Change management professionals are increasingly requested to provide measurement, data, and insights to various stakeholder groups. Not only does this include tracking various change outcomes such as business readiness or adoption, but stakeholder concerns also include such as change saturation and visibility of incoming initiative impacts.
To become better at working with data there is much that change managers can learn from data scientists (without becoming one of course). Let’s explore how change management can benefit from the practices and methodologies employed by data scientists, focusing on time allocation, digital tools, system building, hypothesis-led approaches, and the growing need for data and analytical capabilities.
1. Time Allocation: Prioritizing Data Collection and Cleansing
Data scientists spend a substantial portion of their time on data collection and cleansing. According to industry estimates, about 60-80% of a data scientist’s time is dedicated to these tasks. This meticulous process ensures that the data used for analysis is accurate, complete, and reliable.
In the below diagram from researchgate.net you can see that for data scientists the vast majority of the time is spent on collecting, cleansing and organising data.
You might say that change managers are not data scientists because the work nature is different, and therefore should not need to carve out time for these activities? Well, it turns out that the type of activities and proportions of time spent is similar across a range of data professionals, including business analysts.
Below is the survey results published by Business Broadway, showing that even business analysts and data analysts spend significant time in data collection, cleansing, and preparation.
Lessons for Change Management
a. Emphasize Data Collection and Cleansing: For change managers, this translates to prioritizing the collection of reliable data related to change initiatives. This might include stakeholder feedback, performance metrics, impact data and other relevant data points. Clean data is essential for accurate analysis and insightful decision-making. Data projects undertaken by change managers are not going to be as large or as complex as data scientists, however the key takeaway is that this part of the work is critical and sufficient time should be allocated and not skipped.
b. Allocate Time Wisely: Just as data scientists allocate significant time to data preparation, change managers should also dedicate sufficient time to gathering and cleaning data before diving into analysis. This ensures that the insights derived are based on accurate and reliable information.
It also depends on the data topic and your audience. If you are presenting comparative data, for example, change volume across different business units. You may be able to do spot checks on the data and not verify every data line. However, if you are presenting to operations business units like call centres where they are very sensitive to time and capacity challenges, you may need to go quite granular in terms of exactly what the time impost is across initiatives.
c. Training and Awareness: Ensuring that the change management team understands the importance of data quality and is trained in basic data cleansing techniques can go a long way in improving the overall effectiveness of change initiatives. Think of scheduling regular data sessions/workshops to review and present data observations and findings to enhance the team’s ability to capture accurate data as well as the ability to interpret and apply insights. The more capable the team is in understanding data, the more value they can add to their stakeholders leveraging data insights.
2. Leveraging Digital Tools: Enhancing Efficiency and Accuracy
Data scientists rely on a variety of digital tools to streamline their work. These tools assist in data collection, auditing, visualization, and insight generation. AI and machine learning technologies are increasingly being used to automate and enhance these processes.
Data scientists rely on various programming, machine learning and data visualisation such as SQL, Python, Jupyter, R as well as various charting tools.
Lessons for Change Management
a. Adopt Digital Tools: Change managers should leverage digital tools to support each phase of their data work. There are plenty of digital tools out there for various tasks such as surveys, data analysis and reporting tools.
For example, Change Compass has built-in data analysis, data interpretation, data audit, AI and other tools to help streamline and reduce manual efforts across various data work steps. However, once again even with automation and AI the work of data checking and cleansing does not go away. It becomes even more important.
b. Utilize AI and Machine Learning: AI can play a crucial role in automating repetitive tasks, identifying patterns, data outliers, and generating insights. For example, AI-driven analytics tools can help predict potential change saturation, level of employee adoption or identify areas needing additional support during various phases of change initiatives.
With Change Compass for example, AI may be leverage to summarise data, call out key risks, generate data, and forecast future trends.
c. Continuous Learning: Continuous learning is essential for ensuring that change management teams stay adept at handling data and generating valuable insights. With greater stakeholder expectations and demands, regular training sessions on the latest data management practices and techniques can be helpful. These sessions can cover a wide range of topics, including data collection methodologies, data cleansing techniques, data visualisation techniques and the use of AI and machine learning for predictive analytics. By fostering a culture of continuous learning, organizations can ensure that their change management teams remain proficient in leveraging data for driving effective change.
In addition to formal training, creating opportunities for hands-on experience with real-world data can significantly enhance the learning process. For instance, change teams can work on pilot projects where they apply new data analysis techniques to solve specific challenges within the organization. Regular knowledge-sharing sessions, where team members present case studies and share insights from their experiences, can also promote collective learning and continuous improvement.
Furthermore, fostering collaboration between change managers and data scientists or data analysts can provide invaluable mentorship and cross-functional learning opportunities. By investing in continuous learning and development, organizations can build a change management function that is not only skilled in data management but also adept at generating actionable insights that drive successful change initiatives.
3. Building the Right System: Ensuring Sustainable Insight Generation
It is not just about individuals or teams working on data. A robust system is vital for ongoing insight generation. This involves creating processes for data collection, auditing, cleansing, and establishing governance bodies to manage and report on data.
Governance structures play a vital role in managing and reporting data. Establishing governance bodies ensures that there is accountability and oversight in data management practices. These bodies can develop and enforce data policies, and oversee data quality initiatives. They can also be responsible for supporting the management of a central data repository where all relevant data is stored and managed.
Lessons for Change Management
a. Establish Clear Processes: Develop and document processes for collecting and managing data related to change initiatives. This ensures consistency and reliability in data handling.
b. Implement Governance Structures: Set up governance bodies to oversee data management practices. This includes ensuring compliance with data privacy regulations and maintaining data integrity. The governance can sponsor the investment and usage of the change data platform. This repository should be accessible to stakeholders involved in the change management process, promoting transparency and collaboration. Note that a governance group can simply be a leadership team regular team meeting and does not need to be necessarily creating a special committee.
c. Invest in system Infrastructure: Build the necessary system infrastructure to support data management and analysis that is easy to use and provides the features to support insight generation and application for the change team.
Data scientists often use a hypothesis-led approach, where they test, reject, or confirm hypotheses using data. This method goes beyond simply reporting what the data shows to understanding the underlying causes and implications.
Lessons for Change Management
a. Define Hypotheses: Before analyzing data, clearly define the hypotheses you want to test. For instance, if there is a hypothesis that there is a risk of too much change in Department A, specify the data needed to test this hypothesis.
b. Use Data to Confirm or Reject Hypotheses: Collect and analyze data to confirm or reject your hypotheses. This approach helps in making informed decisions rather than relying on assumptions or certain stakeholder opinions.
c. Focus on Actionable Insights: Hypothesis-led analysis often leads to more actionable insights. It is also easier to use this approach to dispel any myths of false perceptions.
For example: Resolving Lack of Adoption
Hypothesis: The lack of adoption of a new software tool in the organization is due to insufficient coaching and support for employees.
Data Collection:
Gather data on the presence of managerial coaching and perceived quality. Also gather data on post go live user support.
Collect feedback from employees through surveys regarding the adequacy and clarity of coaching and support.
Analyse usage data of the new software to identify adoption rates across different departments.
Analysis:
Compare adoption rates between employees who received sufficient coaching and support versus those who did not.
Correlate feedback scores on training effectiveness with usage data to see if those who found the training useful are more likely to adopt the tool.
Segment data by department to identify if certain teams have lower adoption rates and investigate their specific training experiences.
Actionable Insights:
If data shows a positive correlation between coaching and support, and software adoption, this supports the hypothesis that enhancing coaching and support programs can improve adoption rates.
If certain departments show lower adoption despite completing coaching sessions, investigate further into department-specific issues such as workload or differing processes that may affect adoption.
Implement targeted interventions such as additional training sessions, one-on-one support, or improved training materials for departments with low adoption rates.
5. Building Data and Analytical Capabilities: A Core Need for Change Management
As data and analytical capabilities become increasingly crucial, change management functions must build the necessary people and process capabilities to leverage data-based insights effectively.
Lessons for Change Management
a. Invest in Training: Equip change management teams with the skills needed to manage data and generate insights. This includes training in data analysis, visualization, and interpretation.
b. Foster a Data-Driven Culture: A lot of organisations are already on the bandwagon of Encourage a culture where data is valued and used for decision-making. The change management needs to promote this equally within the change management function. This involves promoting the use of data in everyday tasks and ensuring that all team members understand its importance. Think of incorporating data-led discussions into routine meeting meetings.
c. Develop Analytical Frameworks: Create frameworks and methodologies for analyzing change management data. This includes defining common key metrics, setting benchmarks, and establishing protocols for data collection and analysis for change data. Data and visual templates may be easier to follow for those with lower capabilities in data analytics.
Practical Steps to Implement Data-Driven Change Management
To integrate these lessons effectively, senior change practitioners can follow these practical steps:
Develop a Data Strategy: Create a comprehensive data strategy that outlines the processes, tools, and governance structures needed to manage change management data effectively.
Conduct a Data Audit: Begin by auditing the existing data related to change management. Identify gaps and areas for improvement.
Adopt a Hypothesis-Led Approach: Encourage the use of hypothesis-led approaches to move beyond descriptive analytics and derive more meaningful insights.
Invest in Technology: Invest in the necessary digital tools and technologies to support data collection, cleansing, visualization, and analysis.
Train the Team: Provide training and development opportunities for the change management team to build their data and analytical capabilities.
Collaborate Across Functions: Foster collaboration between change management and data science teams to leverage their expertise and insights.
Implement Governance Structures: Establish governance bodies to oversee data management practices and ensure compliance with regulations and standards.
By learning from the practices and methodologies of data scientists, change management functions can significantly enhance their effectiveness. Prioritizing data collection and cleansing, leveraging digital tools, building robust systems, adopting hypothesis-led approaches, and developing data and analytical capabilities are key strategies that change management teams can implement. By doing so, they can ensure that their change initiatives are data-driven, insightful, and impactful, ultimately leading to better business outcomes.
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. 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 are trained to view metrics through the lens of change management frameworks and methodologies, focusing on detailed assessments and structured approaches. These include applying ratings and judgments on aspects such as impact levels.
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 stakeholder 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 data and what that means in terms of organisation, coordination, capacity and performance perspectives. Senior managers may prefer higher level data with focus on strategic impacts, overall progress and adoption indicators.
This disconnect can lead to the use of metrics that do not resonate with or are misunderstood by stakeholders.
Metrics from a Change Manager’s Perspective
Change managers may leverage metrics that are derived from the various change management documents such impact assessments, training plan or communications plan. Metrics 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?”.
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. 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 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. 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. 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 mee their needs.
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.
Practical Takeaways for Senior Change Managers
To ensure that change management metrics are effective, consider the following practical takeaways:
Align Metrics with Stakeholder Perspectives
Understand Stakeholder Priorities: Engage with stakeholders to understand their 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: Prioritize metrics that reflect the outcomes and impacts of change, rather than just the activities performed. For example, instead of counting the number of 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.
Track Engagement and Adoption: Monitor metrics that indicate the level of engagement and adoption among stakeholders. This could include surveys, feedback forms, or direct measures of behaviour change.
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.
Narrative Approach: Combine metrics with a narrative that explains the story behind the numbers. 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.
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.
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, 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.
Effective change management requires metrics that not only measure progress but also resonate with business stakeholders and accurately reflect the impact of change initiatives. 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.
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.
Enterprise change management reporting is changing. It no longer consists of general updates of change streams of project progress or updates on various change capability training session volumes and satisfaction rates. Executives are demanding more value from enterprise change functions. The pace of change since Covid has not slowed down. For many, it has increased in pace and volume. To gain better insight into how the change management function is supporting the success of organisations, reports and dashboards have often become a visible linchpin of what value an enterprise change management delivers.
Having the right content and format for your enterprise reports can make or break your reputation. Do it right and you could start a ripple of high-impact and strategic conversations across senior stakeholders that drive focus on improving change. You can be in the spotlight in influencing change leadership and the achievement of change and transformation goals. Do it wrong and you may never have another opportunity to have the room to talk about change management to senior leaders. You may be associated with not providing much value and too ‘operational’.
Unlocking the Potential of Enterprise Change Management Reporting:
At its core, enterprise change management reporting goes beyond merely tracking progress. It encompasses a holistic approach that considers various factors crucial to the success of organizational initiatives. While monitoring progress, readiness, and the amount of work done may be interesting components, true impact comes from focusing on impacts, adoption and predictors for benefit realization.
Executives and stakeholders are not just interested in receiving progress updates; they seek insights into the likelihood of initiative success and the potential risks that may impede desired outcomes. These risks extend beyond project timelines and budget constraints to encompass broader business implications such as performance impacts, capacity constraints, prioritization effectiveness, and the sustainability of behavioural change.
Impacts of change:
Quantifying and visualising impacts are not new to change practitioners. The key is how the data is presented over time. A lot of change practitioners would settle with a standard heatmap based on personal ratings. This does not deliver much value as the data cannot be easily substantiated by evidence (since it is more of a finger in the air estimation). Standard heatmaps also are too high level and does not really support key decision making.
Decision making requires specific data points such as:
Change saturation or change tolerance levels (these levels need to be substantiated based on business indicator reference to justify the levels, and not be someone’s personal opinion)
What division, team, role and which week the saturation points are forecasted
Corresponding data on what initiatives, and their respective impact activities that contribute to the saturation risk, and therefore proposed options
A key part of representing change impacts should not just be at an operational level, which is more concerned about capacity and bandwidth. Impact should also be tied to strategic levers, portfolio types, benefit types and readiness.
Predictive Indicators for Success:
To create impactful change management reports, organizations must incorporate predictive indicators that go beyond change volume and risk assessment. These indicators should provide insights into business performance, strategy achievement, and the realization of intended benefits.
These are some of the ways you can incorporate predictive indicators:
Forecast lines. With sufficient data you can forecast such as impact or capacity levels (which may be seasonal), or even readiness levels across the initiative lifecycle historically across initiatives.
The types of factors that can be included as predictive indicators can include readiness. It could be that readiness levels only get lifted just before go live or at go live. Adoption levels can also be forecasted if you have trend data across initiatives
Change tolerance levels across different parts of the business can also be seen as a predictive way of forecasting how much capacity there is for change beyond which saturation may be a key risk
Adoption and Behaviour Tracking:
Central to successful change management is the adoption and sustained implementation of new processes or technologies. Tracking adoption rates, user engagement, and behavioural changes are crucial indicators of initiative success. However, it’s essential to strike a balance between capturing relevant metrics and overwhelming stakeholders with unnecessary data.
Capturing behaviour change data can be key for larger initiatives or transformations. Behavioural change can be central in a range of changes such as customer centricity, efficiency, team collaboration or effectiveness. Measuring key behaviour changes that drive the initiative outcome the most is critical. For example, having effective conversations with customers to improve customer experience is a behaviour that can be rated, tracked and reported. Depending on the change, there may also be system features that can aid the tracking of these behaviours.
Effective change management goes hand in hand with strategic alignment. Reports should assess how initiatives contribute to overarching business objectives and whether they align with the organization’s strategic direction. Metrics related to revenue growth, cost savings, customer satisfaction, and employee productivity can provide valuable insights into the impact of change initiatives on business performance.
You can also link your change impacts to each strategic lever. In this way you can visually show the size of the impact per strategic lever. This will give your executives a way to examine whether the right level of impacts in the right areas of business are planned as a part of the course of each strategic lever.
The other angle is to visually show the pace of change against the strategic levers. Are certain key initiatives being driven at the right pace at the right time? Will the velocity of change exceed the ability of the business to absorb the changes? Or is the velocity not sufficiently meeting leadership expectations?
Benefit Realization:
Ultimately, the success of change initiatives is measured by their ability to deliver tangible benefits. Change management reports should include metrics that track the realization of expected benefits, whether they are financial gains, process efficiencies, or competitive advantages. By monitoring benefit realization, organizations can course-correct as needed and ensure that investments in change deliver the intended outcomes.
A key responsibility for change is to focus on those foreward looking measures that predict eventual benefit realisation, including readiness, adoption, engagement and behaviour change. Be sure to link these specifically to high benefit initiatives to provide strategic oversight.
Balancing Complexity and Clarity:
While incorporating a diverse range of metrics is essential for comprehensive reporting, it’s equally important to maintain clarity and focus. Reports should be structured in a way that highlights key insights and trends without overwhelming stakeholders with excessive detail. Visualizations such as charts, graphs, and dashboards can help distill complex data into actionable insights, facilitating informed decision-making at all levels of the organization.
All aspects of chart and dashboard designs are critical. These range from colour scheme chosen, number of charts, commentary, titles, legends, sequencing of charts, and type of charts chosen all act to either contribute to simplicity and clarity or complexity and confusion. Your narrative as you talk through the charts also plays a key role in building the story-line, and simplifying the key messages and actions you would like to impart to the audience.
Charts and dashboards tell a story and in presenting them you should always incorporate any actions required from the audience. If this is not done then it will always remain a FYI. FYI content will be deemed lower in the value curve over time and your stakeholders will lose interest. Instead, you should work on crafting a continual story that ebbs and flows. The following are key questions you should be asking when crafting you ongoing charts and dashboards:
Is there an emerging risk or opportunity that warrants specific focus for this month?
How are we tracking the effectiveness of stakeholder actions through data? This feedback loop is critical and gives your stakeholders a reference point for their own effectiveness
Is your data-based story uni-dimensional? Are there other dimensions beyond what you have been presenting that stakeholder should be aware of?
Are you giving stakeholders what they are most interested in? Whether it be strategic success progress, or benefit realisation?
Are you presenting change data in a holistic way in terms of how the business is run? Vs. just focused on standard change management function-specific metrics such as training sessions, or number of workshops completed?
Enterprise change management reporting is a critical tool for navigating the complexities of organizational change. By focusing on predictive indicators, including adoption and behavior tracking, business performance alignment, and benefit realization, organizations can unlock the full potential of their change management initiatives. However, achieving impactful reporting requires a careful balance between complexity and clarity, ensuring that stakeholders receive actionable insights without being inundated with unnecessary information. Ultimately, by harnessing the power of enterprise change management reporting, organizations can drive successful outcomes and thrive in an ever-evolving business landscape.
To find out more about enterprise change management reporting leveraging digital automation and analytics chat to us here.
There is now a lot of attention and focus on data. However, is the same applied to change management data? With the substantial financial investments companies make in change efforts, there’s a growing recognition of the need to leverage change management data strategically. Senior managers and executives are increasingly demanding data-driven insights to make informed business decisions. Here, we explore the challenges associated with change data, the strategic approaches to managing it effectively, and how incorporating it into the decision-making process can drive organizational success.
Common Challenges in Working with Change Data
Ad hoc and Tactical Approaches One common challenge in working with change data is the ad hoc and tactical nature of its collection. Often, data is gathered as needed, primarily at the project level. This can result in a fragmented view of change initiatives, making it challenging to derive meaningful insights. For instance, progress data may be limited to generic metrics such as the number of change impact sessions or completed training sessions, lacking depth and context.
Data Insufficiently Fact-Based Another prevalent issue is the creation of data that lacks a solid factual foundation. Change practitioners sometimes rely on gut-feel ratings or broad categories that are difficult to defend or substantiate infront of stakeholders. Heatmaps, a popular visualization tool, may be based on subjective assessments rather than objective, quantifiable measures, hindering the data’s credibility and utility.
Ineffective Data Visualizations Data visualizations play a crucial role in conveying information effectively. Unfortunately, some visualizations fall short of making a significant impact. Whether they are overly colorful, fail to use the right chart to highlight key points, or present data in a way that obscures the primary message, ineffective visualizations can impede the decision-making processes.
Seeking Easy Fixes Many change practitioners view working with data as a chore and opt for quick fixes. They may collect just enough data to generate a report or dashboard, neglecting the importance of a thorough understanding and management of the data. This short-sighted approach can compromise the quality and reliability of the insights derived from the data.
Strategic Approaches in Working with Change Data
Strategic approaches to manage change data can result in significant value for the organisation. Imagine the power of a range of change management data that highlights anything from impact levels, saturation risks, sentiments, adoption risks and benefit realization progress. Such is the power of change data, if managed effectively. What are some of these strategic approaches?
Managing Data as a Core Routine To address the challenges associated with ad hoc and tactical data collection, organizations must establish routines for managing change data. Monthly data reviews, updates, and audits create a disciplined approach to ensure the data remains accurate, relevant, and valuable. By making data management a core routine, organizations foster a culture of accountability and accuracy. This can be applied across a large program, a business unit, a portfolio of initiatives or across the enterprise.
Leveraging AI for Data Auditing and Cleansing Artificial Intelligence (AI) can play a pivotal role in auditing and cleansing change data. Platforms like The Change Compass offer features that automate these processes, reducing the likelihood of errors and ensuring data integrity. AI-driven tools can identify inconsistencies, outliers, and inaccuracies, providing a more reliable foundation for decision-making.
Linking Change Data with Other Business Sources The true power of change data emerges when it is connected with other relevant business data sources. By integrating change management data with project data, HR data, risk data, and operations data, organizations gain a holistic view of their business landscape. This interconnected approach allows for a comprehensive understanding of key business risks and opportunities, facilitating more informed decision-making.
Incorporating Data into Decision-Making Bodies Change data should not exist in isolation; it should be integrated into key decision-making forums and processes. From executive leadership forums and strategic planning sessions to portfolio planning and operational meetings, incorporating change data into these discussions ensures that insights derived from the data inform critical business decisions. This alignment helps organizations proactively address challenges and capitalize on opportunities.
While recognizing the strategic importance of change data is a significant step forward, change practitioners must actively implement practical measures to enhance their approach to change data management. Here are some recommendations to help change practitioners become more strategic in their utilization of change data:
Standardize/Routinize Data Collection Processes: o Develop standardized processes for collecting change data across different projects and initiatives. o Implement consistent data collection templates and methodologies to ensure uniformity and comparability of data across initiatives and business units
Invest in Training and Skill Development: o Provide training for change practitioners on data management best practices, including data collection, analysis, audit and interpretation. This is critical to drive data capability and maturity. o Foster a data-driven culture within the organization by equipping practitioners with the necessary skills to leverage data effectively.
Utilize Technology and Automation: o Embrace technological solutions, such as data analytics tools and AI-driven platforms, to automate data auditing, cleansing, and visualization processes. o Leverage technology to streamline data collection and reporting, reducing manual effort and minimizing the risk of errors.
Encourage Cross-Functional Collaboration: o Facilitate collaboration between change management teams and other departments, encouraging the sharing of data and insights. o Establish cross-functional teams to integrate change data with project data, HR data, and other relevant business sources.
Implement Data Governance Frameworks: o Develop and implement robust data governance frameworks to ensure the accuracy, security, and compliance of change data. o Define roles and responsibilities for data management within change initiatives, promoting accountability and ownership.
Enhance Data Visualization and Reporting: o Invest in training or hiring professionals with expertise in data visualization to create compelling and impactful reports. o Tailor visualizations to the audience, ensuring that key messages are communicated clearly and effectively.
Conduct Regular Data Reviews and Audits: o Establish a routine for regular data reviews, updates, and audits to maintain the accuracy and relevance of change data. o Use audits as an opportunity to identify and rectify data discrepancies or inconsistencies.
Integrate Change Data into Decision-Making Processes: o Actively participate in executive leadership forums, strategic planning sessions, and other decision-making bodies. o Present change data alongside other relevant business data to contribute to well-informed decision-making.
Measure and Communicate Value: o Develop metrics to measure the value generated by change initiatives and communicate these metrics to key stakeholders. o Regularly assess the impact of change data on decision-making processes and adjust strategies accordingly.
Seek Continuous Improvement: o Foster a culture of continuous improvement within the change management function. o Encourage practitioners to reflect on past experiences, learn from challenges, and refine their approach to change data management over time.
The strategic management of change data is not just a necessity but a critical component of achieving business success in today’s dynamic environment. By addressing common challenges and adopting strategic approaches, organizations can unlock the true potential of change data. As the business landscape continues to evolve, leveraging data-driven insights becomes a strategic imperative for navigating change, mitigating risks, and capitalizing on opportunities. Embracing change data as a strategic exercise positions organizations to not only survive but thrive in an ever-changing marketplace.
Why Nailing the Right Change Management Metrics is Critical and Can Make or Break Your Reputation
As organizations strive to adapt and thrive in dynamic environments, how change management is tracked has become a strategic imperative. However, the success of any change initiative hinges not only on effective planning and execution but also on the ability to measure and communicate its impact accurately. After all, without the right measures how do we know that we are moving in the right direction? In this article, we explore critical change management reports that executives value in shaping organizational understanding and decision-making. We delve into the metrics that may compromise your credibility and, more importantly, highlight the metrics that executives truly value, providing a roadmap to creating reports that resonate with leadership.
Reading your executives and where they are
Prior to designing the right change management reports and metrics it is absolutely essential that you understand where they are coming from. Understanding their key concerns and perspectives will help you design the right content to engage them. Key questions you may want to delve into include:
What issues are top of mind for executives when it comes to managing change?
What has worked or not worked well in the past for change that should be taken into account?
How experienced are these executives in driving complex change?
Putting your strategic hat on, what are the key business performance challenges that executives are facing into? What are the people and change connections to these?
What are the top key organisational risks that executives are focused on? What are the people and change connections to these?
Metrics That May Downgrade Your Credibility
Vanity Metrics – Metrics That Don’t Connect to Business Outcomes
One of the pitfalls in change management reporting is the reliance on vanity metrics—superficial measures that may look impressive but lack a direct connection to tangible business outcomes. Metrics such as the number of training hours delivered, numbers of stakeholder groups who received communications or the volume of communication materials distributed might seem impressive and easy to measure, but they provide little insight into the real impact of the change on the organization.
Executives are not interested in surface-level data; they want to understand how the change contributes to the achievement of strategic objectives and positively influences key performance indicators. To enhance credibility, change management reports must move beyond vanity metrics and focus on indicators that align with broader business goals.
Activity Metrics – Counting Without Context
Measuring the sheer volume of activities related to a change initiative can be misleading, or worse, meaningless, if not accompanied by context and relevance. Activity metrics, such as the number of workshops conducted, numbers of impact assessment activities conducted, number of deliverables worked on, or emails sent, might create an illusion of progress. However, these metrics fail to provide insights into the quality of engagement, the depth of understanding among employees, or the actual impact on work behaviours. Operational managers may find these interesting, but less likely for executives.
Instead of focusing solely on activities, change management reports should emphasize the effectiveness of these activities in driving desired outcomes. Metrics should, instead, highlight the quality of engagement, the level of understanding, and the behavioural shifts observed within the organization.
Cost-Focused Metrics – Counting Dollars Without Value
While cost-related metrics are important for financial stewardship, solely focusing on cost without considering the value generated by the change can undermine the perceived success of the initiative. Metrics such as the budget spent or the cost per participant may provide financial insights but do not necessarily convey the broader impact on organizational performance.
Change management reports should focus more on value metrics than cost metrics. Focusing purely on cost is restricting the value of managing change as another cost to the business. However, focusing on the value created in maximising business performance and achieving greater adoption can significant extend the understanding of change management value. Executives are interested in understanding what business value is created through managing change. Value includes how the targeted benefits are better realised and how the business performance is protected or maximised during the implementation of change.
Intra-Practice Metrics – Metrics That Only Change Management Cares About
It’s a common misstep to develop metrics that only resonate within the change management function but fail to capture the attention of other business units or executives. Metrics that focus exclusively on communication buzz generated, training satisfaction rates, or employee satisfaction with change processes might be valuable for internal assessments but lack the relevance needed to engage executives.
Even the focus on change maturity, that is often the single most critical focus for change management functions, may or may not appeal to a lot of executives. Unless you have already taken the executives on the journey of why focusing on change maturity is critical and you have them fully onboard with this, treat carefully in reporting on change maturity metrics.
At executive level, change management reports should transcend departmental boundaries and speak to the broader organizational impact. This means that your focus should be on reporting at a portfolio level and key strategic initiatives as relevant. Focus on generating insights of what the totality of changes mean to the organisation, and what employee experiences are across multiple initiatives. Metrics should also align with strategic goals and showcase how the change initiatives contributes to overarching business objectives.
The Right Metrics
I. Change Readiness Metrics – Assessing the Pulse of the Organization
Change readiness metrics serve as a barometer for understanding how prepared an organization is for a change initiative. To provide meaningful insights, these metrics should delve into the engagement journey, capturing key elements such as awareness, involvement, and participation.
Awareness: Measure the level of understanding and awareness of the upcoming change across different employee segments.
Involvement: Assess the degree to which employees are actively engaged in the change process, seeking their input and involvement.
Participation: Evaluate the extent to which employees are actively participating in change-related activities and initiatives.
Data Collection Methodology
Utilize a mix of quantitative and qualitative methods to gather data, including surveys, focus groups, and feedback mechanisms.
Ensure a representative sample across different organizational levels and functions to capture a comprehensive view of readiness.
Change Readiness Topic Areas
1. Awareness Assessment:
This section evaluates the extent to which employees are aware of the impending changes across initiatives. It includes an analysis of communication effectiveness, the clarity of messaging, and the overall visibility of the change initiatives. Metrics may encompass the percentage of employees who understand the change purpose and the reach of communication channels.
2. Involvement Evaluation:
Involvement is a key factor in gauging how actively employees are participating in the change process. This explores the degree to which employees feel engaged and have opportunities to contribute to the planning and decision-making aspects of the change. Employees may not have the opportunities to contribute to all types of change initiatives but for those that are relevant this can be quite insightful. Metrics include participation rates in change-related workshops, the number of submitted suggestions, and levels of engagement in feedback sessions.
3. Perceived Impact:
This area delves into employees’ perceptions of how the changes will affect them personally and professionally. It includes an analysis of perceived benefits, risks, and the overall impact on day-to-day responsibilities. Metrics may encompass the percentage of employees who feel well-informed about the impact of the change and qualitative insights from open-ended survey questions.
4. Change Champions performance:
Identifying and nurturing change champions can be crucial for successful change implementation, especially across the change portfolio. The presence of key business change champions who actively support and advocate for the changes within their teams and business units can shed light on how the change is performing. Metrics include the presence of key change champions across business areas, their engagement levels, and the effectiveness of their engagement strategies within their respective departments.
5. Learning and Development Readiness:
Learning and development play a vital role in equipping employees with the skills necessary for the upcoming changes. This section evaluates the organization’s readiness to deliver learning programs effectively, including the availability of resources, the alignment of learning content with change objectives, and the accessibility of learning materials. This can be outlined not just at initiative levels, but from business unit perspectives. Different business units may have different processes and channels from which to deploy learning and development across initiatives. The readiness and maturity of these can make or break the adoption of changes.
6. Resource Allocation and Availability:
Change initiatives often require additional resources, and this section examines the organization’s capacity to allocate and provide the necessary resources for a smooth transition. Metrics include the allocation and availability of SME resources, business representatives, the availability of technology and tools, and the overall preparedness of support functions for the myriad of change initiatives. Is there adequate allocation of these resources? For example, for digital transformation is there still reliance on manual work processes that should be upgrade to drive efficiency and effectiveness?
7. Leadership Alignment:
Leadership alignment is a critical factor influencing change readiness. This section evaluates the extent to which various leaders are aligned with the change vision and actively communicate their support. Metrics encompass leadership messaging consistency, visibility, and the perceived commitment of leaders to the success of the change.
8. Employee Feedback Mechanisms:
Establishing effective feedback mechanisms is essential for continuous improvement during change initiatives. This section assesses the availability, content and effectiveness of channels through which employees can provide feedback, ask questions, and express concerns. Metrics include response rates to feedback requests, the variety of feedback channels used, and themes of responses from targeted employee groups.
Change Readiness Data Collection Methods
Collecting data on change readiness is a crucial step in understanding an organization’s preparedness for a change initiative. Various approaches can be employed to gather relevant information. Here’s a list of key approaches:
Surveys and Questionnaires
Focus Groups
Interviews
Observation
Benchmarking
Document Analysis
Readiness Workshops
Network Analysis
Online Platforms and Social Listening
Pulse Surveys
Interactive Assessments
II. Change Journey Analytics – Navigating the Transformation Landscape
Change journey analytics provide a view of what key employee change experience highlights are, including insights on any behavioural changes, attitudinal changes, the volume of changes and how changes are being driven against key business performance challenges.
Change Volume Risks
Change volume risk measures highlight key change impact volumes across the business over time, with key call outs on any risks on heightened change periods. The volume and nature of changes can be mapped against strategies to indicate to what extent the level and pace of impacts are aligned with strategic plans
Change Activity Design
The totality of change management activities across initiatives from the lens of impacted employee groups should be analysed with potential risks highlighted including the alignment of learning content, communication message consistency and alignment, and to what extent there maybe excessive or below expected types of change activities in facilitating the change journeys
Single View of Change of BAU and Strategic Initiatives
Provide a consolidated view of ongoing business-as-usual (BAU) changes alongside strategic initiatives. This ensures that executives have a comprehensive understanding of the organizational change landscape. From the perspective of the impacted change stakeholders or employee groups, they may not care about the source of the change and whether it is strategic or not. BAU initiatives may also be even more impactful than strategic initiatives.
Business Performance
Link change activities to business performance metrics. Demonstrate how the change initiative contributes to key performance indicators and strategic goals. Also shed light how the nature and volume of changes may or may not impact the overall business performance. Executives are focused on keeping the business running successfully during change implementation as much as possible, with minimum disruption
Nurturing Lasting Transformation: The Role of Adoption Analytics in Sustainable Change
When we discuss adoption analytics, we transcend the traditional boundaries of project management. While implementation marks the beginning of change, adoption analytics guide us through the more profound stages, measuring the extent to which the organization has embraced and embedded the change. It’s about ensuring that the seeds of change and transformation take root, flourish, and yield sustainable benefits.
1. Business Performance Metrics: Gauging Impact on Organizational Vital Signs
To truly understand the success of change initiatives, one must look beyond the surface and delve into its impact on key business performance metrics. This involves a holistic examination of factors such as productivity, efficiency, and customer satisfaction (depending on what the changes are).
Productivity: Assessing the changes’ effects on productivity involves measuring the organization’s output and efficiency post-implementation. Has there been an increase in task completion rates, a reduction in errors, or an enhancement in overall workflow efficiency?
Efficiency: Changes often aim to streamline processes and enhance efficiency. Analyzing the efficiency metrics helps determine whether the new procedures or tools have resulted in a smoother and more effective workflow.
Customer Satisfaction: In many cases, change initiatives are driven by a desire to improve customer experience. Adoption analytics in this context involve gauging customer satisfaction levels, whether through surveys, feedback mechanisms, or other relevant indicators.
By examining these metrics, organizations can gauge the real impact of the change on their vital signs, ensuring that the intended improvements manifest in tangible and measurable ways.
2. Benefit Realization: From Anticipation to Tangible Outcomes
Anticipated benefits form the backbone of any change initiative, but true success lies in the tangible realization of these expected outcomes. Benefit realization assessment through adoption analytics involves tracking key performance indicators (KPIs) directly influenced by the change.
Tracking KPIs: Identify and monitor KPIs that are closely tied to the specific objectives of the change. These could include financial metrics, customer retention rates, employee engagement scores, or any other relevant indicators.
Tangible Outcomes: Work hand-in-hand with initiative benefit owners to ensure clear ownership and tracking of benefits. Establish a system that allows for the ongoing assessment of whether the anticipated benefits are being realized in practice.
Continuous Improvement: Benefit realization is an ongoing process. Regularly review and adjust strategies based on the data collected. This iterative approach ensures that the organization remains agile, adapting to changing circumstances and continuously optimizing the impact of the change.
Collaboration with Initiative Benefit Owners: A Crucial Element
A vital aspect of successful adoption analytics is collaboration with initiative benefit owners. These are individuals or teams responsible for overseeing the realization of anticipated benefits. Establishing clear ownership ensures accountability and facilitates a more targeted and effective approach to tracking and optimizing outcomes.
Clear Communication: Foster open lines of communication between change management teams and initiative benefit owners. Clearly communicate the expected benefits and collaborate on defining relevant metrics and tracking mechanisms.
Regular Check-Ins: Establish a framework for regular check-ins to assess progress, identify challenges, and strategize for ongoing success. These check-ins provide an opportunity to recalibrate efforts based on real-time insights.
Data-Driven Decision Making: Encourage initiative benefit owners to make data-driven decisions. Regularly review adoption analytics data together, and use these insights to inform strategic adjustments, ensuring that the organization is on a trajectory towards sustained success.
Adoption analytics are the linchpin in the journey from change initiation to sustainable integration. By meticulously measuring the impact on business performance and diligently tracking benefit realization, organizations can ensure that their transformative efforts result in lasting and meaningful change. Collaboration with initiative benefit owners enhances this process, fostering a culture of continuous improvement and adaptability that is crucial for navigating the ever-evolving landscape of organizational transformation.
Change practitioners may not be involved in all aspects of benefit realization and tracking. It could be that the focus is on ‘people’ and behaviour elements of changes that contribute to benefit realization. Incorporating these metrics into change management reports offers a comprehensive view of the change journey, from initial readiness to long-term adoption and benefits realization.
Crafting Compelling Change Management Reports
In the fast-paced world of change management, the ability to convey the impact of initiatives through well-crafted reports is a skill that cannot be underestimated. Executives require more than superficial metrics; they demand a nuanced understanding of how change aligns with strategic goals and influences organizational performance.
By steering clear of vanity metrics, activity-focused measurements, and overly cost-centric reporting, change management professionals can elevate their credibility and influence within the organization. Instead, a focus on change readiness, journey analytics, and adoption metrics provides a holistic perspective that resonates with executives, ensuring that the true value of change initiatives is accurately portrayed.
To gear up for the digital/AI-enabled world that we are already in, change practitioners should also be ready to adopt a range of digital tools to better present and converse about change management reports in a way that is interactive, and easy to generate data insights. Executives may ask a series of questions to probe deeper into the data, or want access themselves to be able to look into certain data points. The ability to answer these questions straight away using digital solutions will be the key to creating confidence, impact and trust with executives.
As organizations continue to navigate the complexities of change, the importance of insightful reporting cannot be overstated. It is not just about delivering change; it is about articulating its impact in a language that executives understand and appreciate. In doing so, change management professionals become not just implementers of change but strategic partners in driving organizational success. This is ultimately the goal for change teams and change practices.
