Every large organisation generates significant volumes of change management data. Readiness assessments, impact analyses, stakeholder surveys, adoption trackers, change plans, training records. Most of it is created at the project level, used briefly, and then archived when the project closes. The insight it could generate, about what kinds of change land well, which stakeholder groups are consistently resistant, how cumulative load affects adoption, which interventions work in your culture, largely disappears.
This disposal of valuable data is one of the most common and least-discussed limitations of how organisations currently approach change management. When change data is managed tactically, it serves only the project that created it. When it is managed strategically, it becomes an organisational asset that improves the quality of change decisions across the portfolio, year on year.
Capgemini Invent’s 2023 change management study, surveying 1,175 professionals globally, found that high data maturity in change programmes correlates with a 27% improvement in change success rates, and that data-driven leadership adds a further 23% lift. The research is unambiguous: how you manage change management data is a meaningful predictor of transformation outcomes.
This article is about making that shift, from tactical, project-level data management to strategic change data management that builds cumulative intelligence about how change works in your organisation.
The four common failure modes of change data management
Most organisations do not set out to manage change data poorly. The failure modes are structural, rooted in how change management work is organised rather than individual capability gaps.
Data collection is ad hoc and project-specific. When each project team designs their own impact assessment templates, readiness survey questions, and adoption tracking approaches, the data produced is genuinely useful within that project and largely useless outside it. There is no consistent taxonomy, no standard scales, and no common definitions. When you try to ask a cross-portfolio question , “which of our business units consistently shows lower adoption rates?” , the data cannot answer it because it was never designed to be aggregated.
Data lacks factual grounding. A significant proportion of change data is perception-based, reflecting what change managers think about stakeholder readiness or impact severity rather than what the evidence shows. Heat maps built on subjective ratings, readiness assessments scored by the project team rather than the affected employees, and impact analyses that reflect project plan assumptions rather than actual operational context all share this weakness. The data is not wrong, exactly, but its evidential basis is thin and rarely documented. When challenged by senior stakeholders, it is difficult to defend.
Visualisation obscures rather than reveals. The way change data is visualised has a substantial effect on whether it drives decisions. A heat map that shows everything as amber is not a useful risk management tool; it has simply translated uncertainty into colour. Visualisations that use the wrong chart type for the underlying data pattern, or that present too many variables at once, or that aggregate data in ways that mask important distribution effects, are actively misleading even when the underlying data is sound.
Data is not retained as an asset. When a programme closes, its change data typically closes with it. The lessons embedded in three years of readiness assessments, adoption surveys, and stakeholder feedback are lost. The next programme team starts from scratch, repeating the same diagnostic work, making the same assumptions, and potentially encountering the same predictable resistance that a prior team navigated successfully. This waste is invisible because no one tracks the cost of reinventing the wheel, but it is substantial.
What strategic change management data management actually means
Strategic change management data management is the practice of designing, collecting, governing, and preserving change data as a reusable organisational asset rather than a project-level administrative product. It has five characteristics that distinguish it from tactical data management.
Consistent taxonomy and definitions
A strategic approach starts with agreement on what you are measuring and how. What does ‘high impact’ mean in your organisation’s context? How is change readiness defined and at what granularity? What are the stages of adoption your organisation recognises, and what observable behaviours characterise each stage? These definitions need to be documented, agreed by change leadership, and applied consistently across every programme in the portfolio.
This sounds straightforward but is often contentious, because standardisation requires programme teams to give up some flexibility in how they approach impact assessment and readiness measurement. The benefit, however, is that every new dataset generated becomes immediately comparable with every prior dataset, and portfolio-level analytics become possible.
Portfolio-level collection and aggregation
Individual programme data is useful to the programme team. Portfolio-level data, aggregated across all active and historical programmes, is useful to the change function leadership, to HR, to business unit heads, and to the executive team. Strategic change data management designs data collection with portfolio aggregation in mind from the outset, not as an afterthought.
The questions that portfolio-level change data can answer are categorically more strategic than those accessible from project-level data. Which business units are accumulating unsustainable change load this quarter? Which change types consistently generate higher resistance in your culture? Which combinations of interventions correlate with faster adoption in your organisation specifically? These are the questions that allow a change function to operate proactively rather than reactively.
Fact-based data quality standards
Strategic change data management requires documented standards for what constitutes adequate evidence for different data types. Stakeholder impact ratings should be supported by operational analysis, not solely by project team estimation. Readiness assessments should include both leader perceptions and employee-level indicators, because they frequently diverge. Adoption metrics should triangulate system usage data, survey data, and direct observation rather than relying on a single source.
This does not mean perfection is required before data can be used. It means being explicit about the evidential basis of data and the uncertainty that attaches to it. A readiness rating of 65% that is based on a 40-respondent employee survey is meaningful. The same rating based on a change manager’s estimate without respondent data should be labelled and treated differently.
Retention and longitudinal analysis
One of the most underexploited opportunities in change management is longitudinal analysis of your organisation’s own change history. If your organisation has been running significant change programmes for five or more years, and if that data has been retained in a structured format, you have the basis for genuinely organisation-specific benchmarks.
What percentage of employees in your operations function were typically at target adoption six months after a technology rollout in the past? What does the readiness trajectory typically look like for a business unit facing a structural reorganisation? These organisation-specific patterns are more useful for planning purposes than generic research benchmarks, because they reflect your culture, your leadership style, and your workforce characteristics.
A governance structure for change data
Strategic change data management requires governance: clear ownership, defined data standards, review cycles, and access controls. Without governance, standards erode over time as programme teams revert to their preferred approaches, data quality degrades, and the portfolio view becomes unreliable.
Governance for change data does not need to be elaborate. A data steward role within the change function, clear standards documentation, a quarterly review of data quality across the portfolio, and a defined retention policy are sufficient for most large organisations. The key is that someone is accountable for the quality of the organisational change data asset, not just the quality of their own programme’s data.
AI and automation: what they add to strategic change data management
The intersection of artificial intelligence and change management data is generating genuine capability improvements, particularly in the speed of synthesis and the detection of patterns that manual analysis would miss.
Capgemini’s concept of Intelligent Data-Driven Change Management (IDCM) combines human emotional intelligence with algorithmic insights to support change decisions. In practical terms, this means AI that can monitor multiple data streams simultaneously (survey results, system usage, engagement metrics, communication analytics) and surface signals that warrant human attention, rather than requiring change managers to manually synthesise all of this information.
Key AI applications in strategic change data management include:
Natural language processing of stakeholder feedback and open survey responses, identifying sentiment patterns and emerging concerns at scale without manual qualitative coding
Anomaly detection in adoption curves, flagging when a stakeholder group’s trajectory deviates significantly from expected patterns
Predictive modelling of adoption outcomes based on historical programme data, adjusted for current programme characteristics and context
Automated generation of executive summaries from portfolio data, reducing the reporting burden on change teams while improving reporting consistency
It is important to be clear about what AI does not replace. It does not replace the judgment required to understand why a stakeholder group is resistant, the relationship-building required to address that resistance, or the strategic thinking required to sequence programmes effectively. AI in change management is most valuable as a signal amplifier, drawing human attention to where it is most needed. The strategic framework within which those signals are interpreted remains a human responsibility.
Building a change data ecosystem
For organisations ready to move beyond ad-hoc data management, a change data ecosystem is the infrastructure that makes strategic change data management operational.
A change data ecosystem has three layers. The collection layer is where data enters the system: programme impact assessments, readiness surveys, adoption tracking, training completion, and communication analytics. The aggregation layer is where programme-level data is normalised, consolidated, and stored in a format that enables cross-programme analysis. The decision layer is where the data is used: executive dashboards, portfolio risk views, programme intervention decisions, and historical benchmarks.
Platforms like The Change Compass are purpose-built for this architecture, specifically for the challenge of visualising cumulative change load and adoption status across a complex change portfolio. The value of purpose-built change management software, compared to using general-purpose business intelligence tools, is that the data models and analytical frameworks are pre-configured for change management use cases. You are not building the methodology from scratch; you are applying it.
The shift from reporting to decision intelligence
The ultimate destination of strategic change management data management is decision intelligence: a state where change data actively informs decisions about sequencing, resourcing, intervention design, and programme prioritisation in real time rather than retrospectively.
This virtuous cycle is what mature change functions are beginning to achieve. They use data to improve programmes, which generates better data, which improves the next generation of programmes. The cumulative knowledge advantage this creates over time is significant and durable.
Getting there requires investment in the governance, tooling, and cultural change described in this article. But the starting point is simpler than it might appear. Pick one consistent definition. Apply it across your active programmes. Retain the data when those programmes close. Review what the combined data tells you at the end of the year. You will have begun the shift from tactical to strategic change data management, and the first cycle of learning will show you exactly why it matters.
Frequently asked questions
What is strategic change management data?
Strategic change management data is change-related information that is designed, collected, and governed as an organisational asset rather than a project-level administrative record. It includes readiness assessments, adoption metrics, impact analyses, and stakeholder data that are standardised across programmes and retained for portfolio-level analysis and longitudinal learning.
Why is change management data difficult to manage strategically?
The primary challenge is that change work is traditionally organised at the project level, where data serves only the immediate programme. Creating strategic value from change data requires cross-programme standardisation, governance ownership, and retention infrastructure, none of which emerge naturally from project-centric delivery structures.
How does data maturity affect change management outcomes?
Capgemini Invent’s research found that organisations with high data maturity in their change programmes achieve 27% higher success rates. The mechanism is that mature data management enables faster, more targeted interventions, better portfolio decisions, and more credible reporting to executive stakeholders, all of which directly improve adoption outcomes.
What role does AI play in change management data?
AI tools in change management primarily serve as pattern recognition and signal amplification tools. They can process large volumes of survey data, monitor multiple data streams simultaneously, and flag anomalies in adoption curves that warrant human attention. They do not replace the judgment, relationship, and strategic capabilities of change practitioners; they help those capabilities operate at a scale that manual analysis cannot support.
How should change data be governed?
Effective governance for change data requires a designated data steward, documented standards for data definitions and collection methods, a quality review cycle (typically quarterly), and a retention policy that specifies how long data from completed programmes is preserved and in what format. Governance does not need to be complex, but it does need to be explicit and owned.
Where should an organisation start in managing change data more strategically?
Start with taxonomy. Agree on consistent definitions for impact rating, readiness scoring, and adoption stages across your active change portfolio. Apply those definitions in your next programme cycle. Retain the data when programmes close. Then, at the end of a 12-month cycle, review the combined dataset and ask what questions it can answer that you could not previously answer. The value of the investment will be visible in the first year.
References
Capgemini Invent. Change Management Study 2023. https://www.capgemini.com/insights/research-library/change-management-study-2023/
Capgemini. Data-Driven Change Management is Crucial for Successful Transformation. https://www.capgemini.com/news/press-releases/data-driven-change-management-is-crucial-for-successful-transformation/
ResearchGate. The Role of Change Management in Enhancing Data-Driven Decision Making: Insights from Business Intelligence Initiatives (2024). https://www.researchgate.net/publication/384017092_The_Role_of_Change_Management_in_Enhancing_Data-Driven_Decision_Making_Insights_from_Business_Intelligence_Initiatives
Prosci. The Correlation Between Change Management and Project Success. https://www.prosci.com/blog/the-correlation-between-change-management-and-project-success
Panorama Consulting. Top Organizational Change Management Trends for 2025. https://www.panorama-consulting.com/top-change-management-trends-for-2025/
As the global landscape continues to evolve, so too does the field of change management. The year 2024 promises a shift in the way organizations approach change, driven by a combination of economic factors, continued technological advancements, and the ever-increasing need for adaptability. In this article, we explore the background factors influencing the upcoming changes, and delve into seven key predictions that are set to reshape the realm of change management in the coming year.
Background
Inflation Continue to Drop: A Ray of Economic Hope
One of the pivotal factors shaping the economic landscape in 2024 is the anticipated drop in inflation. After grappling with economic uncertainties, organizations can breathe a sigh of relief as the pressure from rising costs eases. This economic respite paves the way for strategic investments and initiatives, creating a conducive environment for change.
Avoiding Recession: Building Resilience Through Change
The specter of recession has loomed large in recent years, casting a shadow on organizational stability. However, as we step into 2024, the concerted efforts to avoid recession is forecasted to have paid off. Organizations have become more resilient, honing their ability to weather economic storms through strategic change initiatives. This backdrop sets the stage for a transformative year in change management.
Key Predictions
Agile Change as Business as Usual
In 2024, the concept of Agile Change is no longer a mere ‘work in progress’ but rather an integral part of Business as Usual (BAU). Organizations have recognized the need for agility in the face of rapid change, and Agile change methodologies have transitioned from experimental to foundational. This shift represents a change in mindset, emphasizing iterative processes, collaboration, and responsiveness to evolving circumstances. After more than 10 years of agile project methodology in the market place, agile change practices are starting to become ‘the norm’.
The Rise of Adaptive/Hybrid Change Models
Building on the previous point, agility applies beyond at an ‘intra-methodology’ perspective, but also how change approaches and methodologies need to be mixed and matched to work.
The increasing pace of change demands a more flexible approach from change practitioners. The dichotomy between structure and flexibility, innovation and process-focused strategies, gives rise to adaptive and hybrid change models. The emergence of terms like “wagile” (a fusion of waterfall and agile) underscores the need for a balanced approach that combines the best of both worlds. Organizations must strike a delicate balance between structure and flexibility to navigate the complexity of modern change initiatives.
For example, in regulated business functions there may need to be quite rigid planning of exactly when the changes must take place as well as the level of consultation and engagement required. However, the actual design of different engagement, positioning and employee involvement strategies may be tested in an iterative way.
Expanding Skill Sets for Change Practitioners
To meet business needs change practitioners will need to have a broader range of skills beyond ‘people skills’. In 2024, the demand for change professionals with a broader skill set encompassing strategic thinking, digital/data literacy, and business acumen will continue to be on the rise. As change initiatives become more complex, practitioners must equip themselves with multifaceted skills to address the diverse challenges that emerge during the change process.
For example, stakeholders are increasingly looking for data for reporting purposes to get a clearer sense of how changes are tracking. Beyond sentiments and opinions, stakeholders are looking for adoption indicators as well as precise indications of the nature of impacts across the employee population.
The Ascendance of Change Portfolio Management
Change portfolio management will continue to gain increasing visibility and importance in 2024. Organizations are recognizing the need to manage change initiatives collectively, aligning them with strategic objectives. The holistic oversight provided by change portfolio management enables organizations to prioritize, monitor, and evaluate change initiatives in a comprehensive manner, ensuring that resources are optimally allocated for maximum impact.
Whilst stakeholders may not be clear of the differences between transformation, portfolio management and change portfolio management, they are clearer of the benefits required in managing people impacts, against the need to maximise business performance and change adoption.
Leveraging Change Data for Informed Decision-Making
In the evolving landscape of change management, data is no longer just a nice-to-have; it’s a necessity. In 2024, the norm becomes leveraging change data to make informed decisions. Organizations recognize the value of data analytics in understanding the impact of change, identifying patterns, and proactively addressing challenges. This data-driven approach enhances the efficacy of change initiatives and provides a foundation for continuous improvement.
It is no longer that the expectation for data-led decision making rests in project functions such as technical development, business analysis, testing and user-experience. Change management teams are also expected to demonstrate the impact of their work through data.
Increasing Use of Software in Change Implementation
The leverage of software in change implementation should see an uptick in 2024, along with general increase in software usage rates in organisations. Organizations are leveraging technology to streamline and enhance various aspects of the change management process. From change project management tools, change measurement platforms, as well as change portfolio management tools the role of software can accelerate the pace of change initiatives and supports the realisation of benefits.
AI for Change: From Wait-and-See to Full Adoption
Artificial Intelligence (AI) for change management is no longer a ‘wait-and-see’ proposition; it’s a reality in 2024. In 2023 a lot of users have sat on the fence as others argue about the risks in using AI and data security. The launch of Microsoft Co-pilot and the continued adoption of Chat GPT 4 signal a paradigm shift in how organizations approach AI. Users will over time be used to asking a chat bot, using prompts to form analysis and other AI features to augment their work. Advanced AI change tools can also assist in decision-making, predictive analytics, and even virtual facilitation, revolutionizing the efficiency and effectiveness of change processes.
In addition, there will be significant interest in change management tools that have incorporated AI features, from data and trend analysis, risk analysis to recommendations on change approaches.
As organizations navigate the complexities of 2024, change management emerges as a critical linchpin for success. The predictions outlined in this article reflect an emerging shift in the approach to managing change, from the integration of Agile methodologies to the widespread adoption of AI. Change practitioners must equip themselves with a versatile skill set to thrive in this dynamic environment, where strategic thinking, digital literacy, and adaptability are paramount. As we stand on the cusp of a transformative year, organizations that embrace these predictions are poised not only to weather the winds of change but to harness them for sustained success.
In this Change Practitioner Q&A series, we talk to change managers to ask them how they approach their work. This time we are talking to Annah Kaspar.
Change Compass: Describe yourself in 3 sentences
Annah: I’m curious and a little irreverent because I want to know everything (except, controversially, about football). I love to hear people’s stories and tend to empathise deeply. Happiness is going to places I’ve never been, and hanging out with kind and interesting people.
Change Compass: What has been the most challenging situation for you as a change practitioner? Tell us what happened and how you fared through it.
Annah: It was not due to a type of change or a stakeholder group. It was working with a Program Manager who believed change management was an independent addendum of sorts, separate from the ‘main work’ of technology and process. They didn’t see how project stream interdependencies have a direct correlation to the quality of change outcomes, or that the best change outcomes occur when all project team members collaborate. This played out dreadfully when the PM refused to prioritise a gap analysis, despite this being a dependency for identifying changes and impacts.
The PM was unfamiliar with the flow-on effects. Unclear changes and impacts create ineffective change strategies, poor forecasting of time/effort/budget, ineffective stakeholder engagement and misaligned key messages. This creates low confidence in project solutions and poor adoption and change experience.
How did I fare? Suffice it to say it wasn’t fun for me or the stakeholders, and by that time the root cause (no gap analysis) was an abstract concept. I believe delivery alignment within a project team is one key indicator for delivery effectiveness across an organisation. When there are transparent and integrated project delivery plans and open dialogue about how all project team members play a valued role, then I know we can deliver superb change outcomes.
Change Compass: What are the most useful things to focus on when you first start on a project, and why.
Annah: I make a beeline for the project Business Case, or if there isn’t one, I work with others to get clear on the project drivers, especially the benefits. This is the ultimate ‘why’. If there are no connections between the project’s Business Case and the organisation’s strategy then I look to create these, otherwise the project is in trouble before it has even started.
All project outcomes, scope and solutions flow from the case for change. The next most important is a High Level stakeholder scan and a High Level impact scan. This requires data, data, data! The more the better, as it increases the odds of making better judgments. So even though it’s early days, it’s never too soon to capture data, and for that, you need the whole project team onboard with the critical role of collecting and validating it so you can optimise the delivery approach.
Change Compass: As change practitioners we don’t often get to stick around to see the fruits of our labour, but from your experience what are the top factors in driving full change adoption?
Annah: I was once on the receiving side of change, so I have strong views about this! If these four things are covered, then you’ve achieved sustainability:
Active & visible leaders who advocate for the changes and put their reputation on the line to support success,
A project team who co-creates integrated delivery strategies with impacted people
Direct feedback loops for impacted people. These need in-built response mechanisms and complete psychological safety. No feedback should ever be punished or dismissed
Post-project monitoring of key performance indicators (team and individual) with corresponding rewards to reinforce desired results and support where required to uplift results
Change Compass: You’re known to remain calm when there is a lot of stress and project drama around. What is your advice for others?
Annah: My tough but fair mentor once advised me to think up worst-case scenarios to prepare for challenges. It seemed counter-intuitive and overly negative at first, and would stress me out more! But over time, I saw that I too fall into the category of a perfectly nice and reasonable person who is overwhelmed by fear.
This mostly leads to unhelpful perspectives (cognitive distortions or ‘thinking traps’), unhelpful behaviours (character assassination, shutting down, unnecessary displays of overt authority etc) and ultimately a toxic workplace culture. So in difficult situations, the habit of thinking through not-so-great scenarios, combined with mindfulness, is just a basic form of risk management.
I’m now a huge advocate for speaking up early about risks and applying risk management to all aspects of project delivery. It’s not about ticking boxes. It’s about protecting us by counter-intuitively facing discomfort, creating emotional space for ourselves and others to regulate responses, and removing thinking traps so we can make those trade-off decisions to solve a project drama.
Change Compass: Thanks for sharing your experiences and wisdom with us Annah!
Not too long ago, ‘change’ was predominantly linked to technological breakthroughs and process optimizations. Companies were driven to adopt new technologies and methodologies to stay ahead of the competition and meet the growing demands of consumers. The focus was on efficiency, productivity, and achieving higher profits through innovation. Terms like ‘digital transformation’ and ‘disruption’ frequently dominated boardroom discussions and industry conferences.
It has been that the focus was mostly on technology and process. These were considered the ‘hard’ levers that can be pulled to gain significant business improvements. Companies have been spending big on digitizing their business to save costs and investing in streamlining processes as well.
However, the narrative has shifted.
While technology continues to advance at an unprecedented pace, ‘change’ has taken on a more profound and holistic meaning. Today, companies and people, in general, are recognizing that the ability to adapt, evolve, and respond to the world’s myriad challenges is the true essence of progress.
One reason ‘change’ has become a prevailing buzzword is its resonance with a broader audience. Unlike technical jargon, it connects with people on a more personal level, emphasizing that change is not just about adopting new tools and strategies, but about embracing growth and personal development. It speaks to the capacity of individuals to navigate uncertainties, adjust their mindset, and embrace continuous learning.
Moreover, an increasing percentage of companies are aware that their success hinges on the collective ability of their employees to adapt and remain agile. Leaders now recognize that fostering a culture of change and learning is crucial for attracting and retaining talent, boosting employee morale, and nurturing innovation.
Looking around us, the word ‘change’ is everywhere. Not only are people a lot more comfortable talking about change, but there is also a general acknowledgment of change as an overt occurrence.
Advertising and Slogans: Embracing the Spirit of Change
Companies are also quick to adopt the word ‘change’ in their jargon. Here are some examples.
Cisco “Changing the Way We Work, Live, Play, and Learn”
Cisco, a multinational technology company, explicitly uses the word ‘change’ in its advertising and philosophy. The slogan “Changing the Way We Work, Live, Play, and Learn” highlights Cisco’s focus on transforming various aspects of modern life through their technological solutions.
2. Accenture – “Let there be change”
Accenture, a global consulting and professional services firm, uses the phrase “Let there be change” in its advertisements and marketing materials. This tagline reflects the company’s focus on driving transformative change for its clients and within the industries it serves.
3. T-Mobile – “Change starts now”
This encapsulates the company’s commitment to driving transformation and initiating positive changes in the telecommunications industry. The slogan suggests a sense of urgency and empowerment, encouraging customers to take action and embrace the benefits of a new era in mobile communication.
4. PwC – “Solving for global change starts with you”
This tagline conveys the idea that PwC believes individuals have the power to drive positive change on a global scale. It encourages people to take action and play an active role in addressing global challenges and making a difference. By emphasizing that “you” are the starting point for solving global change, PwC highlights the importance of individual responsibility, innovation, and collaboration in creating a more sustainable and equitable world.
5. University of Technology Sydney “Think. Change. Do.”
This represents UTS’s commitment to fostering a transformative learning experience that prepares its students to be active contributors to society and catalysts for positive change. However, please note that taglines can be updated or changed over time, so it’s a good idea to verify the most current information from UTS’s official sources.
The prevalence of ‘change’ in advertising and slogans reflects companies’ desire to connect with their audiences on a deeper level. By evoking the spirit of change, these companies emphasize their commitment to innovation, customer-centricity, and positive societal impact. They appeal to consumers who seek purpose-driven brands and are eager to embrace progress and sustainability.
Change as a Catalyst for Resilience
In an ever-changing world, adaptability is synonymous with resilience. Companies that can quickly adjust to market shifts, economic downturns, and unforeseen challenges are more likely to thrive. ‘Change’ has thus become the rallying cry for building organizations that are not only successful but also capable of weathering storms and bouncing back from setbacks.
What this means for change practitioners
Change practitioners are in an excellent position to help organisations to shift their change capability and deliver on business improvement objectives. Change is increasingly acknowledged across organisations as a critical competency. The focus on change is there and change practitioners should use this to spearhead the momentum.
What next?
To take things to the next level, change practitioners must complement the upscaling of digitization and AI in organisations by augmenting the same in their work. This means incorporating more machine learning and AI, more digitization, and greater usage of data.
Change practitioners should ensure data is a core part of their practice and a foundational way of formulating change approaches and recommendations to their business stakeholders. Business leaders will increasingly leverage data across all business facets in business management, enabled by digital solutions. In a similar manner, change practitioners must also leverage digital solutions to automate and increase the effectiveness of change work.
Within an increasingly complex change environment, change practitioners should be well-versed in collecting and analysing data and generating data insights, again leveraging digital solutions. With the promise of AI and machine learning, there is already plenty of current opportunities to improve the effectiveness of change work, today. The uptake of this is up to each change practitioner.
The rise of ‘change’ as a popular buzzword reflects the transformative times we live in. As technology continues to shape the world around us, it is the capability of human beings to adapt and evolve that has taken center stage. From technological advancements to human adaptability, ‘change’ has transcended industries and become a part of our collective consciousness. For change practitioners, this is an opportune time to use this momentum to ramp up their own adoption of the digitization of change work and use this to improve the effectiveness of change.
Change management professionals often struggle with proving the worth of their services and why they are needed. There are certainly plenty of reasons why change management professionals are required and most experienced project managers and senior leaders would acknowledge this. However, for the less mature organisations that may not have had effective change management experts leading initiatives, the rationale on the additional value of change management may be less clear.
When we look across different project members and project teams, it is easy to argue that without developers, the technical project cannot progress. Without business analysts, we cannot understand and flesh out the core business steps required in the initiative. And of course, we definitely need a project manager for a project. But, what’s the justification for a change manager? Many projects have other project or business representatives do the change work instead.
As an attempt to justify in a very direct way, the value of change management, many resort to ROI calculations and aim toward higher ROI. This ROI of change management may seem like a great way to convey and show in a very direct and financial way, the value of change management towards project success. After all, we use ROI for calculating projects, why not use the same for change management as well to value the people side of change?
There are plenty of articles on how to best calculate change management ROI. Here are a couple:
1. PROSCI
Prosci has a good, clear way of calculating change management ROI within a project (though it doesn’t take into account speed of adoption). You simply evaluate to what extent employee adoption is important to the project. Then you take the overall expected project benefits and deduct the part of the expected benefits if there was no adoption. This is termed “people side benefit contribution”.
People Side Benefit Contribution = Expected Project Benefits – Expected Project Benefits (if adoption and usage = 0)
People Side Benefit Coefficient = People Side Benefit Contribution / Expected Project Benefits
2. Rightpoint
Rightpoint has a variation to this calculation. They have added ELV (Employee Lifetime Value) to the calculation.
Using ROI may be useful when the cost of the initiative is the critical focus for the organisation for its strategic investment. However, it is not the only way to convey the overall value of successful change management. In addition, the ROI method limits the value of change management to focus on the cost invested versus the value created. Also, this type of calculation limits the value of change to a project by project perspective.
So, how else do we show the direct financial value of change management? Let’s look to research. It turns out there are plenty of research examples. Here are some:
McKinsey & Company. (2016). The people power of transformations. This study found that transformation initiatives are 5.8 times more successful if CEOs communicate a compelling change story, and 6.3 times more successful when leaders share messages about change efforts with the rest of the organization. Link here.
Korn Ferry. (2018). Engaging hearts and minds: Preparing for a changing world. This study found that calls out change as a key trend found that companies with high levels of employee engagement had 4.5 times higher revenue growth compared to companies with low levels of engagement, noting that all companies are undergoing change. Link here.
IBM. (2016). Making change work … while the world keeps changing. This study found that 76% of successful projects include change management activities at the beginning of their overall project plans, which is 33% more than less successful projects. Link here.
IBM. (2015) Why a business case for change management. The article references a survey carried out in 2010 where companies that apply a value (benefit) realization approach (of which change management is a core component) complete projects at least twice as quickly and under budget by a factor of at least 1.9 times, Compared to those that don’t. Link here.
Towers Watson. (2013). Change and communication ROI. Organizations with highly effective communication and change management practices are more than twice as likely to significantly outperform their peers in total shareholder returns, versus organizations that are not highly effective in either of these areas. Link here.
Prosci. (2020). Best Practices in Change Management 11th Edition. The paper referred to a Prosci study that found that projects with excellent change management practices 6 times more likelihood of meeting project objectives than those that are poor. Link here.
So the value the importance of change management, let’s take a comparison to see the difference in using a ROI calculation of the value of change management versus using findings from the above research findings to demonstrate the derived value.
Let’s take a typical project example. Company A has ….
Annual revenue of $1 billion with 5% profitability
The revenue growth is 1%
Project A costs $1Million and is targeted for $3 million in benefits.
If the expected project benefits without adoption would be $1Million, then, the people-side contribution is …
$2Million / $3Million = $667K.
Let’s contrast this to other calculations using research.
Research findings | Calculation
Korn Ferry study where companies with high levels of employee engagement had 4.5 times higher revenue growth compared to companies with low levels of engagement. Taking a very conservative approach of portioning on 1/3 of employee engagement linked to change, this means 1.5 times higher revenue growth. | Taking a very conservative approach of portioning 1/3 of employee engagement as linked to change, this means 1.5 times higher revenue growth. This means if the revenue growth is 1%, then the additional revenue is $15 Million per year.
You can see that $15 million in value is much higher than the $667K in initiative ROI. From these examples, you can see that the financial value dwarfs that from the ROI calculation. On top of this, these are from research findings, which may have a stronger perceived validity and be easier to be trusted by stakeholders than the ROI calculation.
To point out, it is not an apple-to-apple comparison between the change management ROI from one initiative to the organisational value of change management across initiatives. However, the call out is that:
The financial value of change management does not need to be limited to individual initiatives
The sum may be greater than its parts. Rather than measuring at initiative levels, research findings are looking at organisational-level value
The value of change management may be more than cost, but also other value drivers such as revenue
As change management practitioners we should not shy away from calling out and citing the value of change management. Cost may be one value, but the true benefit of change management is both the top line as well as the bottom line. Directly referring to the research-backed findings also helps to highlight its value size and importance.
To do this, we should also work to deliver organisational value in managing change and not limit ourselves to one initiative. Focus on uplifting change management capability in the forms of leadership styles, change governance, change analytics, and change champion network capability, just to name a few.
