Unit Economics Applied to Talent Strategy: Building Sustainable Competitive Advantage

Integrating Unit Economics and Talent Strategy: A New Source of Competitive Advantage

I founded Kikagaku, an AI venture company, as a solo entrepreneur. By the time I stepped down in 2023, the company had grown to over 80 full-time employees, and as of 2025, it has approximately 150 employees. This growth is largely attributed to the AI trend. However, I consistently focused on how to build competitive advantage and implemented thorough measures to ensure long-term company growth. I am frequently asked about the strategies that supported this growth, so I would like to share them here. The key was applying unit economics thinking to talent strategy.

In the modern economy, where the source of corporate value is shifting from tangible to intangible assets, talent strategy in knowledge-intensive businesses has become a critical factor determining competitive advantage. Particularly in fields such as training and consulting, "people themselves" are the greatest management resource, and their optimization forms the core of business strategy.

This article examines how to apply the economic framework of unit economics to talent strategy to achieve both short-term profitability and long-term competitive advantage. Based on the real example of Kikagaku, an AI corporate training company that built an organization of over 100 full-time employees without VC funding, I present a way of thinking that strategically utilizes the element of "time".

This perspective goes beyond mere personnel cost management or recruitment strategy, integrating the economic structure of the entire business with competitive strategy. It will provide important strategic insights for executives and leaders aiming to sustainably grow knowledge-intensive businesses.

The Concept of Unit Economics and Its Application to Talent

Basic Framework of Unit Economics

Unit Economics is a method of analyzing business profitability and sustainability on a "unit" basis. According to Karl T. Ulrich, a "unit" refers to quantifiable elements that bring value to a business, such as the sale of a physical product, a consulting contract, or a single customer¹.

This is frequently used to evaluate SaaS (Software as a Service) business models. In SaaS, the following metrics are particularly important:

• LTV (Life Time Value): The total revenue or profit a customer brings to a company over their lifetime
• CAC (Customer Acquisition Cost): The total cost required to acquire a new customer
• LTV/CAC ratio: The ratio of customer lifetime value to customer acquisition cost (generally, a ratio of 3:1 or higher is considered healthy²)
• ARPU (Average Revenue Per User): Average revenue per customer
• Churn Rate: The percentage of customers who leave within a certain period
• CAC Payback Period: The time (in months) it takes to recover the customer acquisition cost

Improving these metrics is the key to enhancing the sustainability and growth potential of a business model.

Applying Unit Economics to Talent Strategy

In Knowledge-Intensive Business Services (KIBS), applying these concepts to talent strategy can fundamentally improve management quality. The correlation can be organized as follows:

Understanding this correlation enables designing and optimizing talent strategy as an economically rational investment activity rather than mere recruitment:

• Talent LTV: Revenue or profit contribution generated by an employee throughout their entire tenure
• Talent CAC: Total costs including recruitment expenses, initial training costs, and early-stage salary when productivity is low
• Talent ARPU: Average revenue generated by an employee over a certain period (monthly/yearly)
• Talent Churn Rate: Percentage of employees who leave within a certain period
• Talent Investment Payback Period: Time required to recover recruitment and training costs

These metrics are interrelated; for example, if talent churn rate increases, talent LTV decreases, and if talent CAC is too high, the investment payback period lengthens. Maintaining an appropriate balance between these metrics forms the foundation of a sustainable talent strategy.

The Current State of the AI/DX Training Market and the Importance of Talent Strategy

Market Environment and Competitive Situation

The AI/DX training market is expanding rapidly. Looking at the Japanese market environment, according to a Ministry of Internal Affairs and Communications survey, the AI-related market was approximately 388.3 billion yen in 2022 and is projected to grow to about 1.1034 trillion yen by 2027³. Additionally, an IPA survey shows that about 56% of Japanese companies are engaging in DX initiatives (compared to about 79% in the US), indicating significant growth potential in Japan's DX market⁴.

Meanwhile, the supply and demand for AI/DX talent is extremely tight. According to a doda survey, as of June 2024, the job opening-to-applicant ratio for "Engineers (IT & Communications)" was 11.06 times, exceptionally high⁵. Furthermore, the Ministry of Economy, Trade and Industry estimates that there could be a shortage of up to 545,000 "advanced IT professionals" in fields such as AI and data science in the future⁶.

In this market environment, companies offering AI/DX training face dual talent challenges. First, they need specialized talent to provide valuable training to customers, and second, they must secure talent for their own business operations (curriculum development, platform construction, etc.). I predicted at the founding stage that building an effective talent strategy would be key to business success in a market where highly specialized talent is scarce overall.

Existing Talent Models and Their Limitations

I analyzed the existing talent models in the AI/DX training market and classified them into two major patterns:

1. Specialist Outsourcing Model Analysis

The model of engaging university professors, researchers, or industry experts as contractors tends to prioritize short-term profitability. Specific metrics are as follows:

• Talent CAC: Relatively low (minimal initial investment as it utilizes existing experts)
• Talent LTV: Medium to low (unstable continuity due to contractor status, high risk of being poached by competitors)
• Talent Churn Rate: High (high mobility, easily transferred depending on conditions)
• Talent ARPU: Moderate (centered on templated basic training, difficult to handle high-unit-price projects)
• Scalability: Low to medium (high dependence on scarce specialists, difficult to expand rapidly)

The biggest challenge with this model is the intensification of talent competition and rising talent costs as market competition increases. Dependence on scarce specialized talent can lead to rising talent CAC and increasing churn rates as the market expands. As a result, there is a high possibility of deteriorating unit economics.

2. In-house Development Model Analysis

The model of employing specialized talent and developing content in-house aims for long-term competitive advantage but has the following characteristics:

• Talent CAC: High (expensive to recruit rare AI/DX specialists as full-time employees)
• Talent LTV: High (easier to build long-term relationships as full-time employees)
• Talent Churn Rate: Moderate (dependent on industry average)
• Talent ARPU: Medium to high (capable of providing high-quality content through in-house development)
• Scalability: Moderate (dependent on the speed of securing talent)

The challenges of this model lie in the size of the initial investment and the difficulty of securing talent. The high recruitment costs of specialized talent can be a financial burden, and the difficulty of securing rare specialized talent itself may hinder rapid growth.

Kikagaku's Strategic Talent Model: Empirical Analysis

Designing a Differentiated Talent Strategy

The talent strategy I adopted when founding Kikagaku was a unique approach different from conventional wisdom. Rather than "engaging AI experts as contractors," which is the typical approach in the AI training industry, I chose to hire "people with high educational skills but no experience in the AI field" as full-time employees and train them internally.

This strategic choice was made to overcome the limitations of existing models and build long-term competitive advantage. Specifically, it included the following elements:

1. Escaping the talent acquisition competition: By focusing on educational skills rather than AI expertise, we avoided competing for talent with competitors
2. Maximizing long-term talent LTV: By hiring as full-time employees and continuously developing them, we achieved long-term relationship building and value creation
3. Internal accumulation of processes and know-how: Through the talent development process, we built organization-specific intellectual assets

Analysis from a Unit Economics Perspective

Analyzing this strategy from a unit economics perspective reveals the following characteristics:

• Talent CAC
  • Recruitment cost itself is low (because we target a talent pool not sought by competitors)
  • However, initial training cost is high (time and cost required for technical education in the AI field)
  • Overall, moderate CAC (the low recruitment cost offsets the high training cost)
• Talent LTV
  • High (long-term relationship building through full-time employment)
  • Value increases over time as expertise develops through training
  • Becomes a differentiating factor through the accumulation of unique know-how from internal training
• Talent Churn Rate
  • Low (increased sense of belonging through internal development)
  • Reduced risk of being poached by competitors (due to unique skill set)
• Talent ARPU
  • Initially low (due to low productivity)
  • Rapidly improves over time (through skill acquisition and know-how accumulation)
  • Achieves high levels in the long term (ability to provide differentiated high-value-added services)
• Talent Investment Payback Period
  • Initially long (due to training period)
  • Gradually shortened with scale and accumulated experience
  • Eventually falls below industry average (due to improved training efficiency)

The characteristic of this approach is that it requires initial investment and time but builds sustainable competitive advantage in the long term. This is similar to the concept in SaaS business that "even if the CAC payback period is long, there is investment value if the customer LTV is large."

Growth Model That Makes Time an Ally

The growth trajectory of AI training businesses diverges significantly based on their approach to "time."

The conventional model utilizes external experts and prioritizes short-term profits, but this efficiency gradually faces obstacles like market competition, rising talent costs, and difficulty in differentiation, creating a "negative loop" that hinders sustainable growth in the long term.

In contrast, Kikagaku's strategy focuses on educational capability, developing inexperienced talent internally and concentrating on internalizing know-how as an asset. While this may appear less profitable initially, as time passes, the development process becomes refined, establishing an autonomous growth cycle—a "positive loop" in which know-how circulates throughout the organization. As a result, high-value-added services and unique competitive advantages become more sustainable.

Where to accept "pain" and what assets to leave for the future—this choice determines the quality of organizational growth even in the same market environment.

Implementation Challenges and Countermeasures

The main challenges in implementing this strategy are the initial investment and length of the training period. Extended time to productivity creates a risk of temporary cash flow deterioration. To address this, Kikagaku implemented the following countermeasures:

1. Phased talent investment: Starting the business alone and reinvesting all profits into developing the next generation of talent
2. Developing the developers: Building a system where initially trained talent trains the next generation
3. Standardization of the training process: Systematizing know-how to continuously improve training efficiency and quality
4. Project stratification: Classifying projects by difficulty level and providing experiences appropriate to growth stages

These countermeasures enabled us to overcome the initial high-cost period and successfully build a sustainable growth cycle.

Building a Growth Model That Makes Time an Ally

Temporal Development of Talent Strategy and Unit Economics

The aforementioned talent strategy undergoes important changes and developments over time. Viewing this as a "temporal development model" from a unit economics perspective, it can be organized as follows:

Each phase of this temporal development model focuses on different aspects of unit economics.

Phase 1: CAC Optimization Period

• Characteristics: Recruiting inexperienced individuals with educational skills and providing specialized education in the AI field
• Unit Economics Metrics: Recruitment CAC↓, Initial investment↑, Investment payback period↑ (inefficient due to trial and error in determining which projects can be implemented), high turnover due to trial and error
• Challenge: How to overcome temporary cash flow deterioration
• Countermeasure: The founder generates revenue and reinvests it in talent development

Phase 2: Churn Rate Stabilization Period

• Characteristics: Developed talent becomes established and organizational culture forms
• Unit Economics Metrics: Churn rate↓, ARPU remains low, talent investment payback period begins to converge as trial and error somewhat settles
• Challenge: How to promote individual growth while maintaining organizational cohesion
• Countermeasure: Establishing a system where developed talent trains the next generation (e.g., mentoring system)

Phase 3: ARPU Enhancement Period

• Characteristics: High-value-added services become possible due to deepening expertise and accumulated unique know-how
• Unit Economics Metrics: Talent ARPU↑, Project unit price↑
• Challenge: How to balance basic training with advanced specialized services
• Countermeasure: Development of fully customized problem-solving services and securing long-term projects

Phase 4: Economies of Scale Realization Period

• Characteristics: Training efficiency improves significantly due to standardized training processes and accumulated know-how
• Unit Economics Metrics: Investment payback period↓, New talent productivity↑
• Challenge: How to respond to organizational complexity associated with scale expansion
• Countermeasure: Building knowledge sharing systems and continuous improvement of training processes

The essence of this model is that each metric positively influences the others over time, forming a positive spiral. For example, a decrease in churn rate increases talent LTV, which combined with improved ARPU, enhances the overall economic performance of the organization. Additionally, optimization of the training process shortens the investment payback period, enabling accelerated growth.

Sources of Economies of Scale in Knowledge-Intensive Businesses

Generally, economies of scale refer to the phenomenon where cost per unit decreases as production volume or business scale increases⁷. This is my favorite concept and a phenomenon I consciously create. While traditional manufacturing leverages physical capital like factory production equipment as the source of economies of scale, what generates economies of scale in knowledge-intensive businesses (especially training and consulting)?

According to University of Manchester research, economies of scale in Knowledge-Intensive Business Services (KIBS) arise from the following elements⁸:

1. Specialization: Accumulation of deep expertise and experience in specific fields
2. Reputation/Brand: Improved customer acquisition efficiency through established reputation
3. Network Effects: Increased network value from many customers or graduates
4. Process Standardization: Improved efficiency through standardized business processes
5. Knowledge Reuse/Systematization: Efficient reuse of developed content and know-how

What becomes apparent from Kikagaku's case is the process by which these elements function in complex ways over time to form "economies of scale in knowledge and processes."

• Deepening and specialization of knowledge: Accumulation of expertise and systematization of know-how through practice
• Optimization of talent development processes: Standardization and continuous improvement of development methods
• Building social credibility and brand: Increased trust through accumulated achievements, leading to more referrals and repeat business
• Knowledge sharing among members: Improved efficiency and innovation through organizational learning
• Expansion of curriculum assets: Accumulation of reusable educational materials and methodologies

These interact with each other to enhance organizational competitiveness over time. What's particularly important is that these involve qualitative improvement, not just quantitative expansion. While there may be physical limits to how many students one instructor can teach, it's possible to significantly improve the return on invested resources (ROI) by enhancing training efficiency and delivery value.

Pricing Strategy and Process Innovation

Theoretical Basis for Why "Initial Discounting" is an Anti-pattern

When launching a knowledge-intensive business, there's a temptation to "offer services cheaply because of lack of track record." However, from the perspectives of unit economics and time horizon, this can be an "anti-pattern" that damages long-term business value. Let's examine the theoretical basis.

Pricing strategies broadly fall into "skimming strategy (high price setting)" and "penetration strategy (low price setting)"⁹.

• Skimming price strategy: Setting a high price when introducing a new product and gradually lowering it over time
• Penetration price strategy: Penetrating the market with low prices, with the possibility of raising prices after gaining market share

Both strategies have their appropriate application conditions, and neither can be said to be universally superior. However, in the context of knowledge-intensive services, skimming strategy is often more rational for the following reasons:

1. Risk of value erosion: Excessive initial discounting may cause customers to perceive the service's true value as low. Customers accustomed to low prices find it difficult to accept appropriate price increases later¹⁰.
2. Customer selection effect: Price also functions to select customer segments. Appropriate (not too high) price setting is effective in acquiring customers who truly understand and value the service. Price-sensitive customers often tend to have lower loyalty as well¹¹.
3. Delayed investment recovery: Low pricing extends the CAC payback period. This is particularly problematic for companies aiming for bootstrap-type growth. To achieve growth without relying on funding, it's important to recover investments early and redirect to reinvestment¹².
4. Manufacturing costs and scale relationship: In businesses where economies of scale function, manufacturing costs decrease over time, allowing the same value to be provided at lower cost. However, in the early stages of entrepreneurship, manufacturing processes are not yet well-established, and the cost of provision is relatively high. Discounting at this stage means one of the following:
   • Pricing at a loss (risk of running out of funds)
   • Pricing that sacrifices quality (risk of damaging reputation)
   • Pricing that reduces personnel costs (risk of talent not developing)

Thus, in knowledge-intensive businesses, "initial discounting" often carries greater risk of long-term value erosion than short-term customer acquisition benefits.

Building a Sustainable Price Model

So how can we set appropriate prices in the initial stage while achieving growth? The following approaches can be considered:

1. Value-based pricing: Setting prices based on the value customers receive (e.g., operational efficiency, cost reduction, revenue increase). This allows for appropriate compensation while providing services with high return on investment for customers¹³.
2. Gradual penetration strategy: Rather than aiming to acquire a large number of customers from the start, begin with a small number of "understanders," gradually expanding the customer base while accumulating achievements and improvements. In terms of normal distribution, this is a strategy that progresses from 3σ (outliers) → 2σ → 1σ.
3. Continuous investment in manufacturing processes: Always invest part of the revenue in improving manufacturing processes (including education) to reduce provision costs while maintaining or improving quality. This naturally increases profit margins over time.
4. Visualization and sharing of value: Establish mechanisms to quantify and visualize the effects or results customers receive. This reduces resistance to pricing and enables value-based dialogue.

In Kikagaku's case, we provided services at appropriate prices to a small number of understanding customers in the initial stage and invested those revenues in talent development and process improvement to achieve steady growth. This "gradual expansion" approach is the core of a sustainable growth model through bootstrapping.

Sustainable Competitive Advantage Through Process Innovation

What emerges from the discussion so far is the perspective that the true source of competitive advantage in knowledge-intensive businesses lies not in "products" but in "processes".

Process innovation, which I consider most important when thinking about business models, refers to innovation in the "method" of providing products or services, rather than overhauling the results of the products or services themselves¹⁴. This is particularly important in knowledge-intensive businesses for the following reasons:

1. Sustainability: Product innovations are easily imitated, but process innovations embedded within organizations are difficult to imitate, providing more sustainable competitive advantage¹⁵.
2. Cumulative effect: Process innovations demonstrate cumulative effects over time, making the element of "time" an ally.
3. Multifaceted value creation: Excellent processes contribute to both cost reduction and quality improvement, bringing value to both customers and providers.

In Kikagaku's case, the following process innovations played important roles:

• Systematization of talent development processes: Development of unique methods for efficiently training inexperienced individuals
• Standardization of content production workflow: Building a quality control system that doesn't depend on individual skills
• Efficiency in customer needs identification process: Refinement of methodologies for issue extraction and solution design
• Building knowledge sharing mechanisms: Systems for sharing and utilizing experiences and insights within the organization

These process innovations enhanced organizational capabilities over time, building sustainable competitive advantage (economic moat¹⁶).

Alignment with Funding Strategy

Relationship Between Unit Economics and Funding

The long-term perspective based on talent strategy and unit economics is closely related to funding strategy. There are broadly two options for funding methods: "bootstrapping" and "external investment (especially VC)."

• Bootstrapping: Establishing and operating a company using only self-funding or business revenue
• Venture Capital (VC): Raising funds in exchange for equity

Which choice is appropriate depends largely on the following factors¹⁷:

1. CAC payback period: If the period to recover customer acquisition costs is short, growth with self-funding becomes easier. If the recovery period is long, external funding may be more likely necessary.
2. Required growth speed: If there's a need to quickly capture market opportunities or first-mover advantages are significant, funding from VCs is appropriate. Conversely, bootstrapping becomes an option if steady growth is preferred.
3. Time horizon and management freedom: VCs typically expect an "Exit" (IPO or M&A) within their investment recovery period of 7-10 years. Bootstrapping is more appropriate for businesses considered over a longer time horizon or when management freedom is prioritized.

In Kikagaku's case, we chose bootstrapping (primarily self-funding) growth for the following reasons:

• A business model focused on talent development takes time for initial investment recovery but can build sustainable advantages in the long term
• The standard investment recovery period for VC funding (7-10 years) doesn't align with our strategy of "making time an ally"
• Wanting to maintain independence in management decisions while focusing on long-term value creation

However, this choice isn't applicable to all businesses. In the following cases, VC funding may be a more appropriate option:

• Businesses requiring large initial investments (e.g., manufacturing, platform building)
• Businesses where first-mover advantages are significant and rapid expansion is necessary
• Businesses where network effects are strong and achieving critical mass is important

This is not a discussion of whether VC or bootstrapping is better. Remember that knowledge and intelligence to make appropriate judgments according to the nature of the business are what's being tested.

At Kikagaku, we chose to grow with self-funding to realize the talent strategy already introduced because we wanted to pursue long-term value from the beginning. The failure of finance at the foundation of capitalist dynamics is extremely difficult to recover from later. Therefore, choices from the founding stage were important. I cannot thank enough the senior entrepreneur who introduced me, an engineer, to the book "Entrepreneurial Finance."

Conclusion and Practical Implications

Key Points for Building Sustainable Competitive Advantage

This article has examined how to apply the concept of unit economics to talent strategy and build sustainable competitive advantage, particularly in knowledge-intensive businesses. Based on the example of Kikagaku, an AI training company I founded, I've presented a way of thinking that strategically utilizes the element of "time."

The key points derived from this examination are as follows:

1. View talent from a unit economics perspective
   • Quantitatively manage metrics such as talent CAC, talent LTV, talent ARPU, and churn rate
   • Understand the interactions between these metrics and their changes over time, and reflect them in strategy
2. Build a differentiated talent strategy
   • Consider unique recruitment and development approaches not bound by industry conventions
   • Develop a recruitment pool different from competitors and prioritize building long-term relationships
3. Have the courage to think on a long-term time horizon
   • Choose strategies that lead to sustainable competitive advantage, even if they require initial investment and time
   • How you perceive market "time" influences important strategic choices, including funding strategy
4. Maintain an appropriate balance between price and value
   • Avoid initial discounting and maintain appropriate pricing that matches the value provided
   • Maintain consistency between value and price while gradually expanding customer segments
5. Continuously invest in process innovation
   • Focus on innovating the "process" that produces products rather than the products themselves
   • Make processes that accumulate and optimize over time the source of competitive advantage

These points are interrelated and demonstrate maximum effect when practiced in an integrated manner. Particularly important is the way of thinking that makes "time" an ally while balancing short-term results and long-term value creation.

The success of knowledge-intensive businesses ultimately depends on the ability to create value through people. Enhancing that ability in an economically rational and sustainable manner will be the key to building long-term competitive advantage.

References

Footnotes

1. Unit Economics and the Financial Model of the Business - Karl T. Ulrich's explanation of how unit economics serves as an important indicator for evaluating a business's feasibility, scalability, and sustainability. ↩

2. LTV/CAC: What it means and how to use it - Analysis by Harvard Business School. In SaaS businesses, an LTV/CAC ratio of 3:1 or higher is considered a benchmark for soundness. ↩

3. 【2024 Latest】What is the Market Size of AI in Japan and Globally? Future Outlook Explained - Survey by Metaverse Research Institute. According to a Ministry of Internal Affairs and Communications survey, Japan's AI market size was approximately 388.3 billion yen in 2022 and is projected to grow to about 1.1034 trillion yen by 2027. ↩

4. DX Strategy, Talent, and Technology in Japan-US Comparison Survey - According to an IPA (Information-Technology Promotion Agency) survey, about 56% of Japanese companies are engaged in DX, compared to about 79% in the US. ↩

5. Is Recruiting DX Talent Difficult? The Necessity of DX Talent and Successful Recruitment Cases - Vollect article. According to the job service doda's survey report, as of June 2024, the job opening-to-applicant ratio for "Engineers (IT & Communications)" was 11.06 times, exceptionally high compared to other industries. ↩

6. What is DX Talent Development? Comprehensive Explanation of the Current State of Talent Development and Methods for Success - SkillUp AI article. According to a Ministry of Economy, Trade and Industry survey (estimate), there could be a shortage of up to 545,000 "advanced IT professionals" in fields such as AI and data science in the future. ↩

7. Economies of Scale: What Are They and How Are They Used? - Investopedia article defines economies of scale as "the phenomenon where cost per unit decreases as production volume or business scale increases." ↩

8. Knowledge-Intensive Business Services: Their Roles as Users, Carriers and Sources of Innovation - University of Manchester research identifies specialization, reputation/brand, network effects, and process standardization as sources of economies of scale in KIBS. ↩

9. Market Skimming Pricing: An Examination of Elements Supporting High Price for New Products in Pakistan - IISTE.org research compares and analyzes the characteristics and application conditions of skimming price strategy and penetration price strategy. ↩

10. Difference between Skimming and Penetration Pricing - Testbook article points out the difficulty of future price increases as a risk of low-price strategy. ↩

11. Pricing Strategy Analysis - Thompson Rivers University analysis explains how price functions to select customer segments. ↩

12. CAC Payback Period: Formula, How To Calculate, & Importance - This article explains why shortening the CAC payback period is important for growth with self-funding. ↩

13. Value-Based Pricing is an approach that sets prices based on the value customers receive, considered particularly important in knowledge-intensive services. ↩

14. Applying the 4 "Ps" of Innovation in Healthcare - Michigan State University article defines process innovation as "innovation in the 'method' by which products or services are created and provided—'how' they are delivered." ↩

15. PRODUCT AND PROCESS INNOVATION: A NEW PERSPECTIVE ON THE ORGANIZATIONAL DEVELOPMENT - ResearchGate study analyzes why process innovation brings sustainable competitive advantage. ↩

16. Warren Buffett's Buy & Hold Strategy: Long-Term Investing Analysis - This article explains the concept of Economic Moat, which refers to a sustainable competitive advantage that protects a company's profits from competitors. ↩

17. Bootstrap financing: Bootstrap vs: Venture Capital: Choosing the Right Funding Path - FasterCapital article analyzes the selection factors between bootstrapping and VC. ↩