Right now I am writing this article from a Four Seasons resort in Hawaii after having 3 flights cancelled in a row. It has been quite a stressful experience as you can imagine and it’s the fourth day of delay. I’m not able to get back home! However, this started to get me thinking about the change experience for the employee or the customer. As change drivers or leaders we tend to focus on how to design the change at a program level and it’s rare for us to really get down to the lowest level of people experience and how this is perceived at a humanistic level throughout the change process.
In the past I’ve used the airport analogy to describe the change journey and how we work to design each of the elements of the whole ecosystem, including pre-departure, transit, in-flight experience, runway preparation and post-landing experience. To read more about each of these elements refer to this article on Landing multiple changes in a complex environment.
Now let’s take a look at my recent bad flight experience and you will see that this easily translates to a typical change experience for those impacted. My first flight was cancelled, and after several hours all passengers were feeling frustrated, wondering what was really going on, and when or if the flight will take off. The announcement did not provide any substantive information and so as a result each passenger had to queue up to ask for further information. This is similar to a restructuring announcement or other major changes whereby there is a generic corporate email sent to all impacted, however the information is so generic that employees will need to resort to their managers (or rumours) to get further information that will meet their individual needs.
For the managers, they often don’t receive the right information or it is insufficiently tailored so that they are not able to translate the organisational level impact to how their specific department or team will be impacted. This could be due to lack of information or skill set in translating the impact for their teams. To this end, we need to ensure we engage with those managers to ensure that their questions are answered and that they’re able to field employe questions, versus having no information.
Part of a good change experience is in anticipating any reactions, feelings and designing an effective process that tackles these head on. To do this, use a human-centred design approach of observation, interviewing, analysing precious incidents and basically adopt a human-centred mindset to pick out key experience insights that need to be addressed. To read more about the human-centred design process please click here.
So what can we learn from the bad pre-departure experience when applied to change?
1. Provide managers and leaders with sufficient information so that they are able to engage with and consult with their impacted employees to ensure that their needs are met, including gathering new ideas from them.
2. Conduct a detailed analysis from an end-user perspective to pre-determine potential humanistic needs and reactions and address these head-on. For example, What types of information are needed to reach the ultimate goal? What are potential employee questions? How do we provide them with effective engagement prior to them asking for it?
3. Proactive engagement to manage potentially negative feelings. Being on the receiving end of a flight cancellation or a successful change initiative is often frustrating and stressful. How do we anticipate these experiences to redesign it into a more positive one? For example, are there certain employee groups we can garner to be change champions to provide additional people support and foster resilience? What artefacts can we provide to shape these experiences? Visually-catching cheat sheets, posters, branded sweets, morning-tea, and effective social media communication, etc.
4. Involve all layers of management so that they are well-equipped to support the change management process and are clear with their role in the process. Are we simply asking them to be on-hand to answer questions? Or do we expect certain layers of management to be change coaches to guide first-line managers on how to lead change and foster a culture of continuous improvement through hard work? What are we asking our Human Resources colleagues to be doing? Or our Risk partners or Finance partners? Be explicit about what specific behaviours and outcomes we are asking for.
5. Empathy. When people are frustrated, feeling vulnerable or stressed, the most important thing to do to address their feelings is to acknowledge and address these feelings by showing empathy. After all we are dealing with people’s emotions. Emotions are not logical and therefore data and facts usually do not create empathy. Empathy is between two individuals. One person showing another person that their feelings are valid, acknowledged and supported. Empathy is best demonstrated through verbal or nonverbal behaviours rather than through emails and online information. This is about a leader or another colleague showing genuine acknowledgement that a fellow colleague feels a certain way, without providing any judgment or even advice. During one of the days when the flight was cancelled, a staff walked around and chatted to everyone in the queue to just listen to them and acknowledge their frustrations – this did more good than anything else the airline did.
6. Create an element of surprise in designing the change process. Most corporate change processes are similar in that they follow a set way of engaging with employees according to the corporate norm of what has worked in the past. However, there are some organizations that keep following norms and do not create a good change experience and keep repeating the same mistakes over a long time. I’m sure we have all experienced this J. For example, it could be a new way for a senior leader walking the floor to connect with impacted employees and stakeholders during the change process, or corporate artefacts that were not anticipated and could be perceived in a positive light.
7. Appealing to the senses. A lot of people remember sensory information more than data or facts. How do we leverage this to create the overall experience? Retail stores often dispense aromatherapy scents to create and environment or calm or excitement depending on the desired experience. Visual information is also important to create the right imagery so that employees can visualise the light at the end of the tunnel and be inspired to go through the tunnel. One can design visual images that help employee remember themes, or analogies that are easily understood and visualised (and therefore easily memorised).
My experience with The Four Seasons hotel from when I entered the hotel through to using its various amenities is that there is significant care and detailed anticipation of user needs. From personal interactions with staff that show care and rapport, through to facilities that are carefully designed to incorporate guest needs. For me the surprise element was the room iPad greeting me with my name and giving me a run down of the weather, things to do and other location and hotel references. The challenge for us as change leaders is to learn from this and think through how we design great change experience that are out of the ordinary and far from the typical ho-hum corporate approaches in initiative roll out.
Why Change Data is the Hidden Superpower Every Business Leader Needs
The Untapped Potential of Change Data
For years, many senior leaders have viewed organisational change as an art, a blend of communications, stakeholder engagement, and leadership sponsorship. While these elements remain vital, something extraordinary has been unfolding under the surface: the rise of change data as a strategic asset.
What if the way we think of change is too small? What if, instead of treating it as a series of projects that need “change management,” we began to see the data generated by these efforts as a strategic lens into how organisations actually function, adapt, and perform?
Across industries, and over the years, we’ve observed first-hand that when organisations begin to harness change data, the outcomes go far beyond “project readiness.” They reshape how leaders make strategic decisions, how work gets done across divisions, and even how the board manages overall business performance.
The true, and often underestimated, secret is this: change data is not just about preparing people for change. It is about transforming the way an organisation leads, manages, and grows.
This article explores how organisations have unlocked these secret powers, and why senior change and transformation practitioners cannot afford to overlook them. In this part, we’ll uncover the foundational role change data plays in shifting mindsets, supporting readiness, and laying the groundwork for enterprise maturity.
Why Change Data Matters More Than Ever
Let’s start with the bigger picture. Today’s organisations face constant transformation: digital initiatives, regulatory adjustments, product innovation, workforce re-skilling, operational efficiency drives, sustainability imperatives, mergers, and more. The volume, speed, and complexity of change is not slowing down.
Most organisations respond by mobilising structured change management practices at the project level. This includes communication strategies, training, stakeholder maps, and readiness assessments. Valuable, yes — but only a narrow slice of the full change impact picture.
What we’ve noticed is that change practitioners typically begin their data journey seeking to address change readiness and saturation, focusing on questions such as:
What initiatives are happening when, and where are they hitting the same stakeholder groups?
How much change are people experiencing at any given time?
Are there upcoming “hot spots” where the risk of overload or disruption is high?
These are good starting points, and addressing them immediately reduces risk and helps leaders and workforce groups feel supported. But this is only the tip of the iceberg.
The deeper value, the secret power of change data, is how it enables organisations to:
Redesign structures of work to better support people through business change. For example, moving from purely project-focused change roles to embedded business change partners, who carry insights across initiatives.
Prepare leaders far more effectively. Division executives who receive targeted change data can anticipate disruption, balance transformation with business-as-usual priorities, and sequence initiatives in ways that protect performance while still delivering progress.
Elevate organisational conversations. At the enterprise level, change data doesn’t just observe disruption; it enables executives to evaluate trade-offs between delivery performance vs. business performance risks.
Put simply: change data transforms transformation — because it turns change into something tangible, measurable, and ultimately manageable at scale.
The First Unlock: Readiness and Saturation Data
Most organisations begin their change data journey addressing two of the most persistent pain points in transformation:
Readiness: Are stakeholders equipped and prepared for upcoming changes?
Saturation: Are people experiencing too much change across overlapping initiatives?
Without data, answers to these questions often rely on perception, anecdote, or late-stage feedback. This reactive approach leads to the classic symptoms of change fatigue: low morale, declining adoption, higher resistance, and frustrated leaders.
When organisations start capturing and reporting change data, however, the picture changes. Suddenly leaders see clear visibility of:
Change calendars that reveal how shifts overlap across projects and BAU activities.
Impact mapping that shows who is affected by what, when, and to what degree.
Hot spot reports that flag functions or business units at risk of overload.
This creates an immediate shift in dialogue. Where once change fatigue was a nebulous concern, leaders now have transparent indicators that guide practical actions like:
Adjusting timelines to avoid overload.
Sequencing initiatives so that employees face logical, not chaotic, transitions.
Allocating resources more intelligently to at-risk teams or functions.
In other words, readiness and saturation data gives leaders evidence-driven tools to manage complexity proactively, not reactively.
From Project Silos to Business Division-Level Change Partnership
However, the story does not end here. After building this readiness and saturation visibility, many organisations realise another breakthrough: change data encourages structural innovation in how change support is delivered.
Traditionally, change management capability is tied closely to individual projects. Each initiative brings in dedicated change resources, who manage impacts and adoption within their project scope. While effective at the micro-level, this creates silos: each project optimises for itself, but no one is accountable for the end-to-end employee experience across multiple changes.
By analysing change data across initiatives, organisations discover the opportunity to reorganise change capability around the business division, not the project. This leads to the creation of business change partners — roles embedded within divisions who leverage data insights to prioritise, balance, and guide cumulative change impact.
This structural shift is powerful because it:
Ensures continuity across initiatives and prevents duplication of stakeholder engagement.
Aligns change work to business priorities and outcomes, not only project metrics.
Provides leaders with trusted advisors embedded in their unit, armed with data describing the total reality of their workforce’s experience.
The impact is transformative. Instead of asking “How do we implement change for this project?” business units start asking “How do we optimise how change lands in our world over the next quarter or year?”.
This is where change management is no longer as a functional service, but as a strategic business capability.
Empowering Leaders to Anticipate and Design Around Change
The shift continues when organisational leaders, especially division heads, receive change data in usable, digestible forms. Suddenly, leadership conversations broaden from project execution to strategic performance.
When data is available, leaders:
Plan BAU activities with foresight. Instead of being blindsided by overlapping project timelines, they can stage internal improvements and initiatives so that business-critical periods (sales peaks, new product launches, market shifts) are not disrupted.
Balance business and transformation goals. With saturation hot spots visible, leaders can argue not only for speed but for sustainable adoption. This reframes transformation success as not just “delivered on time” but “delivered without degrading business performance.”
Design end-to-end transitions at the human level. When you know how employees are being impacted across multiple concurrent initiatives, you can tailor support and reduce fatigue in ways that would never be possible from a single-project lens.
In our experience, these leader-level conversations often spark “lightbulb moments.” Suddenly, senior executives realise change management is not solely about comms and training, it is a strategic enabler of business continuity and performance in times of transformation.
Setting the Stage: The Secret Power of Enterprise-Level Insights
Everything we’ve covered so far, readiness, saturation, structural redesign, business partnership, leader foresight, is just the beginning. These are the foundational benefits organisations experience as soon as they begin systematically capturing and working with change data.
But the real transformation happens when this data scales up to the enterprise level. At this scale, change data becomes a cross-enterprise performance management tool, providing clarity into adoption levels, risk balancing, and even what drives successful behaviour change.
For executives who constantly say “our people are our most important asset,” this is the moment where data finally converts that rhetoric into measurable insights about how people truly experience and deliver change.
From Insights to Impact – How Change Data Transforms Leadership, Governance, and Enterprise Decision-Making
Introduction: Moving from Local Impact to Enterprise Strategy
In the previous section, we explored how organisations begin their journey with change data, tackling readiness and saturation, experimenting with structural improvements like business change partners, and empowering division leaders to design change around business realities. These steps are critical foundations.
But at a certain point, the implications of change data begin to transcend the local or divisional lens. When aggregated and applied effectively, change data becomes a strategic capability at the enterprise level.
At this stage, executives and boards use change insights not only to manage risk but to actively optimise transformation success, protect business performance, and steer organisational strategy in real time.
This marks the transition from using data tactically to leveraging it as part of enterprise governance and maturity. In this part, we’ll explore how organisations use change data to:
Drive effective enterprise and division-level decision-making.
Establish performance-driven governance using change insights.
Embed enterprise adoption, behaviour, and performance metrics.
Create leadership forums and cohorts dedicated to leveraging change data.
Enterprise-Level Decision Making: Balancing Change Risk with Business Performance
Most organisations are adept at managing delivery risk: risks to timelines, budgets, scope, and quality. But what about business performance risks that emerge when too much change hits the organisation at once, or when leaders underestimate the adoption curve required to translate “delivered” into “realised” outcomes?
This is where change data serves as a powerful balancing mechanism between delivery ambition and business reality.
Three Key Levers Enterprise Data Enables:
Visibility of Cumulative Impact
Aggregate data across projects allows executives to see where the “burden of change” is truly falling.
For example, two transformation streams may be well sequenced in PMO timelines, but change impact data reveals their effects converge on the same frontline teams.
Performance Trade-Offs
Using data, leaders can weigh whether accelerating change puts business performance at risk.
Instead of relying on generic “people may be fatigued” cautions, they see quantified measures of readiness, adoption likelihood, and saturation.
Proactive Sequencing and De-Risking
Leaders can now make informed calls on whether to reschedule projects, boost local support, or phase rollouts — before issues manifest.
This reframes steering committees away from firefighting delivery slippage and toward strategic sequencing of value realisation.
The result? Enterprise-level decision forums shift from delivery tracking to transformation performance management.
The Rise of Governance Through Change Insights
At the heart of this enterprise maturity is governance. Change data equips governance bodies: steering committees, transformation councils, boards, with insights that go far beyond RAG status reports.
What Modern Change Governance Looks Like
Integration with Enterprise PMO and Risk Functions Change insights become a complementary dimension of existing project portfolio oversight. This means transformation risks are assessed not only in scope, time, and cost terms, but also in people adoption terms.
Leading Metrics, Not Just Lagging Ones Instead of focusing exclusively on post-rollout surveys, governance discussions use predictive data: “Based on our saturation and readiness analysis, here are the divisions most at risk of under-adoption next quarter.”
Decision-Making Forums Some organisations establish an enterprise change council comprising division heads, HR leaders, and transformation sponsors. Armed with data, these forums monitor adoption, risk distribution, and behavioural alignment, making collective decisions on sequencing and prioritisation.
In practice, this form of governance strengthens accountability. Business leaders can no longer say “change failed because people weren’t ready”, because readiness and adoption metrics were visible, tracked, and governed.
Beyond Readiness: Driving Behavioural Change and Adoption
One of the most significant leaps in value occurs when organisations move past tracking readiness and saturation to deep adoption and behavioural insights.
Senior leaders increasingly ask:
“What actually drives adoption in our context?”
“How do we know whether behavioural change is sticking?”
“Can we predict where we will face resistance or quick uptake?”
How Change Data Supports Adoption Insights
Adoption Pathway Analytics
By tracking adoption over time and correlating it with factors such as communication involvement, leadership sponsorship, or local network champions, organisations can identify adoption predictors.
Behaviour Tracking
Surveys, system usage analytics, and performance KPIs can be cross-referenced with project timelines to assess whether people actually shift behaviours aligned to new ways of working.
Change “Drivers” and “Blockers”
Insights reveal not just whether adoption is happening but which interventions (e.g., leader support, peer champions, targeted comms) accelerate success versus which gaps undercut adoption.
In mature organisations, these metrics elevate the conversation at the board level: Are we investing in change interventions that work, or are we simply rolling out change “playbooks” or models without evidence of effectiveness?
Case in Point: Shifting into Business Management Metrics
Perhaps the most profound step we’ve witnessed is when organisations begin to integrate change metrics into their general business management scorecards.
At this point, change metrics stop being “nice to have” project documentation and become seen as indispensable business performance management tools.
For example:
Quarterly Business Reviews (QBRs) include sections not just on operational KPIs but also on cumulative change impact and adoption progress.
Board Reports incorporate indicators on behavioural shift, workforce adaptation, and portfolio-wide saturation levels.
Divisional Scorecards measure not only EBIT contribution, but “change health” indicators such as employee adaptability, adoption rates, and resistance risk.
The symbolic and practical power of this integration is immense. For leadership teams, it elevates change from “a project issue” to a strategic input into enterprise performance conversations.
And culturally, it signals a decisive shift: change is no longer managed at the cost margins. It is part of how we run the business. Every quarter. Every board meeting. Every leadership conversation.
Building an Enterprise Change Cohort
Finally, one of the most effective mechanisms to embed enterprise change data into decision-making is forming a change cohort drawn from business division leads.
This group becomes a cross-functional brain trust, armed with data, tasked not with “doing change management” but with driving enterprise change outcomes.
They review impact and adoption data across initiatives.
They align recommendations back to business performance needs.
They build accountability for change not in the project office, but in the business.
This is a powerful maturity marker. It signals the organisation recognises that change is not something “delivered to” the business. It is something driven by the business, informed by real data and insights.
The Second Unlock: Enterprise Effectiveness Through Insights
By now, the secret powers of change data are undeniable. Once adopted into enterprise decision-making and governance, organisations begin to:
Mitigate transformation and performance risks proactively.
Redefine governance practice by treating adoption, behaviour, and readiness as measurable priorities.
Integrate change health into performance scorecards, making it inseparable from other business metrics.
Elevate cross-functional leadership forums to align business and transformation agendas.
These are the practices that differentiate organisations still “managing projects” from those building strategic, data-driven, adaptive enterprises.
But the journey does not end here. In fact, the most advanced organisations unlock a third level of maturity: where change data becomes part of talent development, board-level performance reporting, and organisational culture itself.
High Performance Organisations: Embedding Change Data into Leadership, Culture, and Competitive Edge
When Change Data Becomes a Cultural Superpower
Earlier, we explored how organisations begin their journey by tackling readiness and saturation, shifting from project silos towards business partnership. Then, we elevated the conversation to the enterprise level, where governance and leadership use change data to make informed, risk-balanced decisions, manage adoption, and embed “change health” into business performance scorecards.
Now, we move to the final progression, the point where change data and insights are so embedded in leadership, governance, and culture that they become a source of ownership, talent development, and competitive differentiation.
This is the journey from effective change management to change leadership maturity at the highest level.
The three levels of change maturity as supported by change data insights
Foundational: Awareness
Succeeding: Effective decision making
High performance: Ownership and drive
– Clarity of what initiatives do we have and impact levels, including BAU – Stakeholder awareness of key hotspot risks for increased change volume – Business division-focused (vs. project focused) change partner support
– Clear change governance for business decision making leveraging change data insights (enterprise and business division levels) – Enterprise level business readiness and adoption driven through metrics, reporting and continuous improvement, including behavioural change – Enterprise change cohort consisting of Business division leads to drive change outcomes using data insights
– Change metrics embedded as a part of general business for senior leaders, driving ownership of change outcomes – Board level reporting across various facets of change, including behavioural change, adoption and risk – Enterprise change champion network a talent factory where insight data is leveraged and talents get promoted and poached
The High-Performance Tier: Ownership and Drive
At this stage, the use of change data and insights is no longer owned primarily by project teams, central transformation offices, or even dedicated change practitioners. Instead, senior leaders themselves own change outcomes, and they actively institutionalise change insights in everyday business practice.
Three High-Performance Markers
Change Metrics as Senior Leadership Accountability
Change outcomes: adoption rates, behavioural shifts, stakeholder readiness, and risk forecasts, are included in senior leadership scorecards.
Leaders no longer talk about “delivering projects” without reference to how their teams are adapting, adopting, and sustaining new ways of working.
Board-Level Reporting
Change health becomes part of board packs alongside financial performance, compliance, and risk oversight.
Directors don’t just ask, “Are we meeting transformation milestones?” They ask, “Do we have the organisational capacity and adoption to sustain strategic change?”
Change Champion Networks as Talent Factories
Employees who serve as champions or liaisons in major transformations gain exposure, leadership experience, and enterprise-level influence.
Organisations find these roles become stepping stones for emerging leaders, talent pipelines are strengthened, and “change fluency” becomes baked into leadership culture.
These markers demonstrate that the organisation has crossed a key threshold: change insights no longer just support leadership — they drive leadership.
Board-Level Visibility: A Catalyst for Strategic Attention
Boards typically prioritise financial, compliance, and reputational risks. Yet, in today’s change-saturated environment, the greatest unmitigated risk often lies in failed adoption and disrupted business performance.
When change data is integrated into board-level reporting, three powerful shifts occur:
Change Becomes Measurable Governance Boards can demand evidence-based assurance: how many initiatives, what impact, readiness levels, adoption progress. Vague status reports are replaced with data-driven foresight.
Strategic Prioritisation Improves Boards often oversee a portfolio of transformation investments. Change data enables prioritisation: which programs to accelerate, slow, or pivot based on organisational capacity, not just financial ROI.
Cultural Signals Cascade When boards ask targeted questions about adoption, leadership sponsorship, and behavioural change, the organisation as a whole notices. This raises the visibility and legitimacy of managing human-centered change as an enterprise concern.
In practice, board-level visibility embeds long-term discipline. Just as financial mismanagement is unacceptable, so too becomes transformation mismanagement. Change data becomes part of corporate accountability.
The Enterprise Change Network as a Talent Engine
One of the most surprising dividends of using change data effectively is its role in talent growth and leadership development.
Many organisations form change champion networks, employees across functions who advocate, influence, and support adoption. In immature organisations, these networks are ad hoc and under-utilised. But in high-performing enterprises, they evolve into systematic leadership development ecosystems.
Data-Backed Roles of Influence Champions have access to change impact, readiness and adoption data, equipping them with real insights to guide their colleagues and leaders.
Pipeline of Future Leaders Champions operate across silos, build enterprise visibility, and practice skills in communication, influence, and resilience, qualities boards and executives prize in future leaders.
Competitive Differentiation in Talent Retention Organisations known for embedding employees in enterprise change networks build reputational capital. These individuals are promoted internally and sought externally, creating a talent marketplace where change fluency is a form of career currency.
In effect, change data is not just driving transformation; it is shaping the leadership DNA of the next generation.
Cultural Transformation: Change as Business-as-Usual
Perhaps the greatest secret power of change data is how it shifts culture. At the high-performance stage, data-driven insights move beyond being a “change tool” and become part of everyday business management practice.
What does this look like?
Leaders View Change as Continuous, Not Episodic With impact and adoption metrics consistently visible, leaders accept that transformation is not a project to “complete” but a continuous cycle of adaptation.
Change Conversations Become Part of the Operating Rhythm Quarterly reviews, leadership meetings, and town halls consistently include forward views on change impact and adoption progress. It stops being an afterthought.
Learning Loops Drive Continuous Improvement Data doesn’t just describe change; it teaches the organisation how to get better at it. Each initiative provides lessons on what drives adoption, insights that compound across time.
At this point, organisations move from asking, “How do we manage this specific change?” to “How do we become more adaptive as an enterprise?”
This cultural shift is profound. It shifts change away from being experienced as disruption and repositions it as a core muscle of competitive advantage.
Unlocking Competitive Advantage: The Strategic Dividend of Change Insights
Why does all this matter? Because in industries disrupted by digitalisation, customer expectations, regulatory shifts, and global competition, the ability to adapt is itself a sustainable advantage.
Change data and insights arm organisations with:
The foresight to avoid fatigue and disruption risks before they materialise.
The ability to sequence transformations strategically, protecting business performance while innovating.
The intelligence to scale only the interventions that drive adoption and results, not generic templates.
The discipline to couple strategic ambition with human-centred accountability at board level.
And perhaps most importantly:
A workforce and leadership culture where adaptability is seen as the norm, career-enhancing, and strategically valuable.
In this way, data doesn’t simply make change more manageable. It makes the organisation more resilient, adaptive, and competitive, even in the most volatile environments.
The Secret Powers Realised
We have observed with the organisations that we’ve worked with that what started for many organisations as a tactical tool to solve readiness and saturation challenges unfolds into something far greater. Change data has the power to:
Redefine how work is structured (business partnerships vs. project silos).
Enable leaders to design around change impacts, protecting business continuity and maximising performance.
Transform governance into enterprise-level performance management.
Embed accountability for adoption and behavioural change at the executive and board levels.
Create talent engines and cultural transformation that strengthen adaptability as a way of life.
For senior change and transformation practitioners, the lesson is clear: change data is not a side tool, but a strategic superpower. Those who champion it are not just enabling today’s transformation projects; they are shaping the enterprise capability to thrive in a world of constant change.
The organisations that we have seen reach this level of maturity realise that change is not something to manage. It is something to own, optimise, and leverage for competitive advantage. And the key that unlocks it all? Change data and insights.
What we’ve outlined in this article is not just a conceptual framework, but what we’ve observed in the organisations we’ve worked with over the years. To find out more about how your organisation may benefit from change data insights chat to us to find out more.
What are the key components of an agile change management plan?
An agile change management strategy process includes key components such as a clear vision for change, stakeholder engagement strategies, iterative feedback loops, and adaptable processes. These elements ensure effective communication, continuous improvement, and responsiveness to evolving needs, helping teams navigate transitions smoothly while maintaining alignment with organizational goals.
The agile approach of implementing major changes has been popular for quite several years among a range of companies across the business environment, from small startups to large corporations. Most agile processes and methodologies do not explicitly address the role of change management as a function. However, at the same time, most agile practitioners and project practitioners agree that applying agile project management principles, including agile principles, to managing change management approaches is a critical skill set, especially when transitioning from traditional project management approaches used in software development. Surveys conducted by the Project Management Institute consistently found that change management is rated as one of the top skills for a project manager.
In this article, we will delve into a variety of toolkits that support agile methodologies in an agile environment, providing not only an overview of agile change management practices but also in-depth explanations and practical examples to help change managers, team members, and software developers, including the core development team, implement change effectively. Gone are the days when the agile team and change manager, sometimes guided by an agile coach, need to work on large presentations and slides detailing every aspect of the plan. It was not uncommon to see more than 100 slides for a change plan. In the agile world, documentation is important, but more important is the conversation and working with stakeholders.
Toolkit 1: Change Canvas: A Summarized Approach to Change Planning
The Change Canvas, also known as ‘change-on-a-page,’ serves as a condensed version of the change plan. While previous iterations leaned towards a project plan format, the current version focuses on key questions that change practitioners must answer. Previous versions of the change canvas are often designed with more of a project plan slant. In the current version, we focus on a core set of questions that the change practitioner needs to answer in creating a change plan. To download the canvas click here.
Example: “Imagine a technology company undergoing a major software upgrade. The Change Canvas was employed to create a concise summary of the change plan. This one-page document effectively communicated the essence of the software upgrade, outlining key aspects such as the purpose, stakeholders involved, and the approach to implementation. This simplified overview, along with the terms of service, became a valuable reference point during stakeholder meetings, fostering clearer communication and understanding.”
Example: “Imagine a technology company undergoing a major software upgrade. The Change Canvas was employed to create a concise summary of the change plan. This one-page document effectively communicated the essence of the software upgrade, outlining key aspects such as the purpose, stakeholders involved, and the approach to implementation. This simplified overview became a valuable reference point during stakeholder meetings, fostering clearer communication and understanding.”
Toolkit 2: Change Experiment Card: Iterative Approaches for Effective Change
A core part of agile is about experimenting and iterating through a series of changes, versus planning one change. The idea is that each small change is an experiment with a hypothesis that can be tested and proven to be true or false using data. When the overall change becomes a series of smaller changes, each change iterates on the previous change. The overall risk of failure is reduced and each change is one step closer to the ultimate successful end state.
Applying this concept in change management – The change experiment card is a template to help you design, plan, and test your change experiment. To download the template please click here.
Change experiments can range from:
Project message positioning to stakeholders
Learning design effectiveness
Effectiveness of a communications channel in engaging with stakeholders
Change readiness tactic
Effectiveness of the change vision artifact
Example: “In an educational institution implementing a new learning management system, the Change Experiment Card was utilized to plan and test various change experiments. One experiment focused on refining the messaging strategy to engage faculty members effectively. By treating each adjustment as an experiment, the change team gathered valuable data on the impact of messaging changes, allowing for continuous refinement and ultimately ensuring a smoother adoption of the new system.”
Toolkit 3: Behavior Over Time Graph: Anticipating and Tracking Stakeholder Experience
The Behavior Over Time Graph is a powerful tool for anticipating and tracking stakeholder behavior throughout the change process. Explore a specific case where stakeholders’ reactions were plotted over time, providing significant insights into the need for additional interventions, obstacles faced, and alignment with anticipated timelines.
Here is an example of a behavior over time graph.
Example: “During the rollout of a new performance management system in a corporate setting, the Behavior Over Time Graph was employed to track employee sentiments. As the system was implemented, the graph revealed an initial dip in engagement, prompting the change team to introduce targeted communication and training interventions. The subsequent rise in positive sentiments demonstrated the effectiveness of these interventions, showcasing the power of anticipating and responding to stakeholder behavior over time.”
The Connected Circles Analysis chart is indispensable for understanding the influencing powers of various stakeholders in an agile project. Through a practical example, discover how this analysis unveiled power dynamics, aiding the change manager in resolving relationship issues, mitigating risks, and leveraging the network for improved outcomes within the stakeholder group. A range of stakeholders are thrown together within the same project from the beginning and there is a high expectation of successful collaboration and teamwork across the board. This analysis helps you to visualise the power dynamism and influence mechanisms amongst different stakeholders.
With the insight gained from this, the change manager can better focus on how to resolve any relationship issues, risks, and leverage the network to achieve better relationships and outcomes within the group.
Example: “In a cross-functional agile project within a large organization, the Connected Circles Analysis chart was used to understand the influencing powers of various stakeholders. By visualizing the dynamics, the change manager identified potential conflicts and areas of collaboration. This insight facilitated proactive measures to enhance relationships, resolve conflicts, and leverage the collective influence of stakeholders for a more cohesive and collaborative project environment.”
Toolkit 5: Causal Loop Diagram: Systems Thinking for Agile Projects
Systems thinking is critical in agile projects, emphasizing the need to understand how different components interact. The Causal Loop Diagram helps analyze key factors and their causal relationships within the system.
The below example shows employee sentiments toward a system change. This is a very simplified version of what happens since in real scenarios there could be various factors that are reinforcing each other, leading to lots of arrows pointing at different directions. At a more sophisticated level, you may assign points in terms of the strength of the causal relationship. At a basic level even plotting the causal relationship between a few key factors may generate key insight into the ‘why’ of the dynamics of a situation.
Example:
“In a manufacturing company implementing agile practices across departments, the Causal Loop Diagram was applied to understand the dynamics of employee sentiments toward process changes. By mapping out the causal relationships between factors such as training effectiveness, leadership communication, and workflow adjustments, the change team gained a holistic view. This enabled them to address root causes, leading to a more systemic and sustainable improvement in employee sentiments over time.”
In the dynamic landscape of organizations undergoing numerous agile changes, the ability to capture and visualize these transformations becomes paramount for informed decision-making. Data visualization emerges as a powerful tool, offering stakeholders a comprehensive understanding of the organizational change landscape. It enables them to navigate through various changes, identify key capacity challenges, recognize crunch periods, understand the velocity of changes over time, and pinpoint areas requiring additional support.
To effectively navigate this complex terrain, organizations can leverage advanced tools such as The Change Compass. This tool provides a consolidated view of change, facilitating improved planning and implementation strategies. By integrating operational routines that consistently focus on change data alongside other business and project information, organizations can systematically enhance their change capability. This process involves regular reviews, engaging stakeholder discussions, iterative refinement of change tactics, and adaptive adjustments to plans in anticipation of evolving change dynamics.
In adopting such a holistic approach, organizations not only streamline their change management processes but also foster a culture of constant improvement and adaptability. The use of tools like The Change Compass becomes instrumental in creating a unified vision of change, aligning stakeholders, and ensuring that the organization remains agile and responsive in the face of ongoing transformations.
In today’s fast-paced business environment, most organizations are engaged in numerous change initiatives, including organizational transformation, simultaneously. These initiatives might range from digital transformation efforts to restructuring, new product launches, or cultural shifts. For change management practitioners and leaders, the challenge is not only to ensure each initiative succeeds but also to align these efforts strategically to maximize overall business benefit. Let’s explore practical strategies for aligning multiple initiatives and measuring change adoption, providing actionable insights for change practitioners and leaders.
The Complexity of Multiple Change Initiatives
The complexity of managing multiple change initiatives lies in the potential for overlap, conflicting priorities, and resource strain. Each initiative, while aiming to deliver specific benefits, competes for attention, time, and resources. Moreover, when several initiatives target similar business outcomes, it becomes challenging to attribute success to any single effort. Most business units are only measuring a certain number of business metrics, and with a large number of initiatives there will bound to be overlaps. This makes it essential to adopt a strategic approach that ensures alignment and optimal resource utilisation.
One of the most critical aspects of managing multiple change initiatives is measuring the adoption of each change. This involves not only tracking how well each initiative is being implemented but also creating a clear and detailed plan to understand its impact on the organization. The following strategies can help you effectively measure change adoption across various initiatives:
1. Establish Common Metrics
Establishing common metrics across all change initiatives is a foundational step in ensuring that change adoption is measured consistently and effectively. Common metrics provide a standardized way to evaluate progress, compare the success of different initiatives, and gain a holistic view of the organization’s overall change efforts. This approach allows for “apples-to-apples” comparisons, enabling senior leaders to make informed decisions about resource allocation, prioritization, and potential adjustments needed to maximize business benefits.
By identifying and applying a set of core metrics consistently across all change initiatives, organizations can better track the adoption process, identify areas where additional support may be needed, and ultimately ensure that changes are embedded successfully and sustainably.
Here’s a deeper look at some of the common metrics that can be established (note that we take a holistic and strategic lense in ‘adoption’, and not limiting adoption to the end of the project):
Employee Awareness and Understanding of the Change
Employee awareness and understanding are the first critical steps in the change adoption process. Without a clear understanding of what the change entails, why it is happening, and how it will impact their work, employees may experience discomfort and are unlikely to fully embrace the change. Measuring awareness and understanding helps ensure that communication efforts are effective and that employees have the necessary information to begin adopting the change.
Awareness Surveys: Regular surveys can be conducted to assess employees’ awareness of the change initiative. Questions can focus on whether employees are aware of the change, if they understand the reasons behind it, and if they can articulate the expected outcomes.
Knowledge Assessments: Beyond awareness, knowledge assessments can help gauge how well employees understand the details of the change. This could involve quizzes, interactive sessions, or discussions that test their understanding of new processes, tools, or organizational structures.
Communication Effectiveness: Track the effectiveness of communication campaigns through metrics such as email open rates, attendance at town halls or webinars, and engagement with internal communication platforms. High levels of engagement can indicate that employees are receiving and processing the information about the change.
Employee Engagement and Buy-in
Employee engagement and buy-in are essential for successful change adoption. If employees are not engaged or do not buy into the change, they are less likely to put in the effort needed to adopt new behaviours, processes, or tools, which decreases the chances of success. Measuring engagement and buy-in provides insight into how committed employees are to making the change successful.
Engagement Scores: Use engagement surveys to measure overall employee engagement levels before and after the change initiative. These scores can help you understand the impact of the change on employee morale and identify any groups that may need additional support.
Feedback Channels: Monitor and analyse feedback from employees through formal and informal channels. This includes responses to surveys, comments in focus groups, and feedback collected through suggestion boxes or digital platforms. The sentiment expressed in this feedback can be a strong indicator of buy-in.
Participation Rates: Track participation in change-related activities such as training sessions, workshops, and change champion programs. High participation rates typically indicate strong engagement and willingness to adopt the change.
Utilisation of New Systems, Processes, or Tools
The utilisation of new systems, processes, or tools introduced by a change initiative is a direct measure of adoption. If employees are not using the new tools or following the new processes, the change initiative cannot deliver its intended benefits. Measuring utilisation helps ensure that the changes are being practically applied in day-to-day operations.
System Usage Analytics: For technology-driven changes, track the usage of new systems through analytics. Metrics such as login frequency, time spent on the system, and the completion of key tasks can provide a clear picture of adoption.
Process Adherence: Implement tracking mechanisms to monitor adherence to new processes. This could involve audits, self-reporting, or the use of process management tools that track whether employees are following the new workflows.
Tool Adoption Rates: Measure the adoption rates of any new tools introduced as part of the change. This could include tracking the number of users, the frequency of use, and the breadth of functionality being utilised.
Proficiency in Applying the Change
Proficiency in applying the change is a crucial metric because it not only indicates whether employees are using the new systems, processes, or tools, but also how effectively they are using them. This metric helps ensure that employees have the necessary skills and competencies to fully leverage the change and achieve the desired outcomes.
Skill Assessments: Conduct skill assessments to measure employees’ proficiency in using new tools, systems, or processes. This could involve practical exams, simulations, or peer reviews where employees demonstrate their competency.
Performance Metrics: Monitor performance metrics related to the new processes or tools. For example, if a change initiative involves a new sales system, track metrics like sales conversion rates, the accuracy of data entry, or the speed of customer service resolution.
Certification Programs: Implement certification or accreditation programs where employees must demonstrate a certain level of proficiency to earn certification. Tracking the completion rates of these programs can indicate overall proficiency levels.
Realization of Expected Business Benefits
The ultimate goal of any change initiative is to realize clear goals and the expected business benefits, whether they be financial, operational, or strategic. Measuring the realization of these benefits provides a clear indication of the success of the change initiative and its impact on the organization.
Benefit Tracking: Establish specific, measurable business benefits for each change initiative, such as cost savings, revenue growth, improved customer satisfaction, or increased productivity. Each initiative should have clear objectives to track these metrics regularly and assess whether the change is delivering the expected outcomes.
ROI Analysis: Conduct return on investment (ROI) analysis for each initiative, comparing the costs of implementation against the benefits realized. This helps quantify the financial impact of the change and determine its overall value to the organization.
Outcome-Based Metrics: Focus on outcome-based metrics and key performance indicators (KPIs) that align with the organization’s strategic goals. For example, if a change initiative aims to improve customer experience, track customer satisfaction scores, retention rates, and repeat business.
Note that these may not be activities that change practitioners are leading within a project setting, however they should play a key part in contributing to the design and tracking of the adoption which then leads to the ultimate benefits.
Implementing Common Metrics in Practice
Implementing common metrics across multiple change initiatives requires a coordinated effort and a strong governance framework. Here are some practical steps to ensure that these metrics are applied effectively:
Alignment with Strategic Goals: Ensure that the selected metrics align with the organization’s broader strategic goals. This alignment helps prioritize initiatives and ensures that all change efforts contribute to the organization’s overall objectives.
Centralized Data Management: Establish a centralized data management system to collect, store, and analyze metrics across all initiatives. This system should allow for easy comparison and aggregation of data, providing a comprehensive view of change adoption.
Consistent Methodology: Develop a consistent methodology for measuring and reporting metrics. This includes standardized survey questions, data collection tools, and reporting formats to ensure that metrics are comparable across different initiatives.
Continuous Monitoring and Reporting: Regularly monitor and report on the metrics to track progress and identify any areas of concern. Strong leadership is essential in using dashboards and scorecards to provide real-time visibility into change adoption across the organization.
Feedback and Adjustment: Use the insights gained from these metrics to provide feedback to initiative leaders and make necessary adjustments. Continuous improvement is key to ensuring that change initiatives remain on track and deliver the expected benefits.
Implementing metric tracking can be a very manual and labour intensive process. However, there are various digital tools that can be leverage to automate the data capture and streamline the data analysis and insight generation process. Chat to us to find out how The Change Compass can help.
2. Conduct Regular Assessments
Regular assessments are critical to understanding how well each initiative is being adopted and its impact on the organisation. These assessments should be scheduled at key milestones and involve both quantitative and qualitative evaluation.
Pulse Surveys: Conduct pulse surveys at regular intervals to gauge employee sentiment and engagement with each initiative. These short, focused surveys can provide real-time insights into how changes are being received and where additional support may be needed. However do note that pulse survey in themselves may only provide very superficial insights without the depth that may be required to understand the ‘why’ or ‘how’.
Performance Reviews: Where possible integrate change adoption metrics into regular performance reviews. This ensures that the impact of initiatives is continuously monitored and that any issues are addressed promptly.
Change Audits: Periodically perform change audits to assess the effectiveness of each initiative. This involves reviewing processes, outcomes, and feedback to determine whether the change is being adopted as intended.
3. Leverage Existing Channels
Leverage existing communication and feedback channels to measure adoption. This approach ensures that you are not overloading employees with new processes and allows for seamless integration into their daily routines.
Employee Feedback Platforms: Utilise platforms already in place, such as intranet forums like Yammer, suggestion inboxes, or regular team meetings, to gather feedback on change initiatives. This feedback can provide valuable insights into adoption levels and potential areas of resistance.
Usage Analytics: For technology-driven initiatives, use existing analytics tools to monitor system usage and user behaviour. This can help identify adoption rates and areas where additional training or support may be needed.
Regular Check-ins: Integrate adoption tracking into regular team check-ins. This allows managers to discuss progress with their teams and identify any challenges early on.
4. Quantify Qualitative Data
While quantitative metrics are essential, qualitative data provides context and deeper insights into how changes are being adopted. It’s important to develop methods to quantify this qualitative data to better understand the impact of your initiatives. Quantitative data are easier to present, and may be more memorable to your stakeholders.
Sentiment Analysis: Use sentiment analysis tools to analyse employee feedback, comments from surveys, or even social media mentions. This helps quantify the overall sentiment towards each initiative, providing a clearer picture of adoption.
Focus Groups: Conduct focus groups to gather in-depth feedback on specific initiatives. While this data is qualitative, you can quantify it by categorizing responses into themes and measuring the frequency of each theme.
Narrative Metrics: Develop narrative metrics that capture the stories behind the numbers. For example, if an initiative aims to improve customer service, track success stories where employees went above and beyond as a result of the new changes.
5. Analyse Trends and Patterns
Analysing trends and patterns over time is essential for understanding the broader impact of multiple initiatives. By looking at adoption data longitudinally, you can identify which initiatives are driving long-term change and which may require adjustments.
Adoption Trajectories: Track the adoption trajectories of each initiative. Are there certain initiatives that show rapid early adoption but then plateau? Understanding these patterns can help refine strategies to sustain momentum.
Cross-Initiative Analysis: Compare adoption trends across different initiatives. Look for correlations or conflicts between initiatives. For example, if one initiative shows strong adoption while another lags, investigate whether they are competing for the same resources or if there is confusion about priorities.
Predictive Analytics: Use predictive analytics to forecast future adoption trends based on historical data. This can help in proactive decision-making and resource allocation. This is absolutely the value of data, when you have historical data you can easily forecast what lies ahead and provide an overlay for change portfolio consideration during business planning cycles.
6. Communicate Progress Transparently
Transparent communication is vital for building trust and ensuring that everyone in the organization is aware of the progress of each initiative. This helps in aligning efforts and maintaining momentum.
Regular Updates: Provide regular updates on the progress of each initiative. Use a variety of channels such as newsletters, town halls, or internal social media to keep everyone informed.
Success Stories: Share success stories that highlight the benefits of adoption. This not only celebrates achievements but also reinforces the value of the initiatives and encourages further adoption.
Dashboard Reporting: Develop a dashboard that tracks and displays adoption metrics for all initiatives in real-time. Make this dashboard accessible to key stakeholders to ensure transparency and accountability.
7. Establish a Governance Framework
A governance framework is essential for coordinating multiple initiatives and ensuring that they are aligned with the organization’s strategic goals. This framework should provide structure, oversight, and guidance for all change efforts.
Steering Committees: Establish steering committees composed of senior leaders who oversee the progress of all initiatives. These committees should ensure that initiatives are aligned with business objectives and that resources are appropriately allocated.
Change Champions: Identify change champions within the organization who can advocate for adoption and provide support to their peers. These individuals play a crucial role in driving change from within and ensuring alignment across initiatives, similar to a strong leadership team.
Standardised Processes: Develop standardized business processes for planning, implementing, and measuring change initiatives. This ensures consistency and allows for more effective comparison and integration of efforts. In establishing the right routines they become embedded within business practices and are not seen as an ‘additional effort required’ on top of their day-jobs.
Aligning Multiple Initiatives for Maximum Business Benefit
While measuring adoption is crucial, aligning multiple initiatives to maximize business benefits is the ultimate goal. Here are key strategies to ensure alignment:
1. Prioritise Initiatives Based on Strategic Value
Not all initiatives are created equal. Prioritising initiatives based on their strategic value ensures that resources are allocated effectively and that the most critical changes receive the attention they deserve.
Value Assessment: Conduct a value assessment for each initiative to determine its potential impact on the organization’s strategic goals. Focus on initiatives that align most closely with these goals.
Resource Allocation: Allocate resources based on the strategic value of each initiative. This may involve dedicating more resources to high-priority initiatives while scaling back on others.
Phased Implementation: Consider implementing high-priority initiatives in phases. This allows you to focus efforts on achieving quick wins, which can build momentum for broader change.
Integration of change initiatives is essential to avoid duplication of efforts and to ensure that all initiatives are working towards common goals. This requires a coordinated approach and effective communication across initiatives and stakeholders.
Change Integration Plan: Develop a change integration plan that outlines how different initiatives will work together. This plan should identify potential overlaps and ensure that all initiatives are aligned. It could be that lower prioritised initiatives be pushed out making the runway for more strategic initiatives with higher priorities. It could also be ‘packaging’ change releases across different initiatives where they make sense to deliver change to the impacted teams in a more cohesive and easier-to-digest manner, similar to a comprehensive change management plan. This may be due to the nature of the changes or the volume and capacity required in the impact of the changes.
Cross-Functional Teams: Establish cross-functional teams to oversee the integration of initiatives. These teams should include team members who are representatives from each initiative to ensure collaboration and alignment. Ideally, cross-functional forums already exist and this is just tapping into an existing channel.
Unified Communication Strategy: Create a unified communication strategy that aligns messaging across initiatives. This helps avoid confusion and ensures that employees receive consistent information. To do this, data is required to be able to have a clear view in terms of communication content and planned releases.
3. Monitor and Adjust in Real-Time
The business environment is dynamic, and change initiatives need to be adaptable. Monitoring progress in real-time and being willing to adjust strategies is crucial for success. At a minimum, set up routine reporting timelines so that data and reporting are harmonised and embedded within the operating rhythms of those involved.
Real-Time Monitoring: Use real-time data to monitor the progress of each initiative within the change process. This allows you to identify issues early and make adjustments as needed.
Agile Approach: Adopt an agile approach to change management, where initiatives are continuously reviewed and adjusted based on feedback and changing circumstances.
Flexibility in Execution: Be prepared to pivot if an initiative is not delivering the expected results or needs to be adjusted based on the challenges of impacted business teams. This might involve reallocating resources, adjusting timelines, or even pausing initiatives that are not aligned with current business needs.
Successfully managing and aligning multiple change initiatives is a complex but achievable task. By establishing common metrics, conducting regular assessments, leveraging existing channels, and quantifying qualitative data, you can effectively measure adoption. Aligning initiatives for maximum business benefit requires prioritisation, integration, and real-time monitoring. For change management practitioners and leaders, these strategies are essential for driving organisational success in a world of increased rate of change. By strategically aligning multiple initiatives, you can ensure that the organisation not only adapts to change but thrives in it.
Though not elaborated, what is inherent in this article is the importance of behaviour in adoption, understanding it, and measuring it. To read more about driving behaviour change check out The Ultimate Guide to Behaviour Change.
Organisational change management professionals are increasingly requested to provide measurement, data, and insights to various stakeholder groups. Not only does this include tracking various change management 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 best practices 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.
Data scientists spend a substantial portion of their time on data collection and cleansing from data sources. 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 as a part of a structured approach. 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.
What is data change management and why is it important?
Data change management involves overseeing and controlling changes in data systems to ensure accuracy and consistency. It’s crucial for minimizing errors, maintaining data integrity, and enhancing decision-making processes. Effective management safeguards against potential risks associated with data alterations, ensuring organizations can adapt to shifts in information seamlessly.
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 in the desired future state. 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.
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 data governance and 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.
a. Establish Clear Processes: Develop and document processes for collecting and managing data related to change initiatives and document any new processes. This ensures consistency and reliability in data handling. There should also be effective communication of these processes using designated communication channels to ensure smooth transition and adherence.
b. Implement Governance Structures: Set up governance bodies to oversee data governance practices as a part of data governance efforts. 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. Data governance group members (potentially representative business owners) foster a sense of ownership and can be empowered to resolve potential issues with data and usage. Key performance indicators and key change indicators may be setup as goals.
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 and data teams 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.
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.
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 to encourage a culture where data is valued and used for decision-making from current state to future state. The change process 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.
