approach to changing behaviours in patients suffering from various psychological conditions or disorders. Cognitive approaches are based on the fact that the way one thinks determines one’s reaction and therefore one’s behaviour. For example, self-talk is a mechanism to change one’s opinion or perception. Constantly reinforcing and verbalising positive statements about oneself may improve one’s own perception of oneself. Alternatively, constant negative self-talk leads to negative self-perception.
Behavioural approaches are based on research that started with Pavlov’s research on dogs where he associated bells as a trigger for food. After a period of time, every time the dogs heard the bell they would start salivating, with salivating being the behaviour. This process of associating a trigger with a behavioural reaction is also called ‘conditioning’. The process of conditioning is to ‘re-program’ the subject so that a new behaviour is introduced in reaction to a trigger.
There are many ways in which cognitive behavioural approaches may be applied to changing a person’s behaviour. For example, lets use the previous example of implementing a new system.
Creating or changing impression of the new system
A communications campaign may be devised to create or change the existing impression of the new system. This would be similar to any marketing campaign that associated particular imagery or messages with a feeling or impression. Over a period of repetition, the employees will start to associate positive impressions and key messages with the new system. Any tag-lines that are reinforced by manager briefings or town hall sessions would also act the reinforce the same messages.
As a part of the formal training for the new system, it could be that other than learning the ins and outs of operating the new system, the employee needs to be more proactive in looking at customer information to provide more value-add suggestions to the customer. Practices during the session, along with small nudges and subsequent reinforcements by the team leader or manager, through a corporate social learning platform, would act to build the behaviour change.
The trigger for new behaviours could be any acronyms, diagrams, tag lines, or pictures, and short videos and infographics created as a part of the campaign or training content. It is however important that there is a period of positive reinforcement or else the behaviour may not occur. The reinforcement may take form in terms of manager support, communication messages, prizes, competitions, and reporting on behaviour progress.
This is why post-release embedment is so important as the embedment process focuses on constantly reinforcing the behaviour so that it becomes second nature. Without this, the newly acquired behaviour will not be sustained. This is like exercise. Exercising a few times and your body starting to get the drift of what to do is just the start of the change. Without a period of constant exercising, it will not become a habit.
The other important cognitive behavioural approach to embedding new behaviour is ensuring adequate and effective social support. Some employees may be quite self-sufficient and are able to resolve any system issues themselves. Others may require a lot more hand-holding. This is why there must be change champions in place who can coach and support employees, as highlighted by social learning theory, as an effective way to support the right behaviours and resolve any obstacles in adopting the new system fully.
How to measure behaviours
Measuring behaviours is absolutely critical because without effective measurement it is difficult to ascertain to what extent the desired behaviours have been obtained and sustained. It is the old adage “What gets measured matters”.
So what are some of the ways in which to measure behaviours? These are some common examples.
Manager rating based on observation
Video recording
Phone/call listening
Attendance (e.g. training)
Test
System/digital reporting that tracks behaviour in a system
Employee-wide surveys specifically designed to focus on targeted behaviours
What categories in which to measure behaviours?
There are many considerations or dimensions in measuring behaviours. The following are some of these:
Time: How long would you want to measure the behaviours to ensure that they have fully embedded and incorporated into business-as-usual. Typical practice is several months after the ‘release’. Tracking reinforces behaviours. This means the longer the tracking mechanism continues – the more likelihood the behaviours will last longer
Level of behaviour change: Is the behaviour being measured black and white in its determination? I.e. is it easy to categories if the behaviour has occurred or not? Or are there different levels of behaviour achievement? E.g. If you are measuring if call centre staff has exhibited behaviour is reviewing customer data and offer suggestions, are there different levels of ‘value add’ behaviours based on customer data, in which case there could be a scale to rate this. Alternatively, it could also be a yes/no type of classification
Frequency: How frequent is the behaviour being displayed? Is it that the goal is to promote the frequency of the desired behaviour? Or are there certain limits expected? For example, if we would like call centre staff to offer value add calls with the customer, are there particular ‘ceilings’ or limited after which it may no longer be valuable for the customer?
Situational considerations: Ranking and classifying behaviours should also always consider situational factors. For example, it could be that the customer was not in the right emotional state to receive value-add suggestions and therefore the behaviour would not be appropriate for that situation. It could also be that the call centre consultant has been suffering from sickness or has been struggling with family difficulties and therefore for a period of time was not performing effectively. As a result, previously acquired behaviours could have dropped temporarily
How do we drive full embedment of behaviours?
These are some key call-outs in ensuring that the behaviours you have set out to transition to not only are achieved but are sustained, and to prevent relapse. Pretty much all aspects of change could determine the extent to which behaviours become adopted or not.
1. Executive sponsorship and drive. You will hear a lot of this in literature and articles that with executive sponsorship and drive it is much easier for behaviours to be sustained.
2. Employee community support and reinforcement. This point acts almost as the balancing point of the previous one. With sufficient employee community support and reinforcement, it is possible to drive continual behavioural reinforcement even without strong executive sponsorship.
3. Measurement and reporting. With the right measurement and reporting, employees receive feedback on what their performance has been, and this constant feedback acts as a strong reinforcement feedback loop for managers, training teams, and their direct reports. This is especially the case if everyone can see others’ behavioural performance. It could be by business unit or individual, but ‘naming and shaming’ can work if that is consistent with the organisational cultural values.
4. Early and continuous engagement. This is a change management 101 point. With early and continuous engagement workflow, impacted team members will feel much more engaged with the change. As a result, they will want to exhibit the desired behaviours to make it a success because they feel that they are the ones driving the changes. Alternatively, if the change is perceived as designed and implemented by another party without consultation with the impacted group, there could be resistance or a lack of embedment during the contemplation phase.
5. Culture of continuous improvement. A culture of continuous improvement can also support continual and full embedment of behaviours. If there is a strong culture of analysing the current performance and working on root cause analysis for performance improvement, along with teamwork on appropriate actions to improve performance, then behaviours will be adopted. In this situation, any situational or personal factors or not exhibiting behaviours may be called out and addressed to achieve the targeted outcome.
Complexity of embedding multiple behaviours across multiple initiatives
Most organisations are implementing multiple initiatives at the same time. This is the norm as organisations stay competitive, stay relevant, and in business. When multiple projects are going on all driving seemingly different behaviours.
How do we embed multiple behaviours?
1. Understand the different behaviours across initiatives. Rather than focusing on every single behaviour driven by every initiative, the key is to capture and record the top few behaviours targeted by each initiative. For large organisations with lots of initiatives, this may seem like an impossible feat. It could be organising 1-2 workshops to capture these behaviours. Do note that different initiatives may be at different stages of the product life cycle and therefore it may not be possible to capture all behaviours at a particular point in time. Having a regular change portfolio meeting where this could be discussed and captured iteratively would be ideal.
The Change Compass has just released a feature to aid the collection of core behaviours across initiatives so that these may be analysed, understood, and linked to aid better implementation alignment. You can tag key target behaviours to each initiative or project. For example, customer-centricity or efficiency. Then you can look through those initiatives impacting one part of the business and the core behaviours being driven across multiple initiatives.
2. Analyse and group the captured behaviours. After compiling the behaviours across initiatives the next step is to group and understand them.
Are there behaviours that are part of the same theme? For example, what are initiatives that are promoting a closer focus on the customer by promoting better listening and empathy skills?
Are there any behaviours that are ‘contradictory’ to other behaviours? Here is a real example. For a bank, one initiative was tasked to retire and close off a particular credit card due to a lack of profitability. However, at the same time, the same team was asked to try and sell more of their business unit head to meet their sales target.
3. Examine behaviours that are grouped into the same theme and think of ways to better align and join the dots to improve execution and behaviour embedment. This step is the most crucial step and involves running workshops across initiatives to better align approaches and plan for synergistic implementation of change across initiatives. Key discussion points or opportunities may include:
Aligning key messages and positioning for common behavioural themes. For example, if 2 initiatives are focused on improving customer-centric, how might these better align their communication activities, look and feel of communications collateral, wording, and positioning of behaviours.
Align, cross-leverage and cross-reference learning content. If multiple initiatives are all driving common behaviours, can content be cross-reinforced across multiple initiatives to drive a consistent and aligned user experience? This also ensures that there is no duplication of efforts in covering the same content
Align the sequencing and implementation of change activities. If 2 initiatives are both driving similar behaviours, can the various change activities be better sequenced and aligned to drive a better outcome than 2 separate siloed approaches? For example, can the executive sponsor speak to both initiatives in their town hall address, and can change champions be cross-leveraged to talk about both initiatives to help impacted teams join the dots around the common behaviours?
Successful and fully embedded behavioural change is the epitome of successful change and transformation initiatives. Achieving this is not always easy but having the right focus and adopting a structured approach to design behaviour change will ensure initiative success. Don’t be afraid of experimenting to test different ways in which to drive behaviour change. Keep iterating with different approaches to drive the full adoption of behaviours, which in turn will then ensure the full achievement of initiative benefits.
What is behaviour change in the workplace? Workplace behaviour change refers to a sustained shift in how employees perform their roles, interact with systems, or work with others, as a result of an organisational change initiative. The key word is sustained: a behaviour change is not complete when someone adopts a new way of working once, but when that way of working becomes the default, replacing the previous habit reliably over time.
Why is behaviour change so difficult in organisations? Behaviour change is difficult because it runs up against the force of habit. Research in behavioural neuroscience shows that habitual behaviours are encoded in the basal ganglia, a part of the brain that operates largely outside conscious awareness. Changing ingrained workplace habits requires deliberate repetition, environmental design (making the new behaviour easier than the old one), and consistent reinforcement from managers and peers.
What is the Fogg Behaviour Model and how does it apply to change management? The Fogg Behaviour Model, developed by BJ Fogg at Stanford University, holds that behaviour occurs when motivation, ability, and a prompt converge at the same moment. In a change management context, this means that training alone (building ability) will not drive behaviour change if motivation is absent or if the cue to act is missing from the work environment. Effective change design addresses all three elements simultaneously.
How long does it take to embed a new behaviour at work? The popular notion that habits form in 21 days has no scientific basis. Research published in the European Journal of Social Psychology found that it takes an average of 66 days for a new behaviour to become automatic, with a range from 18 to 254 days depending on the complexity of the behaviour and individual factors. For complex workplace behaviours, change teams should plan for reinforcement over a minimum of three to six months post-go-live.
How do you measure whether a behaviour change has been embedded? The most reliable measures combine observational data (direct observation by managers or coaches using a structured checklist), system-generated data (for tech-enabled changes, usage data reveals whether people are working in the new way), and outcome data (whether the business result the behaviour was designed to achieve is materialising). Self-reported surveys are useful for tracking sentiment and confidence but should not be the sole measure of behaviour change.
Buddhism embraces change as an inherent aspect of life, emphasizing the Pali word for impermanence, anicca. Change is viewed not as a threat, but as an opportunity for growth and enlightenment. By understanding and accepting the transient nature of existence, individuals can cultivate resilience and inner peace, ultimately leading to personal transformation and liberation.
I recently visited my brother and his family in Queensland near the North Eastern tip of Australia. Other than enjoying the nice beaches and tropical surroundings I spend some time with my 2 nephews. One of them is still in secondary school participating in various swimming carnivals over the same weekend. It seemed like yesterday that I had to hold his hand and walk him across the street. And now he is 6 foot three tall and still growing. Like many others undergoing change I reminisced the old days when he was small and cute and cherished the past. Not that the present isn’t great – but a part of us always miss the past and long for some of it to come back.
This made me wonder how generations have undergone change through the ages. Change is a fact of life as we grow and age – life and death. The Kubler-Ross model of the change curve is based on death and grief. This is often utilised to model the experiences that people undergo during change. However, the experience of change is an individual one and one that is dependent on the nature of the change and also how we perceive it. The same change event can be interpreted by one as a positive one and another as a negative one. As a result, for the same change event, for one the Kubler-Ross model of emotional experience can be valid, whilst for another completely the irrelevant.
How do we best deal with the constant changes and the nature of things in our lives? Buddhism, as part of its core Buddhist practice, is steeped in the philosophy that change in life is inevitable, reflecting the teachings of the Buddha as outlined in the sutra. Our thoughts are constantly changing, as are things around us, much like how the monks experience change in their monastic lives. Friends and even family can come and go, so can our belongings, but our attachment to them can lead to suffering. It teaches us that the more we try and hold on to things, the more grief and suffering this will cause us. The more we cling on to the past, the more it will cause us pain. This pain, if not embraced as part of our journey, prevents us from attaining a state of bliss and nirvana that comes from adjusting to the change and the new state of being.
“When we meet real tragedy in life, we can react in two ways–either by losing hope and falling into self-destructive habits, or by using the challenge to find our inner strength.” Dalai Lama.
In Buddhist meditation training, we are taught to be mindful and notice each moment, each sensation, and the dhamma of the environment that we are in. With the ebb and flow of each changing thought or changing moment, we simply notice it, acknowledge it, and apply the same mindfulness to the new state. We notice any feelings we have, acknowledge it as a part of how we react to the situation and move on to continually focus on the new state.
Building change readiness
In the modern organization we are constantly facing a multitude of different changes at the same time. How might we apply the same buddhist philosophy to these changes? We can do this by building awareness within ourselves and our employees that changes are constant, like life itself.
Draw attention to the various changes in an open and matter of fact way.
Build broader consensus of the environment that we are in.
Establish expectation that there will continue to be ongoing changes.
As needed establish routines and operating rhythms to bring the information about the changes to everyone (mindfulness of changes) and acknowledge the environment and challenges that the organization is facing.
Investigate and analyse what channels are required to bring the changes to light so that everyone is well aware and ready for the changes.
“If you want others to be happy, practice compassion. If you want to be happy, practice compassion.” Dalai Lama.
At the same time we need to highlight and prepare employees for the new changes. And as the changes happen, make these explicit. Acknowledge any reactions to the change, address these head on and reference back to what is happening currently. Show compassion for those impacted by the change by being open and supportive. In corporate lives we often only focus on profit and bottom line. Being profitable and financial successful can create good for the organization and its people. However, we can also do a better job at being compassionate about people’s work lives. We can do this by HOW we implement changes. Are we open about what the change is? Or do we hide behind corporate jargon? Do we continuously engage with impacted parties so that they have an optimal change experience?
To build capability for constant changes, we need to consider how leaders message and story-tell the journey of the changes employees have faced, past, present and what the future holds. Link this to the theme of constant change.
Build employee resilience through mindfulness of change. Just like the theme of life and death, draw out the need for constant evolvement within the organization to stay current and relevant.
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Here is a number that rarely appears in transformation business cases: the productivity cost of the change itself.
Organisations routinely model the financial benefits of a new system or operating model. They calculate the headcount savings, the efficiency gains, the revenue uplift. What they rarely model is the six to twelve months during which the productivity of their workforce will fall , sometimes sharply , before those benefits are realised.
This is the productivity dip. Every major change initiative creates one. The question is not whether it will happen, but how severe it will be, how long it will last, and whether you have done enough to shorten it. This article examines what drives the productivity dip during change, what the evidence says about its scale, and what practitioners can do to manage it.
What the data says about productivity loss during change
The productivity impact of organisational change is well-documented, even if it remains chronically underestimated in programme planning.
Willis Towers Watson’s research on workplace transformation found that over a third of employers experienced a measurable decline in productivity as a result of significant organisational change. More than half reported high to moderate anxiety among employees during major transitions, and two-thirds reported work distraction , a leading indicator of productivity loss.
Gallup’s State of the Global Workplace research quantifies the broader disengagement effect: global employee disengagement costs the global economy an estimated $438 billion in lost productivity annually. When organisations run poorly managed change programmes, they accelerate this disengagement among their most affected employee groups.
A 2025 analysis by ActivTrak found that the share of employees at risk of disengagement increased by 23% between 2024 and 2025, with research suggesting that disengagement and attrition could cost a median-size S&P 500 company between $228 million and $355 million per year. Not all of this is attributable to change management failures, but programme-driven change saturation is consistently identified as a contributing factor.
The implication is clear: the productivity dip is not a minor footnote to a transformation programme. For large organisations, it is a multi-million-dollar risk that deserves the same analytical rigour as any other programme cost.
Why the productivity dip happens: the mechanics of transition
Understanding why productivity falls during change is the first step to managing it. The dip is not a single phenomenon , it has several distinct causes that often compound each other.
The learning curve effect
When people are asked to work in new ways , using new systems, following new processes, operating in new team structures , they inevitably take longer to do what they could previously do almost automatically. This is the classic learning curve. Productivity falls in the short term because competence takes time to build.
The steeper the change, the steeper the learning curve. A minor process update might create a negligible dip. An enterprise-wide ERP implementation that changes how every transaction is processed can create a performance trough that lasts months.
The uncertainty and anxiety effect
Change creates uncertainty, and uncertainty is cognitively expensive. Research on workplace anxiety during transformation consistently shows that when employees are uncertain about their role, their job security, or how they are expected to perform in the new environment, their capacity for focused work drops significantly.
People spend time processing the change , discussing it with colleagues, seeking information, managing anxiety , rather than delivering at their normal pace. This is not irrational behaviour. It is a predictable response to an uncertain environment.
The cumulative change load effect
The productivity dip is significantly amplified when employees are experiencing multiple significant changes simultaneously. A team navigating a restructure, a new performance management framework, and a technology platform migration at the same time is not facing three manageable changes , they are facing a compounding load that can exceed their capacity to absorb and adapt.
McKinsey’s 2024 research on transformation highlights this directly: organisations running multiple transformations concurrently face compounding risk that goes beyond what individual programme risk assessments typically capture. Managing cumulative change load is one of the most important, and most underinvested, aspects of enterprise change management.
The disengagement effect
Not all employees who struggle with change become disengaged, but a significant proportion do , particularly those who feel the change was poorly communicated, who did not feel involved in the process, or who do not understand the rationale for what is being asked of them.
Disengaged employees are not simply less productive in a quantifiable sense. They are also more likely to resist the change actively or passively, to share negative sentiment with peers, and to leave the organisation , taking institutional knowledge and capability with them.
Five evidence-based strategies to minimise the productivity dip
The productivity dip cannot be eliminated entirely. But it can be shortened, shallowed, and managed. Here are five strategies supported by research and practitioner experience.
1. Quantify the expected dip in the business case
The single most important thing you can do to prepare your organisation for the productivity dip is to make it visible before the programme begins.
Build a productivity impact model into the programme business case. Estimate the duration and depth of the dip for the most affected groups, and translate it into financial terms. This does two things: it sets realistic expectations with leadership, and it creates a budget case for investment in change management support.
A business case that shows a twelve-month payback period based solely on benefit realisation, without accounting for a six-month productivity trough, is presenting a misleadingly optimistic picture. Making the dip explicit is not pessimism , it is intellectual honesty, and it protects the programme when the inevitable short-term performance decline materialises.
2. Invest in change management earlier, not later
Prosci’s research on change management timing consistently shows that change management deployed early in a project lifecycle , during design, not just implementation , is significantly more effective than change support added after go-live.
By the time productivity is visibly declining, the window for the most impactful interventions has usually passed. Early change management focuses on leader alignment, employee awareness, and readiness building , all of which reduce the depth of the dip at go-live.
The organisations that minimise productivity loss are those where change practitioners have been involved in programme design, not just programme delivery.
3. Manage cumulative change load deliberately
If your employees are experiencing three, four, or five significant changes simultaneously, no amount of good communication will fully offset the cognitive and emotional load they are carrying.
Change portfolio management , the discipline of tracking and managing the total volume of change across an organisation , is a practical response to this problem. By mapping which groups are affected by which initiatives, and sequencing or pacing change to avoid overload in any single group, organisations can meaningfully reduce the cumulative impact on productivity.
This kind of portfolio visibility requires data , specifically, change impact data aggregated across programmes in a consistent format. Platforms like Change Compass are built precisely for this purpose, enabling enterprise change teams to identify which groups are most at risk of change saturation and to make evidence-based decisions about pacing and prioritisation.
4. Invest in targeted capability building, not just training
The standard response to the learning curve effect is training. But generic, volume-led training programmes are one of the least efficient ways to address a productivity dip. The most effective interventions are targeted to the specific capability gaps created by the change, delivered in a format that matches how each group actually learns, and timed to when people are ready to apply the new capability.
This requires a clear picture of what each affected group needs to know and be able to do differently. The change impact assessment drives this, as discussed earlier in this series. The key principle is that training design should follow impact analysis, not precede it.
Just-in-time training , delivered close to the point where new capability is needed , consistently outperforms early, front-loaded training for productivity recovery. People forget what they learned two months ago. They retain what they practise immediately.
5. Build a visible measurement and recovery framework
One of the reasons productivity dips persist longer than they need to is that organisations lack the mechanisms to detect them early and respond quickly. If you are waiting for quarterly performance data to identify that productivity has declined, you are months behind where you need to be.
Build a measurement framework that includes leading indicators of the dip , early adoption rates, support ticket volumes, manager-reported confidence levels, self-reported readiness surveys , alongside lagging indicators of business performance. Monitor these indicators weekly during and immediately after go-live, and have a response protocol for groups showing early warning signs.
Research by Gartner on change management success suggests that the organisations with the best change outcomes have systematised their response to performance signals, rather than treating each dip as a unique event requiring an ad hoc response.
The role of leadership in managing the productivity dip
No technical change management strategy will fully compensate for leaders who are not genuinely present during a transition. One of the strongest predictors of how quickly productivity recovers is whether employees’ direct managers are visible, informed, and actively supporting the change.
This matters for a specific reason: the primary source of information and reassurance for most employees during a change is their direct manager, not a central communications team. If managers are uncertain, avoidant, or visibly resistant, that signals to their teams that the change is more threatening than the official messaging suggests.
Equipping managers to lead through change , with clear information, talking points, and personal support , is one of the highest-return activities in a change programme. The productivity cost of a disengaged middle-management layer is far higher than the cost of a structured manager engagement programme.
Monitoring productivity recovery in real time
One of the practical challenges of managing the productivity dip is knowing when you are actually through it. Without consistent measurement, organisations often assume recovery has occurred before it has , and withdraw change support too early as a result.
Effective recovery monitoring combines quantitative data (system usage rates, process cycle times, quality metrics) with qualitative signals (employee confidence surveys, manager assessments, support volumes). Tracking both allows you to distinguish between apparent recovery (people have stopped complaining) and actual recovery (performance has returned to baseline or better).
Digital change management platforms like Change Compass can support this monitoring by consolidating adoption data across the programme portfolio, flagging groups where adoption is lagging behind plan, and providing a single view of change health across the organisation.
The productivity dip during change is predictable, quantifiable, and manageable. It is not an inevitable cost of doing business. Organisations that treat it as such , accepting performance decline as unavoidable , are leaving value on the table and creating unnecessary difficulty for their employees.
The key disciplines are: building the dip into your business case so it is expected and budgeted for, investing in change management early rather than reactively, managing cumulative change load at the portfolio level, targeting capability building to actual gaps, and measuring recovery with enough granularity to respond when groups fall behind.
None of these is technically complex. What they require is the conviction that the productivity dip matters enough to plan for , and a change function with the data and the mandate to act.
Frequently asked questions
What is the productivity dip during change?
The productivity dip is the temporary decline in workforce output that occurs when an organisation implements significant change. It is caused by the combined effects of learning new processes or systems, the cognitive cost of uncertainty, and the disruption of established working patterns. The depth and duration of the dip vary depending on the scale of change, the level of preparation, and the quality of change management support.
How long does the productivity dip typically last?
Duration varies considerably by change type and management quality. Minor process changes may create a dip of days to weeks. Major technology implementations or structural reorganisations can produce a productivity trough lasting three to nine months. With strong change management, including early preparation, targeted training, and leadership engagement, the dip can be shortened significantly compared to unmanaged transitions.
How do you measure the productivity dip during change?
Effective measurement combines leading and lagging indicators. Leading indicators include system adoption rates, self-reported confidence surveys, support ticket volumes, and manager-assessed readiness. Lagging indicators include output metrics, quality measures, and cycle times. Tracking both provides early warning of groups at risk and confirms when genuine recovery has been achieved.
Can the productivity dip be avoided entirely?
Not entirely , some degree of performance decline is inherent in the transition to new ways of working. However, the depth and duration of the dip can be reduced substantially through proactive change management. Organisations with excellent change management support are documented to achieve significantly better project timelines and outcomes than those with poor or absent change management.
What role does cumulative change load play in the productivity dip?
Cumulative change load , the total volume of change being asked of an employee or group at any one time , is one of the strongest amplifiers of the productivity dip. A group experiencing three significant changes simultaneously faces a compounding burden that can exceed their capacity to adapt. Managing cumulative load through change portfolio visibility and deliberate sequencing is one of the most effective structural interventions available.
How does leadership behaviour affect the productivity dip?
Leadership behaviour is a critical moderating factor. Visible, informed leaders who actively communicate the rationale for change and support their teams through transition consistently produce faster recovery curves than absent or resistant leaders. Equipping managers with the information and tools to lead through change is one of the highest-return investments in the change management toolkit.
Most organisations treat change management as something that happens within projects. A sponsor is appointed, a communication plan is written, some training is delivered, and the initiative moves on. Then the next project starts, and the whole cycle repeats from scratch, as if the organisation learned nothing from the last one.
This project-by-project approach is the hallmark of low change management maturity. And it has a measurable cost. Prosci’s research shows that organisations with excellent change management are seven times more likely to meet project objectives. WTW’s 2023 global study of 600 organisations found that companies taking a proactive, data-driven approach to change management drove nearly three times more revenue than those with below-average change effectiveness. These results do not come from applying change management to one project at a time. They come from building it as a permanent organisational capability.
This guide provides a practical framework for assessing and advancing your organisation’s change management maturity, moving from ad hoc project support to embedded organisational competency.
What change management maturity means
Change management maturity describes the degree to which an organisation has embedded change management as a consistent, scalable, and continuously improving capability, rather than an activity performed inconsistently within individual projects.
Two established models have shaped the field. The Prosci Change Management Maturity Model evaluates organisations across five capability areas: leadership, application, competencies, standardisation, and socialisation. The Change Management Institute (CMI) model takes a similar five-level approach but emphasises three domains: project change management, business change readiness, and strategic change leadership.
Both models share a core insight: maturity is not about doing change management on more projects. It is about building the systems, governance, leadership behaviours, and measurement practices that make effective change management the default way the organisation operates.
The five levels of change management maturity
While the Prosci and CMI models differ in their specifics, they converge on a five-level progression. The framework below synthesises both into a practical model you can use for self-assessment.
| Level | Name | Characteristics | Typical pain points | |——-|——|—————-|——————-| | 1 | Ad hoc | No consistent CM approach. Success depends on individual heroics. | Repeated mistakes, no institutional learning, inconsistent stakeholder experience | | 2 | Emerging | Some projects apply CM, but methods and quality vary widely. | Pockets of excellence alongside projects with no CM at all; no shared tools or templates | | 3 | Standardised | Organisation-wide CM standards exist. Common tools, templates, and training. | Standards exist on paper but are not consistently enforced; compliance is uneven | | 4 | Managed | CM integrated into project governance. Metrics tracked and reported. Portfolio-level visibility. | Governance can feel bureaucratic; risk of CM becoming a checkbox exercise rather than strategic | | 5 | Optimised | CM is a core organisational competency. Continuous improvement, data-driven, enterprise-wide. | Maintaining momentum; avoiding complacency; adapting to new types of change (AI, automation) |
Most organisations sit at Level 1 or 2. Gartner’s research found that only 32% of business leaders report achieving healthy change adoption, which suggests that the majority of organisations have not yet built the capability infrastructure needed for consistent success.
Diagnosing your current maturity level
Before you can advance maturity, you need to know where you are. The following diagnostic questions map to each level and can be used as a practical self-assessment.
Level 1 diagnostic: Ad hoc
Is change management applied inconsistently, with some projects having dedicated CM support and others having none?
Do project teams create their own approaches from scratch each time?
Is there no central function, community of practice, or shared methodology for change management?
If you answered yes to most of these, your organisation is at Level 1. The priority is to establish a baseline methodology and begin demonstrating value on a small number of visible projects.
Level 2 diagnostic: Emerging
Do some project teams apply change management using a recognised methodology, but others do not?
Are there pockets of CM expertise but no organisation-wide standard?
Is change management viewed as a project-level activity rather than an organisational capability?
Level 2 organisations need to standardise their approach, building shared tools, templates, and training that create consistency across the project portfolio.
Level 3 diagnostic: Standardised
Does the organisation have a documented CM methodology, standard templates, and training programmes?
Are change practitioners trained in a common approach?
Is CM expected on all significant projects, even if enforcement is inconsistent?
Level 3 organisations have the foundations in place. The challenge is moving from standards that exist to standards that are enforced and integrated into governance. For more on building assessment capability, see our guide to change management assessments.
Level 4 diagnostic: Managed
Is CM formally integrated into project governance (gate reviews, investment decisions, steering committees)?
Are CM metrics tracked, reported, and used to inform decisions?
Does the organisation assess change at the portfolio level, not just initiative by initiative?
Is there executive-level accountability for change management effectiveness?
Level 4 organisations are performing well. The opportunity is to move from managed governance to true organisational capability, where CM is embedded in culture, not just process.
Level 5 diagnostic: Optimised
Is CM viewed as a strategic organisational competency, not a project support function?
Does the organisation continuously improve its CM practices based on data and lessons learned?
Are leaders at all levels competent in change leadership, not just change practitioners?
Is change management integrated into strategic planning, not just project delivery?
Level 5 is rare. Organisations that reach it treat change capability as a competitive advantage and invest accordingly.
The business case for investing in change management maturity
The evidence linking maturity to performance is strong and growing.
McKinsey’s research found that only 26% of transformations succeed at both improving performance and sustaining those improvements. However, organisations that take a rigorous, structured approach report success rates of 79%, three times the average. That gap represents the difference between ad hoc project-level change management and mature, systematic capability.
The financial implications are equally clear. WTW’s research found that “change accelerator” organisations outperformed on one-year revenue change (6% versus -30% for less capable organisations), three-year revenue growth (4% versus -7%), and gross profit margin (19% versus -13%).
These are not marginal differences. They represent the compounding effect of consistently managing change well across the entire organisation, which is precisely what maturity enables.
Common maturity traps to avoid
The journey from Level 1 to Level 5 is not linear, and several common mistakes can stall progress or create the illusion of maturity without the substance.
Over-investing in training without governance
Sending 200 people through change management certification does not build maturity if there is no governance framework requiring them to apply what they learned. Training builds individual competency; maturity requires organisational systems that activate and sustain that competency.
Confusing activity with capability
An organisation that produces change impact assessments, communication plans, and training schedules for every project may look mature. But if those artefacts are produced by rote without influencing decisions, they are documentation, not capability. True capability means the organisation uses change management data to make different decisions than it would otherwise make.
Trying to jump levels
Organisations at Level 1 sometimes attempt to leap directly to Level 4 by implementing enterprise-wide governance without first building the foundational methodology and skills. This typically produces a bureaucratic framework that practitioners resent and circumvent. Each level builds on the one below it.
Treating maturity as a destination
Level 5 is not a finish line. Organisations that reach high maturity must continue investing to maintain it, adapting their practices to new types of change (AI-driven transformation, continuous delivery models, distributed workforces) and refreshing their capability as experienced practitioners move on.
How to advance from your current level
Moving from Level 1 to Level 2
Focus on demonstrating value. Select 2-3 high-visibility projects and apply a structured CM methodology rigorously. Document outcomes and build an internal evidence base. Establish a small community of practice to begin sharing approaches and lessons learned.
Moving from Level 2 to Level 3
Standardise the methodology. Create organisation-wide templates, tools, and training. Establish minimum CM requirements for all projects above a defined threshold. Build or hire a central CM capability that supports project teams.
Moving from Level 3 to Level 4
Integrate CM into governance. Add CM criteria to project gate reviews and investment decisions. Build portfolio-level visibility of change load and adoption. Establish metrics and reporting that reach executive leadership. See our guide on measuring change management outcomes for practical measurement frameworks.
Moving from Level 4 to Level 5
Embed CM into culture. Develop change leadership competency at all management levels, not just among CM practitioners. Build continuous improvement mechanisms that use data to refine practices. Integrate CM into strategic planning, not just project delivery. Invest in digital platforms that enable real-time, portfolio-wide change intelligence.
How digital platforms accelerate maturity
Building change management maturity at Levels 3-5 requires data infrastructure that manual methods cannot provide. Portfolio-level visibility, real-time adoption tracking, cumulative impact analysis, and measurement dashboards all require tooling.
Digital change management platforms such as The Change Compass enable organisations to manage change at the portfolio level, visualise cumulative impact across stakeholder groups, and track adoption metrics in real time. This is particularly valuable for organisations at Level 3 and above, where the shift from project-level to portfolio-level capability requires data that spreadsheets and manual processes cannot sustain. For organisations moving beyond heatmaps toward dynamic analytics, digital platforms are not optional; they are foundational.
Change management maturity is not about achieving a perfect score on a model. It is about building the organisational capability to manage change consistently, measure its impact rigorously, and improve continuously. Start by diagnosing where you are today using the five-level framework. Identify the specific gaps between your current level and the next. Invest in the systems, governance, skills, and leadership behaviours that will close those gaps. The organisations that build change management maturity do not just deliver better individual projects; they build a compounding advantage that makes every subsequent transformation more likely to succeed.
Frequently asked questions
What is change management maturity? Change management maturity describes the degree to which an organisation has embedded change management as a consistent, scalable, and continuously improving capability. It progresses through five levels, from ad hoc project support to a core organisational competency integrated into governance, culture, and strategic planning.
How long does it take to advance change management maturity? Moving one level typically takes 12-24 months of sustained effort. Moving from Level 1 to Level 3 can take 2-4 years. Progress depends on executive sponsorship, investment in capability building, and willingness to integrate CM into governance. Trying to compress timelines by skipping levels typically backfires.
Do you need a consultant to build change management maturity? External consultants can accelerate specific stages, particularly initial methodology design and benchmarking against industry peers. However, sustainable maturity must be built internally. The most effective approach is to use external expertise to establish foundations and transfer capability, then build and maintain maturity through internal teams and systems.
What is the relationship between change management maturity and organisational culture? Culture and maturity reinforce each other. An organisation with a strong change culture, where leaders model adaptive behaviours and employees expect continuous improvement, will find it easier to advance maturity. Conversely, building maturity practices (governance, measurement, shared methodology) gradually shifts culture toward greater change capability. Neither can be built in isolation.
Can an organisation be at different maturity levels for different types of change? Yes. Many organisations demonstrate higher maturity for technology-driven changes (where project methodologies enforce CM) than for cultural or structural changes. This is common and worth diagnosing explicitly, as it reveals where targeted investment is needed.
How do you measure change management maturity? Use a structured self-assessment against the five maturity levels, evaluating capability areas such as methodology standardisation, governance integration, leadership competency, measurement practices, and portfolio-level visibility. Complement self-assessment with benchmarking against industry standards (Prosci or CMI models) and track progress annually.
Suggested title: Change management maturity: a practical guide to building organisational capability
Suggested meta description: Assess your change management maturity across 5 levels with diagnostic questions and a practical framework for advancing organisational capability.
How can understanding the change adoption curve benefit organizations?
Understanding the change adoption curve benefits organizations by identifying how different individuals or groups respond to change. By recognizing these stages—innovators, early adopters, early majority, late majority, and laggards—companies can tailor their strategies to enhance communication, support, and ultimately improve the success of change initiatives.
Measuring change adoption is one of the most important parts of the work of change practitioners. It is the ultimate ‘proof’ of whether the change interventions have been successful or not in achieving the initiative objectives. It is also an important way in which the progress of change management can clearly be shown to the project team as well as to various stakeholder groups. The ability to show clearly the progress of change outcome is critical to focus your stakeholders’ actions on the right areas. It is one of the key ways to ‘prove your worth’ as a change practitioner.
Measurement takes time, focus and effort. It may not be something that is a quick exercise. There needs to be precise data measurement design, a reliable way of collecting data, and data visualisation that is easily understood by stakeholders.
With the right measurements of change adoption, you can influence the direction of the initiative, create impetus amongst senior stakeholders, and steer the organisation toward a common goal to realise the change objectives. Such is the power of measuring change adoption.
The myth of the change management curve
One of the most popular graphs in change management, and often referred to as the ‘change curve’, is the Kubler-Ross model that outlines the stages of personal transition. The model was specifically designed by psychiatrist Elisabeth Kubler-Ross to refer to terminally ill patients as a part of the book ‘On Death and Dying’. For whatever reason, it has somehow gained popularity and application in change management, making it crucial to be very careful when applying this model to address potential adoption barriers in a change context.
There is little research evidence to back this up even in psychological research. When applied in change management, there is no known research that supports this at all. So be careful when you come across models such as this one that is simple and seem intuitively ‘correct’, as they may overlook stakeholders’ voices and input, which can lead to new ideas. On the other hand, there is ample research by McKinsey that shows the best way for effectively managed initiatives and transformations is that stakeholders do not go through this ‘valley of death’ journey at all.
If the ‘change curve’ is not the correct chart to follow with regard to change adoption, then what is the right one to refer to? Good question.
The ‘S’ curve of change adoption is one that can be referenced. It is well backed in terms of research from technology and new product adoption. It begins with a typically slow start followed by a significant climb in adoption followed by a flattened level at the end. Most users typically do not uptake the change until later on.
Here is an example of key technologies and the speed of adoption in U.S. households since the 1900s.
With the different types of change contexts, the shape of the S curve will be expected to differ as a result. For example, you are working on a fairly minor process change where there is not a big leap in going from the current process to the new process. In this case, the curve would be expected to be a lot more gentle since the complexity of the change is significantly less than adopting a complex, new technology.
On the other hand, if you are working on many iterative agile changes, each iteration that impacts users may be a small S curve in themselves. Ideally, each iteration work together towards a greater piece of overarching change.
Going beyond what is typically measured
Most change practitioners are focused on measuring the easier and more obvious measures such as stakeholder perceptions, change readiness, and training completion. Whilst these are of value, they in themselves are only measuring certain aspects of the change process. They can be viewed as forward-looking indications of the progress that supports moving toward eventual change adoption, versus the eventual change adoption.
To really address head-on the topic of measuring adoption of new products, it is critical to go beyond these initial measures toward those elements that indicate the actual change in the organisation, especially focusing on early adopters. Depending on the type of change this could be system usage, behaviour change, following a new process or achieving cost savings targets.
Project Benefit realization
It goes without saying that to really measure change adoption the change practitioner must work closely with the project manager to understand in detail the benefits targeted, and how the prescribed benefits will be measured. The project manager could utilise a range of ways to articulate the benefits of the project. Common benefit categories include:
Business success factors such as financial targets on revenue or cost
Product integration measures such as usage rate
Market objectives such as revenue target, user base, etc.
These categories above are objectives that are easier to measure and tangible to quantify. However, there could also be less tangible targets such as:
Competitive positioning
Employee relations
Employee experience
There could be various economic methods of determining the targeted benefit objectives. These include payback time or the length of time from project initiation until the cumulative cash flow becomes positive, or net present value, or internal rate of return on a new tool.
Employee capability
Customer experience
There could be various economic methods of determining the targeted benefit objectives. These include payback time or the length of time from project initiation until the cumulative cash flow becomes positive, or net present value, or internal rate of return.
The critical aspect for change practitioners is to understand what the benefit objectives are, how benefit tracking will be measured and to interpret what steps are required to get there. These steps include any change management steps required to get from the current state to the future state.
Here is an example of a mapping of change management steps required in different benefit targets:
Increased customer satisfaction and improved productivity through implementing a new system. | Users able to operate the new system.Users able to improve customer conversations leveraging new system features.Users proactively use the new system features to drive improved customer conversations.Managers coaching and provide feedback to usersBenefit tracking and communications.Customer communication about improved system and processesDecreased customer call waiting time . | % of users passed training test.System feature usage rate.Customer issue resolution time.User feedback on manager coaching.Monthly benefit tracking shared and discussed in team meetings.Customer satisfaction rate. Customer call volume handling capacity.
Measuring behavioural change
For most change initiatives, there is an element of behaviour change, especially for more complex changes. Whether the change involves a system implementation, changing a process or launching a new product, behaviour change is involved. In a system implementation context, the behaviour may be different ways of operating the system in performing their roles. For a process change, there may be different operating steps which need to take place that defers from the previous steps. The focus on behaviour change aims to zoom in on core behaviours that need to change to lead to the initiative outcome being achieved.
How do we identify these behaviours in a meaningful way so that they can be identified, described, modelled, and measured?
The following are tips for identifying the right behaviours to measure:
Behaviours should be observable. They are not thoughts or attitudes, so behaviours need to be observable by others
Aim to target the right level of behaviour. Behaviours should not be so minute that they are too tedious to measure, e.g. click a button in a system. They also should not be so broad that it is hard to measure them overall, e.g. proactively understand customer concerns vs. what is more tangible such as asked questions about customer needs in XXX areas during customer interactions.
Behaviours are usually exhibited after some kind of ‘trigger’, for example, when the customer agent hear certain words such as ‘not happy’ or ‘would like to report’ from the customer that they may need to treat this as a customer complaint by following the new customer complaint process. Identifying these triggers will help you measure those behaviours.
Achieve a balance by not measuring too many behaviours since this will create additional work for the project team. However, ensure a sufficient number of behaviours are measured to assess benefit realisation
Measuring micro-behaviours
Behaviour change can seem over-encompassing and elusive. However, it may not need to be this. Rather than focusing on a wide set of behaviours that may take a significant period of time to sift, focusing on ‘micro-behaviours’ can be more practical and measurable. Micro-behaviours are simply small observable behaviours that are small step-stone behaviours vs a cluster of behaviours.
For example, a typical behaviour change for customer service reps may be to improve customer experience or to establish customer rapport. However, breaking these broad behaviours down into small specific behaviours may be much easier to target and achieve results.
For example, micro-behaviours to improve customer rapport may include:
User the customer’s name, “Is it OK if I call you Michelle?”
Build initial rapport, “How has your day been?”
Reflect on the customer’s feeling, “I’m hearing that it must have been frustrating”
Agree on next steps, “would it help if I escalate this issue for you?”
Each of these micro-behaviours may be measured using call-listening ratings and may either be a yes/no or a rating based assessment.
After having designed the right measurement to measure your change adoption, the next step would be to design the right reporting process. Key considerations in planning and executing on the reporting process includes:
Ease of reporting, you should aim to automate where possible to reduce the overhead burden and manual work involved. Whenever feasible leverage automation tools and in-app options to move fast and not be bogged down by tedious work
Build expectations on contribution to measurement. Rally your stakeholder support so that it is clear the data contribution required to measure and track change adoption
Design eye-catching and easy to understand dashboard of change adoption metrics.
Design reinforcing mechanisms. If your measurement requires people’s input, ensure you design the right reinforcing mechanisms to ensure you get the data you are seeking for. Human nature is so that whenever possible, people would err on the side of not contributing to a survey unless there are explicit consequences of not filling out the survey.
Recipients of change adoption measurement. Think about the distribution list of those who should receive the measurement tracking. This includes not just those who are in charge of realising the benefits (i.e. business leaders), but also those who contribute to the adoption process, e.g. middle or first-line managers.
Example of change adoption dashboard from Change Automator
Measuring Adoption Across Initiatives
You may be driving multiple initiatives as a part of a large program or a portfolio of initiatives. The key challenge here is to establish common adoption measures that are apple-to-apple metrics comparisons across initiatives. Yes, each initiatives will most likely have different sets of what constitutes adoption. However, there are still common ways to report on adoption across initiatives such as overall percentage of adoption of identified adoption elements, or percentage of the number of milestones reached. You can also utilise manager reports of behaviours adopted, as well as system records of utilisation of certain features for example.
Understanding change adoption is not only helpful to understand what works for one initiative, it can also be a linchpin to help you scale change adoption across change initiatives across your whole portfolio. Talk to us to find out more about how The Change Compass, a digital adoption platform, can help you understand what change interventions lead to higher change adoption rates in the flow of work, through data. Using a data-led approach in deciphering what drives change adoption can truly drive successful change outcomes.
Change adoption refers to the extent to which employees have actually changed their behaviour to work in the new way required by a change initiative. Full adoption means the new behaviour has been embedded and the old way of working has been replaced. Partial adoption – where employees comply in some contexts but revert to old habits in others – is a common failure mode that is often mistaken for success.
How long does change adoption take?
Simple process changes may reach full adoption within 30-60 days of go-live. Significant system changes or behavioural changes typically take 90-180 days to reach stable adoption. Cultural or leadership changes may take 12-24 months or more to fully embed.
What is the difference between change adoption and change compliance?
Compliance is doing the required thing when observed or required; adoption is doing the new thing consistently because it has become the normal way of working. Employees who are complying but not adopting will revert to old behaviours when oversight is reduced.
