Change management and clinical psychology, while seemingly distinct disciplines, share a foundational principle: both are focused on people and their ability to adapt, grow, and thrive through transitions. Change managers navigate organizational transformation, helping individuals and groups adjust to new realities, while clinical psychologists support individuals in addressing psychological challenges and fostering mental wellness. By exploring the practices of clinical psychologists, change managers can adopt a more evidence-based, empathetic, and tailored approach to managing change.
We delve into how clinical psychologists approach their work, highlighting principles and practices that can inform and enhance change management strategies.
Clinical Psychology: An Evidence-Based Practice
At its core, clinical psychology is deeply rooted in science. Clinical psychologists rely on evidence-based methods to understand, assess, and treat psychological issues. Their approach includes:
Assessment through Observation and Interviews
Clinical psychologists begin by observing symptoms and conducting detailed interviews to gain insights into an individual’s mental health. They evaluate not only the reported symptoms but also environmental and contextual factors influencing the individual’s well-being. This comprehensive assessment forms the basis for understanding the person’s unique situation.
Tailored Treatment Plans
Clinical psychologists craft individualized treatment plans based on their assessments. These plans are not static; they evolve based on the individual’s progress, feedback, and emerging needs. By constantly monitoring outcomes, they ensure the approach remains effective and relevant.
Cognitive-Behavioural Strategies
Cognitive-behavioural therapy (CBT) is a cornerstone of clinical psychology. It operates on two levels:
Cognitive: Addressing and reshaping unhelpful thought patterns that influence emotions and behaviours.
Behavioural: Directly targeting behaviours to create positive changes in day-to-day functioning.
These principles provide a structured yet flexible framework for guiding individuals toward improved mental health and well-being.
Parallels Between Clinical Psychology and Change Management
Change management, like clinical psychology, requires a nuanced understanding of human behaviour and a strategic approach to fostering adaptation. Here are key parallels and insights that change managers can draw from clinical psychology:
1. Evidence-Based Assessments
In organizational settings, change managers must assess the current state to identify potential challenges and opportunities. Borrowing from clinical psychology, they can develop a more scientific approach by:
Conducting interviews and surveys to understand employee concerns, resistance, and expectations.
Observing team dynamics and organizational culture to identify systemic barriers to change.
Analyzing environmental factors, such as stakeholder needs, organisational cultural traits and industry factors.
This evidence-based diagnostic process allows change managers to pinpoint issues with precision, ensuring their interventions are well-informed and targeted.
2. Tailored Change Strategies
Just as clinical psychologists create personalized treatment plans, change managers should design strategies tailored to their organization’s specific needs. This involves:
Recognizing that one-size-fits-all approaches rarely succeed in complex organizational ecosystems.
Customizing interventions based on the unique characteristics of teams, departments, and leadership styles.
Adapting strategies dynamically as new challenges arise or as feedback is gathered during implementation.
For example, a department struggling with resistance to new technology may require hands-on coaching and reassurance, while another may benefit more from open forums for dialogue and feedback.
3. Focus on Cognitive and Behavioural Dimensions
Cognitive-behavioural strategies in clinical psychology offer valuable insights for managing change.
Cognitive Aspect:
Change often triggers fear, uncertainty, and doubt. By addressing these thought patterns, change managers can help individuals reframe their perspectives. For example:
Communicating the benefits of change in clear, relatable terms to counteract negative assumptions. Position the change in a way that helps to inspire people and encourage them to come onboard the change process
Offering opportunities for employees to voice their concerns, fostering a sense of control and participation.
Behavioural Aspect:
Behavioural change is essential for successful adaptation. Change managers can:
Encourage new behaviours through positive reinforcement, such as recognition programs. Other methods include leader or champion role modelling, measurement and feedback.
Provide practical tools and resources to help employees adopt new processes or technologies.
By targeting both cognition and behaviour, change managers can facilitate deeper, more sustainable transformations.
Applying Clinical Psychology Principles in Change Management
To effectively integrate the principles of clinical psychology into change management, practitioners should consider the following actionable steps:
Step 1: Conduct a Holistic Assessment
Use diagnostic tools such as stakeholder analysis, employee sentiment surveys, and readiness assessments to gather comprehensive data.
Identify key influencers, potential resistors, and systemic issues that may impact the change effort.
Step 2: Develop a Personalized Approaches
Segment stakeholders based on their unique needs, roles, and levels of impact. Use personas where helpful to gain deeper sense of preferences, challenges and needs.
Design interventions that align with these segments. For example, senior leaders may require coaching on communication strategies, while frontline employees might benefit from hands-on workshops.
Step 3: Monitor and Adjust Strategies
Implement feedback loops to track progress and outcomes.
Use data analytics and qualitative feedback to tweak strategies as needed. For instance, if resistance persists, additional engagement sessions, leader encouragement or communication campaigns might be warranted.
Step 4: Foster Constructive Cognition
Encourage employees to view change as an opportunity for growth rather than a threat. Using a cognitive behavioural approach, ‘constructive self-talk’ can be utilised to be positioned as communication phrases (as well as leader or change champion talking guides) and positioning to influence how employees think about the change. Positive behaviours should also be acknowledged, role modelled and reinforced by leaders.
E.g. Rather than employees feeling like “here is another change that we need to go through that will mean we are busier and need to work longer”, use communication phrases such as “we are making it easier for our customers” or “we are contributing to reducing the complexity through this new process” at a level that targeted employee groups can connect to.
Share success stories and celebrate small wins to build momentum and confidence.
Step 5: Prioritize Emotional Well-Being
Recognize the emotional toll that significant change can take. Identifying the emotions that employee groups are feeling is the first step (as distinct from what they are thinking or saying). Offer resources such as coaching, change champion or peer support groups, or group workshops. Equip leaders with the skills to provide empathetic support to their teams.
Also, take holistic approach to look at the change environment for impacted stakeholders and assess the change loading can reveal potential risks in people capacity challenges that could derail the change.
Case Study: Clinical Psychology-Inspired Change Management
Consider an organization undergoing a major digital transformation. Employees are required to adopt new technologies, shift workflows, and learn new skills. Resistance is high, with many expressing anxiety and frustration.
Step 1: Assessment
A series of focus groups and surveys reveal that employees feel unprepared and fear obsolescence. Leaders recognize a culture of risk aversion and limited digital literacy.
Step 2: Tailored Strategy
Based on these insights, the change management team implements a phased approach:
Cognitive: Town halls and internal campaigns highlight the long-term benefits of digital transformation, such as enhanced job security and efficiency.
Behavioural: Practical workshops and mentoring programs are introduced to build digital skills incrementally.
Step 3: Monitoring and Adaptation
As the rollout progresses, feedback indicates a need for additional hands-on support. The team introduces digital “help desks” and assigns technology champions in each department.
Step 4: Celebrating Wins
Early adopters are recognized through an internal awards program, creating positive reinforcement for desired behaviours.
The result? A smoother transition, increased adoption rates, and improved employee confidence in navigating the change.
Challenges and Considerations
While clinical psychology offers valuable lessons, change managers must adapt these principles to fit organizational contexts. Key considerations include:
Balancing individual and collective needs. While clinical psychology focuses on individuals, change management must address both individual and group dynamics.
Recognizing limitations in time and resources. Unlike therapy, organizational change often operates within tight deadlines and budgets.
Navigating power dynamics and politics inherent in organizational settings.
By being mindful of these challenges, change managers can apply clinical psychology principles effectively and pragmatically.
The synergy between clinical psychology and change management offers a powerful toolkit for navigating the complexities of human behaviour during change. By adopting evidence-based assessments, tailoring strategies, and leveraging cognitive-behavioural insights, change managers can foster more effective and sustainable transformations. Ultimately, integrating these principles enhances not only the success of change initiatives but also the well-being of the individuals and teams at their core.
Change adoption is the heart of every change practitioner’s work. It’s the primary measure of whether a change initiative truly succeeds, yet, surprisingly, many organizations still fail to adequately track, measure, and manage change adoption. Without a clear understanding of how well end-users are adopting the change, it’s nearly impossible to gauge the initiative’s real impact on the business. Change adoption must be both intentional and managed, not just assumed.
If you search for change adoption on Google the top articles seem to refer to the same things. These include transition preparation, communication, training and support. The top 2 articles are by Whatif and Walkme and seem to emphasise the importance of in-app training products they offer. The Prosci article emphasise the ADKAR model on the other hand.
While common strategies for change adoption—such as communication, training, and support—are essential, these are foundational steps and not the complete formula for sustained adoption. There’s a nuanced spectrum of factors that contribute to adoption, including the type of change, the stakeholders, the organization’s capacity for change, measurement metrics, and performance management. The following insights explore these core factors and share practical strategies, bolstered by real-world examples, to help change practitioners improve adoption rates across their organizations.
1. Understanding the Type of Change
The nature of the change plays a significant role in determining how to drive adoption. A change can range from a simple update in process to a fundamental shift in behaviour, and this range requires different approaches:
– Simple Changes : Minor changes, like a new software feature or a small process tweak, may only need a basic communication update. For instance, consider an HR team implementing a new self-service portal for employees to access their pay stubs. In this case, a simple email announcement explaining how to access the feature, along with a short tutorial video, might be all that’s required to ensure adoption.
– Complex, Behavioural Changes : For more complex changes that impact behaviours or workflows, adoption strategies need to be more involved. Imagine an organization implementing a new performance review system that shifts from annual reviews to ongoing, quarterly feedback sessions. This type of change isn’t just procedural—it demands a shift in how employees and managers think about performance. Here, communication alone won’t be sufficient. It requires ongoing training, leadership modeling, reinforcement through feedback loops, and alignment with performance metrics. Regular team meetings can serve as a platform for leaders to showcase the change, while role-playing sessions can help embed the new behaviours.
Analogy : Think of the change type as similar to cooking different dishes. For a quick salad, all you need is the right ingredients and a bowl to toss them in. For a complex dish like a soufflé, you’ll need precise measurements, specific tools, and careful monitoring to ensure it doesn’t collapse. The type of change similarly determines the level of preparation and intervention required.
2. Tailoring Strategies to Stakeholder Types
Understanding your end-users or stakeholders—those directly impacted by the change—is crucial. Each group will have different engagement channels and needs, which means you can’t rely on a one-size-fits-all communication plan. To drive adoption, you need to deliver information in ways that resonate with each audience.
– Identify Effective Channels : For example, one team may prefer to discuss updates in weekly meetings, while another may respond better to monthly town hall sessions. When a global retail company rolled out a new inventory management system, the change team customized its communication and training by region. Regional managers were empowered to communicate the changes in a way that suited their teams’ preferences, whether that meant team huddles, newsletters, or one-on-one conversations. As a result, the change was embraced much more readily because each team felt that the approach was tailored to their needs.
– Build Change into Routine Communication : To make the change part of the team’s daily workflow, leverage existing channels, like monthly business reviews or quarterly updates. For instance, if sales teams have weekly performance meetings, consider incorporating brief updates about how the change (such as a new CRM feature) can benefit their sales process, along with success stories from team members.
Analogy : Think of stakeholder engagement as similar to hosting a dinner party. You wouldn’t serve the same meal to every guest without considering their preferences. Similarly, change practitioners need to “serve” the change in ways that appeal to each stakeholder group’s tastes and communication preferences.
3. Aligning with Organisational Change Capacity
Change capacity—the organization’s ability to absorb and adopt change—is a critical but often overlooked factor. The timing of introducing new changes matters, especially when the change is complex. If an organization is already handling multiple projects or transformations, adding another initiative can result in resistance or “change fatigue.”
– Manage Competing Priorities : Suppose a financial services company is simultaneously upgrading its internal software, launching a new customer-facing app, and implementing a data security compliance initiative. Launching yet another change, like a new employee recognition program, may overwhelm employees, who may deprioritize it in favour of what they perceive as more urgent projects. Change practitioners should work closely with program managers to prioritize initiatives and strategically phase them to avoid saturation.
– Change Portfolio Management : Treat change initiatives as part of a portfolio. By actively managing this portfolio, you can ensure changes are introduced in waves that the organization can absorb. Regularly review the status of active changes with stakeholders to reassess the capacity and timing. This way, your adoption efforts won’t be diluted by other competing projects.
Analogy : Imagine trying to load groceries into an already-full refrigerator. Some items will fit, but others might have to wait. The same concept applies to organizational change capacity—only so much can fit into the organization’s “refrigerator” at once before things start falling out.
4. Defining and Measuring Adoption Metrics
Effective change adoption strategies hinge on clear metrics. Without defined adoption goals and measurement tools, it’s difficult to determine if users are actually embracing the change or merely checking boxes. Metrics will vary depending on the change and should be relevant to the behaviours or outcomes desired.
– Set Clear Adoption Metrics : For example, a company introducing a new collaborative software might measure adoption through the frequency of use, the number of shared documents, or the volume of cross-departmental activity within the platform. Each of these metrics helps track actual usage and determine if employees are using the tool to its full potential.
– Gauge Awareness, Willingness, and Competency : Assess and understand stakeholder readiness for the change at hand. Do they have the awareness, motivation and know-how for the new expected behaviours? Conduct regular surveys or feedback sessions to assess where teams are on the adoption curve. This approach can highlight areas where additional support is needed, such as more coaching or stronger reinforcement from leadership.
Analogy : Think of adoption metrics like the gauges in a car’s dashboard. Each gauge (speed, fuel, engine temperature) provides specific insights into the car’s overall performance, just as adoption metrics give insights into how well a change is taking hold within the organization.
5. Ongoing Performance Management for Sustained Adoption
Adoption isn’t a “one and done” effort. It requires continuous management, monitoring, and, ideally, integration into performance management. By tracking and reinforcing adoption metrics over time, organizations can keep the change front and centre and drive deeper, lasting adoption.
– Incorporate Adoption into KPIs : Align adoption goals with KPIs to maintain visibility. For example, if the goal is to increase the use of a project management tool, set a KPI that tracks project updates within the tool. Managers can be held accountable for meeting this KPI, incentivizing their teams to incorporate the tool into their workflow.
– Regular Check-Ins and Feedback: Use data-driven insights to adjust your strategy as needed. For instance, if certain teams lag in adoption rates, consider arranging tailored training sessions or conducting one-on-one interviews to understand the barriers they’re experiencing. Continuous feedback loops allow change practitioners to refine their approach based on real-time adoption data. Performance needs to be constantly nurtured, reinforced and managed. No ‘set and forget’ approach will work.
Analogy: Sustaining adoption is like maintaining a healthy habit. Just as regular exercise requires motivation, tracking, and routine check-ins to stay consistent, ongoing performance management helps ensure that change remains a part of the organizational fabric.
Data as the Catalyst for Improved Change Adoption
Data-driven insights are game-changers for change adoption. They enable change practitioners to move beyond guesswork and implement strategies with measurable, predictable results. By leveraging analytics, organizations can identify successful tactics based on stakeholder type, change type, and historical adoption patterns.
For example, by analyzing adoption data from previous projects, a technology company could discover that smaller, incremental training sessions worked better for developers than day-long sessions. This insight could inform future adoption strategies and improve the likelihood of success for similar changes.
Utilizing data to understand what drives adoption allows change practitioners to apply these learnings across the organization, achieving more consistent and reliable outcomes. Through correlation and prediction, organizations can anticipate which approaches will work best for each type of change and tailor their strategies accordingly.
This is exactly what we’ve been doing at The Change Compass. We’ve incorporated automation and AI to provide data insights that tell you what tactics and approaches work to maximise change adoption based on data. You can also drill into what works for particular stakeholders, business units and types of changes. Data insights can also inform what volume of change may stifle change adoption.
Designing change approach and interventions should not be guess work. So far, companies try to enhance their rates of change adoption success by hiring change management specialists, together with stakeholder feedback. However, the most senior stakeholder or those with the loudest voice in the room don’t always get the outcome. These are still based on opinions, versus what has proven to work based on data. Imagine the power of implementing this across the enterprise and the ability to avoid costly mistakes and mishaps in the tens (or hundreds) of millions of investments in change initiatives per annum.
Building a Culture of Adoption
Improving change adoption is not a one-time effort but an ongoing, intentional process that combines targeted communication, stakeholder engagement, capacity planning, performance tracking, and data-driven insights. By focusing on the unique aspects of each change, tailoring strategies to specific stakeholder groups, and continuously managing performance, change practitioners can significantly increase adoption rates. Ultimately, success lies in building a culture where change is not just accepted but actively integrated into the organization’s DNA.
When change adoption becomes a measurable, manageable, and data-driven process, practitioners can guide their organizations through change with confidence and clarity, transforming resistance into resilience and integration into innovation.
Change management practitioners are often tasked with ensuring that transitions are smooth and successful. However, to truly excel in this role, it’s crucial to embrace a systems thinking approach—an understanding that organisations are complex, interconnected systems where every change can create ripple effects throughout. One of the most potent tools for fostering systems thinking is the use of change data within change portfolio management. Here, we will focus on how change data can build interconnectedness across the organisation, enhance the management of change initiatives, and ultimately improve business results.
Understanding Systems Thinking
The below are some of the core principles in Systems Thinking and how they may be applied to change portfolio management through data and analysis.
Principle 1: Interconnectedness
At the core of systems thinking is the principle of interconnectedness. Organisations are not merely a collection of individual parts; rather, they consist of various components that interact in complex ways. When change is initiated in one area, it can have unintended consequences in another. For instance, a change in the sales strategy might impact customer service processes, employee motivation, and even supply chain operations. By recognising these interconnected relationships, practitioners can make more informed decisions that take the broader organisational context into account.
In fact, change impact assessment is the process of identifying and ascertaining the linkages across the system. With each change, the various impacts across different processes, people working to support those processes and the systems involved in the processes.
Principle 2: Feedback Loops
Another fundamental aspect of systems thinking is the identification and understanding of feedback loops. These loops can be either reinforcing (positive) or balancing (negative). A reinforcing feedback loop occurs when a change in one part of the system leads to further changes in the same direction, creating a cycle of growth or enhancement. For example, an increase in employee training may lead to improved performance, which in turn boosts morale and reduces turnover, further enhancing overall productivity.
Conversely, balancing feedback loops act to stabilize the system. They can dampen the effects of change, preventing extremes from occurring. Recognising these feedback mechanisms allows practitioners to leverage positive feedback loops to enhance desired outcomes while being vigilant against the negative loops that may emerge, which could undermine the change initiatives.
Here is an example of a feedback loop –
Goal: Prevent stagnation or failure by adjusting strategies based on real-time feedback.
Use case: Ensuring that deviations or resistance are managed effectively to keep the change on track.
How it works:
Collect data from employee surveys, performance metrics, and feedback sessions to understand what’s working or not.
Identify points of resistance and take corrective actions (e.g., additional training or clarifying leadership vision).
Example: If employees express frustration with new tools, gather input and refine the rollout to address concerns.
What are key benefits of feedback loops?
Increased adaptability: Ensures the organisation can react to unforeseen challenges during implementation.
Engaged workforce: Employees feel more involved when they see their feedback incorporated into the process.
Sustainable change: Continuous feedback ensures that change efforts stay relevant, preventing them from losing momentum or being abandoned.
Principle 3: Causality
Systems thinking also emphasizes understanding causality—how different components of the organisation influence one another. This perspective is vital in change management, as it shifts the focus from merely addressing symptoms of problems to exploring their root causes. This can be applied throughout the change lifecycle ranging from understanding the impacts across the organisation, through to anticipating resistance and motivation levels to support the change.
Here is an example of applying the principle of causality in systems thinking
Change Initiative: Implementing a New KPI-Based Evaluation System
Initial Cause: Leaders decide to replace the existing subjective performance reviews with measurable KPIs to improve accountability.
Direct Effect: Employees shift their focus to achieving their KPIs.
This change seems positive—employees now have clear, measurable targets to meet.
Ripple Effects Across the System:
Short-term unintended outcome: Employees may begin to focus only on achieving their KPIs, ignoring tasks that are not directly rewarded, such as collaboration or innovation.
Behavioural impact: Some employees might feel micromanaged or disengaged if they view the new system as rigid or unfair.
Team dynamics: Competitive behaviour between employees could increase, reducing collaboration and creating silos.
Long-term Causal Feedback:
Lower collaboration can negatively affect innovation and employee morale, leading to attrition of high performers.
A balancing feedback loop emerges when HR notices a decline in collaboration scores and recommends revising KPIs to include teamwork-related metrics.
Principle 4: Holistic Perspective
Adopting a holistic perspective is crucial in systems thinking. Instead of viewing the organisation as a set of isolated parts, practitioners should consider the organisation as a dynamic whole. This approach enables better problem-solving and decision-making by considering all relevant factors and their interactions. A holistic view facilitates a deeper understanding of how changes in one area may impact others, ultimately leading to more sustainable and effective change initiatives.
For example, An organisation is running several parallel initiatives under a broader digital transformation effort, including:
CRM System Implementation
Agile Ways of Working Initiative
Cloud Migration for Core IT Systems
Employee Upskilling Program on Digital Tools
Application of Holistic Perspective
Identifying Interdependencies
The CRM system needs to integrate with both legacy IT infrastructure and future cloud platforms.
The agile transformation affects how teams work, influencing the success of the CRM project and cloud migration by demanding faster collaboration cycles.
The upskilling program needs to ensure employees are trained not only in new digital tools but also on agile practices and cloud-based platforms.
Avoiding Initiative Silos
Without a holistic view, each project might focus only on its own goals, causing schedule conflicts (e.g., IT resources are overbooked for the cloud migration and CRM deployment).
Teams might experience change fatigue if initiatives are rolled out simultaneously without coordination. For example, employees may struggle to participate in the upskilling program while also meeting deadlines for the agile rollout.
Portfolio-Level Governance and Prioritization
Using a holistic lens, the portfolio management team can sequence projects logically. For example:
First: Migrate critical systems to the cloud to ensure the CRM implementation has a stable foundation.
Second: Begin the agile transformation to align working methods before launching cross-functional CRM initiatives.
Third: Schedule employee upskilling to ensure readiness before key milestones in the CRM and cloud projects.
Optimizing Resources and Reducing Risks
Viewing the portfolio holistically allows management to optimize resource allocation (e.g., sharing skilled IT personnel across cloud and CRM projects efficiently).
By aligning initiatives, the company mitigates the risk of conflicting efforts and reduces change fatigue through coordinated communication and engagement plans.
Principle 4: Emergence
Finally, the concept of emergence in systems thinking highlights how complex behaviours can arise from simple interactions among components. The principle of emergence in systems thinking refers to the idea that when individual elements interact, new patterns or behaviours emerge that were not predictable by examining the parts alone. In change portfolio management, this means that the outcomes of managing multiple change initiatives may be different—often more complex or unexpected—than the sum of each individual change project. Emergent behaviours can create both opportunities and risks.
Scenario: Managing a Sustainability Transformation Portfolio
A large organisation launches several interconnected initiatives to become a more sustainable enterprise:
Carbon Reduction Initiative – Shift to renewable energy and reduce emissions.
Sustainable Supply Chain Project – Engage suppliers on environmental standards.
Green Product Innovation Program – Develop eco-friendly products.
Employee Engagement Initiative – Promote green behaviours among employees.
Application of Emergence
Unexpected Synergies Emerge
Employees participating in the engagement initiative start identifying operational inefficiencies, such as excess waste, leading to additional cost savings.
The green product innovation program creates a culture of experimentation that spills over into other departments, resulting in improved collaboration and faster innovation cycles across the organisation, beyond sustainability-focused efforts.
Emergent Risks and Complex Interactions
Suppliers struggling to meet new sustainability requirements may delay the sustainable supply chain project, impacting both product launches and company operations.
Employees feel overwhelmed by the number of sustainability programs and resist further change, creating unexpected resistance that spreads to unrelated initiatives, such as digital transformation efforts.
New Opportunities Emerge from Interactions
As cross-functional teams work together, new business models emerge. For example, sales and product teams discover that green products appeal to a new customer segment, leading to revenue growth opportunities not originally anticipated in the change portfolio plan.
Collaborations with suppliers in the supply chain project uncover the potential for joint ventures focused on sustainable technology.
It may not be possible to forecast or anticipate all types of employee behaviours and reactions to new changes introduced. However, engaging your stakeholders and involving them in the change process may help you identify these in advance.
The Role of Change Data in Building Systems-Thinking Within Change Portfolio Management
Change portfolio management involves overseeing a collection of change initiatives and ensuring that they align with the organisation’s strategic objectives. The integration of change data into this process can significantly enhance systems thinking capabilities.
Creating a Data-Driven Culture
One of the first steps in leveraging change data is to establish a data-driven culture. Practitioners should promote the importance of data in decision-making processes across the organisation. By providing visibility of the changes that are upcoming, they can empower employees at all levels to utilize change data in their daily work. This cultural shift fosters an environment where data becomes a common language, allowing for clearer communication about changes and their potential impacts. However, do note that different type of employees may require different type of data.
Mapping Change Initiatives
Using change data, organisations can create visual maps of their change initiatives. These maps can illustrate how different initiatives are interconnected and highlight the dependencies between them. For example, a visual representation can show how a new software implementation relies on training programs or how changes in one department may impact others. By visualizing these relationships, practitioners can better assess the potential ripple effects of changes and make more informed decisions.
Monitoring and Analysing Feedback Loops
By actively monitoring change data, organisations can identify and analyse feedback loops in real-time. This ongoing analysis allows practitioners to quickly respond to emerging trends or unintended consequences. For instance, if data shows a decline in employee productivity following a process change, practitioners can investigate and implement corrective actions before the situation worsens. By understanding these feedback loops, organisations can not only react to changes but also proactively shape their outcomes.
Causal Analysis
Incorporating change data into causal analysis enables organisations to identify the root causes of issues. Practitioners can use data analytics to explore the relationships between different components of the organisation, leading to a clearer understanding of how changes impact various outcomes. This data-driven approach allows for more targeted interventions, ensuring that efforts are directed towards addressing the underlying issues rather than merely treating surface-level symptoms.
Holistic Change Portfolio Assessment
When practitioners evaluate their change portfolio, they should adopt a holistic approach that considers the interplay between various initiatives. By analysing change data in aggregate, organisations can identify patterns and trends that may not be visible when examining initiatives in isolation. This holistic assessment allows practitioners to prioritise initiatives that align with broader organisational goals, ultimately leading to more effective change management.
Fostering Collaborative Environments
Change data can also be a catalyst for fostering collaborative environments. By sharing insights and findings from change initiatives, organisations can create a culture of collaboration where teams learn from one another’s experiences. This exchange of information can lead to emergent solutions that drive innovation and improve change outcomes. Additionally, collaborative tools and platforms can be leveraged to facilitate communication and knowledge sharing across departments.
Building Connectedness Across the Organisation
The integration of change data into change portfolio management fosters interconnectedness within the organisation. By emphasising the importance of data and encouraging collaboration, practitioners can create a more cohesive organisational culture that embraces change.
Enhancing Communication
Clear communication is essential for effective change management. Change data provides a foundation for transparent communication about initiatives and their impacts. Practitioners can use data visualizations and reports to communicate progress, challenges, and successes, fostering a sense of shared understanding across the organisation.
Breaking Down Silos
Change data can also help break down silos within the organisation. By sharing data and insights across departments, practitioners can encourage collaboration and foster a sense of unity. This interconnectedness enhances problem-solving capabilities, as diverse teams bring different perspectives to the table, leading to more innovative solutions. Issues may be pre-empted if stakeholders can pick up on impacts that may be missed for example.
Aligning Goals and Objectives
When change initiatives are informed by change data, it becomes easier to align goals and objectives across the organisation. Practitioners can use data to ensure that all initiatives are working towards the same strategic objectives, reducing the likelihood of conflicting priorities. This alignment creates a more focused approach to change management, ultimately leading to improved business results.
Improving Business Results Through Systems Thinking
The application of systems thinking through change data in change portfolio management can lead to substantial improvements in business results. By fostering interconnectedness, enhancing communication, and breaking down silos, organisations can create a more agile and responsive environment.
Increased Agility
Organisations that embrace systems thinking and utilize change data are better equipped to respond to changes in the external environment. By understanding the interconnectedness of their initiatives, practitioners can pivot quickly in response to emerging trends or challenges. This agility is essential in today’s fast-paced business landscape.
Enhanced Employee Engagement
When employees see their work as part of a larger, interconnected system, they are more likely to feel engaged and motivated. By involving employees in the change process and using data to demonstrate the impact of their contributions, organisations can foster a sense of ownership and commitment to change initiatives.
Improved Decision-Making
Systems thinking promotes better decision-making by encouraging practitioners to consider the broader context of their actions. When decisions are informed by change data, organisations can identify potential consequences and make choices that align with their strategic goals. This improved decision-making ultimately leads to more successful change outcomes.
Sustainable Change Initiatives
Finally, the application of systems thinking and change data can lead to more sustainable change initiatives. By focusing on root causes, leveraging feedback loops, and fostering collaboration, organisations can implement changes that are not only effective in the short term but also sustainable over time. This sustainability is crucial for long-term business success.
Change data is a powerful lever that change management practitioners can use to foster systems thinking within their organisations. By recognising the interconnectedness of change initiatives, understanding feedback loops, exploring causality, adopting a holistic perspective, and nurturing environments for emergence, organisations can improve their approach to change management. Through these efforts, practitioners can build connectedness across the organisation, ultimately enhancing how change is managed and driving improved business results. Embracing systems thinking in change portfolio management is not just a best practice; it’s a necessity for organisations seeking to thrive in an ever-evolving business landscape.
Change managers are not just facilitators of change transition; they are strategic partners who must understand and navigate complex organisational landscapes. One key skill that is often under-emphasised in this role is analytical capability. By adopting a strategic consultant’s mindset and employing robust analytical skills, change managers can significantly enhance their effectiveness throughout the project lifecycle. Let’s explore how change managers can leverage analytical skills at each phase of the project lifecycle, emphasising frameworks like MECE and TOSCA to drive successful change initiatives.
The Importance of an Analytical Lens
Change management involves facilitating transitions while ensuring that stakeholders are engaged and informed. However, to do this effectively, change managers must analyse complex data sets, identify patterns, and make informed decisions based on evidence. This analytical lens can be applied through every stage of the project lifecycle: commencement, planning, execution, monitoring, and closure.
Gone are the days when change practitioners are making recommendations ‘from experience’ or based on stakeholder input or feedback. For complex transformation, stakeholders now (especially senior stakeholders) demand a more rigorous, data-driven approach to drive toward solid change outcomes.
1. Project Commencement Phase
At the project commencement phase, the groundwork is laid for the entire change initiative. Change managers need to scan the organizational environment through the lens of impacted stakeholders, gathering relevant information and data.
Example: Consider a company planning to implement a new customer relationship management (CRM) system. The change manager should begin by analysing the existing state of customer interactions, assessing how the change will impact various departments such as sales, marketing, and customer service. This involves conducting stakeholder interviews, reviewing existing performance metrics, and gathering feedback from employees.
Using a MECE (Mutually Exclusive, Collectively Exhaustive) framework, the change manager can categorize stakeholder concerns into distinct groups—such as operational efficiency, user experience, and integration with existing systems—ensuring that all relevant factors are considered. By identifying these categories, the change manager can articulate a clear vision and define the desired end state that resonates with all stakeholders.
The above is from Caseinterview.com
Hypothesis: Sales Team Will Resist the New CRM System Due to Lack of Training and User-Friendliness
Step 1: Identify the Hypothesis
Hypothesis: The sales team will resist the new CRM system because they believe it is not user-friendly and they fear insufficient training.
Step 2: Break Down the Hypothesis into MECE Categories
To validate this hypothesis, we’ll break it down into specific categories that are mutually exclusive and collectively exhaustive. We’ll analyse the reasons behind the resistance in detail.
Categories:
User Experience Issues
Complexity of the Interface
Navigation Difficulties
Feature Overload
Training and Support Concerns
Insufficient Training Programs
Lack of Resources for Ongoing Support
Variability in Learning Styles
Change Management Resistance
Fear of Change in Workflow
Previous Negative Experiences with Technology
Concerns About Impact on Performance Metrics
Step 3: Gather Data for Each Category
Next, we need to collect data for each category to understand the underlying reasons and validate or refute our hypothesis.
Category 1: User Experience Issues
Data Collection:
Conduct usability testing sessions with sales team members.
Administer a survey focusing on user interface preferences and pain points.
Expected Findings:
High rates of confusion navigating the new interface.
Feedback indicating that certain features are not intuitive.
Category 2: Training and Support Concerns
Data Collection:
Survey the sales team about their current training needs and preferences.
Review existing training materials and resources provided.
Expected Findings:
Many team members express a need for more hands-on training sessions.
A lack of available resources for ongoing support after the initial rollout.
Category 3: Change Management Resistance
Data Collection:
Conduct focus groups to discuss fears and concerns regarding the new system.
Analyse historical data on previous technology implementations and employee feedback.
Expected Findings:
Employees voice concerns about how the CRM will change their current workflows.
Negative sentiments stemming from past technology rollouts that were poorly managed.
Step 4: Analyse Data Within Each Category
Now that we have gathered the data, let’s analyse the findings within each MECE category.
Analysis of Findings:
User Experience Issues:
Complexity of the Interface: Usability tests reveal that 70% of sales team members struggle to complete certain tasks in the CRM.
Navigation Difficulties: Survey responses show that 80% find one step of the navigation counterintuitive, leading to frustration.
Training and Support Concerns:
Insufficient Training Programs: Surveys indicate that only 40% of employees feel adequately trained to use this part of the new system.
Lack of Resources for Ongoing Support: Focus groups reveal that team members are unsure where to seek help after the initial training.
Change Management Resistance:
Fear of Change in Workflow: Focus group discussions highlight that 60% of participants fear their productivity will decrease with the new system, at least during the post Go Live period.
Previous Negative Experiences: Historical data shows that past technology rollouts had mediocre adoption rates due to insufficient support, reinforcing current fears.
Step 5: Develop Actionable Recommendations
Based on the analysis of each category, we can create targeted recommendations to address the concerns raised.
Recommendations:
User Experience Issues:
Conduct additional usability testing with iterative feedback loops to refine the CRM interface before full rollout.
Simplify the navigation structure based on user feedback, focusing on the most frequently used features.
Training and Support Concerns:
Develop a comprehensive training program that includes hands-on workshops, tutorials, and easy-to-access online resources.
Establish a dedicated support team to provide ongoing assistance, ensuring team members know whom to contact with questions.
Change Management Resistance:
Implement a change management strategy that includes regular communication about the benefits of the new system, addressing fears and expectations.
Share success stories from pilot programs or early adopters to demonstrate positive outcomes from using the CRM.
By following this detailed step-by-step analysis using the MECE framework, the change manager can thoroughly investigate the hypothesis regarding the sales team’s resistance to the new CRM system. This structured approach ensures that all relevant factors are considered, enabling the development of targeted strategies that address the specific concerns of stakeholders. Ultimately, this increases the likelihood of successful change adoption and enhances overall organizational effectiveness.
Data-Driven Decision Making:
At this stage, change managers should work closely with the project sponsor and project manager to determine effective positioning. A data-driven approach allows the change manager to form a hypothesis about how the change will impact stakeholders. For instance, if data suggests that the sales team is particularly resistant to change, the manager might hypothesize that this resistance stems from a lack of understanding about how the new CRM will enhance their workflow.
2. Planning Phase
Once the project is initiated, the planning phase requires detailed strategy development. Here, analytical skills are essential for conducting stakeholder analysis and impact assessments.
Example: In our CRM implementation scenario, the change manager must analyse the data collected during the commencement phase to identify the specific impacts on different departments. This involves grouping and sorting the data to prioritize which departments require more extensive support during the transition.
Using the TOSCA (Target, Objectives, Strategy, Constraints, Actions) framework provides a structured approach to guide the change management process for the CRM implementation. This framework helps clarify the overall vision and specific steps needed to achieve successful adoption. Below is a detailed exploration of each component:
1. Target
Definition: The target is the overarching goal of the change initiative, articulating the desired end state that the organization aims to achieve.
Application in CRM Implementation:
Target: Improve customer satisfaction and sales efficiency.
This target encapsulates the broader vision for the CRM system. By focusing on enhancing customer satisfaction, the organization aims to create better experiences for clients, which is crucial for retention and loyalty. Improving sales efficiency implies streamlining processes that enable sales teams to work more effectively, allowing them to close deals faster and serve customers better.
2. Objectives
Definition: Objectives are specific, measurable outcomes that the organization intends to achieve within a defined timeframe.
Application in CRM Implementation:
Objectives: Increase customer retention by 20% within a year.
This objective provides a clear metric for success, enabling the organization to track progress over time. By setting a 20% increase in customer retention as a target, the change manager can align training, support, engagement and system adoption with this goal. This objective also allows for measurable evaluation of the CRM’s impact on customer relationships and retention efforts.
3. Strategy
Definition: The strategy outlines the high-level approach the organization will take to achieve the objectives. It serves as a roadmap for implementation.
Application in CRM Implementation:
Strategy: Implement phased training sessions for each department, with tailored support based on the unique impacts identified.
This strategy emphasizes a thoughtful and structured approach to training, recognizing that different departments may face distinct challenges and needs when adapting to the new CRM. By rolling out training in phases, the organization can focus on one department at a time, ensuring that each team receives the specific support they require. Tailoring the training content based on the unique impacts identified earlier in the MECE analysis helps maximize engagement and effectiveness, addressing concerns about usability and fostering greater adoption of the CRM.
4. Constraints
Definition: Constraints are the limitations or challenges that may impact the successful implementation of the strategy. Recognizing these upfront allows for better planning and risk management.
Application in CRM Implementation:
Constraints: Limited budget and time restrictions.
Acknowledging these constraints is critical for the change manager. A limited budget may affect the types of training resources that can be utilized, such as hiring external trainers or investing in advanced learning technologies. Time restrictions might necessitate a more rapid rollout of the CRM system, which could impact the depth of training provided. By recognizing these constraints, the change manager can plan more effectively and prioritize key areas that will deliver the most value within the available resources.
5. Actions
Definition: Actions are the specific steps that will be taken to implement the strategy and achieve the objectives.
Application in CRM Implementation:
Actions: Develop a communication plan that includes regular updates and feedback mechanisms.
This action focuses on the importance of communication throughout the change process. A well-structured communication plan ensures that all stakeholders, particularly the sales team, are kept informed about the implementation timeline, training opportunities, and how their feedback will be incorporated into the process. Regular updates foster transparency and help build trust, while feedback mechanisms (such as surveys or suggestion boxes) allow team members to voice concerns and share their experiences. This two-way communication is essential for addressing issues promptly and reinforcing a culture of collaboration and continuous improvement.
By applying these frameworks, change managers can make informed recommendations that align with organizational objectives. This structured approach helps ensure that all relevant factors are accounted for and that stakeholders feel included in the planning process.
3. Execution Phase
As the project moves into the execution phase, the change manager must remain agile, continually collecting organizational data to confirm or reject the hypotheses formed during the planning stage.
Example: In an agile setting, where iterative processes are key, the change manager should implement mechanisms for ongoing feedback. For instance, after each sprint of CRM implementation, the manager can gather data from users to assess how well the system is being received. Surveys, usage analytics, and focus groups can provide rich insights into user experiences and pain points.
This ongoing data collection allows change managers to adjust their strategies in real-time. If feedback indicates that certain features of the CRM are causing confusion, the change manager can pivot to provide additional training or resources targeted specifically at those areas. This iterative feedback loop is akin to the work of strategic consultants, who continuously assess and refine their approaches based on empirical evidence.
Example in Practice: Imagine a situation where the sales team reports difficulties with the new CRM interface, leading to decreased productivity. The change manager can analyse usage data and user feedback to pinpoint specific issues. This data-driven insight can guide the development of targeted training sessions focusing on the problematic features, thus addressing concerns proactively and fostering user adoption.
4. Monitoring Phase
Monitoring the change initiative is crucial for ensuring long-term success. Change managers need to analyse performance metrics to evaluate the effectiveness of the implementation and its impact on the organization.
Example: For the CRM project, key performance indicators (KPIs) such as sales conversion rates, customer satisfaction scores, and employee engagement levels should be monitored. By employing data visualization tools, change managers can easily communicate these metrics to stakeholders, making it clear how the change initiative is progressing.
A fact-based approach to analysing these metrics helps in making informed decisions about any necessary adjustments. If, for instance, customer satisfaction scores are declining despite an increase in sales, the change manager may need to investigate further. This might involve conducting interviews with customers or analysing customer feedback to identify specific areas for improvement.
Suppose the organization observes a drop in customer satisfaction scores following the CRM implementation. The change manager could work with other stakeholders to conduct a root cause analysis using customer feedback and service interaction data to identify patterns, such as longer response times or unresolved issues. By addressing these specific problems, the change manager can refine the CRM processes and enhance overall service quality.
5. Closure Phase
The closure phase involves reflecting on the outcomes of the change initiative and drawing lessons for future projects. This is where the analytical skills of change managers can shine in assessing the overall impact of the change.
Example: After the CRM system has been fully implemented, the change manager should conduct a comprehensive review of the project along with the project team (retro). This involves analysing both qualitative and quantitative data to evaluate whether the initial objectives were met. Surveys can be distributed to employees to gather feedback on their experiences, while sales data can be analysed to determine the financial impact of the new system.
Using frameworks like MECE can help in categorizing the lessons learned. For instance, feedback could be sorted into categories such as user experience, operational efficiency, and overall satisfaction, allowing the change manager to develop clear recommendations for future initiatives.
Lessons Learned: If the analysis shows that certain departments adapted more successfully than others, the change manager could investigate the factors contributing to this variance. For example, departments that received more personalized support and training may have demonstrated higher adoption rates. This insight can inform strategies for future change initiatives, emphasizing the importance of tailored support based on departmental needs.
Building Relationships with Senior Leaders
In addition to the technical aspects of change management, the ability to communicate effectively with senior leaders is crucial. Seasoned change managers must clearly understand organizational objectives and be able to articulate how the change initiative contributes to these goals.
Example: During discussions with senior leadership, a change manager along with the rest of the project team can present data showing how the CRM system has improved customer retention rates and increased sales. By positioning this information in an easily understandable and rigorous manner, the change manager demonstrates the value of the initiative and its alignment with broader organizational objectives.
Effective communication ensures that leaders remain engaged and supportive throughout the change process, increasing the likelihood of success. By continuously linking the change initiative to organizational goals, change managers can build trust and credibility with stakeholders at all levels.
Leveraging Analytical Frameworks
Throughout the project lifecycle, incorporating structured analytical frameworks can enhance the decision-making process. Here are two key frameworks that change managers can leverage:
MECE Framework
MECE (Mutually Exclusive, Collectively Exhaustive) helps in breaking down complex information into manageable parts without overlap. By ensuring that all categories are covered without redundancy, change managers can identify all relevant factors affecting the change initiative.
TOSCA Framework
TOSCA (Target, Objectives, Strategy, Constraints, Actions) provides a comprehensive roadmap for change initiatives. By clearly defining each component, change managers can develop coherent strategies that align with organizational goals. This framework not only clarifies the change strategy but also ensures that all team members understand their roles in achieving the objectives.
Continuous Learning and Adaptation
Change management is not a static process; it requires continuous learning and adaptation. As organizations evolve, change managers must stay attuned to emerging trends and best practices in the field. This involves seeking feedback, conducting post-project evaluations, and staying updated on analytical tools and methodologies.
Change managers can attend workshops, participate in industry conferences, and engage with professional networks to enhance their analytical skills and learn from peers. By sharing experiences and insights, change managers can refine their approaches and incorporate new strategies that drive successful change.
The Transformative Power of Analytical Skills
The role of a change manager is multifaceted and requires a broad range of skills. However, one skill that stands out as particularly critical is the ability to think analytically. By adopting a strategic consultant’s mindset and applying analytical skills at each phase of the project lifecycle, change managers can significantly enhance their effectiveness.
From project commencement to closure, employing frameworks like MECE and TOSCA allows change managers to approach challenges in a structured way, making informed decisions that drive successful change. Continuous data collection, stakeholder engagement, and effective communication with senior leaders are essential components of this analytical approach.
In an era where organizations must adapt quickly to change, the ability to analyse complex data sets and derive actionable insights will distinguish successful change managers from the rest. Emphasizing this critical skill not only positions change managers as strategic partners within their organizations but also ensures that change initiatives lead to lasting, positive transformations.
As change practitioners, let us elevate our analytical capabilities and drive impactful change with confidence and clarity. By embracing this essential skill, we can navigate the complexities of organizational change and lead our teams toward a successful future.
Measuring change adoption is one of the most important parts of the work of change practitioners. It is the ultimate ‘proof’ of whether the change interventions have been successful or not in achieving the initiative objectives. It is also an important way in which the progress of change management can clearly be shown to the project team as well as to various stakeholder groups. The ability to show clearly the progress of change outcome is critical to focus your stakeholders’ actions on the right areas. It is one of the key ways to ‘prove your worth’ as a change practitioner.
Measurement takes time, focus and effort. It may not be something that is a quick exercise. There needs to be precise data measurement design, a reliable way of collecting data, and data visualisation that is easily understood by stakeholders.
With the right measurements of change adoption, you can influence the direction of the initiative, create impetus amongst senior stakeholders, and steer the organisation toward a common goal to realise the change objectives. Such is the power of measuring change adoption.
The myth of the change management curve
One of the most popular graphs in change management and often referred as the ‘change curve’ is the Kubler-Ross model. The model was specifically designed by psychiatrist Elisabeth Kubler-Ross to refer to terminally ill patients as a part of the book ‘On Death and Dying’. For whatever reason, it has somehow gained popularity and application in change management. Therefore, be very careful when using applying this model in a change context.
There is little research evidence to back this up even in psychological research. When applied in change management there is no known research that supports this at all. So be careful when you come across models such as this one that is simple and seem intuitively ‘correct’. On the other hand, there is ample research by McKinsey that for effectively managed initiatives and transformations, stakeholders do not go through this ‘valley of death’ journey at all.
If the ‘change curve’ is not the correct chart to follow with regard to change adoption, then what is the right one to refer to? Good question.
The ‘S’ curve of change adoption is one that can be referenced. It is well backed in terms of research from technology and new product adoption. It begins with a typically slow start followed by a significant climb in adoption followed by a flattened level at the end. Most users typically do not uptake the change until later on.
Here is an example of key technologies and the speed of adoption in U.S. households since the 1900s.
Source: HBR.org
With the different types of change contexts, the shape of the S curve will be expected to differ as a result. For example, you are working on a fairly minor process change where there is not a big leap in going from the current process to the new process. In this case, the curve would be expected to be a lot more gentle since the complexity of the change is significantly less than adopting a complex, new technology.
On the other hand, if you are working on many iterative agile changes, each iteration that impacts users may be a small S curve in themselves. Ideally, each iteration work together towards a greater piece of overarching change.
Going beyond what is typically measured
Most change practitioners are focused on measuring the easier and more obvious measures such as stakeholder perceptions, change readiness, and training completion. Whilst these are of value, they in themselves are only measuring certain aspects of the change. They can be viewed as forward-looking indications of the progress that supports moving toward eventual change adoption, versus the eventual change adoption.
To really address head-on the topic of measuring adoption, it is critical to go beyond these initial measures toward those elements that indicate the actual change in the organisation. Depending on the type of change this could be system usage, behaviour change, following a new process or achieving cost savings targets.
Project Benefit realization
It goes without saying that to really measure change adoption the change practitioner must work closely with the project manager to understand in detail the benefits targeted, and how the prescribed benefits will be measured. The project manager could utilise a range of ways to articulate the benefits of the project. Common benefit categories include:
Business success factors such as financial targets on revenue or cost
Product integration measures such as usage rate
Market objectives such as revenue target, user base, etc.
These categories above are objectives that are easier to measure and tangible to quantify. However, there could also be less tangible targets such as:
Competitive positioning
Employee relations
Employee experience
Product or solution leadership
Employee capability
Customer experience
There could be various economic methods of determining the targeted benefit objectives. These include payback time or the length of time from project initiation until the cumulative cash flow becomes positive, or net present value, or internal rate of return.
The critical aspect for change practitioners is to understand what the benefit objectives are, how benefit tracking will be measured and to interpret what steps are required to get there. These steps include any change management steps required to get from the current state to the future state.
Here is an example of a mapping of change management steps required in different benefit targets:
Project benefits targeted
Likely change management steps required
Change management measures
Increased customer satisfaction and improved productivity through implementing a new system.
Users able to operate the new system. Users able to improve customer conversations leveraging new system features. Users proactively use the new system features to drive improved customer conversations. Managers coaching and provide feedback to usersBenefit tracking and communications. Customer communication about improved system and processes Decreased customer call waiting time .
% of users passed training test. System feature usage rate. Customer issue resolution time. User feedback on manager coaching. Monthly benefit tracking shared and discussed in team meetings. Customer satisfaction rate. Customer call volume handling capacity.
Measuring behavioural change
For most change initiatives, there is an element of behaviour change, especially for more complex changes. Whether the change involves a system implementation, changing a process or launching a new product, behaviour change is involved. In a system implementation context, the behaviour may be different ways of operating the system in performing their roles. For a process change, there may be different operating steps which need to take place that defers from the previous steps. The focus on behaviour change aims to zoom in on core behaviours that need to change to lead to the initiative outcome being achieved.
How do we identify these behaviours in a meaningful way so that they can be identified, described, modelled, and measured?
The following are tips for identifying the right behaviours to measure:
Behaviours should be observable. They are not thoughts or attitudes, so behaviours need to be observable by others
Aim to target the right level of behaviour. Behaviours should not be so minute that they are too tedious to measure, e.g. click a button in a system. They also should not be so broad that it is hard to measure them overall, e.g. proactively understand customer concerns vs. what is more tangible such as asked questions about customer needs in XXX areas during customer interactions.
Behaviours are usually exhibited after some kind of ‘trigger’, for example, when the customer agent hear certain words such as ‘not happy’ or ‘would like to report’ from the customer that they may need to treat this as a customer complaint by following the new customer complaint process. Identifying these triggers will help you measure those behaviours.
Achieve a balance by not measuring too many behaviours since this will create additional work for the project team. However, ensure a sufficient number of behaviours are measured to assess benefit realisation
Measuring micro-behaviours
Behaviour change can seem over-encompassing and elusive. However, it may not need to be this. Rather than focusing on a wide set of behaviours that may take a significant period of time to sift, focusing on ‘micro-behaviours’ can be more practical and measurable. Micro-behaviours are simply small observable behaviours that are small step-stone behaviours vs a cluster of behaviours.
For example, a typical behaviour change for customer service reps may be to improve customer experience or to establish customer rapport. However, breaking these broad behaviours down into small specific behaviours may be much easier to target and achieve results.
For example, micro-behaviours to improve customer rapport may include:
User the customer’s name, “Is it OK if I call you Michelle?”
Build initial rapport, “How has your day been?”
Reflect on the customer’s feeling, “I’m hearing that it must have been frustrating”
Agree on next steps, “would it help if I escalate this issue for you?”
Each of these micro-behaviours may be measured using call-listening ratings and may either be a yes/no or a rating based assessment.
After having designed the right measurement to measure your change adoption, the next step would be to design the right reporting process. Key considerations in planning and executing on the reporting process includes:
Ease of reporting, you should aim to automate where possible to reduce the overhead burden and manual work involved. Whenever feasible leverage automation tools to move fast and not be bogged down by tedious work
Build expectations on contribution to measurement. Rally your stakeholder support so that it is clear the data contribution required to measure and track change adoption
Design eye-catching and easy to understand dashboard of change adoption metrics.
Design reinforcing mechanisms. If your measurement requires people’s input, ensure you design the right reinforcing mechanisms to ensure you get the data you are seeking for. Human nature is so that whenever possible, people would err on the side of not contributing to a survey unless there are explicit consequences of not filling out the survey.
Recipients of change adoption measurement. Think about the distribution list of those who should receive the measurement tracking. This includes not just those who are in charge of realising the benefits (i.e. business leaders), but also those who contribute to the adoption process, e.g. middle or first-line managers.
Example of change adoption dashboard from Change Automator
Measuring Adoption Across Initiatives
You may be driving multiple initiatives as a part of a large program or a portfolio of initiatives. The key challenge here is to establish common adoption measures that are apple-to-apple metrics comparisons across initiatives. Yes, each initiatives will most likely have different sets of what constitutes adoption. However, there are still common ways to report on adoption across initiatives such as overall percentage of adoption of identified adoption elements, or percentage of the number of milestones reached. You can also utilise manager reports of behaviours adopted, as well as system records of utilisation of certain features for example.
Understanding change adoption is not only helpful to understand what works for one initiative, it can also be a linchpin to help you scale change adoption across change initiatives across your whole portfolio. Talk to us to find out more about how The Change Compass can help you understand what change interventions leads to higher change adoption rates, through data. Using a data-led approach in deciphering what drives change adoption can truly drive successful change outcomes.
Feeling a bit lost and would like to have a chat about how to measure adoption by utilising digital solutions? Contact us here.
