Organizations are in a constant state of transformation—whether adopting new technologies, undergoing structural changes, or responding to market changes. The success of these initiatives hinges on strong change management strategies that provide clarity and direction.
Yet, many transformation efforts fall short. According to Harvard Business Review, 70% of transformation efforts fail due to resistance and lack of support—a challenge that effective change management can help mitigate. Poorly defined objectives, inconsistent communication, and an absence of data-driven decision-making are common culprits. Without clear goals or the ability to measure progress, organizations risk employee pushback and stalled efforts, often due to misaligned resources or incompatible company culture.
A data-driven approach to change management helps organizations navigate these complexities with precision. Data helps leaders verify, understand, and quantify actions, allowing for informed business decisions. And decisions around change should be no different. Whether implementing a new technology or spearheading a major reorganization, using data as a guide provides a compass to steer change initiatives and make necessary course corrections.
# What is Change Analytics?
At Propeller, we believe that measuring and analyzing change adoption across impacted employees is essential. Of equal importance is understanding if the change in question drove anticipated business success. To ensure measurement outcomes that best meet goals and align with organizational capabilities, we look at two dimensions: adoption and success.
- Adoption - When impacted employees have successfully adopted a change, this means the shift in behavior goals has been met. To achieve this, you need to guide employees through the change journey. This is typically where most change measurement strategies and data collection activities stop.
- Success – Measuring success requires up-leveling your data collection strategy and expanding beyond the strict confines of your project guardrails. Business success means that not only have the behavior goals of the project been met but also that you can demonstrate that this behavior change is driving desired business outcomes.
Evaluating adoption measures against pre-defined targets lets you determine when the change journey can conclude. Analyzing key business metrics impacted by a change enables you to make informed, post-change business decisions. By considering both factors, you provide a data-driven approach that guides organizational strategy.
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# Importance of Data-Driven Decision Making in Change Management
Sound change management decisions are grounded in data. Without it, leadership choices can appear arbitrary or lacking justification. The right data provides not only guideposts but also acts as checks and balances, clearly defining what is and isn’t working while offering objective proof to stakeholders.
Data allows the change management strategy to be resilient. The continuous feedback loop that data provides allows strategies to be fluid rather than static. By modeling different scenarios, organizations can uncover potential risks early, providing the organization time to course-correct.
The right metrics also enable organizations to benchmark against industry peers. Data can show you how and where to allocate resources for optimal efficiency and effectiveness. Data illuminates areas of success and identifies opportunities for improvement, enabling a strategic alignment with long-term organizational goals.
# The Impact of a Data-Driven Change Management Strategy
At the heart of any data-driven change management approach is the belief that data magnifies intuition, leading to well-informed decisions that benefit both the employee and the business. Propeller’s two-part change management measurement methodology leverages data to drive adoption and measure business success, ensuring that each initiative delivers measurable impact.
By taking these steps and establishing a data-driven change program, you enable your organization to:
- Equip business leaders with the tools to understand and drive adoption.
- Make informed decisions around program go-lives or product launch readiness.
- Gamify change plans, increasing employee engagement and morale.
- Understand if the change had the desired result on business success measures and adapt accordingly.
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With data-driven insights, organizations can approach change management with precision, adaptability, and a clear understanding of how to foster employee adoption while achieving desired business outcomes. By leveraging these insights, change management strategies can be elevated from reactive efforts to proactive, strategically orchestrated transformations, ensuring sustainable growth and innovation.
# 5 Steps for Creating a Change Management Measurement Strategy
Most organizations are eager to implement a data-driven change strategy, encountering little stakeholder resistance. The challenge usually lies in how to gather and organize data in a way that is accessible and digestible by those who need to make project decisions. To prepare a change measurement strategy, you must follow a few key steps:
# 1. Establish Employee Adoption Goals
Adoption goals are established during the change journey and are often part of any solid change management strategy. These goals can be as straightforward as achieving a particular rating on sentiment scores or percent training completion. Similarly, project teams might set a goal of a percentage decrease in help desk tickets or time spent in the system after launch.
You should customize your adoption measurement strategy for individual stakeholder groups just like a training curriculum. Do managers need to score higher on readiness surveys? Should change champions rate higher levels of confidence in the new system? Should project Subject Matter Experts (SMEs) be held to a higher training score to pass? The goals set around adoption measures should be clear and communicated widely across the project team.
Tips to Ensure Successful Change Management
- Communicate the change management strategy early, effectively, and often
- Set specific goals
- Provide training and ongoing support
- Designate change management champions
- Track metrics and utilize data
- Include risk mitigation
- Be flexible; allow your change management strategy to shift as needed
- Share wins and success stories
# 2. Define Your Change Management Success Goals
Success goals, on the other hand, are independent of the change. Therefore, success goals must be established and baselined before the change journey begins and continue to be tracked after the change journey concludes.
Measuring success requires that you associate already established business metrics with the change. You can then understand how your change ultimately impacted those measures. Success measures may be defined as Key Performance Indicators (KPIs) depending on the organization’s priorities.
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Tying organizational change to business metrics ensures that changes are being implemented for reasons that will provide value to the organization. Below are business metrics often associated with common organizational changes.
# 3. Define Collection Methods
Once employee engagement and business goals have been defined, you can begin identifying the best data collection methods.
Change adoption tracks how employees engage in the change and meet or exceed expectations in the new way of working. Data collection for adoption can look like:
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# 4. Plan Around Project Milestones
Data collection is not a one-time push at go-live, nor does it require full throttle throughout the entire project. Your measurement strategy should be flexible to scale up and down as needed at various project stages.
- Kickoff and Planning - The early stages of the measurement are focused on analysis and assessment. This often translates to common change deliverables like stakeholder heat maps and change impact assessments. However, in the context of a broader and comprehensive measurement strategy, the project's beginning should also focus on establishing a baseline. For example, if you collect sentiment scores before going live, you must develop those questions and guidelines at the beginning to have a consistent data set for later comparison.
- Implementation – As the project progresses, the measurement strategy and data collection must also shift to focus on employee engagement and change readiness levels. As you get closer to the change, the measurement strategy should focus on tracking how people feel about the change and the new ways of working.
- Post Launch - Only after the change has occurred can you analyze the impact on business outcomes. This is the only project phase where success metrics can be considered in combination with adoption metrics.
A comprehensive measurement and data collection strategy spans the entire project lifecycle. The type of data to collect and whether to measure adoption or success depends on the proximity to the change, either before or after it.
“The companies best positioned to change in the next decade will be the ones that set themselves up well now, by collecting the right kind of data and investing in their analytics capacity.” - Harvard Business Review
# 5. Understand Data Maturity Capabilities
Finally, achieving a data-driven change program relies on the level of organizational analytic maturity. Setting realistic expectations upfront alleviates wasted time and unattainable goals. Depending on the type of measurement and analytics output requested, requirements may vary. However, three basic considerations are:
- Data Availability - Ensure the data required to measure outcomes is both accessible and in a usable format. Often, employee data gathered to measure adoption is collected using survey platforms that might contain only some relevant information. Be sure to consider how the data output must join with employee master data.
- Resourcing - Anticipate resourcing requirements for collecting, cleansing, and interpreting data. Remember, data transformation and data cleansing are routinely the most time-consuming part of analytics projects.
- Data Strategy - Have a predefined strategy to drive action based on the data collected, including targets for measures. For example, if you are measuring training comprehension, what target score do you hope to achieve, and how will you support employees who do not meet that score?
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# A Successful Change Management Process
A successful change management process begins and ends with data. To build a solid foundation, organizations must objectively assess areas for improvement and define clear goals supported by measurable outcomes. By creating a comprehensive plan—complete with timelines, steps, potential obstacles, resources, and budgets—organizations ensure alignment and buy-in from key stakeholders.
Throughout the process, data plays a pivotal role. It provides the insights needed to evaluate progress, refine strategies, and ensure continuous improvement. Consistent communication, backed by data, fosters alignment across teams and builds confidence in the change strategy. Training and resources tailored to employee needs further ease transitions and drive adoption.
At the conclusion of the process, data not only validates the success of the change strategy but also reveals its impact on business outcomes. The ability to integrate these changes into company culture—supported by measurable KPIs—ensures lasting value and organizational growth.
Need help implementing your change management strategy? Contact our experts.