ROI Case File No.412 'The Compass Called Certification'
The Compass Called Certification
Chapter 1: Invisible Progress
"We have no idea how far our employees are progressing with their studies."
The HR Director of Novatech pointed to a stack of textbooks on the desk. They were all reference materials for the Class 2 Architectural Construction Management Technician certification.
"We support our young employees in obtaining certifications. The company covers textbook costs and provides bonuses for those who pass. However, only about 30% of exam takers actually pass each year."
Frustration permeated the HR Director's voice.
"The problem is that we have no visibility into study progress. When we ask 'Are you studying?', everyone says 'Yes.' But when we have them take practice exams, more than half don't reach the passing threshold."
The materials he produced showed three years of exam results. The number of test-takers was increasing annually, but the pass rate remained flat.
"What's even more serious," the HR Director continued, "is that certification acquisition isn't leading to reduced turnover. Even after obtaining certifications, employees eventually leave for other companies because the career path remains unclear."
"In other words," Claude summarized, "the educational investment isn't translating into company loyalty or growth motivation."
"Exactly," the HR Director nodded. "We want to transform our certification support system from mere 'textbook distribution' to 'visible growth.' We're considering digital tool implementation, but we don't know what to measure or how."
It was a typical challenge where the causal relationship between investment and outcomes remained invisible.
Chapter 2: Drawing the Chain of Causation
"This case calls for an approach using the LOGIC model."
Gemini drew an arrow on the whiteboard. The arrow extended from left to right, divided into several stages.
"The LOGIC model—formally the Logic Model," I began explaining, "is a framework that logically organizes the causal relationships from Input to Outcome."
"Specifically," Claude supplemented, "we think in five stages: Input, Activities, Output, Outcome, and Impact—by visualizing this chain, 'what produces what' becomes clear."
The HR Director tilted his head. "But educational effectiveness is difficult to measure, isn't it?"
"That's precisely why," I answered, "we need to clearly define each stage and break it down into measurable indicators."
[Step 1: Defining Input]
"First, let's organize Input—what the company is providing," Gemini proposed.
The HR Director began explaining. "Currently, the company covers textbook costs of about 20,000 yen per person. And we provide a 50,000 yen bonus for those who pass."
"Is that all?" I asked.
"Well, basically."
"Then," Claude pointed out, "securing study time, creating an environment where questions can be asked, advice from senior employees—aren't these also provided?"
The HR Director pondered. "Certainly, we tacitly allow studying during work hours, and seniors do teach sometimes. But we hadn't recognized these as 'inputs.'"
"That's the key point," I emphasized. "In the LOGIC model, we identify all inputs, including invisible ones. That becomes the key to understanding the causal relationship with outcomes later."
[Step 2: Clarifying Activities]
"Next, Activities," Gemini continued. "We need to specify what employees are actually doing."
"Currently," the HR Director answered, "each person reads textbooks and solves practice problems. That's it."
"That's insufficient," Claude pointed out. "Learning activities need more structure."
I wrote items on the whiteboard. "For example: creating weekly study plans, recording daily study hours, monthly practice exams, study sessions with senior employees, Q&A on online question boards—the system should support these activities."
"And importantly," Gemini added, "make these activities 'measurable.' Record everything as data: how many hours studied, how many problems solved, how many questions asked."
[Step 3: Measuring Output]
"Third is Output," I explained. "We define what is produced as a direct result of activities."
"For example," Claude showed concrete examples, "total study time of 100 hours, 500 problems solved, 10 study sessions attended. These are all 'outputs' of activities."
"But," the HR Director questioned, "if these numbers are high, does that mean they'll pass?"
"Not necessarily," I answered. "That's why we need to analyze the relationship with the next stage, 'Outcome.'"
[Step 4: Defining Outcome]
"Outcome," Gemini explained, "is the change caused by Output. For Novatech, the short-term outcome is 'passing the certification exam,' right?"
"Yes," the HR Director nodded.
"But," I continued, "what about medium-term outcomes? What changes do you expect in employees after they obtain certifications?"
The HR Director answered. "Improved practical abilities on-site. And increased company loyalty, leading to reduced turnover."
"That's the outcome," Claude organized. "And to measure it, you need performance evaluation data after certification acquisition and retention rate data."
[Step 5: Depicting Impact]
"Finally, Impact," I explained. "This refers to long-term changes to the organization as a whole or to society."
"In Novatech's case," Gemini continued, "excellent engineers staying leads to improved construction quality. Customer satisfaction increases. The company's reputation rises, making new recruitment easier—these are 'impacts.'"
The HR Director's expression changed. "So the certification support system isn't just an educational investment, but a strategic initiative affecting the company's overall competitiveness."
"Exactly," I answered. "What the LOGIC model visualizes is this chain of causation."
Chapter 3: Designing Measurement
"So how should we implement this LOGIC model?" the HR Director asked.
"We'll develop a digital tool—a certification support app," Claude answered. "But what's important is clarifying 'what to measure.'"
I began writing a list of measurement indicators on the whiteboard.
"Input-level indicators: number of textbooks provided, question response rate for the learning environment, senior employee involvement time."
"Activity-level indicators: average daily study time, weekly plan achievement rate, number of problems solved, number of study sessions attended."
"Output-level indicators: total study time, practice exam score trends, number of times the question board was used."
"Outcome-level indicators: certification exam pass rate, changes in performance evaluation after passing, retention rate after one year."
"Impact-level indicators: overall department construction quality evaluation, customer satisfaction score, trends in job applicant numbers."
The HR Director showed a surprised expression. "Will we measure this many indicators?"
"You don't need to measure everything at once," Gemini answered. "What's important is gradually expanding the measurement scope."
"Specifically," I continued, "for the first three months, concentrate on activity-level and output-level indicators. Record study time, number of problems, practice exam scores—and analyze their correlation with pass rates."
"Then," Claude added, "based on those analysis results, clarify 'what learning patterns lead to passing.' For example, studying 30 minutes daily is more effective than cramming 3 hours on weekends."
"Once that's understood," Gemini continued, "we can recommend effective learning patterns to the next exam takers. This establishes reproducibility."
Chapter 4: Visible Growth
The HR Director gazed at the chain of causation drawn on the whiteboard.
"Until now, we simply thought 'if we distribute textbooks, passers will increase.' But actually, there were many stages from input to outcome."
"The value of the LOGIC model," I answered, "is not treating the causal relationship as a black box. By visualizing what produces what and where the chain of causation breaks—we find clues for improvement."
Claude quietly added words. "And only by measuring can we answer the question 'Does this initiative really work?'"
The HR Director stood up and bowed deeply. "Thank you. Starting next month, we'll begin developing the pilot app."
After he left, Gemini said admiringly, "The LOGIC model is often used in fields like education and welfare where 'outcomes are hard to see.'"
"Yes," I answered. "But the essence of the LOGIC model transcends fields. The way of thinking that logically organizes the causal relationship between investment and outcomes and makes it measurable—can be applied to any decision-making."
Outside the window, construction site cranes were moving.
Four months later, a report arrived from Novatech.
Of the 15 people who used the pilot app, 12 passed the certification exam. The pass rate was 80%—a dramatic improvement from the previous 30%.
And through analysis, common patterns among passers were found. "Minimum 30 minutes of daily study," "80% or higher achievement rate for weekly plans," "gradual score improvement in monthly practice exams"—these indicators were clear signals predicting success.
The chain of causation was proven by data.
"Even if the path from input to outcome can be logically drawn, whether it actually functions remains unknown. What the LOGIC model teaches is: establishing causal relationships as hypotheses, verifying through measurement, and finding reproducible patterns. That is the only way to produce certain outcomes."
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