Every change management team can describe what they did. Very few can demonstrate what difference it made. This measurement gap is not just an inconvenience; it is the single biggest reason change management struggles to secure resources, retain executive attention, and prove its value as a strategic function.
The data makes the case unequivocally. Prosci’s benchmarking research across 2,600 practitioners found that 88% of projects with excellent change management met or exceeded their objectives, compared to just 13% with poor change management. Gartner’s 2025 research found that organisations achieving healthy change adoption report two times higher year-over-year revenue growth. The correlation between effective change management and business performance is not in question. What is in question is whether your organisation can measure it.
This guide provides a practical framework for measuring change management success, from selecting the right KPIs to designing dashboards that influence executive decisions.
The measurement problem: activities versus outcomes
The most common mistake in measuring change management success is confusing activity with impact. Counting the number of communications sent, training sessions delivered, or stakeholder meetings held tells you nothing about whether anyone changed their behaviour. Yet these activity metrics dominate most change management reports.
Why activity metrics persist
Activity metrics are easy to collect, which is precisely why teams default to them. They also feel productive to report. But they create a dangerous illusion: a team that has delivered 40 training sessions and sent 200 communications can appear highly effective while the change itself is failing.
The shift to outcome measurement
Measuring change management success requires tracking what actually changed as a result of your interventions, not just what interventions you delivered. This means measuring whether people are using new systems, following new processes, demonstrating new behaviours, and whether those behavioural changes are producing the business outcomes the initiative was designed to achieve.
Prosci’s research on change management metrics reinforces this point: of organisations that measured compliance and overall performance, 76% met or exceeded project objectives. Among those that did not measure, only 24% achieved the same result.
A three-tier metrics framework for change management success
Effective measurement organises metrics into three tiers, each serving a different purpose and measured at a different point in the change lifecycle.
Tier 1: Leading indicators (pre-change and early implementation)
Leading indicators tell you whether the conditions for successful adoption are being established. They are predictive: if leading indicators are weak, adoption will almost certainly fall short.
Key leading indicators include:
Awareness levels: Percentage of affected stakeholders who can articulate what is changing and why
Sponsor engagement score: Frequency and quality of visible sponsorship behaviours (rated by direct reports, not self-assessed)
Readiness assessment results: Composite scores from structured readiness evaluations across impacted groups
Training effectiveness: Post-training knowledge assessment scores (not just completion rates)
Sentiment indicators: Employee pulse survey results on confidence, concern levels, and perceived support
Tier 2: Adoption indicators (during and post-implementation)
Adoption indicators measure whether the target population is actually using, following, or demonstrating what the change requires. This is where most measurement programmes either succeed or fail.
Key adoption indicators include:
System usage rates: Login frequency, feature utilisation, and transaction volumes in new systems
Process compliance: Percentage of transactions following the new process versus the old one
Behavioural observation data: Manager-reported or peer-reported evidence of new behaviours in practice
Error and rework rates: Declining error rates indicate proficiency is building; stable or rising rates indicate adoption gaps
Support ticket trends: Decreasing support requests over time suggest growing self-sufficiency
Impact indicators connect change adoption to the business outcomes the initiative was designed to deliver. This is where change management proves its strategic value.
Key impact indicators include:
Business outcome metrics: Revenue, cost savings, productivity gains, or customer satisfaction improvements attributable to the change
Sustained adoption rates: Usage and compliance levels 90 and 180 days post-implementation (not just at go-live)
Employee experience scores: Engagement, wellbeing, and voluntary turnover in heavily impacted groups
Speed to proficiency: Time from go-live to target performance levels
Return on change investment: Ratio of realised benefits to total change management investment
Leading versus lagging indicators: a comparison
Understanding the distinction between leading and lagging indicators is essential for designing a measurement approach that is both predictive and evaluative.
| Dimension | Leading indicators | Lagging indicators | |———–|——————-|——————-| | Timing | Measured before and during change | Measured after implementation | | Purpose | Predict likelihood of success | Confirm whether success occurred | | Action value | High, can course-correct in real time | Lower, confirms outcomes retrospectively | | Examples | Awareness scores, sponsor engagement, training effectiveness | Adoption rates, business outcomes, ROI | | Risk if ignored | You discover problems too late to fix them | You cannot prove value to stakeholders | | Data sources | Surveys, assessments, observations | System data, financial reports, performance metrics |
The most effective measurement programmes balance both: leading indicators to steer decisions during implementation, and lagging indicators to demonstrate value after the fact. For a deeper exploration of measurement methodology, see our ultimate guide to measuring change management outcomes.
Seven KPIs every change management team should track
While the specific metrics will vary by initiative, these seven KPIs provide a solid foundation for measuring change management success across most organisational changes.
1. Stakeholder awareness rate
Definition: Percentage of impacted stakeholders who can correctly describe what is changing, why, and how it affects their role. How to measure: Short pulse surveys (3-5 questions) administered at key milestones. Target: 80%+ awareness before go-live.
2. Active sponsor engagement score
Definition: A composite score measuring the frequency and visibility of sponsor behaviours, including communication, participation in change events, and removal of barriers. How to measure: Monthly assessment by the change team using a standardised rubric, validated by team feedback. Target: 7/10 or above on a standardised scale.
3. Training proficiency rate
Definition: Percentage of trained users who demonstrate competency in post-training assessments (not just attendance). How to measure: Knowledge checks, simulations, or practical demonstrations administered after training. Target: 85%+ pass rate on proficiency assessments.
4. Adoption rate
Definition: Percentage of the target population actively using the new system, process, or behaviour as designed. How to measure: System analytics, process audits, or structured observations. Target: 70%+ within 30 days of go-live, 90%+ within 90 days.
5. Time to proficiency
Definition: Average number of days from go-live until users reach target performance levels. How to measure: Track performance metrics (speed, accuracy, volume) from go-live and identify when they reach pre-defined thresholds. Target: Varies by change complexity; benchmark against organisational norms.
6. Change saturation index
Definition: Number of concurrent changes impacting each stakeholder group, weighted by degree of disruption. How to measure: Portfolio-level change impact assessment mapping all initiatives against affected groups. Target: No group exceeds 2-3 significant concurrent changes.
7. Benefit realisation rate
Definition: Percentage of projected business benefits actually realised within the defined timeframe. How to measure: Compare actual business outcomes against the benefits case approved at project initiation. Target: 80%+ of projected benefits realised within 12 months.
Common measurement traps to avoid
Even well-intentioned measurement programmes can go wrong. Watch for these patterns:
Measuring too late. Waiting until post-implementation to assess adoption means you have no opportunity to course-correct. By the time the data confirms a problem, the project team has moved on. Build measurement into every phase, starting with leading indicators well before go-live.
Activity metrics masquerading as outcomes. “We delivered 40 training sessions” is not a success metric. “85% of trained users passed the proficiency assessment” is. Always ask: does this metric tell me whether anything actually changed?
Vanity metrics. High email open rates and training attendance figures look good in reports but tell you nothing about whether behaviour changed. Focus on metrics that are uncomfortable to report when they are low, because those are the ones that matter.
Single-point-in-time measurement. Adoption at go-live is not the same as sustained adoption. Many changes show strong initial compliance that erodes within 90 days. Measure at 30, 90, and 180 days post-implementation to track sustainability.
Ignoring the portfolio view. Measuring success for each initiative independently can mask portfolio-level problems. A team that successfully adopted one change may have done so at the expense of another. Measure change management success at both the initiative and portfolio level.
How digital analytics platforms support measurement
WTW’s 2023 global study of 600 organisations found that companies taking a data-driven, proactive approach to change management drove nearly three times more revenue than those with below-average change effectiveness. The implication is clear: measurement is not just a reporting exercise; it is a competitive advantage.
Digital change management platforms such as The Change Compass enable organisations to track adoption metrics across the full change portfolio in real time, aggregate leading and lagging indicators into decision-ready dashboards, and identify measurement gaps before they become blind spots. For organisations managing multiple concurrent changes, these platforms replace manual spreadsheet tracking with continuous, portfolio-wide measurement intelligence.
To measure change management success effectively, stop counting what you did and start tracking what changed. Build a three-tier measurement framework that captures leading indicators early enough to steer decisions, adoption indicators during implementation to confirm behavioural change, and impact indicators after implementation to prove business value. The organisations that measure change management success rigorously do not just deliver better projects; they build the evidence base that secures ongoing investment in change capability.
Frequently asked questions
What are the most important KPIs for change management? The most critical KPIs are adoption rate (percentage of the target population using the new system or process as intended), sponsor engagement score, time to proficiency, and benefit realisation rate. These four metrics collectively measure whether the change was adopted, supported, efficient, and valuable to the business.
How do you measure change management ROI? Change management ROI compares the realised business benefits of a change initiative against the total investment in change management activities. Calculate it by quantifying the financial value of benefits achieved (cost savings, revenue gains, productivity improvements) and dividing by the total cost of change management resources, tools, and time. Express as a ratio or percentage.
What is the difference between leading and lagging indicators in change management? Leading indicators are predictive metrics measured before and during implementation, such as awareness levels, sponsor engagement, and training proficiency. Lagging indicators are retrospective metrics measured after implementation, such as adoption rates, sustained usage, and business outcome improvements. Both are essential for a complete measurement picture.
How soon after implementation should you measure change adoption? Measure at three intervals: 30 days post-implementation for initial adoption and early usage patterns, 90 days for sustained adoption and proficiency development, and 180 days for embedded behaviour change and benefit realisation. Single-point measurement at go-live is insufficient because it captures compliance, not true adoption.
Why do most organisations struggle to measure change management success? The most common barriers are reliance on activity metrics rather than outcome metrics, lack of pre-defined baselines against which to measure progress, absence of portfolio-level measurement capability, and insufficient integration between change management data and business performance data. Addressing these gaps requires both a measurement framework and the tooling to execute it at scale.
How do you build a change management measurement dashboard? An effective dashboard organises metrics into the three tiers (leading, adoption, impact), displays them against targets and baselines, and updates in near-real time. Include traffic-light indicators for at-risk metrics, trend lines showing trajectory over time, and portfolio-level aggregation across all active initiatives. Design it for the audience: executives want outcomes and ROI; project teams want adoption trends and risk indicators.
Suggested title: How to measure change management success: KPIs, metrics, and frameworks for 2026
Suggested meta description: Discover a 3-tier framework for measuring change management success with 7 essential KPIs. Move from activity tracking to outcome measurement.
Is change management just a job or a career? When you clock in and clock out everyday do you ever wonder what is the purpose of all this work? Yes, your natural response could be, well, managing change helps improve employee work experience and we help company land initiatives. We help maximise initiative benefits. Is this all? And are these the only ultimate outcomes?
For those of us who have made change management a career, we often roll out eyes across initiatives as we see common trends and occurrences across initiatives. What would have been highly stressful or dramatic is just seen as ‘yet again’ more of the same. You know what I mean …
Sponsors who only show up for announcements and ghost the project team the rest of the time
Corporate communications wrestle you to the ground by taking out factual information about the initiative that are critical
You send out a series of initiative communications and the impacted teams rarely read them
Some of your stakeholders nod and agree furiously in project meetings and do nothing afterwards, despite repeated engagement and consultations
Thanks for corporate-wide budget cuts, your project is now sliced into bare bones, and all the work required to drive behaviour change evaporate into thin air, to be replaced by a pure system implementation
Don’t get me wrong. There is definitely a lot of organisational benefits in managing change. There are definitely ample studies that draw attention to how, without successful change efforts, initiatives are doomed for failure. We definitely play a key role in achieving those hefty millions in benefits that are targeted. Also, let’s not forget that most of us are in this because we care about people. We truly believe that creating a good experience for people is the essence of what drives successful change.
The big questions is – what is your purpose and the meaning you are striving for when you work in change management? Beyond the cheque that pays the bills, why do we work hard to improve how change is managed? What is our north star? What truly motivates through thick and thin, through obstacles that stakeholders put along the way?
This is a personal question and not always an easy one to answer. There are some who are happy to go to work, get paid, ignore the BS within the corporate environment, just to feed their family and pay the mortgage. Others may have stumbled into change management and find it interesting work. However, to really strive in leading change, year after year, initiative after initiative, there would need to be some kind of burning flame inside you that keeps pushing you forward.
Exploring your own motivation in driving change not only helps you to understand your own behaviour and the source of your energy, it also helps you be clear about what you really care about. Clarity about your passion helps you to know what to reach for next time you are feeling down about how the project is going, or none of your change tactics are panning out.
For me, the meaning of managing change is only realised after experiencing a series of bad changes. Let me share more. I’ve worked for organisations where I have seen how hurtful and how traumatic bad changes have been for employees. A typical context is organisational restructuring. These are just a few examples what could happen ….
Employees are marched out by security after having lost their jobs on the day of the announcement, in case they retaliate and ‘steal’ company secrets, in public display for everyone to see
Leaders lie through their teeth about what is going to happen to the restructure in order to keep the workers productive, and eventually everyone realises it’s all been a series of lies and fabrications
Consultants are brought in to do the analysis and leaders basically reference what the message is from consultants, without interpreting what this really means for their people. Employees with years of tenure who have significant insight into how to improve business outcomes are ignored
In order to gain better roles and responsibilities managers backstab each other and even team members to jostle their way to favourite positions in the new org chart
For the individuals involved it could be such traumatic experiences that they may be scarred by the experience. Counselling may be required and organisational stress levels may be through the roof. It is not just those individual employees, but their families and friends could also be impacted like ripples in a pond.
Even if you don’t focus on the most dramatic of changes, a series of smaller badly run changes can still impact employees, their belief in the company, their trust in management, their work life health as well as overall health. Multiple smaller changes can add up.
So for me, the real meaning behind managing and leading change is about all those individuals that could be impacted, whether it be employees, customers or partners. Each is a person with a set of circumstances. They may be dealing with other stressors in their family or friendship circles already, or that they may be particularly vulnerable. This is particularly the case in our virtual working world.
Every person deserves to lead a happy, healthy work life. And change is such an important and memorable part of working life that every life you touch is a touch of dialling up the happiness/health level. It may not be the jumping up and clicking heels type of happiness. It would be managing risks so that negative experiences are avoided or minimised. Now imagine a long list of multiple changes all effective managed. Such is the power of managing change. We touch working lives in profound ways.
This is why at The Change Compass our vision is to improve the experience of people during change. “People’s work lives shape who we are and bad change experiences can be traumatic. With great change experiences, we can change the world”.
Now, isn’t this something to get motivated about through thick and thin?
What is YOUR meaning in managing change? How have your experiences shaped your approach and belief in managing change? How do you keep going day in and day out especially when times are tough?
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!
