Change adoption is the heart of every change practitioner’s work. It’s the primary measure of whether a change initiative truly succeeds, yet, surprisingly, many organizations still fail to adequately track, measure, and manage change adoption. Without a clear understanding of how well end-users are adopting the change, it’s nearly impossible to gauge the initiative’s real impact on the business. Change adoption must be both intentional and managed, not just assumed.
If you search for change adoption on Google the top articles seem to refer to the same things. These include transition preparation, communication, training and support. The top 2 articles are by Whatif and Walkme and seem to emphasise the importance of in-app training products they offer. The Prosci article emphasise the ADKAR model on the other hand.
While common strategies for change adoption—such as communication, training, and support—are essential, these are foundational steps and not the complete formula for sustained adoption. There’s a nuanced spectrum of factors that contribute to adoption, including the type of change, the stakeholders, the organization’s capacity for change, measurement metrics, and performance management. The following insights explore these core factors and share practical strategies, bolstered by real-world examples, to help change practitioners improve adoption rates across their organizations.
1. Understanding the Type of Change
The nature of the change plays a significant role in determining how to drive adoption. A change can range from a simple update in process to a fundamental shift in behaviour, and this range requires different approaches:
– Simple Changes : Minor changes, like a new software feature or a small process tweak, may only need a basic communication update. For instance, consider an HR team implementing a new self-service portal for employees to access their pay stubs. In this case, a simple email announcement explaining how to access the feature, along with a short tutorial video, might be all that’s required to ensure adoption.
– Complex, Behavioural Changes : For more complex changes that impact behaviours or workflows, adoption strategies need to be more involved. Imagine an organization implementing a new performance review system that shifts from annual reviews to ongoing, quarterly feedback sessions. This type of change isn’t just procedural—it demands a shift in how employees and managers think about performance. Here, communication alone won’t be sufficient. It requires ongoing training, leadership modeling, reinforcement through feedback loops, and alignment with performance metrics. Regular team meetings can serve as a platform for leaders to showcase the change, while role-playing sessions can help embed the new behaviours.
Analogy : Think of the change type as similar to cooking different dishes. For a quick salad, all you need is the right ingredients and a bowl to toss them in. For a complex dish like a soufflé, you’ll need precise measurements, specific tools, and careful monitoring to ensure it doesn’t collapse. The type of change similarly determines the level of preparation and intervention required.
2. Tailoring Strategies to Stakeholder Types
Understanding your end-users or stakeholders—those directly impacted by the change—is crucial. Each group will have different engagement channels and needs, which means you can’t rely on a one-size-fits-all communication plan. To drive adoption, you need to deliver information in ways that resonate with each audience.
– Identify Effective Channels : For example, one team may prefer to discuss updates in weekly meetings, while another may respond better to monthly town hall sessions. When a global retail company rolled out a new inventory management system, the change team customized its communication and training by region. Regional managers were empowered to communicate the changes in a way that suited their teams’ preferences, whether that meant team huddles, newsletters, or one-on-one conversations. As a result, the change was embraced much more readily because each team felt that the approach was tailored to their needs.
– Build Change into Routine Communication : To make the change part of the team’s daily workflow, leverage existing channels, like monthly business reviews or quarterly updates. For instance, if sales teams have weekly performance meetings, consider incorporating brief updates about how the change (such as a new CRM feature) can benefit their sales process, along with success stories from team members.
Analogy : Think of stakeholder engagement as similar to hosting a dinner party. You wouldn’t serve the same meal to every guest without considering their preferences. Similarly, change practitioners need to “serve” the change in ways that appeal to each stakeholder group’s tastes and communication preferences.
3. Aligning with Organisational Change Capacity
Change capacity—the organization’s ability to absorb and adopt change—is a critical but often overlooked factor. The timing of introducing new changes matters, especially when the change is complex. If an organization is already handling multiple projects or transformations, adding another initiative can result in resistance or “change fatigue.”
– Manage Competing Priorities : Suppose a financial services company is simultaneously upgrading its internal software, launching a new customer-facing app, and implementing a data security compliance initiative. Launching yet another change, like a new employee recognition program, may overwhelm employees, who may deprioritize it in favour of what they perceive as more urgent projects. Change practitioners should work closely with program managers to prioritize initiatives and strategically phase them to avoid saturation.
– Change Portfolio Management : Treat change initiatives as part of a portfolio. By actively managing this portfolio, you can ensure changes are introduced in waves that the organization can absorb. Regularly review the status of active changes with stakeholders to reassess the capacity and timing. This way, your adoption efforts won’t be diluted by other competing projects.
Analogy : Imagine trying to load groceries into an already-full refrigerator. Some items will fit, but others might have to wait. The same concept applies to organizational change capacity—only so much can fit into the organization’s “refrigerator” at once before things start falling out.
4. Defining and Measuring Adoption Metrics
Effective change adoption strategies hinge on clear metrics. Without defined adoption goals and measurement tools, it’s difficult to determine if users are actually embracing the change or merely checking boxes. Metrics will vary depending on the change and should be relevant to the behaviours or outcomes desired.
– Set Clear Adoption Metrics : For example, a company introducing a new collaborative software might measure adoption through the frequency of use, the number of shared documents, or the volume of cross-departmental activity within the platform. Each of these metrics helps track actual usage and determine if employees are using the tool to its full potential.
– Gauge Awareness, Willingness, and Competency : Assess and understand stakeholder readiness for the change at hand. Do they have the awareness, motivation and know-how for the new expected behaviours? Conduct regular surveys or feedback sessions to assess where teams are on the adoption curve. This approach can highlight areas where additional support is needed, such as more coaching or stronger reinforcement from leadership.
Analogy : Think of adoption metrics like the gauges in a car’s dashboard. Each gauge (speed, fuel, engine temperature) provides specific insights into the car’s overall performance, just as adoption metrics give insights into how well a change is taking hold within the organization.
5. Ongoing Performance Management for Sustained Adoption
Adoption isn’t a “one and done” effort. It requires continuous management, monitoring, and, ideally, integration into performance management. By tracking and reinforcing adoption metrics over time, organizations can keep the change front and centre and drive deeper, lasting adoption.
– Incorporate Adoption into KPIs : Align adoption goals with KPIs to maintain visibility. For example, if the goal is to increase the use of a project management tool, set a KPI that tracks project updates within the tool. Managers can be held accountable for meeting this KPI, incentivizing their teams to incorporate the tool into their workflow.
– Regular Check-Ins and Feedback: Use data-driven insights to adjust your strategy as needed. For instance, if certain teams lag in adoption rates, consider arranging tailored training sessions or conducting one-on-one interviews to understand the barriers they’re experiencing. Continuous feedback loops allow change practitioners to refine their approach based on real-time adoption data. Performance needs to be constantly nurtured, reinforced and managed. No ‘set and forget’ approach will work.
Analogy: Sustaining adoption is like maintaining a healthy habit. Just as regular exercise requires motivation, tracking, and routine check-ins to stay consistent, ongoing performance management helps ensure that change remains a part of the organizational fabric.
Data as the Catalyst for Improved Change Adoption
Data-driven insights are game-changers for change adoption. They enable change practitioners to move beyond guesswork and implement strategies with measurable, predictable results. By leveraging analytics, organizations can identify successful tactics based on stakeholder type, change type, and historical adoption patterns.
For example, by analyzing adoption data from previous projects, a technology company could discover that smaller, incremental training sessions worked better for developers than day-long sessions. This insight could inform future adoption strategies and improve the likelihood of success for similar changes.
Utilizing data to understand what drives adoption allows change practitioners to apply these learnings across the organization, achieving more consistent and reliable outcomes. Through correlation and prediction, organizations can anticipate which approaches will work best for each type of change and tailor their strategies accordingly.
This is exactly what we’ve been doing at The Change Compass. We’ve incorporated automation and AI to provide data insights that tell you what tactics and approaches work to maximise change adoption based on data. You can also drill into what works for particular stakeholders, business units and types of changes. Data insights can also inform what volume of change may stifle change adoption.
Designing change approach and interventions should not be guess work. So far, companies try to enhance their rates of change adoption success by hiring change management specialists, together with stakeholder feedback. However, the most senior stakeholder or those with the loudest voice in the room don’t always get the outcome. These are still based on opinions, versus what has proven to work based on data. Imagine the power of implementing this across the enterprise and the ability to avoid costly mistakes and mishaps in the tens (or hundreds) of millions of investments in change initiatives per annum.
Building a Culture of Adoption
Improving change adoption is not a one-time effort but an ongoing, intentional process that combines targeted communication, stakeholder engagement, capacity planning, performance tracking, and data-driven insights. By focusing on the unique aspects of each change, tailoring strategies to specific stakeholder groups, and continuously managing performance, change practitioners can significantly increase adoption rates. Ultimately, success lies in building a culture where change is not just accepted but actively integrated into the organization’s DNA.
When change adoption becomes a measurable, manageable, and data-driven process, practitioners can guide their organizations through change with confidence and clarity, transforming resistance into resilience and integration into innovation.
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 as the ‘change curve’ is the Kubler-Ross model. 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. Therefore, be very careful when using applying this model 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’. On the other hand, there is ample research by McKinsey that for effectively managed initiatives and transformations, 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.
Source: HBR.org
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. 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, it is critical to go beyond these initial measures toward those elements that indicate the actual change in the organisation. 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
Product or solution leadership
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:
Project benefits targeted
Likely change management steps required
Change management measures
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 processes Decreased 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 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 can help you understand what change interventions leads to higher change adoption rates, through data. Using a data-led approach in deciphering what drives change adoption can truly drive successful change outcomes.
Feeling a bit lost and would like to have a chat about how to measure adoption by utilising digital solutions? Contact us here.
In today’s fast-paced business environment, most organizations are engaged in numerous change initiatives simultaneously. These initiatives might range from digital transformation efforts to restructuring, new product launches, or cultural shifts. For change management practitioners and leaders, the challenge is not only to ensure each initiative succeeds but also to align these efforts strategically to maximize overall business benefit. Let’s explore practical strategies for aligning multiple initiatives and measuring change adoption, providing actionable insights for change practitioners and leaders.
The Complexity of Multiple Change Initiatives
The complexity of managing multiple change initiatives lies in the potential for overlap, conflicting priorities, and resource strain. Each initiative, while aiming to deliver specific benefits, competes for attention, time, and resources. Moreover, when several initiatives target similar business outcomes, it becomes challenging to attribute success to any single effort. Most business units are only measuring a certain number of business metrics, and with a large number of initiatives there will bound to be overlaps. This makes it essential to adopt a strategic approach that ensures alignment and optimal resource utilisation.
Measuring Change Adoption Across Multiple Initiatives
One of the most critical aspects of managing multiple change initiatives is measuring the adoption of each change. This involves not only tracking how well each initiative is being implemented but also understanding its impact on the organization. The following strategies can help you effectively measure change adoption across various initiatives:
1. Establish Common Metrics
Establishing common metrics across all change initiatives is a foundational step in ensuring that change adoption is measured consistently and effectively. Common metrics provide a standardized way to evaluate progress, compare the success of different initiatives, and gain a holistic view of the organization’s overall change efforts. This approach allows for “apples-to-apples” comparisons, enabling senior leaders to make informed decisions about resource allocation, prioritization, and potential adjustments needed to maximize business benefits.
By identifying and applying a set of core metrics consistently across all change initiatives, organizations can better track the adoption process, identify areas where additional support may be needed, and ultimately ensure that changes are embedded successfully and sustainably.
Here’s a deeper look at some of the common metrics that can be established (note that we take a holistic and strategic lense in ‘adoption’, and not limiting adoption to the end of the project):
Employee Awareness and Understanding of the Change
Employee awareness and understanding are the first critical steps in the change adoption process. Without a clear understanding of what the change entails, why it is happening, and how it will impact their work, employees are unlikely to fully embrace the change. Measuring awareness and understanding helps ensure that communication efforts are effective and that employees have the necessary information to begin adopting the change.
Awareness Surveys: Regular surveys can be conducted to assess employees’ awareness of the change initiative. Questions can focus on whether employees are aware of the change, if they understand the reasons behind it, and if they can articulate the expected outcomes.
Knowledge Assessments: Beyond awareness, knowledge assessments can help gauge how well employees understand the details of the change. This could involve quizzes, interactive sessions, or discussions that test their understanding of new processes, tools, or organizational structures.
Communication Effectiveness: Track the effectiveness of communication campaigns through metrics such as email open rates, attendance at town halls or webinars, and engagement with internal communication platforms. High levels of engagement can indicate that employees are receiving and processing the information about the change.
Employee Engagement and Buy-in
Employee engagement and buy-in are essential for successful change adoption. If employees are not engaged or do not buy into the change, they are less likely to put in the effort needed to adopt new behaviours, processes, or tools. Measuring engagement and buy-in provides insight into how committed employees are to making the change successful.
Engagement Scores: Use engagement surveys to measure overall employee engagement levels before and after the change initiative. These scores can help you understand the impact of the change on employee morale and identify any groups that may need additional support.
Feedback Channels: Monitor and analyse feedback from employees through formal and informal channels. This includes responses to surveys, comments in focus groups, and feedback collected through suggestion boxes or digital platforms. The sentiment expressed in this feedback can be a strong indicator of buy-in.
Participation Rates: Track participation in change-related activities such as training sessions, workshops, and change champion programs. High participation rates typically indicate strong engagement and willingness to adopt the change.
Utilisation of New Systems, Processes, or Tools
The utilisation of new systems, processes, or tools introduced by a change initiative is a direct measure of adoption. If employees are not using the new tools or following the new processes, the change initiative cannot deliver its intended benefits. Measuring utilisation helps ensure that the changes are being practically applied in day-to-day operations.
System Usage Analytics: For technology-driven changes, track the usage of new systems through analytics. Metrics such as login frequency, time spent on the system, and the completion of key tasks can provide a clear picture of adoption.
Process Adherence: Implement tracking mechanisms to monitor adherence to new processes. This could involve audits, self-reporting, or the use of process management tools that track whether employees are following the new workflows.
Tool Adoption Rates: Measure the adoption rates of any new tools introduced as part of the change. This could include tracking the number of users, the frequency of use, and the breadth of functionality being utilised.
Proficiency in Applying the Change
Proficiency in applying the change is a crucial metric because it not only indicates whether employees are using the new systems, processes, or tools, but also how effectively they are using them. This metric helps ensure that employees have the necessary skills and competencies to fully leverage the change and achieve the desired outcomes.
Skill Assessments: Conduct skill assessments to measure employees’ proficiency in using new tools, systems, or processes. This could involve practical exams, simulations, or peer reviews where employees demonstrate their competency.
Performance Metrics: Monitor performance metrics related to the new processes or tools. For example, if a change initiative involves a new sales system, track metrics like sales conversion rates, the accuracy of data entry, or the speed of customer service resolution.
Certification Programs: Implement certification or accreditation programs where employees must demonstrate a certain level of proficiency to earn certification. Tracking the completion rates of these programs can indicate overall proficiency levels.
Realization of Expected Business Benefits
The ultimate goal of any change initiative is to realize the expected business benefits, whether they be financial, operational, or strategic. Measuring the realization of these benefits provides a clear indication of the success of the change initiative and its impact on the organization.
Benefit Tracking: Establish specific, measurable business benefits for each change initiative, such as cost savings, revenue growth, improved customer satisfaction, or increased productivity. Regularly track these metrics to assess whether the change is delivering the expected outcomes.
ROI Analysis: Conduct return on investment (ROI) analysis for each initiative, comparing the costs of implementation against the benefits realized. This helps quantify the financial impact of the change and determine its overall value to the organization.
Outcome-Based Metrics: Focus on outcome-based metrics that align with the organization’s strategic goals. For example, if a change initiative aims to improve customer experience, track customer satisfaction scores, retention rates, and repeat business.
Note that these may not be activities that change practitioners are leading within a project setting, however they should play a key part in contributing to the design and tracking of the adoption which then leads to the ultimate benefits.
Implementing Common Metrics in Practice
Implementing common metrics across multiple change initiatives requires a coordinated effort and a strong governance framework. Here are some practical steps to ensure that these metrics are applied effectively:
Alignment with Strategic Goals: Ensure that the selected metrics align with the organization’s broader strategic goals. This alignment helps prioritize initiatives and ensures that all change efforts contribute to the organization’s overall objectives.
Centralized Data Management: Establish a centralized data management system to collect, store, and analyze metrics across all initiatives. This system should allow for easy comparison and aggregation of data, providing a comprehensive view of change adoption.
Consistent Methodology: Develop a consistent methodology for measuring and reporting metrics. This includes standardized survey questions, data collection tools, and reporting formats to ensure that metrics are comparable across different initiatives.
Continuous Monitoring and Reporting: Regularly monitor and report on the metrics to track progress and identify any areas of concern. Use dashboards and scorecards to provide real-time visibility into change adoption across the organization.
Feedback and Adjustment: Use the insights gained from these metrics to provide feedback to initiative leaders and make necessary adjustments. Continuous improvement is key to ensuring that change initiatives remain on track and deliver the expected benefits.
Implementing metric tracking can be a very manual and labour intensive process. However, there are various digital tools that can be leverage to automate the data capture and streamline the data analysis and insight generation process. Chat to us to find out how The Change Compass can help.
2. Conduct Regular Assessments
Regular assessments are critical to understanding how well each initiative is being adopted and its impact on the organisation. These assessments should be scheduled at key milestones and involve both quantitative and qualitative evaluation.
Pulse Surveys: Conduct pulse surveys at regular intervals to gauge employee sentiment and engagement with each initiative. These short, focused surveys can provide real-time insights into how changes are being received and where additional support may be needed. However do note that pulse survey in themselves may only provide very superficial insights without the depth that may be required to understand the ‘why’ or ‘how’.
Performance Reviews: Where possible integrate change adoption metrics into regular performance reviews. This ensures that the impact of initiatives is continuously monitored and that any issues are addressed promptly.
Change Audits: Periodically perform change audits to assess the effectiveness of each initiative. This involves reviewing processes, outcomes, and feedback to determine whether the change is being adopted as intended.
3. Leverage Existing Channels
Leverage existing communication and feedback channels to measure adoption. This approach ensures that you are not overloading employees with new processes and allows for seamless integration into their daily routines.
Employee Feedback Platforms: Utilise platforms already in place, such as intranet forums like Yammer, suggestion inboxes, or regular team meetings, to gather feedback on change initiatives. This feedback can provide valuable insights into adoption levels and potential areas of resistance.
Usage Analytics: For technology-driven initiatives, use existing analytics tools to monitor system usage and user behaviour. This can help identify adoption rates and areas where additional training or support may be needed.
Regular Check-ins: Integrate adoption tracking into regular team check-ins. This allows managers to discuss progress with their teams and identify any challenges early on.
4. Quantify Qualitative Data
While quantitative metrics are essential, qualitative data provides context and deeper insights into how changes are being adopted. It’s important to develop methods to quantify this qualitative data to better understand the impact of your initiatives. Quantitative data are easier to present, and may be more memorable to your stakeholders.
Sentiment Analysis: Use sentiment analysis tools to analyse employee feedback, comments from surveys, or even social media mentions. This helps quantify the overall sentiment towards each initiative, providing a clearer picture of adoption.
Focus Groups: Conduct focus groups to gather in-depth feedback on specific initiatives. While this data is qualitative, you can quantify it by categorizing responses into themes and measuring the frequency of each theme.
Narrative Metrics: Develop narrative metrics that capture the stories behind the numbers. For example, if an initiative aims to improve customer service, track success stories where employees went above and beyond as a result of the new changes.
5. Analyse Trends and Patterns
Analysing trends and patterns over time is essential for understanding the broader impact of multiple initiatives. By looking at adoption data longitudinally, you can identify which initiatives are driving long-term change and which may require adjustments.
Adoption Trajectories: Track the adoption trajectories of each initiative. Are there certain initiatives that show rapid early adoption but then plateau? Understanding these patterns can help refine strategies to sustain momentum.
Cross-Initiative Analysis: Compare adoption trends across different initiatives. Look for correlations or conflicts between initiatives. For example, if one initiative shows strong adoption while another lags, investigate whether they are competing for the same resources or if there is confusion about priorities.
Predictive Analytics: Use predictive analytics to forecast future adoption trends based on historical data. This can help in proactive decision-making and resource allocation. This is absolutely the value of data, when you have historical data you can easily forecast what lies ahead and provide an overlay for change portfolio consideration during business planning cycles.
6. Communicate Progress Transparently
Transparent communication is vital for building trust and ensuring that everyone in the organization is aware of the progress of each initiative. This helps in aligning efforts and maintaining momentum.
Regular Updates: Provide regular updates on the progress of each initiative. Use a variety of channels such as newsletters, town halls, or internal social media to keep everyone informed.
Success Stories: Share success stories that highlight the benefits of adoption. This not only celebrates achievements but also reinforces the value of the initiatives and encourages further adoption.
Dashboard Reporting: Develop a dashboard that tracks and displays adoption metrics for all initiatives in real-time. Make this dashboard accessible to key stakeholders to ensure transparency and accountability.
7. Establish a Governance Framework
A governance framework is essential for coordinating multiple initiatives and ensuring that they are aligned with the organization’s strategic goals. This framework should provide structure, oversight, and guidance for all change efforts.
Steering Committees: Establish steering committees composed of senior leaders who oversee the progress of all initiatives. These committees should ensure that initiatives are aligned with business objectives and that resources are appropriately allocated.
Change Champions: Identify change champions within the organization who can advocate for adoption and provide support to their peers. These individuals play a crucial role in driving change from within and ensuring alignment across initiatives.
Standardised Processes: Develop standardized processes for planning, implementing, and measuring change initiatives. This ensures consistency and allows for more effective comparison and integration of efforts. In establishing the right routines they become embedded within business practices and are not seen as an ‘additional effort required’ on top of their day-jobs.
Aligning Multiple Initiatives for Maximum Business Benefit
While measuring adoption is crucial, aligning multiple initiatives to maximize business benefits is the ultimate goal. Here are key strategies to ensure alignment:
1. Prioritise Initiatives Based on Strategic Value
Not all initiatives are created equal. Prioritising initiatives based on their strategic value ensures that resources are allocated effectively and that the most critical changes receive the attention they deserve.
Value Assessment: Conduct a value assessment for each initiative to determine its potential impact on the organization’s strategic goals. Focus on initiatives that align most closely with these goals.
Resource Allocation: Allocate resources based on the strategic value of each initiative. This may involve dedicating more resources to high-priority initiatives while scaling back on others.
Phased Implementation: Consider implementing high-priority initiatives in phases. This allows you to focus efforts on achieving quick wins, which can build momentum for broader change.
Integration of change initiatives is essential to avoid duplication of efforts and to ensure that all initiatives are working towards common goals. This requires a coordinated approach and effective communication across initiatives and stakeholders.
Change Integration Plan: Develop a change integration plan that outlines how different initiatives will work together. This plan should identify potential overlaps and ensure that all initiatives are aligned. It could be that lower prioritised initiatives be pushed out making the runway for more strategic initiatives with higher priorities. It could also be ‘packaging’ change releases across different initiatives where they make sense to deliver change to the impacted teams in a more cohesive and easier-to-digest manner. This may be due to the nature of the changes or the volume and capacity required in the impact of the changes.
Cross-Functional Teams: Establish cross-functional teams to oversee the integration of initiatives. These teams should include representatives from each initiative to ensure collaboration and alignment. Ideally cross functional forums already exist and this is just tapping into an existing channel.
Unified Communication Strategy: Create a unified communication strategy that aligns messaging across initiatives. This helps avoid confusion and ensures that employees receive consistent information. To do this, data is required to be able to have a clear view in terms of communication content and planned releases.
3. Monitor and Adjust in Real-Time
The business environment is dynamic, and change initiatives need to be adaptable. Monitoring progress in real-time and being willing to adjust strategies is crucial for success. At a minimum, set up routine reporting timelines so that data and reporting are harmonised and embedded within the operating rhythms of those involved.
Real-Time Monitoring: Use real-time data to monitor the progress of each initiative. This allows you to identify issues early and make adjustments as needed.
Agile Approach: Adopt an agile approach to change management, where initiatives are continuously reviewed and adjusted based on feedback and changing circumstances.
Flexibility in Execution: Be prepared to pivot if an initiative is not delivering the expected results or needs to be adjusted based on the challenges of impacted business teams. This might involve reallocating resources, adjusting timelines, or even pausing initiatives that are not aligned with current business needs.
Successfully managing and aligning multiple change initiatives is a complex but achievable task. By establishing common metrics, conducting regular assessments, leveraging existing channels, and quantifying qualitative data, you can effectively measure adoption. Aligning initiatives for maximum business benefit requires prioritisation, integration, and real-time monitoring. For change management practitioners and leaders, these strategies are essential for driving organisational success in a world of increased rate of change. By strategically aligning multiple initiatives, you can ensure that the organisation not only adapts to change but thrives in it.
Though not elaborated, what is inherent in this article is the importance of behaviour in adoption, understanding it, and measuring it. To read more about driving behaviour change check out The Ultimate Guide to Behaviour Change.
In the world of change management, Go Lives are often seen as significant milestones. For many project teams, these events represent the culmination of months or even years of hard work, signaling that a new system, process, or initiative is officially being launched. It’s common for stakeholders to view Go Lives as a key indicator of the success of a change initiative. However, while Go Lives are undeniably important, relying on them as the primary measure of change impact can be misleading and potentially harmful to the overall change effort.
Go Lives are just one piece of the puzzle. Focusing too heavily on these milestones can lead to an incomplete understanding of the change process, neglecting crucial activities that occur both before and after Go Live. Let’s outline the risks associated with using Go Lives to report on change management impacts and offers best practices for a more holistic approach.
Go Lives: A Double-Edged Sword
Go Lives are naturally a focal point for project teams. They represent a clear, tangible goal, and the success of a Go Live can boost morale, validate the efforts of the team, and provide a sense of accomplishment. From a project delivery perspective, Go Lives are critical. They signal that the project has reached a level of maturity where it is ready to be released to the broader organization. In terms of resourcing and business readiness, Go Lives ensure that everything is in place for the new system or process to function as intended.
However, the very attributes that make Go Lives attractive can also make them problematic as indicators of change impact. The simplicity and clarity of a Go Live event can lead stakeholders to overestimate its significance, from a impacted business perspective. The focus on Go Lives can overshadow the complex and often subtle changes that occur before and after the event. While a successful Go Live is necessary for change, it is not sufficient to guarantee that the change will be successful in the long term.
The Pre-Go Live Journey: Laying the Foundation for Change
A significant portion of the change management journey occurs long before the Go Live date. During this pre-Go Live phase, various engagement and readiness activities take place that are critical to shaping the overall impact of the change. These activities include town hall meetings, where leaders communicate the vision and rationale behind the change, and briefing sessions that provide detailed information about what the change will entail.
Training and learning sessions are also a crucial component of the pre-Go Live phase. These sessions help employees acquire the necessary skills and knowledge to adapt to the new system or process. Discussions, feedback loops, and iterative improvements based on stakeholder input further refine the change initiative, ensuring it is better aligned with the needs of the organization.
These pre-Go Live activities are where much of the groundwork for successful change is laid. They build awareness, generate buy-in, and prepare employees for what is to come. Without these efforts, the Go Live event would likely be met with confusion, resistance, or outright failure. Therefore, it is essential to recognize that the impact of change is already being felt during this phase, even if it is not yet fully visible.
Post-Go Live Reality: The Real Work Begins
While the Go Live event marks a significant milestone, it is by no means the end of the change journey. In fact, for many employees, Go Live is just the beginning. It is in the post-Go Live phase that the true impact of the change becomes apparent. This is when employees start using the new system or process in their daily work, and the real test of the change’s effectiveness begins.
During this phase, the focus shifts from preparation to adoption. Employees must not only apply what they have learned but also adapt to any unforeseen challenges that arise. This period can be fraught with difficulties, as initial enthusiasm can give way to frustration if the change does not meet expectations or if adequate support is not provided.
Moreover, the post-Go Live phase is when the long-term sustainability of the change is determined. Continuous reinforcement, feedback, and support are needed to ensure that the change sticks and becomes embedded in the organization’s culture. Without these ongoing efforts, the change initiative may falter, even if the Go Live event was deemed a success.
The Risk of Misleading Stakeholders
One of the most significant dangers of focusing too heavily on Go Lives is the risk of misleading stakeholders. When stakeholders are led to believe that the Go Live event is the primary indicator of change impact, they may not fully appreciate the importance of the activities that occur before and after this milestone. This narrow focus can lead to a number of issues.
Firstly, stakeholders may prioritize the Go Live date to the exclusion of other critical activities. This can result in insufficient attention being paid to pre-Go Live engagement and readiness efforts or to post-Go Live adoption and support. As a consequence, the overall change initiative may suffer, as the necessary foundations for successful change have not been properly established.
Secondly, stakeholders may develop unrealistic expectations about the impact of the change. If they believe that the Go Live event will immediately deliver all the promised benefits, they may be disappointed when these benefits take longer to materialize. This can erode confidence in the change initiative and reduce support for future changes.
Finally, a narrow focus on Go Lives can create a false sense of security. If the Go Live event is successful, stakeholders may assume that the change is fully implemented and no further action is required. This can lead to complacency and a lack of ongoing support, which are essential for ensuring the long-term success of the change.
Best Practices for Reporting Change Management Impact
To avoid the pitfalls associated with relying on Go Lives as indicators of change impact, change management practitioners should adopt a more holistic approach to reporting. This involves considering the full scope of the change journey, from the earliest engagement activities to the ongoing support provided after Go Live. Here are some best practices for reporting on change management impact:
Integrate Pre-Go Live Metrics:
Track and report on engagement activities, such as attendance at town hall meetings, participation in training sessions, and feedback from employees.
Monitor changes in employee sentiment and readiness levels throughout the pre-Go Live phase.
Report on aggregate pan-initiative change initiative impost on business units, pre-Go Live
Emphasize Post-Go Live Support:
Develop metrics to measure the effectiveness of post-Go Live support, such as the number of help desk inquiries, employee satisfaction with the new system, and the rate of adoption.
Highlight the importance of continuous feedback loops to identify and address any issues that arise after Go Live.
Communicate the need for ongoing reinforcement and support to stakeholders, emphasizing that change is an ongoing process
Report on post-Go Live adoption time impost expected across initiatives
Provide a Balanced View of Change Impact:
Ensure that stakeholders understand that Go Live is just one part of the change journey and that significant impacts occur both before and after this event.
Use a combination of quantitative and qualitative data to provide a comprehensive view of change impact.
Regularly update stakeholders on progress throughout the entire change journey, not just at the time of Go Live.
Manage Expectations:
Clearly communicate to stakeholders that the full impact of the change may not be immediately visible at the time of Go Live.
Set realistic expectations about the timeline for realizing the benefits of the change.
Prepare stakeholders for potential challenges in the post-Go Live phase and emphasize the importance of ongoing support.
While Go Lives are important milestones in the change management process, they should not be used as the sole indicator of change impact. The journey to successful change is complex, involving critical activities before, during, and after the Go Live event. By adopting a more holistic approach to reporting on change management impact, practitioners can provide stakeholders with a more accurate understanding of the change journey, manage expectations more effectively, and ensure the long-term success of the change initiative.
The key takeaway is that change management is not just about delivering a project; it’s about guiding an organization through a journey of transformation. Go Lives are just one step in this journey, and it is the responsibility of leaders to ensure that every step is given the attention it deserves.
Change management professionals are increasingly requested to provide measurement, data, and insights to various stakeholder groups. Not only does this include tracking various change outcomes such as business readiness or adoption, but stakeholder concerns also include such as change saturation and visibility of incoming initiative impacts.
To become better at working with data there is much that change managers can learn from data scientists (without becoming one of course). Let’s explore how change management can benefit from the practices and methodologies employed by data scientists, focusing on time allocation, digital tools, system building, hypothesis-led approaches, and the growing need for data and analytical capabilities.
1. Time Allocation: Prioritizing Data Collection and Cleansing
Data scientists spend a substantial portion of their time on data collection and cleansing. According to industry estimates, about 60-80% of a data scientist’s time is dedicated to these tasks. This meticulous process ensures that the data used for analysis is accurate, complete, and reliable.
In the below diagram from researchgate.net you can see that for data scientists the vast majority of the time is spent on collecting, cleansing and organising data.
You might say that change managers are not data scientists because the work nature is different, and therefore should not need to carve out time for these activities? Well, it turns out that the type of activities and proportions of time spent is similar across a range of data professionals, including business analysts.
Below is the survey results published by Business Broadway, showing that even business analysts and data analysts spend significant time in data collection, cleansing, and preparation.
Lessons for Change Management
a. Emphasize Data Collection and Cleansing: For change managers, this translates to prioritizing the collection of reliable data related to change initiatives. This might include stakeholder feedback, performance metrics, impact data and other relevant data points. Clean data is essential for accurate analysis and insightful decision-making. Data projects undertaken by change managers are not going to be as large or as complex as data scientists, however the key takeaway is that this part of the work is critical and sufficient time should be allocated and not skipped.
b. Allocate Time Wisely: Just as data scientists allocate significant time to data preparation, change managers should also dedicate sufficient time to gathering and cleaning data before diving into analysis. This ensures that the insights derived are based on accurate and reliable information.
It also depends on the data topic and your audience. If you are presenting comparative data, for example, change volume across different business units. You may be able to do spot checks on the data and not verify every data line. However, if you are presenting to operations business units like call centres where they are very sensitive to time and capacity challenges, you may need to go quite granular in terms of exactly what the time impost is across initiatives.
c. Training and Awareness: Ensuring that the change management team understands the importance of data quality and is trained in basic data cleansing techniques can go a long way in improving the overall effectiveness of change initiatives. Think of scheduling regular data sessions/workshops to review and present data observations and findings to enhance the team’s ability to capture accurate data as well as the ability to interpret and apply insights. The more capable the team is in understanding data, the more value they can add to their stakeholders leveraging data insights.
2. Leveraging Digital Tools: Enhancing Efficiency and Accuracy
Data scientists rely on a variety of digital tools to streamline their work. These tools assist in data collection, auditing, visualization, and insight generation. AI and machine learning technologies are increasingly being used to automate and enhance these processes.
Data scientists rely on various programming, machine learning and data visualisation such as SQL, Python, Jupyter, R as well as various charting tools.
Lessons for Change Management
a. Adopt Digital Tools: Change managers should leverage digital tools to support each phase of their data work. There are plenty of digital tools out there for various tasks such as surveys, data analysis and reporting tools.
For example, Change Compass has built-in data analysis, data interpretation, data audit, AI and other tools to help streamline and reduce manual efforts across various data work steps. However, once again even with automation and AI the work of data checking and cleansing does not go away. It becomes even more important.
b. Utilize AI and Machine Learning: AI can play a crucial role in automating repetitive tasks, identifying patterns, data outliers, and generating insights. For example, AI-driven analytics tools can help predict potential change saturation, level of employee adoption or identify areas needing additional support during various phases of change initiatives.
With Change Compass for example, AI may be leverage to summarise data, call out key risks, generate data, and forecast future trends.
c. Continuous Learning: Continuous learning is essential for ensuring that change management teams stay adept at handling data and generating valuable insights. With greater stakeholder expectations and demands, regular training sessions on the latest data management practices and techniques can be helpful. These sessions can cover a wide range of topics, including data collection methodologies, data cleansing techniques, data visualisation techniques and the use of AI and machine learning for predictive analytics. By fostering a culture of continuous learning, organizations can ensure that their change management teams remain proficient in leveraging data for driving effective change.
In addition to formal training, creating opportunities for hands-on experience with real-world data can significantly enhance the learning process. For instance, change teams can work on pilot projects where they apply new data analysis techniques to solve specific challenges within the organization. Regular knowledge-sharing sessions, where team members present case studies and share insights from their experiences, can also promote collective learning and continuous improvement.
Furthermore, fostering collaboration between change managers and data scientists or data analysts can provide invaluable mentorship and cross-functional learning opportunities. By investing in continuous learning and development, organizations can build a change management function that is not only skilled in data management but also adept at generating actionable insights that drive successful change initiatives.
3. Building the Right System: Ensuring Sustainable Insight Generation
It is not just about individuals or teams working on data. A robust system is vital for ongoing insight generation. This involves creating processes for data collection, auditing, cleansing, and establishing governance bodies to manage and report on data.
Governance structures play a vital role in managing and reporting data. Establishing governance bodies ensures that there is accountability and oversight in data management practices. These bodies can develop and enforce data policies, and oversee data quality initiatives. They can also be responsible for supporting the management of a central data repository where all relevant data is stored and managed.
Lessons for Change Management
a. Establish Clear Processes: Develop and document processes for collecting and managing data related to change initiatives. This ensures consistency and reliability in data handling.
b. Implement Governance Structures: Set up governance bodies to oversee data management practices. This includes ensuring compliance with data privacy regulations and maintaining data integrity. The governance can sponsor the investment and usage of the change data platform. This repository should be accessible to stakeholders involved in the change management process, promoting transparency and collaboration. Note that a governance group can simply be a leadership team regular team meeting and does not need to be necessarily creating a special committee.
c. Invest in system Infrastructure: Build the necessary system infrastructure to support data management and analysis that is easy to use and provides the features to support insight generation and application for the change team.
Data scientists often use a hypothesis-led approach, where they test, reject, or confirm hypotheses using data. This method goes beyond simply reporting what the data shows to understanding the underlying causes and implications.
Lessons for Change Management
a. Define Hypotheses: Before analyzing data, clearly define the hypotheses you want to test. For instance, if there is a hypothesis that there is a risk of too much change in Department A, specify the data needed to test this hypothesis.
b. Use Data to Confirm or Reject Hypotheses: Collect and analyze data to confirm or reject your hypotheses. This approach helps in making informed decisions rather than relying on assumptions or certain stakeholder opinions.
c. Focus on Actionable Insights: Hypothesis-led analysis often leads to more actionable insights. It is also easier to use this approach to dispel any myths of false perceptions.
For example: Resolving Lack of Adoption
Hypothesis: The lack of adoption of a new software tool in the organization is due to insufficient coaching and support for employees.
Data Collection:
Gather data on the presence of managerial coaching and perceived quality. Also gather data on post go live user support.
Collect feedback from employees through surveys regarding the adequacy and clarity of coaching and support.
Analyse usage data of the new software to identify adoption rates across different departments.
Analysis:
Compare adoption rates between employees who received sufficient coaching and support versus those who did not.
Correlate feedback scores on training effectiveness with usage data to see if those who found the training useful are more likely to adopt the tool.
Segment data by department to identify if certain teams have lower adoption rates and investigate their specific training experiences.
Actionable Insights:
If data shows a positive correlation between coaching and support, and software adoption, this supports the hypothesis that enhancing coaching and support programs can improve adoption rates.
If certain departments show lower adoption despite completing coaching sessions, investigate further into department-specific issues such as workload or differing processes that may affect adoption.
Implement targeted interventions such as additional training sessions, one-on-one support, or improved training materials for departments with low adoption rates.
5. Building Data and Analytical Capabilities: A Core Need for Change Management
As data and analytical capabilities become increasingly crucial, change management functions must build the necessary people and process capabilities to leverage data-based insights effectively.
Lessons for Change Management
a. Invest in Training: Equip change management teams with the skills needed to manage data and generate insights. This includes training in data analysis, visualization, and interpretation.
b. Foster a Data-Driven Culture: A lot of organisations are already on the bandwagon of Encourage a culture where data is valued and used for decision-making. The change management needs to promote this equally within the change management function. This involves promoting the use of data in everyday tasks and ensuring that all team members understand its importance. Think of incorporating data-led discussions into routine meeting meetings.
c. Develop Analytical Frameworks: Create frameworks and methodologies for analyzing change management data. This includes defining common key metrics, setting benchmarks, and establishing protocols for data collection and analysis for change data. Data and visual templates may be easier to follow for those with lower capabilities in data analytics.
Practical Steps to Implement Data-Driven Change Management
To integrate these lessons effectively, senior change practitioners can follow these practical steps:
Develop a Data Strategy: Create a comprehensive data strategy that outlines the processes, tools, and governance structures needed to manage change management data effectively.
Conduct a Data Audit: Begin by auditing the existing data related to change management. Identify gaps and areas for improvement.
Adopt a Hypothesis-Led Approach: Encourage the use of hypothesis-led approaches to move beyond descriptive analytics and derive more meaningful insights.
Invest in Technology: Invest in the necessary digital tools and technologies to support data collection, cleansing, visualization, and analysis.
Train the Team: Provide training and development opportunities for the change management team to build their data and analytical capabilities.
Collaborate Across Functions: Foster collaboration between change management and data science teams to leverage their expertise and insights.
Implement Governance Structures: Establish governance bodies to oversee data management practices and ensure compliance with regulations and standards.
By learning from the practices and methodologies of data scientists, change management functions can significantly enhance their effectiveness. Prioritizing data collection and cleansing, leveraging digital tools, building robust systems, adopting hypothesis-led approaches, and developing data and analytical capabilities are key strategies that change management teams can implement. By doing so, they can ensure that their change initiatives are data-driven, insightful, and impactful, ultimately leading to better business outcomes.
