Successful change management relies on having the right metrics to measure progress, gauge impact, and communicate with stakeholders. Moreover, the right metrics can drive continuous improvement and help directly achieve change outcomes. However, not all metrics are beneficial, and some can mislead or fail to meet stakeholder needs, especially when managing change projects. Let’s check out the top change management metrics to avoid and go through examples to take note.
Understanding the Disconnect: Change Managers vs. Business Stakeholders
A significant reason certain change management metrics fall short is the differing perspectives between change managers and business stakeholders. Change managers and change practitioners are trained to view metrics through the lens of change management frameworks and methodologies, focusing on detailed assessments and structured approaches as a part of the change management strategy. These include applying ratings and judgments on aspects such as impact levels indicating levels and areas of impact.
In contrast, business stakeholders prioritize business operations, strategic outcomes, and practical implications. The busy business stakeholder is often looking for practical implications from metrics that can be used to directly drive decision making, meaning “what do I do with this data to improve the ultimate business outcome”.
Of course, different stakeholders have different data needs, and you need to show the right metric to the right type of stakeholder. For example, operations-focused stakeholders expect fairly detailed metrics and internal historical data to understand what that means in terms of organisation, coordination, capacity, and performance perspectives. Senior managers may prefer higher-level data with a focus on strategic impacts, overall progress, and adoption indicators of change success rate.
This disconnect can lead to the use of metrics that do not resonate with or are misunderstood by stakeholders that disrupt change success.
Change managers may leverage metrics that are derived from the various change management documents such impact assessments, training plan or communications plan. Metrics are also often chosen for ease of use and ideally are not overly complicated to execute.
For example, impact assessments typically involve rating stakeholder groups and initiatives on a traffic light system (red, amber, green) based on their impact. While this approach is systematic, it can be problematic for several reasons:
Lack of Sufficient Stakeholder Context: Business stakeholders might not understand the practical implications of these ratings. For instance, an “impact rating per initiative” may not clearly convey what the rating means for day-to-day operations or strategic goals. For example, if an initiative has a red impact rating, stakeholders might not grasp the specific operational changes or strategic adjustments needed, in essence, “what do I do with this?”. So, incorrect usage of data could result in lack of stakeholder engagement.
Misinterpretation of Traffic Light Ratings: The red, amber, green system can be misleading. Stakeholders might interpret red as an indicator of alarm or imminent risk, while green may be seen as a sign that no action is needed. This is because stakeholders are trained to interpret traffic light ratings this way (from the various project/business updates they’ve attended). In reality, red might simply mean high impact, requiring focused attention, and green might indicate a low impact but still require monitoring. For instance, a red rating might indicate significant process changes that need careful management, not necessarily a negative outcome.
Hard to defend ratings if prompted: Business stakeholders may also want to drill into how the ratings are determined, and based on what basis. They may expect a logical data-backed reasoning of how each colour scheme is determined. If a rating is based on an overall ‘personal judgment’ this may be hard to defend infront of a group of stakeholders.
Examples of Potentially Misleading Metrics
Certain metrics, although straightforward, can be easily misinterpreted and fail to provide a realistic picture of change impacts as a part of effective change management. Often these are selected because they are easy to report on. However, easy, make not give you the outcome you are looking for.
Number of Go-Lives: Tracking the number of Go-Lives over time might seem like an effective way to represent change volume. However, the most significant impacts on people given time often occur before or after the Go-Live date. For example, the preparation and training phase before Go-Live and the adoption phase afterward are critical periods that this metric overlooks. A Go-Live date might indicate a milestone but not the challenges, progress or impacts faced during the implementation phase.
Number of Activities Implemented: Similar to Go-Lives, this metric focuses on quantity rather than quality. Simply counting the number of activities does not account for their effectiveness or the actual change they drive within the organisation. For example, reporting that 50 training sessions were conducted does not reveal whether employees found them helpful or if they led to improved performance.
Number of impacts or stakeholders impacted: Again, using a numerical way to indicate progress can be very misleading, or unmeaningful. This is because it may be ‘interesting’ but with no real action for your stakeholder to take in order to somehow lead to a better overall change outcome. If metrics do not result in some kind of action, then over time it will not shape your change(s) toward the targeted outcomes. Or worse, your stakeholders may lose interest and lose confidence in the strategic impact of these metrics.
Another common way to report change metrics is to use the number of impacts or number of stakeholders impacted by the organizational change. This can be in terms of the following:
Number of divisions impacted
Number of stakeholder groups impacted
Number of employees impacted
Number of initiatives per division/stakeholder
Metrics That May Be Too Operational
Metrics that are overly operational can fail to capture meaningful progress or adoption. Perhaps if the metric are for reporting within the Change Management team that may be OK. However, when you are showing metrics to stakeholders, a different set of expectations should be cast.
If you are presenting metrics to senior managers, you need to ensure that they hit the mark for that audience group. If the group is more interested in strategic impact, and higher level progress outcomes, you need to tailor accordingly.
Examples of metrics that may be too operational include:
Number of Communications Sent: This metric measures activity but not effectiveness. Sending numerous emails or messages does not guarantee that the message is received, understood, or acted upon by stakeholders. For instance, stakeholders might receive 100 emails, but if the content is unclear, the communication effort is wasted. Or worse, the emails may not even have been read.
Number of Training Sessions Attended: This one is a classic. While training is crucial, the number of sessions attended does not necessarily reflect the attendees’ understanding, engagement, or the practical application of the training. For example, employees might attend training but not apply the new skills if the training is not relevant to their roles for various reasons.
Number of workshops/meetings: Another way of articulating the change management progress in terms of activities is the number of workshops or meetings conducted with stakeholders including focus groups to indicate employee engagement. Again, this may be good to track within the change management team. However, presenting this metric to stakeholders may not be appropriate as it may not meet their needs nor indicate change management success.
Number of changes: This may be a common way to report on changes planned, but it doesn’t really inform the extent of the change. One change can be significantly impactful whilst another does not have major stakeholder impacts and are more system impacts. Listing number of changes may be deceiving or misleading. This kind of data may not get you the level of acceptance targeted.
The way metrics are presented is just as important as the metrics themselves. Poor visualization can lead to misinterpretation, confusion, and misguided decisions. Here are some common pitfalls to avoid:
Ineffective Use of Pie Charts
Pie charts can be misleading when used to show data points that are not significantly different. For example, using a pie chart to represent the percentage of divisions impacted by a change might not effectively communicate the nuances of the impact if the differences between the divisions are minimal. A pie chart showing 45%, 30%, and 25% might not convey the critical differences in impact levels among divisions.
Misleading Traffic Light Ratings
Using red, amber, and green to indicate high, medium, and low impacts can send the wrong message. Stakeholders might associate these colours with good and bad outcomes rather than understanding the actual levels of impact. Stakeholder may be used to interpreting these in the context of their usual project or business updates where red indicated alarm and ‘bad’. This can lead to unnecessary alarm or complacency. For instance, a green rating might suggest no need for action, while in reality, it might require ongoing monitoring.
Overuse of Colours
Using too many colours in charts and graphs can overwhelm stakeholders, making it difficult to discern the key message. Using colours in data visualisation can be two-edged sword. Colour can effectively point your stakeholders are the area where you want them to focus on. But, too many colours can lose your audience. A cluttered visual can obscure the critical data points and lead to misinterpretation. For example, a graph with ten different colours can confuse stakeholders about which data points are most important.
Data visualisation tools are also important. A lot of people use Power BI which works for a foundational level of charts. For tailored charts, specifically designed to to influence stakeholders to clearly see certain angles of risks and opportunities leverage tools such as Change Compass.
Practical Takeaways for Senior Change Managers
To ensure that change management metrics are effective and take into account best practices practices, consider the following practical takeaways:
Align Metrics with Key Stakeholder Perspectives
Understand Stakeholder Priorities: Engage with stakeholders to understand their business goals, priorities and concerns. Tailor your metrics to address these aspects directly. For example, if stakeholders are concerned about operational efficiency, focus on metrics that reflect improvements in this area.
Use Business Language: Frame your metrics in a way that resonates with business stakeholders. Avoid change management jargon and reference, and ensure that the implications of the metrics are clear and actionable. For example, instead of using technical terms, explain how the metrics impact business outcomes. Think in terms of business activities, milestones, busy periods, and capacity challenges.
Focus on Meaningful Metrics
Measure Outcomes, Not Just Activities: Change leaders should prioritize metrics that reflect the outcomes and impacts of change indicate level of knowledge, rather than just the activities performed as a part of change management KPIs. For example, instead of counting the total number of employees attending change management training sessions, measure the improvement in employee performance or knowledge retention post-training.
Example: Instead of reporting that 100 employees attended training sessions, report that 85% of attendees showed improved performance in their roles after training, or that certain level of competencies were gained. Note that quantifiable metrics have more impact on the audience.
Track Engagement and Adoption: Monitor metrics that indicate the level of engagement and adoption among stakeholders or their perception of the change. This could include surveys, feedback forms, or direct measures of behaviour change and the overall success rate of the change.
Example: Use post-training surveys to measure employee confidence in applying new skills or managerial rating of application of learnt skills rather than employee satisfaction of the training sessions using satisfaction scores. Track the percentage of employees who actively use new tools or processes introduced during the change.
Example: Instead of reporting that 100 employees attended training sessions, report that 85% of attendees showed improved performance in their roles after training, or that certain level of competencies were gained.
Example: Use post-training surveys to measure employee confidence in applying new skills or managerial rating of application of learnt skills. Track the percentage of employees who actively use new tools or processes introduced during the change.
Improve Metric Visualization
Simplify Visuals: Use clear, simple visuals that highlight the key messages. Avoid clutter and ensure that the most important data points stand out.
Example: Use bar charts or line graphs to show trends over time rather than pie charts that can be harder to interpret.
Contextualize Data: Provide context for the data to help stakeholders understand the significance. For example, instead of just showing the number of Go-Lives, explain what each Go-Live entails and its expected impact on operations. Or better, focus on showing the varying levels of impact on different stakeholders across time within the initiative.
Example: Accompany a Go-Live count with a visual showing the varying impact level of various implementation activities of the changes.
Example: Use bar charts or line graphs to show trends over time rather than pie charts that can be harder to interpret.
Example: Accompany a Go-Live count with a visual showing the varying impact level of various implementation activities of the changes.
Narrative Approach: Combine metrics with a narrative that explains the story behind the numbers as a part of the change management process. This can help stakeholders understand the broader context and implications.
Example: Instead of presenting raw data, provide a summary that explains key trends, successes, and areas needing attention.
Educate your stakeholders: Depending on stakeholder needs you may need to take them on a phased approach to gradually educate them on change management metrics and how you ultimately want them to drive the outcomes.
Example: You may start the education process to focus on more simplistic and easy-to-understand measures, and as your stakeholders are more change-mature, move to drill into more detailed metrics that explain the ‘why’ and ‘how’ to drive outcome success.
Continuously improvement: Provide regular updates on key metrics and adjust them based on feedback from stakeholders. Continuous communication ensures that everyone remains aligned and informed.
Example: Hold monthly review meetings with stakeholders to discuss the latest metrics, address concerns, and adjust strategies as needed.
Example: Instead of presenting raw data, provide a summary that explains key trends, successes, and areas needing attention.
Example: You may start the education process to focus on more simplistic and easy-to-understand measures, and as your stakeholders are more change-mature, move to drill into more detailed metrics that explain the ‘why’ and ‘how’ to drive outcome success.
Example: Hold monthly review meetings with stakeholders to discuss the latest metrics, address concerns, and adjust strategies as needed.
Examples of Effective Metrics
Employee Adoption and Engagement
Percentage of Employees Adopting New Process/System: This metric measures the rate at which employees are using new processes or systems introduced during the change. High adoption rates indicate successful integration.
Implementation: Use software usage analytics or surveys to track tool adoption rates.
Visualization: A graph showing adoption rates over time.
Employee Feedback Scores: Collect feedback on change initiatives through surveys or stakeholder ratings to measure sentiment/feedback and identify areas for improvement.
Implementation: Conduct regular surveys asking employees about their experience with the change process. Do note that depending on the change you may expect negative feedback due to the nature of the change itself (vs the way it was implemented).
Visualization: Bar/Line charts comparing feedback scores across different departments or time periods. Bar/Line charts are the standard go-to for data visualisation. They are easy to understand and interpret.
Implementation: Use software usage analytics or surveys to track tool adoption rates.
Visualization: A graph showing adoption rates over time.
Implementation: Conduct regular surveys asking employees about their experience with the change implementation process. Do note that depending on the change you may expect negative feedback due to the nature of the change itself (vs the way it was implemented).
Visualization: Bar/Line charts comparing feedback scores across different departments or time periods. Bar/Line charts are the standard go-to for data visualisation. They are easy to understand and interpret.
Impact on Business Outcomes
Improvement in Key Performance Indicators (KPIs): Track changes in KPIs that are directly impacted by the change initiatives, such as productivity, customer satisfaction, customer experience, improvement in process inconsistencies or financial performance.
Implementation: Identify relevant KPIs and measure their performance before and after change initiatives.
Visualization: Use line/bar graphs to show trends in KPI performance over time.
Operational Efficiency Metrics: Measure improvements in operational processes, such as reduced cycle times, error rates, or cost savings.
Implementation: Track specific operational metrics relevant to the change initiatives.
Visualization: Bar charts or heatmaps showing improvements in efficiency metrics across different operational areas.
Implementation: Identify relevant KPIs and measure their performance before and after change initiatives.
Visualization: Use line/bar graphs to show trends in KPI performance over time.
Implementation: Track specific operational metrics relevant to the change initiatives.
Visualization: Bar charts or heatmaps showing improvements in efficiency metrics across different operational areas.
Change management effectiveness requires metrics that not only measure progress but also resonate with business stakeholders and accurately reflect the impact of change initiatives. They should provide valuable insights. Avoiding common pitfalls such as relying on easily misinterpreted or overly operational metrics is crucial. By aligning metrics with stakeholder perspectives, focusing on meaningful outcomes, improving visualization, and communicating effectively, senior change and transformation professionals can ensure that their metrics truly support the success of their change initiatives.
The top change management metrics to avoid are those that fail to provide clear, actionable insights to business stakeholders. By understanding and addressing the disconnect between change managers and business stakeholders, and by prioritizing metrics that truly reflect the impact and progress of change, you can drive more effective and successful change management efforts by influencing your stakeholders in your organisation.
As a next step, Chat with us if you would like to discuss more about leveraging AI and technology to generate high-impact change management metrics and data for your stakeholders, both at project and portfolio levels, using data visualisation tools.
Change management is an intricate dance between vision, strategy, execution, and perhaps most importantly, adoption. The ultimate goal of any change initiative is not merely to implement new systems, processes, or regulations, but rather to embed these changes into the very fabric of the organization, ensuring widespread adoption and long-term sustainability.
What are the key adoption metrics that companies should track?
Key adoption metrics include user engagement rates, feature usage, retention rates, and the number of customers providing customer feedback. Tracking these metrics helps companies assess the effectiveness of their change management strategies, ensuring successful implementation and identifying areas for improvement. Consistent evaluation leads to enhanced user experiences and better overall outcomes during the adoption process.
What are the key adoption metrics that companies should track?
Key adoption metrics companies should track, including essential product adoption metrics, such as product stickiness, user engagement, customer retention rates, and conversion rates. Additionally, monitoring customer feedback and satisfaction scores can provide insights into how well the change is being received and inform the product roadmap, which is crucial for fostering customer loyalty. These metrics help organizations measure the success of their change initiatives and identify areas for improvement.
However, achieving full adoption is no small feat. Many change initiatives falter along the way, failing to garner the buy-in and commitment necessary for success. Even when adoption is initially achieved, sustaining it over time presents its own set of challenges.
What are the key adoption metrics that companies should track?
Key adoption metrics companies should track include user engagement, feature usage and adoption, onboarding process drop offs, retention rates, daily active users, feature activation rate, product adoption rate, and feedback scores. These indicators help assess user behavior and how well employees embrace new tools or processes, including the adoption of new features, guiding improvements in the parts of your product experience and ensuring successful implementation of the product’s core features. Monitoring these metrics fosters a culture of continuous improvement, offers insights into user behavior, and better aligns with organizational goals.
Change adoption is not a one-size-fits-all endeavor. It’s influenced by a myriad of factors, including organizational culture, leadership support, employee engagement, and the nature of the change itself. Therefore, it’s essential to approach the measurement of adoption metrics with a nuanced understanding of these dynamics.
Before diving into specific metrics, let’s explore some fundamental principles of change adoption:
Context Matters: Every change initiative is unique, shaped by its context, stakeholders, and objectives. What works for one organization may not necessarily work for another. Therefore, it’s crucial to tailor adoption metrics to align with the specific goals and dynamics of each initiative.
Focus on Outcomes: Adoption metrics should go beyond mere activities or outputs and focus on outcomes. Instead of measuring how many employees attended training sessions, for example, focus on whether the training resulted in improved performance or behaviour change, and that the feature adoption rate is adequate. For example, the average time of performing a process or task, average session duration, and monthly active users for a product feature.
Continuous Monitoring: Change adoption is not a one-time event but an ongoing process. Continuous monitoring of adoption metrics allows organizations to identify trends, address challenges, and make course corrections as needed.
Now, let’s explore user adoption and adoption metrics across different types of change initiatives, including those related to user personas:
Metrics for System Implementations:
System implementations, whether it’s a new CRM platform, ERP system, or productivity tool, often represent significant investments for organizations. To ensure a return on investment, it’s crucial to measure adoption effectively. Here are some key metrics to consider:
System Feature Usage Frequency: Measure how frequently employees utilize various features of the new system. This metric provides insights into whether employees are leveraging the system to its full potential and identifies areas for additional training or support.
Process Efficiency: Assess the efficiency gains achieved through the implementation of the new system. This metric quantifies improvements in workflow efficiency, resource utilization, and cycle times.
Customer Conversation Audit: If the change is aimed to improve the quality of customer interactions post-implementation, then the customer conversation should be audited. This metric focuses on whether the system enhances customer information accessibility, improves service representation, and ultimately leads to higher customer satisfaction.
Sales Volume: If the system aims to boost sales, track changes in sales volume post-implementation. This metric provides a tangible indicator of the system’s impact on revenue generation and business performance.
Information Completeness: Measure the completeness of customer information captured by the new system. This metric highlights the system’s effectiveness in capturing and storing relevant data, which is critical for decision-making and customer service.
Customer Satisfaction: Gauge customer satisfaction levels following the system implementation. This metric reflects the system’s ability to meet customer needs, deliver value, and enhance overall experience and satisfaction.
Metrics for Compliance Initiatives:
Compliance initiatives, whether it’s adherence to regulatory standards, industry certifications, or internal policies, require meticulous attention to detail. Here are some key metrics to consider for measuring compliance adoption:
Process Compliance: Monitor adherence to regulatory processes and requirements. This metric ensures that the organization remains compliant with relevant regulations and mitigates the risk of non-compliance penalties.
Rated Compliance of Targeted Behaviours: Evaluate the compliance level of specific behaviours targeted by the regulatory change. This metric provides insights into whether employees are adopting the prescribed behaviours and following compliance protocols.
Frequency of Team Leader Coaching: Track the frequency of coaching sessions conducted by team leaders to reinforce compliance behaviours. This metric emphasizes the role of leadership in driving and sustaining compliance across the organization.
Customer Feedback: Solicit feedback from customers regarding their experience with the organization post-compliance implementation. This metric captures customer perceptions of the organization’s adherence to regulatory standards and its commitment to compliance.
Number of Incidents: Depending on the nature of compliance requirements, track the number of incidents related to non-compliance. This metric serves as an early warning system for identifying areas of weakness in compliance efforts and implementing corrective actions.
Metrics for Restructuring Initiatives:
Restructuring initiatives, whether driven by mergers, acquisitions, organizational realignment, or cost-cutting measures, often have far-reaching implications for employees, departments, and the overall organizational structure. Measuring adoption in restructuring initiatives requires a nuanced understanding of the changes’ impact on employee morale, productivity, and alignment with organizational goals. Here are some key metrics to consider:
Employee Engagement and Morale: Measure changes in employee engagement and morale before, during, and after the restructuring initiative. Surveys, focus groups, and one-on-one interviews can provide valuable insights into employees’ perceptions, concerns, and levels of commitment to the new organizational structure.
Organizational Alignment: Assess the degree to which the restructuring initiative aligns with the organization’s strategic objectives and long-term vision. Key performance indicators (KPIs), such as revenue growth, market share, and customer satisfaction, can help gauge the effectiveness of the restructuring in driving organizational alignment and performance.
Communication Effectiveness: Evaluate the effectiveness of communication channels and messaging during the restructuring process. Metrics such as employee feedback on communication clarity, frequency of updates, and perceived transparency can shed light on the effectiveness of communication strategies in managing change and alleviating uncertainty.
Employee Productivity and Performance: Monitor changes in employee productivity and performance following the restructuring initiative. Key metrics may include employee turnover rates, absenteeism, and performance evaluations. By tracking these metrics over time, organizations can assess the impact of restructuring on employee motivation, workload, and job satisfaction.
Leadership Effectiveness: Assess the effectiveness of leadership in navigating the restructuring process and driving adoption of the new organizational structure. Metrics such as employee ratings of leadership communication, support, and decision-making can provide valuable feedback on leadership effectiveness and its impact on employee morale and commitment.
Team Dynamics and Collaboration: Measure changes in team dynamics, collaboration, and cross-functional cooperation post-restructuring. Surveys, team assessments, and project outcomes can help identify strengths and weaknesses in team dynamics and collaboration, enabling organizations to address barriers to adoption and foster a culture of teamwork and collaboration.
Implementing and Measuring Adoption Metrics:
Once you’ve identified the relevant adoption metrics for your change initiative, the next step is to implement and measure them effectively. Here are some practical strategies to consider:
Surveys: Utilize surveys to gather feedback from employees, customers, and other stakeholders. Design surveys to capture both quantitative data, such as ratings and frequencies, and qualitative insights into the perceived effectiveness of the change initiative.
Observations: Encourage stakeholders, subject matter experts (SMEs), change champions, and leaders to observe and provide feedback on the implementation process. Their firsthand observations can uncover valuable insights into adoption barriers and successes.
System Tracking Data: Leverage data captured by the system itself to track usage patterns, process compliance, and other relevant metrics. Analyze this data to identify trends and areas for improvement in adoption efforts.
Employee or Stakeholder Feedback Sessions: Conduct regular meetings, interviews, or workshops to solicit feedback from employees and stakeholders. Create a safe and open environment for sharing concerns, challenges, and suggestions related to the change initiative.
Continuous Improvement: Use adoption metrics as a basis for continuous improvement. Regularly review and analyze adoption data to identify areas of success and opportunities for enhancement. Make adjustments to strategies, communication plans, and support mechanisms as needed to drive greater adoption.
Measuring Behaviours in System Implementations:
A significant portion of change involved system or digital change. In system implementations, the successful adoption of new technologies and processes often hinges on changes in employee behaviours. While it’s essential to track macro-level outcomes such as system usage frequency and process efficiency, measuring micro-behaviours provides a stronger link to the direct, underlying drivers of adoption. Here’s how to measure targeted and specific micro-behaviours in the context of a system implementation:
User Interface Navigation: Assess employees’ proficiency in navigating the new system’s user interface. Track metrics such as the time taken to complete common tasks, the number of clicks required to access key features, and the frequency of help requests. If these are not available, observational studies and user feedback can also provide valuable insights into usability issues and training needs.
Data Entry Accuracy: Measure the accuracy of data entry performed by employees using the new system. Compare the quality of data input before and after the implementation, looking for improvements in data accuracy, completeness, and consistency. Conduct periodic audits and spot checks to identify errors and areas for improvement.
Workflow Integration: Evaluate the extent to which employees integrate the new system into their existing workflows. Track metrics such as the proportion of tasks completed using the new system versus legacy systems, the frequency of workarounds or manual interventions, and the level of integration with other tools or processes. Interviews and focus groups can uncover barriers to workflow integration and inform targeted interventions.
Collaboration and Knowledge Sharing: Measure employees’ engagement in collaborative activities and knowledge sharing facilitated by the new system. Look for indicators such as the frequency of document sharing, participation in online discussions or forums, and contributions to shared repositories or knowledge bases. Social network analysis and peer assessments can highlight patterns of collaboration and identify key influencers or knowledge brokers within the organization.
Adoption of Best Practices: Assess employees’ adoption of best practices and standardized workflows supported by the new system. Monitor adherence to established guidelines, protocols, and procedures, looking for deviations or non-compliance. Use performance metrics such as error rates, rework cycles, and customer satisfaction scores to evaluate the effectiveness of best practices in driving desired outcomes.
Change Agent Engagement: Measure the engagement and effectiveness of change agents, champions, or ambassadors tasked with promoting adoption of the new system. Track metrics such as the frequency of communication and training sessions led by change agents, the level of participation in peer support networks or mentoring programs, and the impact of their advocacy efforts on adoption rates. Surveys and feedback mechanisms can assess the perceived credibility, accessibility, and responsiveness of change agents.
Implementing and Measuring Micro-Behaviours:
Define Clear and Measurable Objectives: Identify specific behaviours that are critical to the success of the system implementation and define clear, measurable objectives for each behaviour. Ensure alignment with broader adoption goals and desired outcomes.
Select Relevant Metrics: Choose metrics that are closely aligned with the targeted micro-behaviours and are actionable, observable, and trackable over time. Consider a combination of quantitative data (e.g., completion rates, error rates) and qualitative insights (e.g., user feedback, observational data) to provide a comprehensive understanding of behaviour change.
Utilize Multiple Data Sources: Gather data from multiple sources, including system logs, user activity tracking, surveys, interviews, and observational studies. Triangulating data from different sources enhances the reliability and validity of measurement and provides a more holistic view of behaviour change.
Monitor Progress Continuously: Establish a system for continuous monitoring of micro-behaviours throughout the implementation process. Regularly review and analyze data to identify trends, patterns, and areas for improvement. Use real-time feedback mechanisms to address issues and reinforce positive behaviours promptly.
Provide Timely Feedback and Support: Provide employees with timely feedback on their performance and progress toward behaviour change goals. Offer targeted support, training, and resources to address skill gaps, overcome barriers, and reinforce desired behaviours. Celebrate successes and recognize individuals or teams that demonstrate exemplary behaviour change.
Iterate and Adapt: Continuously iterate and adapt your measurement approach based on ongoing feedback and insights. Adjust metrics, data collection methods, and interventions as needed to respond to changing circumstances, emerging challenges, and evolving user needs. Be flexible and open to experimentation to optimize the effectiveness of your behaviour change efforts.
How Many Metrics Should I Use?
When it comes to measuring behaviour change in change initiatives, the age-old adage “less is more” holds true. While it may be tempting to track a multitude of metrics in the hopes of capturing every aspect of adoption, focusing on the critical few behaviours that will have the most direct impact on the outcome of the change is essential. You are also not going to have the bandwidth and resources to measure ‘everything’. Here’s how to determine the right number of metrics to use:
Focus on Key Objectives: Start by identifying the key objectives of the change initiative. What are the primary outcomes you hope to achieve? Whether it’s increased system usage, improved process efficiency, enhanced customer satisfaction, or compliance with regulatory standards, prioritize the behaviours that directly contribute to these objectives.
Prioritize High-Impact Behaviours: Narrow down your list of behaviours to those that have the most significant impact on achieving your key objectives. What are the critical few behaviours that, if changed, would lead to the greatest improvement in outcomes? Focus on behaviours that are both important and feasible to change within the scope of the initiative.
Consider Complexity and Manageability: Be mindful of the complexity and manageability of the behaviours you choose to measure. While it’s important to capture a comprehensive view of behaviour change, tracking too many metrics can become overwhelming and dilute focus. Aim for a manageable number of metrics that are meaningful, actionable, and directly linked to the desired outcomes.
Quantitative vs Qualitative Metrics: Whilst quantitative metrics are usually preferred by executives and easier to report on, sometimes you may need to incorporate qualitative metrics to gain a holistic understanding of behaviour change. Quantitative metrics such as completion rates, error rates, and productivity measures provide objective data on behaviour performance, while qualitative insights from surveys, interviews, and observations offer deeper context and understanding.
Consider Interdependencies and Trade-Offs: Recognize that behaviours are often interconnected, and changes in one behaviour may impact others. Consider the interdependencies and potential trade-offs between different behaviours when selecting your metrics. Focus on behaviours that have a ripple effect and can drive change across multiple dimensions of the initiative.
By focusing on the critical few behaviours that have the most direct impact on the outcome of the change, you can streamline measurement efforts, maintain clarity of purpose, and maximize the effectiveness of your change initiative. Remember, the goal is not to measure everything, but to measure what matters most and use that information to drive meaningful behaviour change and achieve successful adoption of the change.
Change adoption dashboard
Now that you have determined exactly what you want to measure to drive adoption, you may want to create a dashboard. Check out our article on ‘Designing a Change Adoption Dashboard’.
Change adoption is the ultimate goal of any change initiative, and effective measurement of adoption metrics is key to integrating change into daily lives and achieving a product’s success. By understanding the dynamics of change adoption and the user journey, selecting the right metrics, and implementing them effectively, change practitioners and product managers can navigate the complexities of change and drive meaningful outcomes for their organizations. Remember, adoption is not a destination but a journey, and with the right metrics and strategies in place, sustainable change is within reach.
To find out more about leveraging a digital platform to create a change adoption dashboard click the below to chat to us.
Change management is an intricate dance between vision, strategy, execution, and perhaps most importantly, adoption. The ultimate goal of any change initiative is not merely to implement new systems, processes, or regulations, but rather to embed these changes into the very fabric of the organization, ensuring widespread adoption and long-term sustainability.
However, achieving full adoption is no small feat. Many change initiatives falter along the way, failing to garner the buy-in and commitment necessary for success. Even when adoption is initially achieved, sustaining it over time presents its own set of challenges.
Understanding the Dynamics of Change Adoption:
Change adoption is not a one-size-fits-all endeavor. It’s influenced by a myriad of factors, including organizational culture, leadership support, employee engagement, and the nature of the change itself. Therefore, it’s essential to approach the measurement of adoption metrics with a nuanced understanding of these dynamics.
Before diving into specific metrics, let’s explore some fundamental principles of change adoption:
Context Matters: Every change initiative is unique, shaped by its context, stakeholders, and objectives. What works for one organization may not necessarily work for another. Therefore, it’s crucial to tailor adoption metrics to align with the specific goals and dynamics of each initiative.
Focus on Outcomes: Adoption metrics should go beyond mere activities or outputs and focus on outcomes. Instead of measuring how many employees attended training sessions, for example, focus on whether the training resulted in improved performance or behaviour change.
Continuous Monitoring: Change adoption is not a one-time event but an ongoing process. Continuous monitoring of adoption metrics allows organizations to identify trends, address challenges, and make course corrections as needed.
Now, let’s explore adoption metrics across different types of change initiatives:
Metrics for System Implementations:
System implementations, whether it’s a new CRM platform, ERP system, or productivity tool, often represent significant investments for organizations. To ensure a return on investment, it’s crucial to measure adoption effectively. Here are some key metrics to consider:
System Feature Usage Frequency: Measure how frequently employees utilize various features of the new system. This metric provides insights into whether employees are leveraging the system to its full potential and identifies areas for additional training or support.
Process Efficiency: Assess the efficiency gains achieved through the implementation of the new system. This metric quantifies improvements in workflow efficiency, resource utilization, and cycle times.
Customer Conversation Audit: If the change is aimed to improve the quality of customer interactions post-implementation, then the customer conversation should be audited. This metric focuses on whether the system enhances customer information accessibility, improves service representation, and ultimately leads to higher customer satisfaction.
Sales Volume: If the system aims to boost sales, track changes in sales volume post-implementation. This metric provides a tangible indicator of the system’s impact on revenue generation and business performance.
Information Completeness: Measure the completeness of customer information captured by the new system. This metric highlights the system’s effectiveness in capturing and storing relevant data, which is critical for decision-making and customer service.
Customer Satisfaction: Gauge customer satisfaction levels following the system implementation. This metric reflects the system’s ability to meet customer needs, deliver value, and enhance overall satisfaction.
Metrics for Compliance Initiatives:
Compliance initiatives, whether it’s adherence to regulatory standards, industry certifications, or internal policies, require meticulous attention to detail. Here are some key metrics to consider for measuring compliance adoption:
Process Compliance: Monitor adherence to regulatory processes and requirements. This metric ensures that the organization remains compliant with relevant regulations and mitigates the risk of non-compliance penalties.
Rated Compliance of Targeted Behaviours: Evaluate the compliance level of specific behaviours targeted by the regulatory change. This metric provides insights into whether employees are adopting the prescribed behaviours and following compliance protocols.
Frequency of Team Leader Coaching: Track the frequency of coaching sessions conducted by team leaders to reinforce compliance behaviours. This metric emphasizes the role of leadership in driving and sustaining compliance across the organization.
Customer Feedback: Solicit feedback from customers regarding their experience with the organization post-compliance implementation. This metric captures customer perceptions of the organization’s adherence to regulatory standards and its commitment to compliance.
Number of Incidents: Depending on the nature of compliance requirements, track the number of incidents related to non-compliance. This metric serves as an early warning system for identifying areas of weakness in compliance efforts and implementing corrective actions.
Metrics for Restructuring Initiatives:
Restructuring initiatives, whether driven by mergers, acquisitions, organizational realignment, or cost-cutting measures, often have far-reaching implications for employees, departments, and the overall organizational structure. Measuring adoption in restructuring initiatives requires a nuanced understanding of the changes’ impact on employee morale, productivity, and alignment with organizational goals. Here are some key metrics to consider:
Employee Engagement and Morale: Measure changes in employee engagement and morale before, during, and after the restructuring initiative. Surveys, focus groups, and one-on-one interviews can provide valuable insights into employees’ perceptions, concerns, and levels of commitment to the new organizational structure.
Organizational Alignment: Assess the degree to which the restructuring initiative aligns with the organization’s strategic objectives and long-term vision. Key performance indicators (KPIs), such as revenue growth, market share, and customer satisfaction, can help gauge the effectiveness of the restructuring in driving organizational alignment and performance.
Communication Effectiveness: Evaluate the effectiveness of communication channels and messaging during the restructuring process. Metrics such as employee feedback on communication clarity, frequency of updates, and perceived transparency can shed light on the effectiveness of communication strategies in managing change and alleviating uncertainty.
Employee Productivity and Performance: Monitor changes in employee productivity and performance following the restructuring initiative. Key metrics may include employee turnover rates, absenteeism, and performance evaluations. By tracking these metrics over time, organizations can assess the impact of restructuring on employee motivation, workload, and job satisfaction.
Leadership Effectiveness: Assess the effectiveness of leadership in navigating the restructuring process and driving adoption of the new organizational structure. Metrics such as employee ratings of leadership communication, support, and decision-making can provide valuable feedback on leadership effectiveness and its impact on employee morale and commitment.
Team Dynamics and Collaboration: Measure changes in team dynamics, collaboration, and cross-functional cooperation post-restructuring. Surveys, team assessments, and project outcomes can help identify strengths and weaknesses in team dynamics and collaboration, enabling organizations to address barriers to adoption and foster a culture of teamwork and collaboration.
Implementing and Measuring Adoption Metrics:
Once you’ve identified the relevant adoption metrics for your change initiative, the next step is to implement and measure them effectively. Here are some practical strategies to consider:
Surveys: Utilize surveys to gather feedback from employees, customers, and other stakeholders. Design surveys to capture both quantitative data, such as ratings and frequencies, and qualitative insights into the perceived effectiveness of the change initiative.
Observations: Encourage stakeholders, subject matter experts (SMEs), change champions, and leaders to observe and provide feedback on the implementation process. Their firsthand observations can uncover valuable insights into adoption barriers and successes.
System Tracking Data: Leverage data captured by the system itself to track usage patterns, process compliance, and other relevant metrics. Analyze this data to identify trends and areas for improvement in adoption efforts.
Employee or Stakeholder Feedback Sessions: Conduct regular meetings, interviews, or workshops to solicit feedback from employees and stakeholders. Create a safe and open environment for sharing concerns, challenges, and suggestions related to the change initiative.
Continuous Improvement: Use adoption metrics as a basis for continuous improvement. Regularly review and analyze adoption data to identify areas of success and opportunities for enhancement. Make adjustments to strategies, communication plans, and support mechanisms as needed to drive greater adoption.
Measuring Behaviours in System Implementations:
A significant portion of change involved system or digital change. In system implementations, the successful adoption of new technologies and processes often hinges on changes in employee behaviours. While it’s essential to track macro-level outcomes such as system usage frequency and process efficiency, measuring micro-behaviours provides a stronger link to the direct, underlying drivers of adoption. Here’s how to measure targeted and specific micro-behaviours in the context of a system implementation:
User Interface Navigation: Assess employees’ proficiency in navigating the new system’s user interface. Track metrics such as the time taken to complete common tasks, the number of clicks required to access key features, and the frequency of help requests. If these are not available, observational studies and user feedback can also provide valuable insights into usability issues and training needs.
Data Entry Accuracy: Measure the accuracy of data entry performed by employees using the new system. Compare the quality of data input before and after the implementation, looking for improvements in data accuracy, completeness, and consistency. Conduct periodic audits and spot checks to identify errors and areas for improvement.
Workflow Integration: Evaluate the extent to which employees integrate the new system into their existing workflows. Track metrics such as the proportion of tasks completed using the new system versus legacy systems, the frequency of workarounds or manual interventions, and the level of integration with other tools or processes. Interviews and focus groups can uncover barriers to workflow integration and inform targeted interventions.
Collaboration and Knowledge Sharing: Measure employees’ engagement in collaborative activities and knowledge sharing facilitated by the new system. Look for indicators such as the frequency of document sharing, participation in online discussions or forums, and contributions to shared repositories or knowledge bases. Social network analysis and peer assessments can highlight patterns of collaboration and identify key influencers or knowledge brokers within the organization.
Adoption of Best Practices: Assess employees’ adoption of best practices and standardized workflows supported by the new system. Monitor adherence to established guidelines, protocols, and procedures, looking for deviations or non-compliance. Use performance metrics such as error rates, rework cycles, and customer satisfaction scores to evaluate the effectiveness of best practices in driving desired outcomes.
Change Agent Engagement: Measure the engagement and effectiveness of change agents, champions, or ambassadors tasked with promoting adoption of the new system. Track metrics such as the frequency of communication and training sessions led by change agents, the level of participation in peer support networks or mentoring programs, and the impact of their advocacy efforts on adoption rates. Surveys and feedback mechanisms can assess the perceived credibility, accessibility, and responsiveness of change agents.
Implementing and Measuring Micro-Behaviours:
Define Clear and Measurable Objectives: Identify specific behaviours that are critical to the success of the system implementation and define clear, measurable objectives for each behaviour. Ensure alignment with broader adoption goals and desired outcomes.
Select Relevant Metrics: Choose metrics that are closely aligned with the targeted micro-behaviours and are actionable, observable, and trackable over time. Consider a combination of quantitative data (e.g., completion rates, error rates) and qualitative insights (e.g., user feedback, observational data) to provide a comprehensive understanding of behaviour change.
Utilize Multiple Data Sources: Gather data from multiple sources, including system logs, user activity tracking, surveys, interviews, and observational studies. Triangulating data from different sources enhances the reliability and validity of measurement and provides a more holistic view of behaviour change.
Monitor Progress Continuously: Establish a system for continuous monitoring of micro-behaviours throughout the implementation process. Regularly review and analyze data to identify trends, patterns, and areas for improvement. Use real-time feedback mechanisms to address issues and reinforce positive behaviours promptly.
Provide Timely Feedback and Support: Provide employees with timely feedback on their performance and progress toward behaviour change goals. Offer targeted support, training, and resources to address skill gaps, overcome barriers, and reinforce desired behaviours. Celebrate successes and recognize individuals or teams that demonstrate exemplary behaviour change.
Iterate and Adapt: Continuously iterate and adapt your measurement approach based on ongoing feedback and insights. Adjust metrics, data collection methods, and interventions as needed to respond to changing circumstances, emerging challenges, and evolving user needs. Be flexible and open to experimentation to optimize the effectiveness of your behaviour change efforts.
How Many Metrics Should I Use?
When it comes to measuring behaviour change in change initiatives, the age-old adage “less is more” holds true. While it may be tempting to track a multitude of metrics in the hopes of capturing every aspect of adoption, focusing on the critical few behaviours that will have the most direct impact on the outcome of the change is essential. You are also not going to have the bandwidth and resources to measure ‘everything’. Here’s how to determine the right number of metrics to use:
Focus on Key Objectives: Start by identifying the key objectives of the change initiative. What are the primary outcomes you hope to achieve? Whether it’s increased system usage, improved process efficiency, enhanced customer satisfaction, or compliance with regulatory standards, prioritize the behaviours that directly contribute to these objectives.
Prioritize High-Impact Behaviours: Narrow down your list of behaviours to those that have the most significant impact on achieving your key objectives. What are the critical few behaviours that, if changed, would lead to the greatest improvement in outcomes? Focus on behaviours that are both important and feasible to change within the scope of the initiative.
Consider Complexity and Manageability: Be mindful of the complexity and manageability of the behaviours you choose to measure. While it’s important to capture a comprehensive view of behaviour change, tracking too many metrics can become overwhelming and dilute focus. Aim for a manageable number of metrics that are meaningful, actionable, and directly linked to the desired outcomes.
Quantitative vs Qualitative Metrics: Whilst quantitative metrics are usually preferred by executives and easier to report on, sometimes you may need to incorporate qualitative metrics to gain a holistic understanding of behaviour change. Quantitative metrics such as completion rates, error rates, and productivity measures provide objective data on behaviour performance, while qualitative insights from surveys, interviews, and observations offer deeper context and understanding.
Consider Interdependencies and Trade-Offs: Recognize that behaviours are often interconnected, and changes in one behaviour may impact others. Consider the interdependencies and potential trade-offs between different behaviours when selecting your metrics. Focus on behaviours that have a ripple effect and can drive change across multiple dimensions of the initiative.
By focusing on the critical few behaviours that have the most direct impact on the outcome of the change, you can streamline measurement efforts, maintain clarity of purpose, and maximize the effectiveness of your change initiative. Remember, the goal is not to measure everything, but to measure what matters most and use that information to drive meaningful behaviour change and achieve successful adoption of the change.
Change adoption dashboard
Now that you have determined exactly what you want to measure to drive adoption, you may want to create a dashboard. Check out our article on ‘Designing a Change Adoption Dashboard’.
Change adoption is the ultimate goal of any change initiative, and effective measurement of adoption metrics is key to achieving success. By understanding the dynamics of change adoption, selecting the right metrics, and implementing them effectively, change practitioners and leaders can navigate the complexities of change and drive meaningful outcomes for their organizations. Remember, adoption is not a destination but a journey, and with the right metrics and strategies in place, sustainable change is within reach.
To find out more about leveraging a digital platform to create a change adoption dashboard click the below to chat to us.
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.
The Strategic Blind Spot in Enterprise Change Management
In today’s volatile business environment, enterprise change management (ECM) functions are under mounting pressure to prove their value. Despite the proliferation of change initiatives – ranging from digital transformation to operational restructuring – many organizations still treat ECM as a support function, primarily focused on capability building and project resourcing. This narrow focus, while important, leaves a critical gap: ECMs are often missing the opportunity to deliver the highest value services – enterprise change measurement and strategic/operational planning.
The Current State: A Tactical Focus
Most ECM functions have evolved to emphasize two core activities:
Capability Building: Developing change skills and mindsets across the business, often through training, coaching, and establishing communities of practice
Project Resourcing: Supplying skilled change practitioners to projects, ensuring adequate coverage for major initiatives.
While these activities are foundational, they tend to position ECM as a cost centre rather than a strategic partner. When business conditions tighten, these functions are often among the first to face budget cuts or downsizing, as their value is often perceived as indirect or non-essential to core business outcomes.
The Consequence: Vulnerability in Uncertain Times
This tactical orientation creates a paradox. As organizations face more frequent and complex change, the need for robust change management increases. Yet, when times are tough, ECM functions are often scaled back precisely when their expertise could be most valuable. This cycle undermines organizational resilience and readiness, leaving businesses exposed to greater risks during periods of transformation.
The Missed Opportunity: High-Value Services
The most significant gap lies in the underutilization of ECM’s potential to deliver high-value, strategic services. These include:
Enterprise Change Performance: Systematically tracking and analyzing the impact, readiness, and adoption of change across the organization.
Strategic and Operational Planning: Partnering with strategy teams and business leaders to anticipate change impacts, model scenarios, and inform decision – making.
By not prioritizing these services, ECM functions miss the chance to influence the organization at the highest levels – where decisions about direction, investment, and risk are made.
Why the Gap Exists
Several factors contribute to this strategic blind spot:
Historical Positioning: ECM has traditionally been seen as an “enabler” rather than a “driver” of business outcomes.
Lack of Data: Without robust change measurement, it’s difficult to provide the insights needed for strategic planning and governance.
Resource Constraints: With limited budgets and headcount, ECMs often default to immediate project demands rather than longer-term, enterprise-wide priorities.
Digital Immaturity: Many organizations lack the digital tools to capture, analyze, and sustain data-driven change insights, further limiting ECM’s strategic contribution.
The Path Forward
To break this cycle, ECM functions must reposition themselves as indispensable partners in enterprise strategy and planning. This requires a deliberate shift from a narrow focus on capability and resourcing to a broader remit that includes measurement, insight generation, and strategic advisory services. The following sections will explore how ECMs can leverage data and digital tools to deliver these high-value services, and how this repositioning can fundamentally enhance their role in change governance and business planning.
Elevating Enterprise Change Management – From Tactical Support to Strategic Insight
The Power of Change Measurement
To become a true strategic partner, ECM functions must anchor their value proposition in robust, enterprise-wide change measurement. This means moving beyond anecdotal feedback and isolated project metrics to a disciplined, data-driven approach that captures the full spectrum of change activity, impact, and readiness across the organization.
What Is Enterprise Change Measurement?
Enterprise change measurement is the systematic collection, analysis, and interpretation of data related to all change initiatives within an organization. This includes:
Change Volume and Velocity: How many changes are occurring, and at what pace?
Cumulative Impact: What is the aggregated effect of concurrent changes on teams, processes, and customers?
Readiness and Adoption: How prepared are stakeholders for upcoming changes, and how well are new ways of working being adopted?
Risk and Saturation: Where are the pressure points? Which business units or functions are at risk of change fatigue or resistance?
By establishing a comprehensive measurement framework, ECMs can provide leaders with a “change performance dashboard” that highlights risks, opportunities, and areas requiring intervention.
Why Measurement Matters
Objectivity: Data – driven insights replace subjective opinions, enabling more informed decision – making.
Prioritization: Leaders can see where to focus resources for maximum impact and where to pause or sequence initiatives to avoid overload.
Accountability: Clear metrics enable tracking of change outcomes, supporting continuous improvement and demonstrating the tangible value of ECM.
Proactive Risk Management: Early identification of adoption risks or readiness gaps allows for timely mitigation, reducing the likelihood of failed initiatives.
Leveraging Digital Tools for Continuous Insight
The digital revolution has transformed every aspect of business, and ECM should be no exception. Modern digital tools – ranging from enterprise change management platforms to advanced analytics and AI – make it possible to capture, analyze, and visualize change data in real time.
Key Capabilities of Digital Change Platforms
Automated Data Capture: Streamline the collection of change activity and sentiment data with less manual effort.
Dashboards and Visualizations: Provide leaders with intuitive, up-to-date views of change activity, risk hotspots, and adoption trends.
Scenario Modelling: Use predictive analytics to model the impact of proposed changes on different parts of the organization, supporting better planning and resource allocation.
Feedback Loops: Enable continuous input from stakeholders, surfacing emerging issues and opportunities for course correction.
Building the Digital Foundation
To realize these benefits, ECMs must:
Invest in the Right Tools: Select platforms that fit the organization’s size, complexity, and digital maturity.
Establish Data Governance: Ensure data quality, security, and privacy, with clear ownership and processes for managing change data.
Build Analytical Capability: Develop skills within the ECM team to interpret data, generate insights, and translate findings into actionable recommendations.
Partnering for Strategic and Operational Planning
Armed with robust data and digital insights, ECMs are uniquely positioned to partner with strategy teams and senior leaders in both strategic and operational planning cycles.
Strategic Planning
Change Impact Modelling: Collaborate with strategy leaders to model the implications of major strategic shifts – such as mergers, restructures, or technology rollouts – on people, customers, partners and culture/behaviours.
Resource Forecasting: Advise on the change management resources required to support planned initiatives, ensuring adequate capacity and capability.
Risk Assessment: Highlight potential adoption risks and readiness gaps, enabling proactive mitigation and more resilient strategic execution.
Operational Planning
Change Portfolio Management: Work with business units to sequence and prioritize initiatives, reducing change saturation and maximizing adoption.
Readiness/Adoption Assessments: Provide data – driven readiness assessments to inform operational plans, ensuring teams are prepared for upcoming changes.
Performance Tracking: Monitor adoption and impact metrics post – implementation, feeding lessons learned back into future planning cycles.
Unlocking the Full Value of ECM
By moving up the value chain – from tactical support to strategic insight – ECMs can fundamentally reshape their role within the organization. This shift not only enhances the effectiveness of change initiatives but also positions ECM as a critical enabler of business strategy, resilience, and long-term success.
Embedding Enterprise Change Management in Governance and Planning – Unlocking Strategic Value
From Insight to Influence: The New Role of ECM
When enterprise change management (ECM) functions leverage robust measurement and digital insights, they move from being tactical enablers to strategic influencers. This transition is not just a shift in activity but a fundamental change in how ECM is perceived and positioned within the organization. The true value of ECM emerges when it is embedded in the core governance and planning processes, shaping decisions that drive business performance and resilience.
Integrating ECM Into Change Governance
Change governance is the system by which organizations oversee, prioritize, and manage change initiatives. Traditionally, ECM’s role in governance has been limited, often reactive – providing support when asked or responding to issues as they arise. However, with access to enterprise-wide change data and predictive analytics, ECM can now play a proactive, advisory role.
Key contributions of ECM in change governance include:
Portfolio-level risk assessment: By providing a “change performance dashboard,” ECM can help governance forums visualize where cumulative change is creating risk, enabling more informed decisions about sequencing, prioritization, and resource allocation.
Evidence-based recommendations: ECM brings objective data to the table, shifting conversations from opinion-based debates to fact-based decision-making.
Continuous monitoring: Real-time dashboards and feedback loops allow governance bodies to track adoption, readiness, and business impact, supporting agile responses to emerging issues.
This approach aligns with the Unified Value Proposition for change management, which emphasizes the integration of technical and people aspects to achieve both project objectives and organizational benefits. When ECM is seen as a structured, data-driven discipline, its credibility and influence within governance structures increase significantly.
Shaping Strategic and Operational Planning
The value of ECM is amplified when it is involved early in the strategic and operational planning cycles. By partnering with strategy and business leaders, ECM can:
Model change implications: Use scenario analysis to forecast the impact of strategic decisions on people, processes, and culture, identifying potential bottlenecks or adoption risks before they materialize.
Inform resource planning: Advise on the change management resources and capabilities required to support the planned portfolio, ensuring adequate investment and reducing the risk of under – resourcing critical initiatives.
Enhance readiness and adoption: Integrate readiness assessments and adoption metrics into operational plans, increasing the likelihood of successful outcomes and accelerating benefit realization.
This proactive involvement transforms ECM from a “nice-to-have” support function to an essential partner in delivering business strategy and managing risk.
Real-World Impact: Lessons from Leading Organizations
Organizations that have successfully repositioned ECM as a strategic partner demonstrate tangible business benefits. For example, a large financial services leader, integrated change management and project management, prioritized sponsorship, and leveraged data-driven insights to support multiple simultaneous transformations. The results included reduced risks of change saturation and release clashes, enhanced speed of planning and reduced operational disruptions.
This underscore the importance of:
Early and ongoing ECM involvement in planning and governance
A unified approach that combines technical and people – centric change management
Data-driven decision – making as the foundation for ECM’s strategic contribution
Sustaining the Strategic Role of ECM
To ensure ECM’s strategic value is sustained – even when business conditions become challenging – organizations must:
Institutionalize ECM’s seat at the table: Make ECM participation in governance and planning forums a non-negotiable part of the operating model.
Continue investing in digital tools and analytics: Maintain and evolve the digital infrastructure that enables continuous measurement and insight generation.
Develop ECM talent: Build analytical, advisory, and business partnership skills within ECM teams to match their new strategic mandate.
The Future of ECM Is Strategic
As organizations navigate increasing complexity and accelerated change, the need for strategic, data-driven change management has never been greater. By focusing on high-value services, enterprise change measurement and strategic/operational planning, ECM functions can secure their place as indispensable partners in business success. This shift unlocks their full potential to drive sustainable transformation and competitive advantage.
Change management teams have long prided themselves on enabling organisations to adapt, evolve, and thrive in the face of constant disruption. Yet, a curious irony persists: many change management teams themselves are reluctant to change. They are trapped in a cycle of executing individual projects, refining legacy methodologies, and building capabilities through workshops and sessions-year after year, with little evolution in their own practice. This phenomenon can be described as “Change Management Teams’ Stockholm Syndrome”-where practitioners defend the very systems and routines that may be limiting their impact, just as employees in transformation-fatigued organisations do.
This syndrome is not just about comfort; it is also about fear. Changing the way change is managed is risky. There is a real concern that if things do not go well, the change team may be blamed. The prevailing attitude is often: “If everyone else is doing it this way, why should we change?” This mindset is a significant barrier to progress and innovation.
And this is not to specifically single-out change management teams. In the corporate world, process and methodology helps to create certainty and clarity. Without it, there could be chaos. As a result, organisations as a whole and its teams, tend to stick to the convention to run the business.
The Legacy Methodology Trap
Most change management teams remain wedded to legacy methodologies-structured, linear frameworks that were designed for a pre-digital era. These approaches often emphasise process over people, form over function, and documentation over data. While these methods have served organisations well in the past, they are increasingly mismatched with the realities of today’s digital and AI-driven world.
The result? Change management teams risk becoming irrelevant, unable to provide the strategic value that modern organisations demand. They are seen as facilitators rather than strategists, focused on executing rather than shaping change. This legacy focus also means that teams miss out on the benefits of agile, data-based approaches that are now commonplace in other disciplines such as marketing, operations, human resources and customer experience.
The Cost of Standing Still
The consequences of this stagnation are profound:
No Innovation: Without evolving their own practices, change management teams cannot credibly advocate for innovation elsewhere in the organisation.
Legacy vs. Agile: Teams remain focused on rigid, legacy methodologies, missing opportunities to leverage agile, iterative, and data-driven approaches that are better suited to today’s fast-moving environment.
No Data-Based Insights: Historical data is often ignored, meaning teams cannot learn from past successes or failures, nor can they provide predictive insights to guide future change initiatives.
Inability to Influence Strategically: Without data and digital fluency, change teams struggle to influence at a strategic level, limiting their ability to shape the direction of the organisation.
Credibility Challenges: Project teams and leaders may increasingly question the value of change management, seeing it as a bureaucratic function rather than a strategic partner. On the other hand, change managers spend significant time on arguing/positioning their worth, versus delivering value.
The New Digital and AI Reality
The world has changed. Digital transformation is no longer a buzzword-it is a reality. AI is reshaping how work gets done, automating routine tasks, and providing deep insights that were previously unimaginable. Other disciplines have already embraced these trends, using data to inform decisions, automate low-value work, and focus on high-value strategic activities.
Yet, many change management teams are still operating in a pre-digital mindset. They are not leveraging the power of automation, AI, or data analytics to transform their own work. This is not just a missed opportunity-it is a threat to the relevance and impact of the discipline.
The Comfort of the Familiar
Why do so many change management teams resist changing their own ways of working? The answer lies in what we as change practitioners already know about human psychology. Change is hard, even for those who advocate for it. The status quo is comfortable, and the risks of trying something new are real. Teams may fear failure, blame, or simply the unknown. They may also suffer from “Organisational Stockholm Syndrome,” defending the very systems that exhaust them and limit their potential.
Looking Ahead
The solution is clear: change management teams must catch up with industry trends that other disciplines have already embraced. They must leverage data to inform their work, automate lower-value tasks, and leapfrog to higher-value strategic roles-advising on change strategy, adoption, and benefit optimisation across the organisation. Only by transforming themselves can they credibly support the transformation of others.
Barriers and Breakthroughs in Digital Change Management
Facing the Realities of Digital and Data-Driven Transformation
As change management teams recognise the need to evolve, they encounter a complex array of barriers that are both technical and cultural. The journey toward digital and data-driven change management is not simply about adopting new tools or methodologies; it is about transforming mindsets, processes, and organisational structures. The following barriers are among the most persistent and impactful.
Key Barriers to Digital and Data-Driven Change Management
Resistance to Change
Even within change management teams, resistance is a formidable obstacle. Many practitioners are comfortable with established processes and fear the disruption that comes with new digital tools or methodologies. This resistance is compounded by concerns over job security (e.g. the result of AI and automation), the risk of failure, and the potential for blame if initiatives do not succeed.
Integration with Legacy Systems
Many organisations rely on outdated systems that are not designed to work with modern digital solutions. Integrating new technologies-such as AI-powered analytics or automation platforms – with legacy processes such as spreadsheets and templates that are often complex, time-consuming, and costly. This challenge can stall progress and limit the ability to leverage data-driven insights.
Lack of Digital Expertise
There is a significant skills gap in many change management teams. Digital transformation requires a blend of technical, analytical, critical and strategic competencies that are not always present. Without the right expertise, teams struggle to implement and sustain new digital initiatives.
Poor Data Quality and Access
Effective data-driven change management relies on accurate, timely, and accessible data. However, many organisations struggle with fragmented data sources, inconsistent data quality, and limited access to meaningful insights. Only a minority of companies report having access to accurate data that can inform decision-making.
Failure to Link Strategy to Execution
Even with a clear digital or data-driven strategy, many change management teams struggle to translate this into daily practice. There is often a disconnect between strategic intent and operational execution, leading to missed opportunities and diminished impact.
Inadequate Leadership and Communication
Successful digital transformation requires strong leadership and effective communication. When leaders fail to articulate a compelling vision, provide adequate support, or foster a culture of transparency and trust, change initiatives are more likely to falter.
Cultural Inertia and Lack of Experimentation
Organisational culture plays a critical role in enabling or hindering change. A culture that resists experimentation, learning, and adaptation will struggle to embrace digital and data-driven approaches. Without the ability to experiment and learn from failures, progress is slow and innovation is stifled.
Overcoming the Barriers: Practical Breakthroughs
Despite these challenges, there are proven strategies that change management teams can adopt to overcome barriers and accelerate their digital and data-driven transformation.
Embrace Agile and Data-Driven Methodologies
Shift from rigid, legacy frameworks to agile, iterative approaches that prioritise learning, adaptation, and data-driven decision-making. This allows teams to respond more quickly to changing circumstances and to leverage real-time insights.
Invest in Digital Upskilling
Build digital literacy and analytical skills within the change management team. This can be achieved through targeted training, partnerships with digital experts, and the recruitment of data-savvy professionals.
Improve Data Quality and Accessibility
Implement robust data governance practices to ensure data accuracy, consistency, and accessibility. Invest in tools and platforms that enable seamless data integration and analysis across the organisation.
Strengthen Leadership and Communication
Develop a clear, compelling vision for digital change management and communicate it consistently across the organisation. Engage leaders at all levels to champion the change and provide ongoing support to teams.
Foster a Culture of Experimentation and Learning
Encourage teams to experiment with new tools, methodologies, and approaches. Create a safe environment where failure is seen as an opportunity for learning and improvement.
Align Strategy with Execution
Ensure that digital and data-driven strategies are translated into actionable plans and daily practices. Regularly review progress, gather feedback, and adjust course as needed to maintain alignment and drive results.
The Path Forward
The barriers to digital and data-driven change management are significant, but they are not insurmountable. By addressing resistance, building digital expertise, improving data quality, strengthening leadership, and fostering a culture of experimentation, change management teams can break free from legacy mindsets and unlock new levels of impact and credibility.
Leapfrogging to Strategic Impact
From Execution to Strategic Influence
For too long, change management teams have been seen as facilitators of change rather than architects. Their work has been largely transactional-running workshops, refining methodologies, and supporting project delivery. The digital and AI-driven world, however, demands a fundamental shift in how change is managed and led. The opportunity now is for change management to become a true strategic partner, leveraging data, automation, and AI to shape the direction and success of organisational transformation.
Leveraging Data for Deeper Insights and Predictive Power
The most forward-thinking organisations are already using real-time and historical data to inform every aspect of change. This means moving beyond gut feeling and anecdotal evidence to a world where decision-making is driven by robust analytics. Change management teams can now:
Predict Adoption and Resistance: By analysing readiness, engagement, and adoption metrics, teams can anticipate where resistance will emerge and intervene proactively.
Measure Impact in Real Time: Digital tools and platforms enable continuous monitoring of change initiatives, allowing for rapid course correction and more responsive leadership.
Optimise Communication and Support: Data-driven insights help tailor communication strategies to different stakeholder groups, ensuring messages resonate and support is targeted where it is most needed.
Automating the Routine, Elevating the Strategic
Automation and AI are transforming the landscape of change management by taking over repetitive, low-value tasks. Chatbots, virtual assistants, and automated workflows can handle routine communications, answer common questions, and even deliver personalised training modules. This frees up change practitioners to focus on higher-value activities, such as:
Advising on Change Strategy: With more time and better data, change teams can provide strategic counsel to senior leaders, helping shape transformation agendas and ensure alignment with business goals.
Driving Adoption and Benefit Realisation: By leveraging real-time analytics, teams can identify barriers to adoption early, design targeted interventions, and track the realisation of benefits across the organisation.
Leading Culture Change: Change management is increasingly recognised as a driver of organisational culture. Teams that embrace open, data-driven, and agile approaches can foster a culture of continuous improvement and innovation.
Building Credibility and Influence
As change management teams embrace digital and data-driven approaches, they also build credibility with project teams and leaders. By providing clear, evidence-based recommendations and demonstrating measurable impact, change practitioners can move from being seen as process administrators to trusted advisors. This shift is critical for influencing at a strategic level and ensuring that change management is embedded in the organisation’s DNA.
The Future of Change Management
The future belongs to organisations that treat change as a continuous, strategic process rather than a series of isolated projects. Change management teams that harness the power of data, automation, and AI will be at the heart of this transformation. They will drive not only the adoption of new technologies but also the cultural and behavioural shifts needed for sustainable success.
A Call to Action
For senior change and transformation practitioners, the message is clear: the time to leapfrog is now. By embracing digital tools, data-driven decision-making, and agile, open approaches, change management can move from the back office to the boardroom. The result will be a profession that is more innovative, influential, and indispensable than ever before.
The organisations that succeed in the digital age will be those that empower their change teams to lead, not just facilitate/deliver, transformation-shaping the future of work, culture, and performance for years to come.
