A primary goal of any leadership development program is to create a tight alignment with overarching business objectives. For decades, many organizations treated leadership training as a “soft” benefit, a necessary cost of doing business with intangible outcomes. This approach is no longer sustainable. In an era of data-driven decision-making, every major investment, including the significant cost of developing leaders, must demonstrate its value. While it is critical to measure the effectiveness of leadership training, many organizations struggle, leading to the perception that learning outcomes are a challenge to quantify. This challenge, however, must be met. Failure to measure leaves these programs vulnerable to budget cuts and makes it impossible to know if they are solving the problems they were created to address.
This process of measuring learning effectiveness is known as calculating the learning return on investment, or “learning ROI.” This is not just a financial calculation; it is a holistic evaluation of whether the program initiated a positive change. Measuring the learning ROI from a leadership development program should, therefore, include a blend of both qualitative and quantitative metrics. These metrics must be capable of directly or indirectly linking the learning that occurred in a classroom or online module to the strategic objectives of the business. Without this link, a program is simply a collection of activities, not a strategic lever for organizational success.
The True Cost of Ineffective Leadership
Before embarking on measurement, it is vital to understand the problem we are trying to solve. The cost of not developing leaders, or of running ineffective programs, is staggering. Ineffective leadership is a primary driver of low employee engagement. Teams led by poor managers are less productive, less innovative, and experience more conflict. This directly impacts the bottom line through missed deadlines, lower quality work, and a stifled-of-ideas pipeline. Furthermore, a large body of research clearly indicates that the number one reason people leave their jobs is not pay, but their direct manager. The cost of this turnover, including recruitment, onboarding, and lost productivity, is a massive and often hidden financial drain.
Therefore, a leadership development program is not a luxury; it is a critical intervention aimed at solving these expensive problems. When we frame it this way, the “why” of measurement becomes crystal clear. We are not measuring to justify the training budget; we are measuring to confirm that our multi-million dollar “leadership problem” is being solved. The cost of the program, even if it seems high, is often a fraction of the cost of the problem itself. This reframing moves measurement from a simple administrative “check-the-box” to a core component of the organization’s financial and strategic health.
The First Phase of Analytics: Assessment
Experts in the field of training evaluation and measurement methods identify three distinct phases of learning analytics. The entire process begins long before a single course is designed, in the phase of assessment. This is the foundational diagnostic work. The assessment phase is all about understanding the “why” behind the program. What are the specific business needs that are prompting this investment? It is not enough to say “we need better leadership.” The needs must be specific. Are we trying to increase innovation, improve operational efficiency, or reduce employee turnover? Each ofa these is a distinct business need that will require a different leadership competency.
This phase must also include a clear-eyed analysis of the current performance gaps. Where, specifically, are our current leaders falling short of the desired state? This analysis should be data-driven, looking at existing metrics like employee engagement surveys, performance review data, and talent pipeline health. Finally, the assessment phase must define the precise skill requirements. What, exactly, does a “good leader” in our organization look like? What competencies and behaviors do they exhibit? Only after these business needs, performance gaps, and skill requirements are clearly defined and agreed upon can we begin to design a program, let alone measure it.
Defining and Aligning Business Objectives
The tight alignment to business objectives is the primary goal of any program, and this alignment begins in the assessment phase. Unfortunately, all too often, those responsible for designing leadership development programs fail to think carefully enough about these measures until after the fact, which makes any meaningful evaluation impossible. The selection of the right measures to drive business value, which must link to key performance indicators for the business, is crucial and must be done at the outset. This requires the learning and development team to act as strategic consultants, not just order-takers.
This alignment process involves deep conversations with senior business leaders. The question should not be “What training do you want?” but “What business problem are you trying to solve?” For example, if a senior executive is concerned about high employee turnover in a specific division, the business objective is to “improve retention.” The L&D team can then analyze the performance gaps of managers in that division and identify that they lack skills in coaching and performance feedback. The skill requirement becomes “coaching for development.” The program is then designed to teach this skill, and its success will be measured, in part, by tracking the voluntary turnover rate for the managers who attended the training. This creates a clear, measurable thread from the business objective to the learning program.
Identifying Performance Gaps with Precision
Once the high-level business need is established, the assessment must drill down to identify the specific performance gaps. This is the gap between “what is” and “what should be.” “What is” is the current state of leadership. This can be captured through a variety of data sources. Employee engagement surveys are a goldmine, as they often contain specific items about a manager’s effectiveness, such as “My manager provides me with regular, constructive feedback” or “I feel supported in my career development.” Low scores on these items are a clear indicator of a performance gap. 360-degree feedback data, if available, provides an even more direct and individualized assessment of a leader’s strengths and weaknesses as perceived by their direct reports, peers, and manager.
“What should be” is the desired state. This is defined by a leadership competency model. This model, which must be created with input from senior leadership and aligned to the company’s culture and strategy, outlines the specific behaviors and skills expected of leaders at each level. It answers the question, “What does a great leader do here?” By comparing the current state data (engagement surveys, 360s) against the desired state (the competency model), the organization can pinpoint the most significant and widespread performance gaps. These gaps then become the primary learning objectives for the development program.
Defining Skill Requirements and Competencies
With the performance gaps identified, the final step of the assessment phase is to translate those gaps into specific skill requirements. This is where broad concepts become concrete and actionable. For example, a performance gap like “leaders are not holding their teams accountable” is too vague. A deep analysis might reveal that the root cause is not a lack of desire for accountability, but a lack of skill in navigating difficult conversations. The leader may not know how to address underperformance in a way that is clear, fair, and constructive, so they avoid it altogether.
Therefore, the specific skill requirement becomes “conducting performance accountability conversations.” This is a skill that can be taught. The program can be designed with modules on setting clear expectations, gathering objective data, and using specific communication frameworks for feedback. This level of specificity is what makes measurement possible. It is difficult to measure if someone “became a more accountable leader.” It is much easier to measure if they “learned and applied the 5-step feedback model” in role-play scenarios (Level 2) and if their direct reports, six months later, agree that “My manager addresses poor performance on our team” (Level 3).
The Critical Role of Stakeholder Alignment
Throughout this entire assessment phase, the most important activity is securing stakeholder alignment. The “stakeholders” are not just the participants or the L&D team; they are the senior business leaders who are sponsoring the program and the frontline managers who will be expected to reinforce the new behaviors. If senior leaders are not aligned on the business objectives, the program will lack a clear mandate. If they agree the problem is “turnover” but the L&D team designs a program for “innovation,” it will be judged a failure regardless of its quality.
This alignment requires a formal and iterative process. The L&D team should present their findings from the assessment—the business needs, performance gaps, and skill requirements—to the executive sponsors in a formal review. This meeting is to gain agreement and create a “contract” that says, “We agree that this is the problem, these are the gaps, and this is what success will look like.” This shared definition of success, established before the program is even built, is the most critical component of an effective evaluation. It ensures that everyone is aiming at the same target, and it gives the L&dD team the clear, measurable outcomes they will be held accountable for.
An Overview of the Kirkpatrick Model
The most well-known and widely used framework for evaluating training programs is the Kirkpatrick Model. It provides a useful, four-level structure for establishing an objective assessment of a leadership development program, moving from the immediate and simple to the long-term and complex. The model acts as a pyramid, with each level building upon the one before it. Level 1, “Reaction,” sits at the base, followed by Level 2, “Learning,” Level 3, “Behavior,” and finally Level 4, “Results,” at the peak. A common mistake is to only measure Level 1 and claim success, or to try and jump straight to Level 4 without the proper foundation.
A comprehensive evaluation strategy must gather evidence at all four levels. It is this multi-level data that allows an organization to tell a complete story. For example, a positive Level 1 (participants liked the program) and a positive Level 2 (they passed the knowledge test) are good leading indicators. But if Level 3 data (their behavior did not change) is negative, it shows the program failed to transfer from the classroom to the job. This data is invaluable, as it tells the L&D team where the breakdown occurred. It allows them to diagnose the problem (e.g., the content was good but there was no on-the-job reinforcement) and fix it.
Level 1: Measuring Reaction
The first level of the Kirkpatrick model, Reaction, focuses on learner satisfaction and their general reaction to the training. This is the most common form of evaluation, often called a “smile sheet.” Program participants are given a questionnaire at the end of the program to rate their experience. The goal is to gauge how they felt about the program. Was the content relevant to their leadership role? Was it a good use of their time? Was the facilitator engaging? Was the room comfortable and the food good? These are all measures of satisfaction.
While often criticized as a “vanity” metric, Level 1 data is important. If participants hate the program, find it boring, or do not believe it is relevant, they are unlikely to be engaged enough to learn the material (Level 2), let alone change their behavior (Level 3). A negative Level 1 reaction is a powerful early warning sign that the program design, content, or facilitation is fundamentally flawed. Therefore, this data should be collected and reviewed immediately to make rapid adjustments. This survey can be administered through a simple questionnaire using an off-the-shelf cloud-based survey tool, making it easy and cost-effective to implement.
Designing Effective Level 1 “Smile Sheets”
To get the most out of Level 1, the “smile sheet” must be designed with more care than it usually is. A simple questionnaire that only asks participants to rate the “presenter” or the “room” on a scale of 1 to 5 provides very little actionable data. A more effective Level 1 survey should be designed to measure specific, relevant reactions that align with the program’s objectives. Instead of asking “Was the content good?,” a better set of questions would be “How relevant was this content to the daily challenges you face as a leader?” or “How confident are you in your ability to apply what you learned today?”
The survey should also ask participants to rate whether the training met the stated learning objectives and their own personal learning needs. Open-ended questions are also critical. Asking “What was the most valuable part of this program?” and “What is one thing you would change?” can provide rich, qualitative insights that simple ratings cannot. These questions probe at the perceived value and applicability of the program, which are much more powerful indicators than just satisfaction. They also provide concrete suggestions for continuous improvement.
Level 2: Measuring Learning
The second level of the Kirkpatrick model, Learning, seeks to determine whether learners actually gained the intended knowledge and skills from the leadership development program. This is a critical step up from Level 1. It does not matter how much participants liked the program if they did not learn anything. Level 2 is an assessment of the applicability of the learned information. Did the participants acquire the knowledge, skills, and attitudes that the program was designed to deliver? This level focuses on what they can do at the end of the program that they could not do at the beginning.
There are three key components to measure at Level 2: knowledge, skills, and attitudes. Did they know more? This can be measured with a pre- and post-test. Did their skills improve? This can be measured through role-play exercises, simulations, or case study analyses. Did their attitudes shift? This is harder to measure but can be captured through self-assessment surveys, such as asking about their confidence in their leadership abilities or their belief in the importance of coaching. The program designer should measure and assess all of these, as well as metrics like course usage, completion rates, and course pass rates, though these are measures of participation, not necessarily of learning.
Practical Methods for Measuring Knowledge Gain
Measuring an increase in knowledge is the most straightforward part of Level 2 evaluation. The most effective and objective method is the pre-test and post-test. Before the program begins, participants are given a test on the key concepts that will be covered. This establishes a baseline. At the end of the program, they are given the same test (or an equivalent version). The “delta,” or the difference in scores from the pre-test to the post-test, represents the quantifiable knowledge gain. This is a powerful, objective metric that clearly demonstrates whether the content was successfully transmitted and understood.
For example, if a leadership program has a module on employment law for managers, a pre-test might reveal that only 30 percent of participants can identify the legal “do’s and don’ts” of an interview. If the post-test shows that 95 percent of participants can now identify them, the L&D team has hard data proving the program was effective at increasing knowledge. These tests do not need to be complex. They can be multiple-choice, true/false, or short-answer questions delivered online. This data is not just for evaluation; it helps the facilitator understand which topics may need to be reinforced.
Assessing Skill Acquisition in Leadership
Leadership is not just about what you know; it is about what you can do. Therefore, measuring skill acquisition is arguably more important than measuring knowledge gain. Skills are best measured through observation and application, not written tests. This requires building assessment directly into the program design. The most common method is the use of case studies, simulations, and role-playing exercises. For example, if a program is designed to teach a specific coaching model, the assessment should involve having the participant conduct a live role-play coaching conversation with a trained facilitator or actor.
The assessor can then use a detailed behavioral checklist, or rubric, to score the participant on their ability to use the model. Did they establish rapport? Did they ask open-ended questions? Did they actively listen? Did they help the “employee” create an action plan? This provides a much richer and more accurate assessment of competence than a multiple-choice test. While more resource-intensive to administer, this type of skill-based assessment is the only real way to know if the participant can “do” the thing the program is trying to teach.
The “Application Outcome Survey”
Another valuable measure at Level 2, which bridges the gap to Level 3, is what can be called an “application outcome survey.” This is a follow-up questionnaire, typically sent a few weeks after the program, that asks participants to report on their own use of the learned skills. It is still a measure of learning (or perhaps “confidence to apply”) because it is a self-assessment, not an objective measure of behavior change (which is Level 3). However, it provides useful leading indicators.
To conduct this, you need to carefully craft questions to reflect the application of learned competencies and knowledge. For example, “In the past 30 days, how frequently have you used the 5-step feedback model we learned in the program?” or “Please rate your ability to apply the coaching skills you learned on a scale of 1 to 5.” While this data is based on self-perception and may be inflated, it is still a valuable way to gauge whether the content has “stuck” and whether participants believe they are using it. Low scores on this survey would indicate a significant problem with the program’s relevance or practical application.
Why Behavior Change is the Most Critical Level
Measuring behavior change, Kirkpatrick’s Level 3, is the most important and challenging pivot in the entire evaluation process. It is one thing for a leader to like a program (Level 1) and pass a test on its content (Level 2). It is an entirely different matter for them to take that knowledge and fundamentally change their on-the-job behaviors. This is the single biggest failure point for most leadership development initiatives. The “gap between learning and doing” is vast, and many programs fail to bridge it. Level 3 is designed to measure whether this transfer of learning from the “classroom” to the “workplace” has actually occurred.
The objective of behavior change measurement is to understand whether training was, in fact, transferred to on-the-job behaviors. It is designed to measure a learner’s actual competency and the extent of improvement in their leadership behaviors over time. This is the first level of evaluation that provides a true leading indicator of business results. If a leader’s behavior does not change, it is illogical to expect their team’s engagement or productivity (Level 4) to change. Conversely, if we can prove that leaders are applying the new skills, we can draw a much stronger and more credible line to any subsequent improvements in their team’s performance.
The Best Tool: The 360-Degree “Multi-Rater” Survey
The article states that the best way to conduct this kind of assessment is through the administration of multi-rater pulse surveys. This is a critical insight. A leader cannot be the judge of their own behavior. Self-perception is notoriously unreliable; many of the worst managers are unaware that they are the worst managers. The only objective way to know if a leader’s behavior has changed is to ask the people who experience that behavior every single day: their direct reports. The accumulated results of a multi-rater questionnaire provide an excellent source of data for determining behavioral learning outcomes.
This method, often called a 360-degree survey, is an objective assessment of program participants and their performance improvement (or lack thereof) in specific leadership behaviors. It is an assessment according to those who matter most. This type of feedback is not just for evaluation; it is one of the most powerful development tools in existence. Simply showing a leader the gap between their own self-rating and their team’s rating on a behavior like “provides useful feedback” can be a profound, motivating catalyst for change.
Designing Effective 360-Degree Survey Questions
The design of the 360-degree survey is paramount. The questions must be crafted with precision to be effective. A common mistake is to ask “rater” questions that are vague, subjective, or measure personality. For example, a question like “Is your manager a good leader?” is useless. It is a subjective label, and “good” means different things to different people. A well-designed 360-degree survey does not ask about labels; it asks about specific, observable behaviors.
The questions on the survey must be drawn directly from the leadership competency model and the learning objectives of the program. If the program was designed to teach a 5-step coaching model, the survey for that leader’s direct reports should include items like: “My manager helps me create a development plan,” “My manager asks insightful, open-ended questions,” and “My manager provides me with constructive feedback that helps me improve.” These questions are behavioral, observable, and directly measure the on-the-job application of the skills taught in the program. This direct alignment between the program’s content and the measurement tool is the key to an effective Level 3 evaluation.
Using a Pre-Test and Post-Test Methodology
To effectively measure change in behavior, we must have a baseline. The most robust way to do this is to use a pre-test and post-test methodology for the 360-degree survey. This means that a 360-degree survey is administered to the leader’s direct reports before the leader attends the development program. This “pre-test” provides a clear, quantitative baseline of the leader’s perceived behaviors before the intervention. It identifies their specific strengths and, more importantly, their development gaps, which can be used to help them focus their learning during the program.
Then, at a set interval after the program—for example, six months later—the exact same survey is administered to their direct reports again. This “post-test” allows for a direct, scientific comparison of the scores. Did the leader’s score on “provides constructive feedback” improve from 2.5 (out of 5) to 3.8? This is a quantifiable, objective measure of behavior change. This methodology is powerful because it isolates the leader’s individual improvement and provides clear data on the program’s impact. When aggregated across all participants, the L&D team can confidently report that, on average, participants improved their coaching behaviors by a specific percentage.
The Rise of “Pulse Surveys”
The source material specifically mentions “pulse surveys,” which are a modern evolution of the traditional 360-degree survey. A traditional 360 can be a massive, time-consuming event. It might involve 10 raters answering 100 questions and be conducted only once every one or two years. While powerful, it is not agile. A “pulse” survey, as its name implies, is a much shorter, more frequent survey designed to get a quick “pulse” on a specific set of behaviors. For example, instead of a 100-question annual survey, a team might receive a 5-question pulse survey once a month.
In the context of leadership development, pulse surveys are incredibly valuable. A program director could send a short, 3-question pulse survey to a leader’s direct reports every month for the six months following the program. These questions would be laser-focused on the specific skills taught in the training. This provides a real-time, iterative feedback loop. It allows the L&D team to see if the initial behavior change is “sticking” or if it’s fading over time. It also provides the leader with ongoing, “bite-sized” feedback, allowing them to make continuous, minor adjustments to their leadership style instead of waiting a full year for their next major review.
Ensuring Anonymity, Confidentiality, and Trust
The single most important factor in the success of any multi-rater feedback system is trust. The entire process hinges on the willingness of direct reports to provide honest, candid feedback about their manager. If they fear that their manager will see their individual responses and retaliate, they will not be honest. They will simply give “safe” scores, and the data will be completely useless for both development and evaluation. Therefore, the process must be built on a bedrock of guaranteed anonymity and confidentiality.
Anonymity means the data is aggregated. A manager should never receive a report unless a minimum number of raters, typically three or five, have responded. This makes it impossible to trace a specific comment or low score back to an individual. The data should ideally be collected by a neutral third-key, such as the L&D department or an external vendor, not by the leader’s direct HR business partner. The rules of this process must be communicated clearly and repeatedly to all participants—both the leaders and the raters. Any breach of this trust will permanently destroy the credibility of the program and the evaluation system.
From Level 3 Data to Actionable Insight
Collecting Level 3 data is only half the battle. The data itself does nothing. Its value is in its application. A leader who receives a 360-degree report showing a significant gap between their self-perception and their team’s perception needs support. Simply emailing them the negative report is demotivating and can even be destructive. This data must be delivered in a constructive, supportive context. Ideally, the leader should review their report in a one-on-one session with a trained coach or a member of the L&D team.
This coach can help the leader understand the data, process the emotions that may come with it, and, most importantly, create a concrete action plan. The coach can help the leader “triage” the feedback, focusing on the one or two high-impact behaviors that will make the biggest difference. This follow-up and coaching is what cements the behavior change. It also provides a crucial feedback loop for the L&D team. If 80 percent of a program’s participants are still scoring low on a specific behavior six months later, that is a clear signal that the program’s module on that topic is ineffective and needs to be redesigned.
Defining Kirkpatrick Level 4: Results
Level 4 of the Kirkpatrick Model is where the evaluation process finally connects directly to the business. The goal here is to investigate whether the leadership development program had a tangible, measurable impact on the “bottom line.” This is the level that senior executives and financial officers care about most. While Level 3 measures whether leaders changed their behavior, Level 4 asks the follow-up question: “So what?” Did that behavior change actually do anything? Did it move the needle on the key performance indicators that the business runs on? This level seeks to quantify the hard-dollar value associated with the program.
The data to perform this analysis is best acquired when the leader performance data obtained from the Level 3 analysis is correlated to data on that leader’s direct reports, including measures of direct report retention, engagement, and productivity. The objective is to quantify the value associated with improvement in these indicators. This is a crucial step in building the business case for the program’s continuation and expansion. It moves the conversation from “training is a cost” to “development is an investment” by showing the returns that investment has generated.
The Challenge: Correlation vs. Causation
Before diving into what to measure, it is essential to understand the single biggest challenge at Level 4: the difference between correlation and causation. This is the issue that plagues most Level 4 analyses. It is relatively easy to show a correlation—for example, “The 50 leaders who went through our program saw a 10 percent increase in their team engagement scores.” This is a powerful, positive correlation. However, it does not prove causation. What if, during that same six-month period, the company also paid out record-breaking bonuses, announced a new flexible work policy, and saw its stock price double? Any of these other variables could have been the real cause of the engagement boost.
The issue is that many other variables must be accounted for in a statistical model to validate causation. Therefore, at this level, we must be intellectually honest. For most organizations, it is more practical to build a strong, data-backed correlative case rather than a perfect, academic causal one. By combining positive Level 3 data (behaviors changed) with positive Level 4 data (team metrics improved), we can create a compelling and highly credible “preponderance of the evidence” argument that the leadership program was a primary driver of the positive results.
Choosing the Right Business Metrics
The key to a successful Level 4 evaluation is to select the right business metrics to track. These metrics must be directly influenced by the leaders who attended the program, and they must be aligned with the specific business objectives that were identified in the initial assessment phase. If the program was designed to improve operational efficiency, we should measure metrics like cycle time, error rates, or on-time delivery for the participating leaders’ teams. If the program was focused on sales leadership, we should track metrics like team quota attainment, average deal size, or sales cycle length.
For most leadership development programs, however, the most relevant and universally applicable metrics are not operational, but human. The primary way a leader impacts the bottom line is through their team. Therefore, the most powerful Level 4 metrics are often the ones that measure the health and effectiveness of that team. The most common and credible of these are employee retention, employee engagement, and team productivity. These are the “big three” metrics that are profoundly influenced by a leader’s day-to-day behavior.
Measuring the Impact on Employee Retention
Employee retention is one of the cleanest and most financially significant metrics to track. The cost to replace an employee, especially a skilled professional, is enormous—often estimated at 1.5 to 2 times their annual salary. This includes recruitment costs, training costs, and the lost productivity of an empty seat. Since the number one reason people leave jobs is their direct manager, a program that creates better managers should directly and measurably reduce voluntary turnover.
The measurement here is straightforward. First, you must have the data from your HR information system (HRIS) that tracks voluntary turnover by manager. You would look at the voluntary turnover rate for the teams of the 50 leaders in your program for the 12 months before the intervention. This is your baseline. Then, you track the voluntary turnover rate for those same 50 teams for the 12 months after the program. If you can show that the baseline turnover rate was 15 percent and it dropped to 10 percent after the program, you have a powerful result. You can then monetize this by calculating the savings from the 5 percent of employees who did not leave, providing a hard-dollar benefit for the program.
Quantifying the Impact on Employee Engagement
Employee engagement is another critical Level 4 metric. Engagement is a measure of the discretionary effort an employee is willing to put into their work. Highly engaged teams are more productive, more innovative, and provide better customer service. Like retention, engagement is heavily influenced by the direct manager. A leader who coaches, supports, and empowers their team will create a highly engaged environment. A leader who micromanages, criticizes, and provides no clear direction will create a disengaged, “quiet quitting” environment.
The primary tool for measuring this is the company’s annual or semi-annual employee engagement survey. A well-designed survey will have an “engagement index”—a set of questions that, when combined, provide a single score. The evaluation methodology is similar to that for retention. You would use the engagement scores for the participating leaders’ teams before the program as a baseline. Then, you would look at the scores from the next survey after the program. A clear, positive lift in engagement scores for the “trained” teams, especially when compared to the scores of teams whose leaders did not attend the training, provides a strong, quantifiable link between the program and a critical business outcome.
Assessing Team Productivity and Performance
Productivity is often the hardest of the “big three” to measure, as it can be very context-specific. For some teams, like a sales team or a call center, productivity metrics are readily available: quota attainment, calls per hour, or customer-initiated error reports. In these cases, it is relatively easy to track the team’s output before and after the leader’s development and see if there is a measurable improvement. This provides a direct link to operational performance.
For knowledge-worker teams, such as engineering, marketing, or finance, “productivity” is more subjective. It cannot be measured in “widgets produced.” In these cases, you may need to use proxy metrics. This could include a team’s ability to meet project deadlines, the quality of their work as rated by internal stakeholders, or even the number of new ideas generated. Another powerful approach is to use the team’s own perception of productivity. Many engagement surveys include items like “My team works efficiently” or “We have the resources we need to do our jobs well.” An improvement in these “perceived productivity” scores, as reported by the team, is a valid and powerful Level 4 metric.
Connecting Leadership to Customer Satisfaction
For leaders who manage frontline, customer-facing teams, another powerful Level 4 metric is customer satisfaction. This is particularly relevant for leaders in retail, hospitality, or customer support. The logic is simple: a leader who creates an engaged, supported, and well-trained team (as a result of the program) will lead a team that provides better customer service. This, in turn, will lead to higher customer satisfaction scores, increased customer loyalty, and repeat business.
The data for this analysis would come from the company’s customer feedback system, such as Net Promoter Scores (NPS) or other customer satisfaction (CSAT) surveys. The evaluation would aim to correlate the improvement in a leader’s Level 3 behaviors (e.g., they became a better coach) with the CSAT scores of their specific team. If the teams of trained leaders show a statistically significant increase in customer satisfaction scores compared to the teams of untrained leaders, this builds an incredibly strong business case for the program. It directly links the “soft skill” of leadership to the “hard metric” of customer revenue and loyalty.
Moving Beyond Level 4: The Phillips ROI Model
While the Kirkpatrick Model is foundational, its creator, Don Kirkpatrick, famously stopped at Level 4, “Results.” He believed that a true financial Return on Investment calculation was often too complex and that Level 4 business results were a sufficient endpoint. However, many organizations, particularly those with a strong financial focus, demanded a clear calculation of ROI. This led Jack and Patty Phillips, founders of an influential institute, to build upon Kirkpatrick’s work. They essentially added a “Level 5,” which is the “Learning ROI” mentioned in the source article. Their methodology provides a systematic framework for calculating a true, financial return on investment.
The Phillips ROI Methodology adopts the first four levels of the Kirkpatrick model (Reaction, Learning, Application, and Impact) but then adds a crucial fifth level: ROI. This model also emphasizes the need to isolate the effects of the training from other factors, which is a critical step that makes the final calculation credible. This framework moves the evaluation from a simple “did we improve a business metric?” (Level 4) to “how much was that improvement worth in dollars, and did that dollar amount exceed the cost of the program?” (Level 5).
The Five-Level Framework
The Phillips model is a comprehensive, step-by-step process. It begins with the same foundation as Kirkpatrick. Level 1, Reaction, measures participant satisfaction. Level 2, Learning, measures the acquisition of knowledge and skills. Level 3, Application, measures the change in on-the-job behavior (this is a key language shift from Kirkpatrick’s “Behavior”). Level 4, Impact, measures the business results that are linked to the program, such as the improvement in retention, engagement, or productivity. This is where the Kirkpatrick model typically ends.
The Phillips model adds Level 5, ROI. This level compares the monetized value of the Level 4 business impact against the total, fully-loaded costs of the program. This is expressed as a Benefit-Cost Ratio (BCR) or a percentage ROI. For example, an ROI of 100 percent means that for every dollar invested in the program, the company got one dollar back, plus the original dollar (a net benefit of one dollar). This financial calculation provides the ultimate “bottom-line” justification for the program’s existence and is the language that chief financial officers and CEOs understand best.
The Single Most Critical Step: Isolating Program Impact
The hardest part of any ROI calculation, as the source article notes, is quantifying the benefit. More specifically, it is isolating the portion of that benefit that can be exclusively attributed to the leadership development program. This is the step that makes the Phillips model so much more rigorous than a simple Level 4 analysis. As discussed previously, it is not enough to show that “turnover improved by 5 percent after the program.” We must account for all the other variables that could have contributed to that improvement.
The Phillips methodology provides several systematic techniques to isolate the program’s effects. The most powerful method, but also the most difficult to implement, is the use of a control group. This involves having a “training group” of leaders who attend the program and a “control group” of similar leaders who do not. By measuring the Level 4 results for both groups, you can strip away the impact of other variables. If the control group’s retention rate improved by 2 percent (due to company-wide bonuses), but the training group’s rate improved by 7 percent, you can confidently isolate the program’s effect as the 5-percentage-point difference.
Other Methods for Isolating Program Effects
While control groups are the “gold standard,” they are often not practical. It can be politically or ethically difficult to “withhold” development from one group of leaders. Therefore, the Phillips methodology provides several other practical estimation methods. One is trend line analysis. You can analyze the trend of a metric (e.g., employee turnover) for the two years before the program. If the trend was flat, but then saw a sharp improvement immediately after the program’s launch, you can build a strong case that the program was the primary cause.
Another method is participant and manager estimation. This involves asking the participants and their managers, via a follow-up survey, to estimate what percentage of the improvement in their team’s performance was due to the leadership program. For example, you could ask, “In the last six months, our team’s productivity has increased by 10 percent. In your estimation, what percentage of that increase can be attributed to the skills you learned in the leadership program?” While subjective, when you average this estimate across all participants, it can provide a credible and conservative figure to use in the ROI calculation.
Step 2: Converting Data to Monetary Value
Once you have isolated the program’s impact on a Level 4 metric (e.g., “The program was responsible for a 5 percent reduction in turnover”), the next step is to convert this data into a monetary value. This is what separates Level 4 from Level 5. For some metrics, this is relatively straightforward. To monetize the 5 percent reduction in turnover, the L&D team would partner with HR and Finance to find the company’s agreed-upon “cost to replace” an employee. If that number is, for example, 50,000 dollars, and the program saved 20 employees from leaving, the monetary benefit is 1,000,000 dollars.
For other metrics, this is more challenging. To monetize an improvement in “employee engagement,” you might need to use research that links a 1-point increase in engagement to a 0.5 percent increase in revenue or a 0.2 percent increase in profit margins. You would then apply that formula to the program’s results. The key, as the source article notes, is that this often requires making some assumptions. The best practice is to be extremely transparent about these assumptions, to get them approved by the finance department, and to be conservative in all estimations. It is always better to under-promise and over-deliver, building credibility with your financial stakeholders.
Step 3: Tabulating the Full Program Costs
This is the “cost” side of the Benefit-Cost Ratio and is often the easiest part of the calculation. To be credible, this must be a “fully loaded” cost, not just the vendor’s invoice. This includes all direct costs: vendor fees, program design fees, the cost of materials and course licenses, and any travel, food, and accommodation costs for participants. It should also include the cost of the L&D team’s time to manage and administer the program.
The most significant cost, and the one most often overlooked, is the indirect cost of the participants’ time. The cost of pulling 50 leaders out of their jobs for 40 hours is not zero. This cost should be calculated by multiplying the participants’ average loaded salary (salary plus benefits) by the number of hours they spent in training. Including this cost makes the calculation far more conservative and credible to financial stakeholders. A complete and honest accounting of all costs is essential for the final ROI figure to be taken seriously.
Step 4: The Final Calculation
Once you have the total monetary benefit (Step 2) and the total program cost (Step 3), the final calculation is straightforward. The Benefit-Cost Ratio (BCR) is simply: Total Program Benefits divided by Total Program Costs. A BCR of 3.25 means that for every 1.00 dollar invested, the company received 3.25 dollars in benefits.
The ROI percentage is calculated as: (Total Program Benefits – Total Program Costs) divided by Total Program Costs, and then multiplied by 100. So, if the total benefits were 1,000,000 dollars and the total costs were 250,000 dollars, the calculation would be: (1,000,000 – 250,000) / 250,000 = 3. This is then multiplied by 100 to get an ROI of 300 percent. This single number provides a clear, unambiguous, and financially-defensible answer to the question “Was the program worth it?” and allows senior leaders to compare the investment in leadership development against any other investment the company could make.
The Gold Standard: Proving Direct Causation
The source article correctly points out that the most difficult part of evaluation is validating a direct causal link between the leadership program and a broader business outcome. While the Phillips ROI model provides a robust framework for creating a financial case, the “gold standard” for proving causation comes from the world of scientific and clinical research. This is the world of experimental design. This level of rigor is not always necessary, but for a very large, very expensive, mission-critical program, it may be the only way to prove to skeptical stakeholders that the program, and nothing else, was the cause of the improvement.
Causation, in this case, can best be determined by employing an experimental design involving multiple training groups, non-training control groups, and random assignment to conditions. This approach is designed to systematically eliminate all other “confounding variables” (like a company-wide bonus or a new flexible work policy) so that the only remaining explanation for the difference between the groups is the training program itself. While powerful, these kinds of experiments can be complex to set up and execute.
Setting Up an Experimental Design
To set up a true experiment, you must begin with a large, similar group of leaders (e.g., 200 “frontline managers”). This group is then split into two. The first is the “training group” (or “test group”) who will participate in the leadership development program. The second is the “non-training control group.” This group must be statistically identical to the first in terms of experience, team size, and baseline performance, but they will not receive the training during the study period. This is the most crucial, and often most politically difficult, step.
The key to a true experiment is the random assignment of these leaders into one of the two groups. You cannot let them volunteer, and you cannot let their managers select them, as this would introduce a selection bias (e.g., “only the motivated leaders volunteered” or “only the worst leaders were chosen”). Random assignment ensures that both groups are, on average, identical, and the only systematic difference between them is that one group will get the training. This isolates the “training” as the independent variable.
Using Pre- and Post-Training Quantitative Measures
Once the groups are established, the next step is to use numerous pre- and post-training quantitative measures. Both the training group and the control group are measured on the key metrics before the program begins. This is the “pre-test” and it serves to establish a baseline for both groups. These metrics should include Level 2 (knowledge), Level 3 (behavior via 360-surveys), and Level 4 (team engagement, retention, productivity). The pre-test is used to confirm that the two groups are, in fact, statistically identical at the start.
The leadership program is then delivered to the training group, while the control group goes about their normal business. After a set period, for example, six months, both groups are measured again on the exact same metrics. This is the “post-test.” The analysis then compares the change in scores. For example, if the control group’s team engagement score went up 2 points (due to other company factors), but the training group’s score went up 12 points, the 10-point difference is the “causal effect” of the program. This is the most defensible, “smoking gun” evidence of a program’s impact.
The Practical Challenges and Ethical Considerations
While this experimental design is the gold standard, the source article rightly notes that it is “complex to set up and execute.” The challenges are immense. First, you need a large sample size. A study with only 20 participants (10 in each group) is not statistically valid. You often need hundreds of participants. Second, it is expensive. It requires rigorous data collection, management, and statistical analysis. Third, it is politically and ethically difficult. Denying a “control group” of leaders access to a valuable development opportunity for a year can be seen as unfair and may cause internal friction or attrition.
For these reasons, true experimental design is rare in the corporate world. It is most often seen in very large organizations that are rolling out a massive, multi-million dollar program and need to prove its efficacy before a global launch. For most companies, a “quasi-experimental” design is more practical. This might involve comparing the results of one “test” business unit to a “similar” (but not randomly assigned) business unit, or simply using the Phillips methodology of isolating effects through statistical modeling and estimation.
Conclusion
In summary, leadership development programs require evaluation at all Kirkpatrick levels, and it is essential to consider this evaluation strategy before rolling out a program. However, the purpose of all this data collection should not be purely judgmental. That is, the goal should not be just to create a backward-looking report card that gives the program a “pass” or “fail” grade. While accountability is important, the primary value of evaluation data is in its power to drive continuous improvement.
When the L&D team sees that a program is getting great Level 1 and 2 scores but is failing at Level 3, that is not a failure of the program; it is a priceless diagnostic insight. It tells the team that the problem is not the content but the transfer. This insight allows them to “fix the problem” by focusing their resources on the post-program reinforcement. This could include building manager-led coaching toolkits, creating a peer-mentoring program, or developing a series of “nudge” micro-learnings. This “closing of the loop”—using evaluation data to feed back into the assessment and design phase—is what separates a static, one-and-done training event from a truly dynamic and effective leadership development system.