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.
The need for organizations to remain flexible and responsive to market demands has never been more critical, and scaled agile (SAFe) provide the framework to achieve this. Integrating change management work with SAFe is essential for seamless product delivery but yet is not clearly articulated in literature. However, for agile product delivery to be successful, it must be supported by robust change management work steps. Those that not ensures that all stakeholders are aligned and engaged throughout the process and also that the consecutive changes delivered are adopted. Let’s explore how change managers can effectively integrate their approaches with scaled agile methodologies to enhance product delivery.
Understanding the Intersection of Change Management and Agile
Change management and agile methodologies both aim to facilitate successful project outcomes, but they approach this goal from different angles. Change management focuses on the people side of change, ensuring that stakeholders are prepared, equipped, and supported throughout the transition through to benefit realisation. Agile methodologies, on the other hand, emphasize iterative development, continuous feedback, and rapid adaptation to change.
Whilst SAFe acknowledges the importance of managing the people side of change and leading the change, it does not spell out how exactly this work should be integrated with the methodology in a detailed manner. References to change tends to be at a high level and focuses on communication and readiness activities.
What are key call outs of the SAFe methodology:
1) Lean-Agile Principles: SAFe is grounded in Lean-Agile principles such as building incrementally with fast, integrated learning cycles, basing milestones on objective evaluation, and making value flow without interruptions. These principles help ensure continuous improvement and adaptability
2) Organizational Agility: To remain competitive, enterprises must be agile. SAFe enhances organizational agility by fostering Lean-thinking people and Agile teams, promoting strategic agility, and implementing Lean business operations
3) Lean Portfolio Management: Aligns strategy and execution by applying Lean and systems thinking. It includes strategy and investment funding, Agile portfolio operations, and Lean governance to ensure that the portfolio is aligned and funded to meet business goals
4) Continuous Learning Culture: Encourages a set of values and practices that promote ongoing learning and improvement. This culture is crucial for adapting to changes and fostering innovation within the organization
5) Agile Teams: Agile teams in SAFe operate using methods like SAFe Scrum or SAFe Team Kanban. These teams are responsible for understanding customer needs, planning their work, and delivering value continuously through iterative processes
6) Built-in Quality: Emphasizes the importance of quality at all stages of development. Practices include shift-left testing, peer reviews, and automation to ensure high standards and reduce defects early in the process
7) Value Stream Management (VSM): Focuses on optimizing the flow of value across the entire portfolio. VSM helps organizations improve their value delivery processes by managing and monitoring value streams effectively (Scaled Agile Framework).
8) Lean-Agile Leadership: Leaders play a critical role in fostering a Lean-Agile mindset. They must model the values and principles of SAFe, provide guidance, and create an environment that supports Agile teams and continuous improvement
9) Decentralized Decision-Making: Promotes faster value delivery by empowering teams to make decisions locally. This reduces delays, enhances product development flow, and fosters innovation
10) Customer-Centric Approach: Agile teams are encouraged to maintain close collaboration with customers to understand their needs better and ensure that solutions deliver real value. Techniques like direct customer interaction and feedback loops are essential
Below is a diagram from Scaled Agile Frameworks on key elements of a scaled agile product delivery framework.
Agile-Style Deliverable Artefacts
To support agile product delivery, change managers need to create agile-style deliverable artefacts early in the product delivery cycle. These artefacts serve as essential tools for aligning the team, stakeholders, and the overall change initiative with agile principles. They are significantly ‘lighter’ in volume and more succinct in focusing on key analysis points that determine approaches and actions required to plan and implement the change.
Change artefact 1: Change Canvas
An Agile Change Canvas is a strategic tool designed to plan, manage, and communicate change initiatives effectively within an organization. It begins with basic identification details such as the Project Name, Business Owner, and Author. This section ensures clear accountability and ownership from the outset.
The Change Vision & Objectives outlines the overarching goals and intended outcomes of the project. This vision acts as a guiding star, ensuring all actions align with the desired future state of the organization. Following this, Core Challenges are identified to highlight potential obstacles that could impede progress. Recognizing these challenges early allows for proactive mitigation strategies.
Stakeholder Impacts analyses how different stakeholders will be affected by the change. This includes assessing both the positive and negative impacts on employees, customers, and shareholders, ensuring that their concerns are addressed and their needs met.
The Key Milestones section, presented in a table format, outlines significant checkpoints in the project timeline. Each milestone is associated with a particular function, ensuring that progress is measurable and trackable. Similarly, the Resources section details the necessary financial, human, and technological resources required to implement the change, ensuring that the project is adequately supported.
Why Change section provides the rationale behind the need for change, which could include market demands, competitive pressures, or internal inefficiencies. This section justifies the project’s existence and urgency. Complementarily, What Will Change (WWC) describes the specific changes to be implemented, including processes, technologies, behaviours, and structures, offering a clear picture of the project’s scope.
Key Metrics are identified to measure the success of the change initiative. These metrics are both quantitative and qualitative, providing a comprehensive view of the project’s impact. Change Interventions listed in a table format, detail specific actions or initiatives designed to facilitate the change, ensuring a structured approach to implementation.
To foster a culture of innovation and adaptation, Change Experiments are proposed. These pilot programs test aspects of the change in a controlled environment before full-scale implementation. Finally, Change Risks identifies potential risks associated with the change and outlines strategies for mitigating these risks, ensuring that the project can navigate potential pitfalls effectively.
By incorporating these elements, the Agile Change Canvas provides a comprehensive framework for managing change initiatives, ensuring that all critical aspects are considered, planned for, and communicated effectively to stakeholders.
Using a Kanban board for change management activities provides a visual and dynamic method for tracking, prioritizing, and implementing changes. A Kanban board typically consists of columns that represent different stages of work, such as “To Do,” “In Progress,” and “Done.” For change management, additional columns might include “Proposed Changes,” “Under Review,” “Implementation Planning,” and “Monitoring.”
Whilst most change practitioners are used to kanban boards In working with various change management activities, there is opportunity to use kanban to plan and prioritise a series of agile-style changes and the associated change activities with each change. These ‘change cards’ within the kanban board presents a clear way to visualise a series of changes across the ‘delivery train’ where the project team continuously delivers pieces of change.
Prioritizing Change Management Activities
Visualizing Workflow:
Proposed Changes: This column lists all suggested changes, each represented by a card detailing the change’s purpose, impacted areas, and expected benefits.
Under Review: Changes move here once they are being evaluated for feasibility, risks, and alignment with project goals.
Implementation Planning: Approved changes are further detailed, including resource allocation, timelines, and specific tasks needed for implementation.
In Progress: Changes that are actively being worked on are tracked here, showing current status and any blockers encountered.
Monitoring: Recently implemented changes are monitored to ensure they are delivering the expected outcomes and to identify any issues early.
Done: Fully implemented and stabilized changes are moved here, marking their successful completion.
Setting Priorities:
Value and Impact: In conjunction with the project team prioritize changes based on their potential value and impact. High-value changes that significantly improve project outcomes or stakeholder satisfaction should be addressed first. From a change perspective, the input here is about the readiness of the stakeholder to receive the change, and what timing and work is required to get there.
Urgency and Dependencies: Changes that unblock other work or are time-sensitive should be prioritized. Dependencies between changes must be mapped to ensure logical sequencing. For example, work required to lift capability/leadership or readiness may be critical dependencies, without which the change cannot be delivered successfully.
Feasibility and Risk: Assess the feasibility and risks associated with each change. High-risk changes might require more careful planning and monitoring but should not necessarily be deprioritized if their impact is critical. The change input here is the people impact for the impacted stakeholders with other changes not just within this project/program, but with the overall portfolio or even outside the portfolio (including business-driven changes).
Ordering Change Planning and Implementation
Collaborative Planning:
Engage stakeholders and team members in planning sessions to discuss and agree on the priority of changes. This collaborative approach ensures that all perspectives are considered and that there is buy-in from those affected by the changes. This includes change champions.
Regular Review and Adaptation:
The Kanban board should be regularly reviewed and updated, within the change team and within the project team. During these reviews, re-prioritize changes based on new information, shifting project needs, and feedback from implemented changes. This iterative approach aligns with Agile principles of flexibility and continuous improvement.
Limit Work in Progress (WIP):
To avoid overloading the change team and ensure focus, limit the number of changes in progress at any given time. This constraint encourages the team to complete current tasks before taking on new ones, promoting a steady and manageable workflow.
Use Metrics and Feedback:
Utilize metrics such as cycle time (how long a change takes to move from start to finish, from awareness to engagement to eventual adoption) and work with the project team on the throughput (how many changes are completed in a specific timeframe) to assess the efficiency of the change management process. For example, based on the size and complexity of each discrete piece of change delivered, how long did this take and what was the deviance from actual time period planned? Feedback from these metrics should inform decisions about prioritization and process adjustments.
Benefits of Using Kanban for Change Management
Implementing a Kanban board for change management in Agile projects offers several benefits:
Transparency: Everyone involved can see the status of change activities, leading to better communication and coordination.
Flexibility: The board can be easily adjusted to reflect changing priorities and project dynamics.
Focus: Limiting WIP helps the team maintain focus and reduces the risk of burnout and task switching.
Continuous Improvement: Regular reviews and adaptations promote a culture of continuous improvement, ensuring that change management processes evolve and improve over time.
Change artefact example 3: Change Impact Assessment
A Change Impact Assessment (CIA) is an essential component in managing organizational change, particularly in agile projects where the focus is on iterative and incremental improvements. The assessment helps to understand the scope and magnitude of the change, identify affected stakeholders, and plan interventions to manage impacts effectively. An agile-friendly CIA is more summarised, and gets to the heart of what the impact is, who is impacted, how, to what extent, and when.
Below are the core elements of a change impact assessment, with a comparison to traditional methods:
1. Identifying the Impacts
Agile Approach: In scaled agile projects, the impact identification is ongoing and iterative. Each sprint or iteration is reviewed to assess the impacts of delivered changes. This dynamic approach ensures that emerging impacts are quickly recognized and addressed.
Traditional Approach: Impact identification is typically conducted at the beginning of the project, with periodic reviews. This method can be less responsive to new impacts discovered during the project lifecycle.
2. Stakeholder Identification and Analysis
Agile Approach: Continuous stakeholder engagement is crucial. Stakeholders are regularly consulted, and their feedback is integrated into the process. Agile methods ensure that stakeholders’ changing needs and concerns are promptly addressed.
Traditional Approach: Stakeholder analysis is often conducted early in the project, with limited ongoing engagement. This can result in less adaptability to stakeholders’ evolving requirements.
3. Extent and Nature of Impacts
Agile Approach: The extent of impacts is assessed incrementally, considering the cumulative effect of changes over multiple iterations. This allows for a nuanced understanding of how impacts evolve over time.
Traditional Approach: Typically focuses on a comprehensive initial assessment, with less emphasis on the evolution of impacts throughout the project.
4. Timing of Impacts
Agile Approach: Timing is aligned with the iterative delivery schedule. The impacts are mapped to specific iterations or sprints, allowing for precise planning and mitigation.
Traditional Approach: Timing is generally assessed at the project level, which can make it harder to pinpoint when specific impacts will occur during the project lifecycle.
Typical Sections of an Agile Change Impact Assessment
Impact Overview:
Explanation: Summarizes the nature and scope of the change, providing a high-level view of the anticipated impacts.
Agile Twist: Updated regularly with each iteration to reflect new findings and emerging impacts.
Stakeholder Impact Analysis:
Explanation: Identifies who will be affected by the change and how. It details the extent of the impact on different stakeholder groups.
Agile Twist: Involves continuous stakeholder feedback and updates to capture evolving impacts.
Impact Extent and Nature:
Explanation: Describes the extent (e.g., minor, moderate, significant) and nature (e.g., process, technology, cultural) of the impacts.
Agile Twist: Assessed incrementally, considering both immediate and long-term impacts across iterations.
Impact Timing:
Explanation: Specifies when the impacts are expected to occur, mapped to the project timeline.
Agile Twist: Aligned with sprint or iteration schedules, allowing for detailed timing predictions.
Mitigation Strategies:
Explanation: Outlines plans to manage and mitigate identified impacts.
Agile Twist: Adaptive strategies that are refined continuously based on iteration reviews and stakeholder feedback.
Monitoring and Review:
Explanation: Describes how the impacts will be monitored and reviewed throughout the project.
Agile Twist: Continuous monitoring with iteration-end reviews to ensure timely identification and management of impacts.
Stakeholder Engagement in a Scaled Agile Environment
Planning and designing stakeholder engagement activities in a scaled agile environment requires a dynamic, iterative approach that contrasts significantly with traditional, non-agile methods. In SAFe, the focus is on continuous collaboration, transparency, and adaptability, ensuring that stakeholders are actively involved throughout the project lifecycle.
Iterative and Continuous Engagement
Scaled Agile Approach: Stakeholder engagement is an ongoing process. Agile frameworks emphasize regular touchpoints, such as sprint reviews, planning meetings, and daily stand-ups, where stakeholders can provide feedback and stay informed about progress. These frequent interactions ensure that stakeholder input is continuously integrated, enabling swift adjustments and alignment with evolving needs. This iterative approach fosters a collaborative environment where stakeholders feel valued and engaged throughout the project. Engagement rhythms and processes should also be established not just at a project, but program, portfolio and enterprise levels as required.
Non-Agile Approach: Traditional methodologies often involve stakeholder engagement at fixed points in the project timeline, such as during initial requirements gathering, major milestone reviews, and final project delivery. This approach can lead to periods of limited communication and delayed feedback, which may result in misaligned expectations and missed opportunities for timely course corrections.
Flexibility and Adaptation
Scaled Agile Approach: Agile projects embrace change, allowing stakeholder engagement activities to be flexible and adaptive. As project requirements evolve, the engagement strategy can be adjusted to address new priorities or challenges. This flexibility ensures that stakeholder needs are consistently met, and any concerns are promptly addressed. Agile frameworks encourage a culture of openness and continuous improvement, where stakeholder feedback directly influences the direction of the project. Change managers need to ensure that stakeholder understand this fully, and have the skills to work within this context, not just with the project team but in leading their teams through change, when ‘the change’ may be constantly shifting.
Non-Agile Approach: In contrast, traditional approaches tend to follow a rigid engagement plan that is set at the project’s outset. While this provides a clear structure, it can be less responsive to changing stakeholder needs or external conditions. Adjusting the engagement strategy mid-project can be challenging and may require significant effort, leading to delays and potential dissatisfaction among stakeholders.
Collaborative Tools and Techniques
Scaled Agile Approach: Agile environments leverage a variety of collaborative tools and techniques to enhance stakeholder engagement. Digital platforms such as Jira, Confluence, and Miro facilitate real-time collaboration, transparency, and documentation. Agile ceremonies, such as retrospectives and demos, provide structured opportunities for stakeholders to participate and contribute. These tools and techniques help maintain a high level of engagement and ensure that stakeholders have a clear view of project progress and challenges.
Non-Agile Approach: Traditional methods might rely more heavily on formal documentation and periodic reports for stakeholder communication. While these methods ensure thorough documentation, they can sometimes create barriers to real-time collaboration and immediate feedback. Meetings and reviews are often scheduled infrequently, which can lead to less dynamic interaction compared to agile practices.
Planning Stakeholder Engagement Activities
Regular Touchpoints: Schedule frequent meetings and reviews to ensure continuous stakeholder involvement. Examples include sprint reviews, iteration planning meetings, and daily stand-ups. Business-led rhythm that enable the dissemination and engagement of updates to teams is also critical.
Flexible Engagement Plans: Develop engagement strategies that can be easily adapted based on stakeholder feedback and changing project requirements.
Use of Collaborative Tools: Implement digital tools that facilitate real-time collaboration and transparency. Tools like Jira and Confluence can help keep stakeholders informed and involved. Non-digital engagement tools may also be leveraged to fully engage with stakeholders, beyond one-way push communication. Assessment needs to be made of the openness and ability to engage regarding the change through the chosen channels.
Active Feedback Loops: Establish mechanisms for collecting and integrating stakeholder feedback continuously. This can be done through retrospectives, surveys, and informal check-ins.
Clear Communication Channels: Maintain open and clear communication channels to ensure that stakeholders can easily provide input and receive updates on project progress.
As mentioned previously, the change approach, including engagement approaches, need to take into account the broader organisational context of program, portfolio and enterprise levels. This may mean mapping out the various channels and how they can be used for different changes, stakeholders and organisational levels.
Supporting Agile Delivery Cadence
To align change management activities with agile delivery cadence, it’s essential to integrate them into the core agile events, such as PI (Program Increment) planning and demos. Here’s how:
PI Planning
Program Increment (PI) planning is a critical event in the agile framework, where teams come together to plan and commit to a set of objectives for the next increment. During PI planning sessions, ensure that change management considerations are part of the discussion. This involves:
– Including Change Management Objectives: Ensure that change management objectives are included in the PI planning agenda. This helps align the change activities with the overall delivery goals.
– Identifying Change Risks and Dependencies: Identify any dependencies related to the change initiative that may impact the delivery schedule. This ensures that potential risks are addressed early and do not disrupt the delivery process. Common considerations include the various people change impacts across the program and how they intersect or overlap
– Engaging Stakeholders: Involve key stakeholders in the PI planning sessions. This ensures that they understand the change objectives and are committed to supporting the change initiative. PI planning is also a great opportunity to assess and see in action the level of engagement, support and potential leadership skills of key stakeholders
Demos
Demos are an opportunity to showcase the progress of the agile teams and gather feedback from stakeholders. Use demos to communicate the benefits and progress of change initiatives. Engaging stakeholders in these demos can help them see the value and stay committed to the change. Here’s how:
– Highlighting Change Benefits: During demos, highlight the benefits of the change initiative and how it supports the overall product delivery goals. This helps stakeholders understand the value of the change and its impact on the project.
– Gathering Feedback: Use demos as an opportunity to gather feedback from stakeholders. This helps identify any concerns or areas for improvement and ensures that the change initiative remains aligned with stakeholder needs.
– Showcasing Progress: Showcase the progress of the change initiative during demos. This provides stakeholders with a clear understanding of how the change is evolving and the positive impact it is having on the project.
By embedding change management activities into these agile ceremonies, change managers can ensure that change initiatives are aligned with the delivery schedule and maintain stakeholder buy-in.
Implementing Change Activities as Small Experiments
One of the key principles of agile is to work in small increments and learn quickly. Change management activities can adopt this approach by implementing small experiments, such as:
Messaging
Test different communication messages to see which resonates best with stakeholders. Gather feedback and refine the messaging based on reactions. This iterative approach ensures that the communication strategy is effective and supports the change initiative. Consider the following:
– A/B Testing: Use A/B testing to evaluate different messages. This involves sending two variations of a message to different stakeholder groups and comparing the responses to determine which one is more effective.
– Feedback Collection: Collect feedback from stakeholders on the messaging. This can be done through surveys, focus groups, or informal conversations.
– Message Refinement: Refine the messaging based on the feedback received. This ensures that the communication remains relevant and impactful.
Stakeholder Involvement
Experiment with various levels of stakeholder involvement to determine the most effective way to engage them. Use these insights to inform future engagement strategies. Here’s how:
– Pilot Programs: Implement pilot programs with small groups of stakeholders to test different involvement strategies. This provides valuable insights into what works best and helps refine the engagement approach.
– Engagement Metrics: Track engagement metrics to evaluate the effectiveness of different involvement strategies. This includes participation rates, feedback quality, and overall stakeholder satisfaction.
– Iterative Adjustments: Make iterative adjustments to the involvement strategies based on the insights gained. This ensures that stakeholder engagement remains effective and aligned with the change initiative.
By treating change activities as experiments, change managers can adapt quickly to what works best, ensuring a smoother integration with the agile delivery process.
Best Practices for Integrating Change Management with Agile
Successfully integrating change management with agile methodologies requires a strategic approach. Here are some best practices to consider:
Foster Collaboration
Encourage collaboration between change managers and agile teams, as well as key business stakeholders. This helps ensure that different disciplines and functions are aligned and working towards the same goals. Consider the following strategies:
– Joint Planning Sessions: Conduct joint planning sessions to align change management activities with agile delivery approaches and schedules. This ensures that both disciplines are working towards the same objectives.
– Regular Communication: Establish regular communication channels between change managers and agile teams. This helps keep everyone informed and ensures that any issues or concerns are addressed promptly. Specifically focus on various agile roles such as UX (user experience), business analysis, testing, and portfolio management. There are key intersections of change work and each of these disciplines, beyond general project planning and coordination.
The below is an example of a portfolio level adoption dashboard from The Change Compass.
Change Data-Driven Insights is absolutely a Must-have for SAFe
In SAFe, change management driven by data insights is critical to ensure that changes are not only effective but also efficient and sustainable. Data-driven change management leverages quantitative and qualitative data to guide decisions, optimize processes, and align strategic goals across the organization. By incorporating metrics and analytics, organizations can gain a comprehensive understanding of the impact and progress of change initiatives, allowing for timely adjustments and informed decision-making.
At the portfolio level within a SAFe setting, data-driven insights are essential for prioritizing initiatives and allocating resources effectively. More than this, change data including stakeholder capability, readiness and impact levels can be critical to determine when releases should happen, the priority of releases, and the sequencing of releases.
Ill-prepared or insufficiently skilled stakeholders may require longer time to adapt to the change. Also, looking beyond the project itself, by understanding the overall change landscape for the impacted stakeholders, change releases may need to be chunked and packaged accordingly to maximise adoption success.
Key attention should also be paid to the impact on business performance of impacted stakeholders, not just from a change volume perspective, but also from a strategy perspective in terms of how best to reduce risk of performance disruptions. Is it through exemplary middle leadership? Or frontline engagement? Or the power of change champions embedded across the business?
At the enterprise level, data-driven change management enables organizations to scale agile practices consistently and coherently across multiple portfolios and teams. This involves the use of enterprise-level dashboards and analytics tools that provide a holistic view of the organization’s agile transformation. Key performance indicators (KPIs) such as employee impact data, adoption rates, readiness metrics and productivity metrics help leaders assess the effectiveness of change initiatives and identify areas that require additional support or intervention. For instance, tracking the adoption rate of agile practices across different departments can highlight areas where additional training or coaching is needed to ensure consistent implementation.
Integrating change management with scaled agile methodologies is essential for seamless product delivery in today’s dynamic business environment. By creating agile-style deliverable artefacts early, continuously adapting engagement activities, supporting agile delivery cadence, and implementing change activities as small experiments, measure change progress and outcomes, change managers can effectively support agile product delivery. This integration not only enhances the success of change initiatives but also ensures that product delivery is seamless and aligned with organizational goals.
By fostering collaboration, embracing agile principles, and using data-driven insights, change managers can create a cohesive strategy that maximizes the benefits of both change management and agile methodologies. This holistic approach ensures that change initiatives are successful, stakeholders are engaged, and product delivery is efficient and effective.
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.
Scaled Agile Framework (SAFe) has emerged as a leading methodology to address organisational change demands of fostering flexibility, collaboration, and continuous improvement. A cornerstone of SAFe is the principle of “Measure and Grow,” which emphasizes using data and fact-based decisions to enhance change outcomes over time. Despite its centrality, SAFe does not explicitly detail the change management components essential for its success. Here we outline how change management practitioners can effectively apply the “Measure and Grow” principle to lead change and improve outcomes to support the Scaled Agile environment.
The “Measure and Grow” Principle in Scaled Agile
“Measure and Grow” is integral to SAFe, focusing on systematic measurement and continuous improvement. By leveraging data and analytics, organizations can make informed decisions, identify areas needing attention, and iteratively enhance performance. For change management professionals, this principle translates into a structured approach to evaluate the effectiveness of change initiatives, pinpoint areas for improvement, and implement necessary adjustments.
In a Scaled Agile environment, “Measure and Grow” is a core tenant or principle that applies in all types of agile environments. By continuously assessing and refining change efforts, organizations can align their initiatives with strategic objectives, mitigate risks, and ensure sustained success.
In practice, a lot of organisations have not pinpointed exactly how change management measures can make or break the outcome of the change, and in a SAFe environment, across the program, portfolio as well as enterprise.
The ‘Measure and Grow’ principle as a core part of SAFe (From Scaled Agile Framework)
Key Elements of Measuring and Growing Change Outcomes
To operationalize the “Measure and Grow” principle in change management, it is crucial to establish a set of metrics and assessment frameworks. Here are some broad categories of different types of change measurements that are relevant. Note that since we are talking about SAFe, it is not just at the initiative level that we are talking about metrics. More importantly, it is about establishing a system to promote change improvement across the organisation.
Change Management KPIs and OKRs
Key Performance Indicators (KPIs) and Objectives and Key Results (OKRs) are essential tools for tracking the success of change management initiatives. KPIs provide quantitative measures of performance, while OKRs align change efforts with broader organizational goals. A change management stream or function should focus on establishing KPIs or OKRs to achieve laser focus on achieving change outcomes.
Examples of Initiative-Level Change Management KPIs that may roll out to form portfolio views
Employee Engagement Levels: This KPI assesses how change impacts employee morale and engagement, providing insight into the overall acceptance and support of the change initiative.
Learning Achievement Rates: This can include tracking the percentage of employees who have completed necessary training programs, as well as achieving the target level of competence to ensure that the workforce is adequately prepared for the change.
Feedback Scores: Collecting feedback from stakeholders through surveys or feedback forms helps gauge perception and identify areas needing improvement. It is important to note that depending on the change context, stakeholders may not be happy with the content of the change. However, understanding and tracking this perception is still important.
Change Adoption Rate: This KPI measures the percentage of stakeholders who have adopted the change. High adoption rates are the ultimate goal for initiatives.
Issue Resolution Time: Measuring the time taken to resolve user-related issues related to the change highlights the efficiency of support mechanisms and the responsiveness of the change management team. This is especially important during an agile environment where there may be constant changes.
Change Readiness and Stakeholder Engagement Metrics
Evaluating change readiness and stakeholder engagement is crucial to the success of any change initiative. These metrics help assess the organization’s preparedness for change and the level of involvement and support from key stakeholders. Readiness and engagement rates can also roll up at a portfolio level to provide oversight.
Change Readiness Metrics
Readiness Assessments: Conduct surveys or interviews to gauge the organization’s preparedness for the impending change. This can include evaluating awareness, understanding, and acceptance of the change.
Resource Availability: Measure the availability of necessary resources, such as budget, personnel, and tools, to support the change initiative.
Communication Effectiveness: Assess the clarity, frequency, and effectiveness of communication regarding the change to ensure stakeholders are well-informed and engaged.
Stakeholder Engagement Metrics
Engagement Scores: Use surveys or feedback forms to measure the engagement levels of stakeholders, indicating their commitment and support for the change.
Participation Rates: Track stakeholder participation in change-related activities, such as workshops, meetings, and training sessions, to gauge their involvement.
Influence and Support: Assess the influence and support of key stakeholders in driving the change, ensuring that influential figures are actively endorsing the initiative.
By monitoring these metrics, change management professionals can identify potential barriers to change and take proactive steps to enhance readiness and engagement.
Stakeholder Competency Assessment
Successful change initiatives rely on the competence and readiness of key stakeholders. Assessing stakeholder competency involves evaluating the capability of sponsors and change champions to support and drive the change.
Sponsor Readiness/Capability Assessment
Sponsor Engagement: Measure the level of engagement and commitment from sponsors, ensuring they are actively involved and supportive of the change.
Decision-Making Effectiveness: Assess the ability of sponsors to make timely and effective decisions that facilitate the change process.
Resource Allocation: Evaluate the sponsor’s ability to allocate necessary resources, such as budget and personnel, to support the change initiative.
Change Champion Capability Assessment
Training and Knowledge: Measure the knowledge and training levels of change champions to ensure they are well-equipped to support the change.
Communication Skills: Assess the ability of change champions to effectively communicate the change message and address stakeholder concerns.
Influence and Leadership: Evaluate the influence and leadership capabilities of change champions, ensuring they can effectively drive and sustain the change.
By conducting these assessments, change management professionals can ensure that key stakeholders are prepared and capable of supporting the change initiative.
Change Adoption Metrics
Change adoption metrics provide insight into how well the change has been accepted and integrated into the organization. These metrics help assess the effectiveness of the change initiative and identify areas for improvement. At a portfolio level, there may be different levels of change adoption set for different initiatives depending on priority and complexity.
Key Change Adoption Metrics
Adoption Rate: Measure the percentage of stakeholders who have adopted the change, indicating the overall acceptance and integration of the new processes or systems.
Usage Metrics: Track the usage of new tools, processes, or systems introduced by the change to ensure they are being utilized as intended.
Performance Metrics: Assess the impact of the change on key performance indicators, such as productivity, efficiency, and quality, to determine the overall success of the change initiative.
By monitoring these metrics, change management professionals can gauge the success of the change initiative and identify opportunities for further improvement. To read more about change adoption metrics check out The Comprehensive Guide to Change Management Metrics for Adoption.
Change Impact and Capacity Metrics
Understanding the impact of change and the organization’s capacity to manage it is crucial for successful change management. Change impact metrics assess the effects of the change on the organization, while capacity metrics evaluate the organization’s ability to manage and sustain the change.
Change Impact Metrics
Aggregate impacts: Aggregate impacts across initiatives to form a view of how various teams and roles are impacted by various changes.
Risk Assessments: Identify potential risks associated with the change and evaluate their impact, ensuring that mitigation strategies are in place. A particular focus should be placed on business performance during change, across initiatives.
Capacity Metrics
Resource Capacity: Assess the availability of resources, such as personnel, budget, and tools, to support the change initiative.
Change Fatigue: Measure the risk for potential fatigue within the organization and its impact on stakeholders, ensuring that change initiatives are paced and driven appropriately.
Support Structures: Evaluate the effectiveness of support structures, such as training programs, information hubs, and help desks, in facilitating the change. Support structures may also include change champion networks.
By assessing change impact and capacity, change management practitioners can ensure that the organization is well-equipped to manage and sustain the change initiative.
Change Maturity Assessment
Change maturity assessments provide a comprehensive evaluation of the organization’s capability to manage change effectively. These assessments help identify strengths and weaknesses in the organization’s change management practices and provide a roadmap for improvement.
The Change Management Institute (CMI) Change Maturity Model is a comprehensive framework that takes a holistic approach to enhancing an organization’s change management maturity. It’s divided into three core functional domains, each playing a vital role in the overall journey toward maturity:
Project Change Management
Business Change Readiness
Strategic Change Leadership.
These domains serve as the foundation for achieving higher levels of maturity within the organization.
Within each of these domains, the CMI model outlines a structured path, consisting of five distinct maturity levels. These levels represent a continuum, starting at Level 1, which serves as the foundational stage, and progressing all the way to Level 5, the zenith of maturity and effectiveness. This multi-tiered approach offers organizations a clear roadmap for growth and development, ensuring that they have the tools and insights necessary to navigate the complexities of change management.
By conducting regular change maturity assessments, change management professionals can identify areas for improvement and develop targeted strategies to enhance the organization’s change management capability.
The “Measure and Grow” principle is a powerful tool for improving change outcomes in a Scaled Agile environment. By leveraging data and fact-based decision-making, change management professionals can ensure that change initiatives are effective, aligned with strategic objectives, and continuously improving. Establishing robust metrics and assessment frameworks, such as KPIs, OKRs, change readiness and stakeholder engagement metrics, stakeholder competency assessments, change adoption metrics, change impact and capacity metrics, and change maturity assessments, is essential to applying the “Measure and Grow” principle effectively.
Incorporating these metrics and assessments into change management practices enables organizations to identify areas for improvement, make informed decisions, and drive continuous improvement. By doing so, change management professionals can enhance the effectiveness of change initiatives, ensure successful adoption, and ultimately achieve better business outcomes.
