test ### 1. The _Clockspeed_ Research Hypothesis Charlie explains that his research for the _Clockspeed_ book started with a hypothesis comparing Japanese and American manufacturing in the 1980s and 90s. - **Integrated (Japanese Model):** He hypothesized that Japanese companies, like Toyota, were succeeding because they **insourced their manufacturing technology (process)**. Toyota would design and make its own machine tools to "optimize and coordinate" its **product development** with its **manufacturing development**. He believed this "closer connection" between product technology and manufacturing technology gave them an advantage. - **Dis-integrated (American Model):** In contrast, American companies were **outsourcing their manufacturing technology (process)**. 제시해주신 증거(이미지) 속 화살표가 보여주는 경로는 **"Integrate Process then Integrate Product"** (프로세스 통합 → 제품 통합) 입니다. 이유는 다음과 같습니다. 1. **시작점 (우측 하단):** "Dell PC's / Bicycles" 1가 위치한 이 사분면은 **'모듈형 제품 (MOD. PRODUCT)'**과 **'모듈형 프로세스 (MOD. PROCESS)'**의 영역입니다. 2. **1단계 (위로 이동):** 화살표는 먼저 위쪽으로 이동하여 "Chrysler(90's) / Nokia phones" 2가 있는 사분면으로 향합니다. 이 사분면은 **'모듈형 제품 (MOD. PRODUCT)'**은 유지하되, **'통합형 프로세스 (INTEG. PROCESS)'**로 이동한 영역입니다. (즉, **프로세스를 먼저 통합**합니다.) 3. **2단계 (왼쪽으로 이동):** 그 후 화살표는 왼쪽으로 방향을 틀어 "BMW / iPhones" 3가 있는 사분면에서 끝납니다. 이 사분면은 **'통합형 프로세스 (INTEG. PROCESS)'**를 유지하면서, **'통합형 제품 (INTEG. PRODUCT)'**으로 이동한 최종 영역입니다. (즉, **이후에 제품을 통합**합니다.) 결론적으로, 이 모델은 시장의 경쟁 압력이 기업을 '프로세스 통합'으로 먼저 이끌고, 그 후에 '제품 통합'으로 나아가도록 유도하는 동적 경로를 보여줍니다. In this example, the successful model was the one that tightly integrated the manufacturing _process_ with _product_ development, rather than treating the process as an outsourced commodity. ### 1. 2x2 매트릭스: 독립적인 두 개의 축 프레젠테이션의 핵심 슬라이드 11과 12는 2x2 매트릭스를 제시합니다 1. - 한 축은 **"제품/시스템 아키텍처"** (통합형 vs. 모듈형)입니다2222. - 다른 축은 **"공급망/가치 사슬 아키텍처"** (통합형 vs. 모듈형)입니다3333. 이 모델은 기업이 '무엇을 먼저 할지'를 결정하는 것이 아니라, 이 두 축을 기준으로 4개의 사분면 중 어디에 위치할지를 전략적으로 결정함을 보여줍니다. (예: BMW는 통합형 제품/통합형 가치 사슬 , Dell PC는 모듈형 제품/모듈형 가치 사슬 5555). ### 2. 제품과 프로세스의 분리된 정의 이 프레임워크는 두 개념을 명확히 구분합니다. - **"통합형 제품 아키텍처"** (Integral product architectures)는 부품 간의 긴밀한 결합을 의미합니다 (예: 제트 엔진)6666. - **"통합형 가치 사슬 아키텍처"** (Integral value-chain architecture)는 지리적, 조직적 근접성을 의미합니다 (예: 도요타 시티)7. 이처럼 두 아키텍처는 별개의 슬라이드에서 독립적으로 정의됩니다. ### 3. 제품 혁신 vs. 프로세스 혁신 프레젠테이션은 "전자 분야의 파괴적 **제품** 혁신"과 "자동차 분야의 파괴적 **프로세스** 혁신"을 명확하게 대조합니다8. 또한 포드, 도요타, Dell 등을 "프로세스 혁신가"로 별도 분류합니다 9. 이는 제품과 프로세스가 서로 다른 영역에서 혁신의 대상이 될 수 있음을 보여줍니다. 결론적으로, 이 모델은 '제품을 먼저 통합할 것인가, 프로세스를 먼저 통합할 것인가'의 순서를 묻는 것이 아니라, **제품과 프로세스 각각에 대해 어떤 아키텍처(통합형 또는 모듈형)를 선택하고 정렬(align)할 것인가**를 묻는 프레임워크입니다. --- [[🐙👾charlie-vikash]] as sibiling pair of [[🐢👾scott-josh]] parameter "c" also is relevant with founder's controllability as efficient founders orients toward more controllable side of sellability or deliverability as premature automation is more likely to be avoided with greater control. it has more potential to processify without automating that's more controllable and automated Charlie i'm adding precision to your two tools: "replicate" and "automate". from the two cases (ASB, Renetech), i infer "automate" happens in delivering side () whereas "replication" is for selling side. however, i feel automating is "outsourcing without understanding" (reason why automation can precipitate processification). this can happen both in demand and supply side. in that sense, do you agree to deliver your warning against "premature automation", "automated processification" and "automated replication" might be a better framing? ---- [[🐙🗄️🏎️현지(tesla)]], [[josh_tenanbaum]] # dilemma # processify Think of a process as: "an organized group of related activities [tasks] that work together [to create] value to the customer" (Michael Hammer, 2001). Well-defined processes enable efficiency and repeatability while allowing delegation and decentralization. All start-ups need to invent processes for their development and business needs as they grow. The first time a process is undertaken, to solve some new problem faced by the organization, it might be called a "hack." The second time around, you're still hacking, but the steps and sequence might be a bit clearer. But before an organization starts scaling, its processes typically require knowledge, practice, identified customers, debugging, metrics, some predictability, and a process owner. Task standardization is a prerequisite to process definition, regularization, and reproducibility. Process discipline is a key component of processification. Lack of process adherence is functionally the absence of process. "The only thing worse than a bad process is no process." (Michael Hammer). But, if you freeze processes too soon, the enterprise may lose needed flexibility when it's needed. Every process should have an owner, a well-defined customer, and relevant metrics. Process design requires very different capabilities from process execution. Many "sailors" who are experts at running processes in mature organizations are at a complete loss if asked to design new processes in an early-stage start-up or a rapidly scaling organization. Therein lies the danger of hiring "expert" professional sailors into a new enterprise. Initially, they will need to be familiarized with their new environment and culture. And they need to know or learn the skills to design new processes that may need to be very different from the requirements in their previous organizations. # professionalize Scaling requires that the organization transition from generalist founders to specialist professionals. One challenge with such professionals is that their first inclination is often to try to reproduce exactly the functions and systems they had in their previous organizations, before learning the particular culture and challenges of their new organizations. Integrating new professionals (in marketing, finance, operations, procurement, IT, legal, etc. etc.) into the company culture is crucial to successful organizational growth. Such new hires, if they are effective, will surely influence the culture, but they need to do so by understanding the perspectives of the founding team. So, while the founding nailers may feel they are starved for the capabilities that come with bringing in professionals to help, feelings can turn sour if the cultural chasm is too vast. Bringing in a "professional CEO" can be the most delicate task in this stage of the organization's journey. Some nailing CEOs smoothly adjust to the scaling challenges. But others do not. If the founding CEO is not well suited to scaling, but the team clings to the personality and culture that their initial leader exuded, then the Board should hope to find a new leader who can reassure the team, but lead the scaling stage with vigor and rigor. Professionalization brings more structure, with clearer lines of command and reporting, and more risk of creating silos across the organization. Leadership needs to scale up the communication capabilities of the organization to keep all the organization components still working on the same team and the same mission, even though each group has its own sub-tasks, and newly minted KPIs in many cases. Professionals also bring expertise for compliance, rules, and standards -- capabilities not often found in the jungle environment. But, as the company scales, the risks of not following rules increase. Having the right team is arguably the single most important component of scale-up success. Ultimately, you must hire for the organization you want to become, not the one that got you through the jungle. # acculturate A strong, positive, continually reinforced culture serves as the glue that keeps an organization together, especially once it has outgrown its single room with constant face-to-face communication amongst the founding team. (If that team room is a "Zoom room," the challenges of creating and nurturing the culture are even greater.) Building, evolving, and nourishing a culture that supports the organization's goals and values is critical to efficient scaling. During rapid growth, the sheer number of employees and partners that are added creates significant challenges to acculturate every new joiner, as well as maintain the passion amongst the organization's veterans. Entropy is a natural phenomenon in virtually all organizations, so a culture that is not constantly communicated is liable to fragment over time. Cultural reinforcement must remain the job of the top leadership team. Say it every day if you mean it: Culture starts with the mission and the values. If these elements are expressed with authenticity and passion and are reinforced every day, they will inculcate habits of reinforcement throughout the organization. Such consistency is a tall order for large groups of people. Further, as the organization grows, the culture will be dynamic. Guiding this process requires thought, attention, and lots of communication, and when moving from the jungle to the mountain to the ocean, leaders should acknowledge publicly the evolution and transformation of this culture. Minl Case Study: In their book "How Google Works" (2017), former CEO Eric Schmidt and Jonathan Rosenberg paint a vivid portrait of the creativity and fluidity within Google culture in its early days. More recently, many former employees and commentators have lamented the corporatization of Google and the diminishment of the culture that sparked so much success Yet, a March 2024 Wired story that relates the creation of the transformer model that has revolutionized AI, describes a serendipitous process that has delivered an innovation, so impactful that it literally has changed the world, just as Google Search did three decades earlier. So, despite the dramatic corporatization of the Internet giant, embers of the early innovation-encouraging culture live on. # automate In the nailing stage, when so many activities are experiments that will be adjusted on the next iteration, processes are typically manual by necessity. The flexibility to experiment and adjust repeatedly is the essence of the nailing journey. However, once processification is well underway, manually repeating processes ad nauseum rarely helps quality or productivity. Computers and robots are very good at perfect repeatability of well-defined tasks so automating physical and information processes can enable increased efficiencies of workflows. Automation, done well, simplifies operations by eliminating manual tasks, saving staff from repetitive workloads. However, successful automation requires that processification be done thoughtfully, and there needs to be confidence that the products and processes will be reasonably stable. Automation can turbocharge an organization's growth capabilities. However, done poorly, "implementing [ERP] is like pouring concrete into a company." ("Liquid Concrete," The Economist, Sep 13, 2007). Where labor costs are low, and programming skills are dear, automation is likely to progress more slowly, but even in low labor cost regions, a great deal of effort is often invested in automation, once serious scaling commences. Advocates of AI systems trumpet the opportunities for even greater levels of automation across a broad range of tasks -- physical and intellectual -- historically performed by humans. Learning to exploit such opportunities will require significant experimentation. So scaling firms must not discard their nailing skills -- they will be needed for scaling and automating processes. # segment Early in the nailing stage, entrepreneurs are encouraged to develop their "minimum viable product" for their "beachhead market" (Bill Aulet, MIT, 2024), and by necessity, a single market segment is typically targeted. If that target is well chosen, the "total addressable market" will enable the firm to begin generating revenue and trigger the growth process. However, as, successful firms saturate their beachhead markets, they must explore how to drive growth into adjacent or different market segments. Such segmentation almost always accompanies the scaling stage and typically requires additional and more fragmented efforts in marketing, sales, engineering, product development, finance, and operations. If processification is well underway, some of the developed processes will need to give way to specialized sub-processes. If automation commences too early, costly rework of automated processes may be required to accommodate new market segments with different needs. Segmentation almost always adds complexity and cost to the operations functions that support the products and services designed for the multiplicity of segments. Thus, segmentation is critical for scaling but will challenge the operations function to expand its breadth of activities. Despite scale economies, unit costs may increase. In the nailing stage, the first customers, are often found one by one, requiring significant investment by the founding team. As a company scales, this approach no longer physically works, but it is critical to continue the mindset of staying close to the customers, to continue to test new product or service ideas, and to remain responsive to feedback. Segmentation can bring conflict -- particularly between the sales and operations teams. Sales will typically want to serve as many customers as possible, despite a plethora of idiosyncratic demands. Operations will want to exploit high-volume processes and automation, made easier by lower product variety. Such tension must be addressed by senior leadership. A well-worn adage states that the first requirement of a good strategy is knowing what you are willing to say "NO" to. Some segments may not be worth pursuing Senior leadership therefore must articulate a strategy that addresses potential segmentation and growth conflicts -- and put in place (with the help of Finance and HR) metrics and incentive structures to enable teamwork toward common goals, rather than creating silos with opposing objectives. # evaluate Even when founders articulate a clear vision for their future, internal alignment will require systems to set milestones, measure progress, and identify potential problems. Metrics enable organizations to manage the performance of professionalized teams and the effectiveness of processes. Evaluation is also critical for demonstrating the responsible use of investor funds. Once different teams have (appropriately) different metrics, challenges in organization alignment will arise. Further, the enactment of narrowly defined metrics can stifle the innovative spirit that brought the firm its initial success. On the one hand, the scaling firm must focus on a concise set of objectives and create a measurement system to support those objectives. However, organizations at all stages still need innovation and creativity, and employees energized to feel that their contributions are appreciated. So KPIs and the like must be used in conjunction with "qualitative" assessments that matter in the organization, and that rely on leadership judgment to encourage support of overall corporate goals. In many organizations, crossdepartment collaboration (which can be harder to measure) is at least as important as within-department focus. After the long jungle trek, riddled with ambiguity, many employees may welcome the relief of having a more concrete set of tasks and goals. Start-up fatigue is not only physically rough on people, from long hours devoted to trying to validate the business concept, but also spawns mental fatigue, catalyzed partly by the stresses of uncertainty. Objective metrics enable organizations to set milestones to help prioritize time and resource allocation. # platformize The Internet age has witnessed remarkable scaling speed and scale economies enjoyed by some companies (e.g.. Facebook, Google, Amazon, Uber, Wanbaba, TenCent) that have exploited what is referred to as a platform business model. (See e.g., Cusumano, Gawer, \& Yoffie (2019) or Parker, van Alstyne \& Choudary (2016).) The core idea is to establish a central "platform" that is attractive to multiple kinds of users (e.g., buyers and sellers), which can trigger explosive growth as the addition of more of one type of user (e.g., buyers) attracts a larger number of the other type(s) (e.g., sellers), and vice versa. The model of creating such marketplaces (with "cross-network externalities") is as old as the village square or the shouk, but the Internet has enabled scaling speed to be exponentially faster. In some cases, a good platform can beat an excellent product, so scaling with a platform provides a great opportunity when the business model can accommodate such a structure. Still, this scaling tool must be viewed as exactly that: a tool. Not all businesses are a good fit for this type of business model and attempting to scale in this way requires a well-thought-out business plan and a process for triggering initial growth from at least one "side" of the platform. Mini Case Study: Apple initially built a user base of "music lovers" through aggressive marketing of its iPod product. Once it had many iPod users, Apple was able to sign on music companies to sell their songs on the iTunes platform, which, in turn, attracted even more music lovers to the iPod. Once the iPod gave way to the iPhone, the iTunes platform was able to add a third side to their platform, with a third type of "user," the app developer, which turbo-charged growth even further. # collaborate Very few firms can do it all themselves. Most start-ups collaborate with supplier partners, channel partners, technology partners, distribution partners, etc. Especially when the firm is small, partnering can be challenging, because a small start-up has little leverage with a large supplier or distributor. A successful young firm that has already started scaling has potentially much more leverage to develop relationships with attractive partners. However, collaborative relationships typically require some manner of sharing the pie. Thus, a collaborator is often both a value-adding partner and a competitor for a share of the total valuechain profits available. Sometimes collaboration can be a short-term engagement (sharing resources for example); sometimes it can lead to more significant relationships that might eventually evolve into a merger or acquisition opportunity. Strategic suppliers or distributors can significantly extend the reach of the growing company to sources or customers that might not otherwise be accessible. Collaboration helps companies scale as long as it can provide mutual benefits, is meaningful and mission-driven. and is based on complementary skills, interests, or goals. However, such relationships can add complexity, as the scaling organization must balance multiple interests while keeping an eye on its own long-term goals. # replicate For many business models, scaling requires replication and reproducibility. Once a process has been refined, it may need to be replicated in many locations and settings, sometimes identically, and sometimes with modifications for localized needs for different market segments. Organizations need documentation, training, and measurement to support the capabilities and outcomes of replication efforts. Some retail organizations, like McDonald's and Walmart for example, have proved to be masters of replication, building thousands of retail stores, each of which provides a very similar, If not identical, value proposition. Such models provide very strong economies of scale, whereby innovations in products and/or processes can be provided and implemented many, many times over. Some manufacturing companies also employ replication strategies, having refined processes in one location, they "copy exactly" the factory processes in another location. Successful replication requires thorough documentation and specification of the required processes as well as thorough training of both the teams that will build the replicated operations, as well as those who will run the systems involved. Mini-Gase Study: After oil prices quadrupled in less than a decade in the 1970's, Toyota Motor Corporation got a beachhead in the United States in the early 1980s, and aspired to scale from primarily a national company to a global company. Despite the skepticism of many, the company was able to replicate its vaunted Toyota Production System (TPS) in numerous factories across North America, Europe, Asia, and beyond. Through intensive training regimens applied to each new site, supported by Toyota employees and suppliers, thousands of new Toyota employees were able to master the system of TPS, and deliver quality vehicles on par with those produced by Toyota in Japan. # capiltalize For most start-ups capital investment is critical. A great deal of attention is typically paid to how start-ups can attract and negotiate for initial capital investment. Capital requirements for scaling can vary very widely, depending on the nature of the business. A software company offering a B2C app, for example, will need to pay for engineers, programmers, marketing, product managers, and cloud services, but requires little in terms of facilities, equipment, or any other capital equipment. However, the capital requirements for scaling in manufacturing, for example, to support factories, warehouses, personnel, and infrastructure - sometimes across multiple global locations -- will often dwarf what was needed for the initial start-up, depending on the business. In such cases, leadership can be faced with "The Founder's Dilemma" (Noam Wasserman, 2013) of needing to give up significant control if they want access to the necessary capital to exploit growth opportunities. Software entrepreneurs (at Google, Facebook, and Microsoft, for example), not needing nearly as much capital, may be able to retain significantly more ownership and control than those in heavy manufacturing. Choosing the right investor is critical. Ash Patel of Morado Ventures believes that good and experienced investors should be able to catalyze growth by making warm introductions for a start-up, as well as by passing on learnings from previous companies. In Patel's words, "If your investors can't help in this way, they're the wrong investors! ... When you choose your board, you choose your boss...Don't pick a firm, pick an individual... Just as there has to be chemistry between founders, there must be chemistry between founders and investors." (During the SVC2UK CEO Summit, 2013) --- [[09-26|25-09-26]] • Scale it = Grow in parallel your market size and your production and delivery capability. • Processification: enables reproducibility, delegation, simplicity, efficiency, but risks rigidity, misalignment • Professionalization: expands skill set and allows task and process focus, but risks rigidity, misalignment • Automation: enables leveraged scale, but requires balancing freezing processes vs. fluidity and flexibility • Platformization: enables leveraged scale for multi-sided businesses, but requires balancing constituent interests • Segmentation: enables customer focus and scale, but increases complexity • Acculturation: build cohesiveness and collective purpose, but hard to get it just right (When no one is watching … ) • Capitalization: enables growth, capability development, but adds pressure for financial performance, more overhead and oversight • Collaboration: expands capabilities, but adds managerial complexity • Replication: enables growth, reproducibility, but requires standardization and discipline • Evaluation: measures progress, but potentially reduces innovation [[09-23|25-09-23]] # organizational entropy **Proposition:Organizational Entropy exists** **Second Law of Thermodynamics.** This law states that, as one goes forward in time, the net **entropy** (degree of disorder) of any isolated or closed system will always increase (or at least stay the same). (http://www.exactlywhatistime.com/physics-of- time/the-arrow-of-time/) **Entropy** is the tendency towards disorder (if no energy is exerted to reduce such disorder). **What is Organizational Entropy?** “Let’s imagine that we start a company by sticking 20 people in an office with an ill-defined but ambitious goal and no further leadership. We tell them we’ll pay them as long as they’re there, working. We come back two months later to find that five of them have quit, five are sleeping with each other, and the other ten have no idea how to solve the litany of problems that have arisen. The employees are certainly not much closer to the goal laid out for them. The whole enterprise just sort of falls apart.” (https://fs.blog/2018/11/entropy/) --- [[09-21|25-09-21]] # fiedelity of replication Replication: For many business models, scaling requires replication and reproducibility. Once a process has been refined, it may need to be replicated in many locations and settings, sometimes identically, and sometimes with modifications for localized needs for a different market segment. Organizations need to document and train and measure the capabilities and outcomes of replication efforts. Illustrative cases: Unity Homes, VFA. Unity Homes was conceived to offer lower-priced homes but with a similar value proposition with regard to quality and energy efficiency. Unity homes were custom designed on a modular platform but offered less variety, less complexity, and smaller footprints than the typical Bensonwood home. Unity initially produced its panels in the Bensonwood factory, but that facility was not optimized for lower costs or lower variety required for the mid-tier market. In 2018, Unity opened a second factory in New Hampshire, designed for higher volume, lower variety, and lower cost, and had plans for replication of this factory design in different locations across the United States. The desire to maintain family control and expand through internally generated cash only slowed the growth as compared with what might be possible with a broader capitalization strategy. VFA deployed a platformization strategy to create a business and management internship “fellows” program to match high-capability US millennials with startup companies that might not otherwise have ready access to such talent. Inspired in part by Teach for America, VFA aimed to recruit the best and brightest from the top universities, with a culturalization strategy to instill common innovation and entrepreneurship values throughout their network. VFA targeted small, entrepreneurial ventures in “second tier” entrepreneurial US cities (i.e., outside places like Silicon Valley, Boston, etc.) and deployed its elite troops into those firms, providing these startups with first-class, albeit raw talent, and providing its recruits with a worm’s eye, hands-on experience in building a business. The first cities selected, Detroit, New Orleans, and Providence, had existing entrepreneurial ecosystems in place but had a high need for exceptional talent. VFA then scaled their model with a replication strategy, copying the initial model for many other cities. The startups paid salaries to the fellows, but much of the organization’s overhead was covered by benefactors, whose donations represented charitable contributions for the sake of driving an industrial renaissance in some of America’s bygone business centers. # organizational clockspeed Further, all manufacturing leaders rotate positions, geographically and functionally, every two or three years. These steps have helped reduce organizational clockspeed to about six months and prevent the formation of “silos” or proprietary internal functions. Thus, we can see that ASP has responded to increases in clockspeeds across its products, process, and organization structures. Building on these insights, I next present a systematic methodology for dynamic clockspeed analysis of the chains and illustrate it with examples from defense aerospace and information-entertainment. ---- One tack for assessing organizational clockspeed is suggested by a 1997 article in the New York Times, which observed that in the 1990s, increased stockholder activism and impatient corporate boards seem to have led to an decrease in the average tenure of CEOs in large, publicly-held companies.22 Closely related, a research study at Stanford University measured organizational clockspeed by looking at the frequency of organizational restructurings. 23 That study found that industry sectors where the product clockspeed was higher tend also to have faster organizational clockspeeds. Next I look at universities, a traditionally slow-clockspeed sector, and observe that their main activities -- education and research as information commodities -- may see their organizational clockspeeds driven to dizzying rates. - [[#Table 4: Nail, Scale, Sail|Table 4: Nail, Scale, Sail]] - [[#Table 9: Clockspeed|Table 9: Clockspeed]] - [[#Table 10: product vs process|Table 10: product vs process]] - [[#Table 10: product vs process#Process Bottlenecks|Process Bottlenecks]] [[charlie_fine]], [[charlie24👓_nss🗣️]], [[charlie24🛠️_clockspeed🗣️]], [[val(charlie).png]] ## Table 4: Nail, Scale, Sail | Stage | NAIL IT | SCALE IT | SAIL IT | | ------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Motto | "Carry as little as possible but choose that little with care." | "Ideas are rewarded. Execution is worshipped!" | "Anyone can hold the helm when the sea is calm!" | | Attributes | Speed, Learning, and Frugality | Growth and Discipline (plus Endurance and Resilience) | Stability and continuous Improvement | | Goal | Figure it out | Build capabilities for rapid growth | Maintain a sustainable and profitable growth | | Customer | Customer Intimacy | Customer Segmentation | Customer Data | | Dilemmas | Customers? Employees? Investors? | Segmentation, Evaluation, Collaboration | Exploration and Exploitation | | Definition | Create a value proposition that works for all the members in your value chain. (Profitable Product-Market fit) | Enable and support growth to exploit and expand the value proposition. | Continuously improve and innovate to maintain a competitive advantage. | | Environment | Jungle <br> - Speed and agility <br> - Customer intimacy <br> - Problem driven <br> - People centric <br> - Intense communication <br> - Immediate validation <br> - Trust & achieve consensus <br> - Minimal resource sharing <br> - Define brand and reputation | Mountain <br> - Sustain speed, build quality <br> - Customer segmentation <br> - Revenue driven <br> - Process centric <br> - Experimentation & refinement <br> - Adaptation <br> - Cautious automation <br> - Rationed allocated resources <br> - Build brand and reputation | Ocean <br> - Deceleration and stability <br> - Customer data <br> - Profit driven <br> - System centric <br> - Adaptable <br> - Continuous Improvement <br> - Process re-engineering <br> - Complex resource management <br> - Maintain brand and reputation | | Strategic and Operational Tools | The humble machete <br> - The lean start-up (Eric Reis) <br> - The 24 steps (Bill Aulet) <br> - The business model canvas (Alex Osterwalder) <br> - Entrepreneurship; Choice and Strategy (Gans, Scott, and Stern) | The Swiss Army Knife <br> - Processification <br> - Professionalization <br> - Platformization <br> - Segmentation <br> - Culturalization <br> - Automation <br> - Collaboration <br> - Capitalization <br> - Replication <br> - Evaluation | The navigation panel <br> - Lean & Six Sigma <br> - Optimization <br> - Revenue Management <br> - Theory of Constraints <br> - ERP, CRM <br> - Value Stream Mapping <br> - Business Process Reengineering <br> - Outsourcing Decision Matrix <br> - OGSM & Key Performance Indicators | | Leadership | 1. Leads with inspiration, confidence, rule-breaking mentality in the creation of the business model <br> 2. Builds excitement <br> 3. Culture builder <br> 4. Mission centric <br> 5. Experienced in continuous experimentation and learning | 1. Leads with persistence and consistency in the execution of the business model <br> 2. Builds endurance <br> 3. Institution and Capabilities builder <br> 4. Growth centric <br> 5. Experienced in stabilizing and organizing tasks and people. | 1. Leads with a steady hand and broad vision in the sustainability of the business model <br> 2. Maintains focus <br> 3. System Builder and Operator <br> 4. Profit centric <br> 5. Experienced in managing complex, sophisticated systems and diverse group of people. | | Culture & Org. structure | Culture – founders driven <br> High unpredictability and uncertainty <br> Flat organizational structure ready to iterate and pivot | Culture – organization and team driven <br> Micro-pivots and midterm planning <br> Early hierarchy and committees with clear paths but viable shortcuts | Culture – framework driven <br> Structured and disciplined <br> Complex and hierarchical with long-term vision and multiple resources | | Desired Behaviour | Nailers – problem solving innovator <br> - Excited to solve new problems <br> - Learning-centric generalists <br> - Entrepreneurial <br> - Culture creators <br> - Hands on managers <br> - Resourceful and fearless <br> - Mission driven <br> - Hacking experimenters <br> - Flexible, prepare to pivot <br> "I see a problem; I own the problem!" | Scalers – process creation innovator <br> - Excited to build new processes <br> - Specialists <br> - Organized <br> - Culture Builders <br> - Process managers <br> - Resilient and agile <br> - Process driven <br> - Systematic experimenters <br> - Capabilities replicators <br> "I see a problem; I create a problem-solving process" | Sailers – system innovator <br> - Excited to run systems <br> - Superspecialists <br> - Systematic and disciplined <br> - Culture Sustainers <br> - Managers by exception <br> - Role and rule centric <br> - Metrics driven <br> - Consistent experimenters <br> - Delegators and reporters <br> "I see a problem; I refer the problem" | | Directive | Nail it with Speed! | Scale it with Precision! | Sail it with Consistency! | ## Table 9: Clockspeed | Forces pushing towards disintegration (vertical to horizontal) | Forces pushing towards integration (horizontal to vertical) | |----------------------------------------------------------------|------------------------------------------------------------| | 1. The relentless entry of niche competitors hoping to pick off discrete industry segments. | 1. Technical advances in one subsystem can make that the scarce commodity in the chain, giving market power to its owner. | | 2. The challenge of keeping ahead of the competition across the many dimensions of technology and markets required by an integral system. | 2. Market power in one subsystem encourages bundling with other subsystems to increase control and add more value. | | 3. The bureaucratic and organizational rigidities that often settle upon large, established companies. | 3. Market power in one subsystem encourages engineering integration with other subsystems to develop proprietary integral solutions. | | **Theory** | **Simple Explanation** | **Real-World Example** | | | ------------------------------ | --------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------ | | **Tiering** 🌲 | Instead of one company managing a messy web of suppliers, it organizes them into clean layers (like a pyramid). | Ford works with its main "Tier 1" seat supplier. That supplier then manages the "Tier 2" foam and fabric makers. Ford doesn't have to manage everyone. | ![[Pasted image 20250607112208.png]] | | **Bullwhip Effect** 🤠 | A small change in customer demand creates huge, amplified swings for suppliers further up the chain. | If customer demand for a phone drops 10%, the parts maker might see a 30% drop in orders. The effect gets worse the further you go from the customer. | ![[Pasted image 20250607112217.png]] | | **Clockspeed Amplification** ⏰ | The closer you are to the customer, the faster your part of the business has to innovate and change. | Apple must release new iPhones every year (a fast "clockspeed"). The company that mines the raw metals for the phone works on a much slower cycle (a slow "clockspeed"). | ![[Pasted image 20250607112232.png]] | 2025-05-21 - when does modules become commodities? - core rigidities? ![[clockspeed.png]] ## Table 10: product vs process | Dimension | Disruptive Product Innovation (Electronics) | Disruptive Process Innovation (Autos) | | ---------------- | ----------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Key Driver | Moore's Law - Component Performance | Toyota Production System - Process Efficiency | | Value Creation | New product capabilities & features | Cost reduction & quality improvement | | Market Impact | Creates new markets/applications | Transforms existing markets | | Learning Speed | Fast iteration on product features | Slower iteration on process improvements | | Examples | **New Entrants → Established:**<br>- Intel: Chips<br>- Microsoft: Software<br>- Amazon: E-commerce platforms<br>- Dell: PC assembly | **Process Innovators:**<br>- Toyota: Lean production<br>- Ford: Mass production<br>- Walmart: Supply chain<br>- Southwest: Quick turnaround<br>- McDonald's: Standardization<br>- Zara: Fast fashion | | Clock Speed | Rapid (months to 1-2 years) | Slower (2-5 years) | | Value Capture | Through controlling key components/platforms | Through operational excellence | | Innovation Focus | Product architecture & features | Process optimization & efficiency | integrate process then product # Table 11: FAT-3DCE e.g. for [[🗄️(📝🪢🔴)]], **FOCUS:** How entrepreneurs should sequence customer versus resource partner engagement under dual commitment uncertainty. **ARCHITECTURE:** Reverse parameter engineering where entrepreneurs choose their preferred stakeholder focus first, then engineer acceptance probabilities and costs to make that choice optimal. **TECHNOLOGY:** Newsvendor model with discrete stakeholder commitments where demand represents commitment outcomes and the critical ratio determines optimal stakeholder prioritization. **PRODUCT:** A decision framework that tells entrepreneurs how to engineer stakeholder acceptance probabilities (PR, PC) and commitment costs to validate their preferred customer-first or resource-partner-first strategy. **PROCESS:** Reverse engineering methodology where entrepreneurs (1) choose their comfort-zone stakeholder focus, (2) map current acceptance probabilities, (3) engineer ecosystem parameters, (4) validate optimality using newsvendor critical ratio. **SUPPLY CHAIN:** Academic pipeline from entrepreneurship literature (demand-side input) → operations management theory (transformation via newsvendor model) → strategic management practitioners (output: actionable prioritization tools). # list of bottleneck reference you need to have a clear image of what your supply chain design looks like, who is doing what for whom, and where the “clockspeed bottlenecks” are occurring. The ### Process Bottlenecks The critical path method and the design structure matrix are designed for and applied primarily to the analysis of a single engineering project. Often, each project within a company is managed by its own project manager, not infrequently a heavyweight project manager, as suggested by the lean production paradigm, 211 who may have a great deal of autonomy in managing his or her project, using tools such as CPM and DSM. In such cases, however, there are often resources in the firm that must be shared across multiple projects. For example, in a semiconductor design house, the prototype manufacturing facility is often be shared across all the design projects. In an automotive company, the clay model shop, where models of the concept vehicles are made, is typically shared by the designers in various divisions, each of which is working on its own projects. The process bottleneck perspective, explored in work by research teams at MIT and Stanford,212 reconceptualizes the product development function as analogous to a factory for product development. Instead of focusing on the activities and relationships within the CPM or DSM model for each project, the process bottleneck approach focuses on the resources to be used by all the projects. These resources collectively represent the firm’s product development factory. Applying the concepts from Goldratt’s “theory of constraints,” which states that all factories have a bottleneck (or “constraint”) resource, 213 one then looks for the constraint resources in the company’s product development “factory.” In the product development context, when multiple projects compete for bottleneck resources, each must wait in queue for its turn to access the constraint capacity. Managing these queues and the relative demand versus supply of capacity at them typically has an enormous impact on the development time of the individual projects. In one study at Polaroid, for example, individual projects under the direction of several project managers working separately were often completed many months, or even years, later than scheduled in the CPM models. 214 Our analysis, using the process bottleneck perspective, concluded that these models had ignored in their calculations the large chunks of time that projects waited for an opportunity to be serviced by the scarce bottleneck resources. Once top management realized that someone in the organization below the level of CEO needed to “own the process” of assessing the capacity levels of various product development resources, the knowledge was available to reduce project completion times significantly. ... 👓A number of tools from multiple perspectives exist for two-dimensional concurrent engineering to support this process, including the various perspectives defined by DFM, project scheduling, design structure, process bottleneck, and customer requirements. ... As important as this insight and accompanying analysis is, its power can be increased by applying it to an integrated 3-DCE framework. In many development projects, supplier contributions can be the bottlenecks. These suppliers serve a large number of projects, sometimes more than one from the same customer. Adding key suppliers as resources in the model and, for those who may be bottlenecks, then managing them as carefully as internal bottlenecks are managed, can have a huge impact on total project time and performance. In a research project at General Motors, we analyzed one of the key bottlenecks for the entire vehicle development process: the provision of stamping dies, large steel tools that provide the shape for all stamped metal body parts. 215 --- # operations strategy from [[Space/Library/1논문용/textbook/📖nigel18_operations strategy]] ## **How Operational Excellence Pushes the Trade-off Frontier** The operations management document provides crucial support for your argument through the **efficient frontier** concept. Here's the key insight: ### **Traditional View: Repositioning on the Frontier** Most strategic thinking assumes entrepreneurs must **reposition** along an existing trade-off curve: - **More prediction** → Better stakeholder understanding but slower response - **More prescription** → Faster action but higher misalignment risk This is like the document's example of airlines choosing between cost efficiency OR variety - accepting the trade-off as fixed. ### **Operational Excellence: Pushing Out the Frontier** The document shows operations can **overcome trade-offs entirely** through enhanced capabilities. Key quote: > "operations performance improvement is achieved by overcoming trade-offs, which, in turn, is achieved through enhanced operations capabilities" **Example**: Operation B achieved better variety AND cost efficiency simultaneously through modular design, "pushing out the efficient frontier." ### **Applied to Your Framework** Your push-pull integration represents **frontier-pushing operational excellence**: - **Traditional approaches** accept the prediction-prescription trade-off - **Your integrated approach** develops new capabilities that enable simultaneous learning AND betting - This overcomes the dilemma rather than just repositioning within it The document even mentions the **"tyranny of either/or"** vs **"and/also" approach** - perfectly capturing your integrated solution that achieves both robustness AND efficiency. **Bottom line**: Operational excellence doesn't just optimize within constraints - it develops new capabilities that transcend traditional trade-offs entirely. --- [[2025-11-19]] ![[🗄️🧠charlie 2025_11_19.excalidraw]] 네, 요청하신 내용을 바탕으로 소프트웨어와 하드웨어 스타트업의 특징을 비교하는 마크다운 표를 작성해 드리겠습니다. 각 항목의 의미와 투자자 관점에서의 해석을 포함하여 내용을 체계적으로 정리했습니다. ### **소프트웨어(SW) vs. 하드웨어(HW) 스타트업 비교** | 구분 (Cost Type) | 소프트웨어 (SW / Flexible) | 하드웨어 (HW / Rigid) | | :------------------------------------------------------------------------------------------------------------ | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **Row 1: 실험 비용 (c)**(Experiment Cost)"신호를 만드는 비용"_창업자가 가설을 검증하기 위해 지불해야 하는 초기 비용_ | **[매우 낮음] c↓**<br>1. 💻 **Development (개발):** • 노트북 한 대와 클라우드 계정만 있으면 시제품(MVP) 제작 가능. • 오픈소스 라이브러리, API 활용으로 '0'에 가까운 한계비용.<br>2. ⚙️ **Production (생산):** • 초기 서버 비용 외에 추가 생산 비용 없음. • 복제 비용(Marginal Cost)이 사실상 0원.<br>3. 🧐 **Data Collection (데이터 수집):** • 제품 자체가 데이터 수집기(Logger). • 사용자 행동(클릭, 체류시간)이 실시간으로 자동 수집됨.<br>4. 🏴‍☠️ **Entry Barriers (진입장벽):** • 낮음. 누구나 쉽게 실험을 시작할 수 있어 경쟁이 치열함.📉 **투자자의 정보 비용 (Signaling & Screening)****"신호가 넘쳐난다"**• `c`가 싸서 누구나 데이터를 가져오므로, 투자자는 '데이터 없는 모호함'을 용납하지 않음.• 하지만 검증 데이터가 많아 옥석 가리기(Screening) 비용은 오히려 낮음. | **[매우 높음] c↑**<br>1. 💻 **Development (개발):** • 원자재 소싱, 금형(Tooling) 제작, 시제품 라인 구축 필요. • 물리적 부품의 최소주문수량(MOQ) 비용 발생.<br>2. ⚙️ **Production (생산):** • 시제품 하나를 만들기 위해 공장 스케줄링 및 공급망 세팅 필요. • 단위 생산 비용(Unit Cost)이 높음.<br>3. 🧐 **Data Collection (데이터 수집):** • 연결되지 않은(Offline) 제품은 피드백을 받기 어려움. • 필드 테스트, 파괴 검사 등 물리적 검증에 막대한 시간/비용 소요.<br>4. 🏴‍☠️ **Entry Barriers (진입장벽):** • 높음. 실험 비용 자체가 거대한 진입 장벽(Moat) 역할.📉 **투자자의 정보 비용 (Signaling & Screening)****"신호가 귀하다"**• `c`가 비싸서 초기 데이터가 희귀함.• 투자자는 'Lemon(불량품)'을 거를 수단이 부족하여, 극도로 높은 정보 비대칭 비용을 느낌. → **정밀한 약속(Precision)** 강요. | | **Row 2: 피벗 비용 (k)**(Pivoting Cost)"실수를 바로잡는 비용"_전략 수정 시 발생하는 매몰 비용(Sunk Cost)과 되돌릴 수 없는 정도(Irreversibility)_ | **[매우 낮음] k≈0**<br>1. 🔧 **Updates (수정):** • 원격 배포(OTA)로 즉시 수정 가능. • 사용자가 모르게 기능 추가/삭제 가능 (A/B 테스팅 용이).<br>2. 📊 **Distribution (유통/물류):** • 앱스토어/웹을 통해 즉시 전파. • 재고(Inventory) 개념이 없어 악성 재고 부담 없음.<br>3. 🪦 **End of Life (폐기):** • 코드 삭제, 서버 종료로 끝. • 데이터 마이그레이션 외에 물리적 폐기 비용 없음.<br>4. 💰 **Cost Structure (비용 구조):** • 고정비(인건비) 위주, 변동비 낮음. 방향 전환 시 인력 재배치만 하면 됨.📉 **투자자의 정보 비용 (Risk Assessment)****"실패해도 본전은 건진다"**• 피벗이 쉬워(Low `k`) 초기 판단이 틀려도 수정할 기회가 있음.• 투자자는 모호한 약속(Vagueness)을 봐줄 여유가 있음 (Risk Premium 낮음). | **[매우 높음] k≈1**<br>1. 🔧 **Updates (수정):** • 이미 팔린 제품은 수정 불가 (리콜/수리 필요). • 설계 변경 시 금형 폐기, 생산 라인 재설계 등 연쇄적 비용 발생 (Cascading Cost).<br>2. 📊 **Distribution (유통/물류):** • 유통망에 깔린 제품 회수 비용 막대함. • 피벗 시 기존 제품 재고는 전량 폐기(Write-off)해야 함.<br>3. 🪦 **End of Life (폐기):** • 공장 폐쇄, 폐기물 처리, 환경 규제 준수 등 막대한 철수 비용.<br>4. 💰 **Cost Structure (비용 구조):** • 자산(설비/재고) 비중이 높아, 방향 전환 시 자산 가치 전액 손실 위험.📉 **투자자의 정보 비용 (Risk Assessment)****"한 번 속으면 끝장이다"**• 피벗이 불가능해(High `k`) 초기 판단이 틀리면 투자금 전액 손실.• 투자자는 극도의 검증(Due Diligence)을 요구하며, 모호함을 '실력 없음'으로 간주함 (Risk Premium 극대화). | --- \subsection*{Professor Charles Fine: Operational Architecture, Clockspeed, and Process Evolution} I understand your mental model as organizing entrepreneurial and operational choices along three nested layers: (1) venture stage (``Nail it'', ``Scale it'', ``Sail it''); (2) structural architecture (product and value-chain integration versus modularity, and the clockspeed of products, processes, and organizations); and (3) process capabilities (segment, collaborate, acculturate, processify, automate, platformize, replicate, capitalize, and related tools). Across these layers, you treat operations as the concrete realization of strategic commitments: once we choose where to sit on the product--process and integration--modularity axes, and once the environment forces a particular clockspeed, our job is to design and evolve processes so that the venture can both learn and deliver at that pace without losing control. At the venture-stage layer, I interpret the Nail--Scale--Sail framework as describing three distinct but connected operating environments. In the ``Nail it'' stage, the firm operates in a jungle-like environment where speed, learning, and frugality dominate; leaders are generalist ``nailers'' who personally own problems, hack together experiments, and build founder-driven culture in a flat, highly uncertain organization. In the ``Scale it'' stage, the environment becomes a mountain that must be climbed with endurance and discipline; leaders are specialist ``scalers'' who design and refine processes, build formal structures and early hierarchies, and emphasize process-centric experimentation, segmentation, and replication while still allowing micro-pivots. In the ``Sail it'' stage, the firm moves into an ocean environment with decelerated but complex operations; leaders are ``sailers'' who run large systems, manage by exception through metrics, and sustain culture in a structured, hierarchical organization with sophisticated tools such as Lean Six Sigma, revenue management, ERP and CRM systems, and large-scale process re-engineering. Across these stages, I see you emphasizing that desired behaviors, leadership archetypes, and organizational culture must co-evolve with the operating environment, and that mis-matching people or tools to stage (for example, hiring big-company "sailers" into a nail-it jungle) can be as dangerous as choosing the wrong strategy. On the structural-architecture layer, I interpret your product-versus-process framework as a two-by-two matrix that distinguishes integral versus modular product architectures from integral versus modular value-chain architectures, with firms choosing their position rather than being assigned one. Integral product architectures tightly couple components (as in jet engines), while integral value-chain architectures tightly couple geographies and organizations (as in Toyota City); modularity on either dimension relaxes those couplings. You then contrast disruptive product innovation (typified by electronics and Moore's Law, where value is created through rapid improvements in component performance, new product features, and fast product clockspeeds) with disruptive process innovation (typified by autos and the Toyota Production System, where value is created through cost reduction, quality improvement, and slower but compounding process clockspeeds). I take from this that entrepreneurs must make explicit architectural choices about whether they are primarily innovating in product architecture or in process architecture, and whether they intend to compete with integrated or modular product and supply chain designs, rather than sleepwalking into those positions. Clockspeed is, in my reading, the unifying temporal dimension of your structural view. Product clockspeed measures how quickly a firm must change its products; process clockspeed measures how quickly underlying operational routines must evolve; and organizational clockspeed measures how frequently structures, roles, and even leadership must be reconfigured. You emphasize how these clockspeeds amplify along the value chain: closer proximity to the end-customer usually implies faster clockspeeds, stronger bullwhip effects, and greater pressure to innovate, while upstream activities such as raw material extraction operate at slower clockspeeds. You also highlight the tension between forces pushing toward disintegration (for example, entry of niche competitors, the difficulty of keeping an integrated system leading-edge, and bureaucratic rigidities) and forces pushing toward integration (for example, technical or market power in a subsystem that encourages bundling and proprietary solutions). In my research, I interpret this as a dynamic constraint: any experimental or strategic design I propose must be feasible at the product, process, and organizational clockspeeds implied by the firm’s position in the supply chain and competitive ecosystem. At the process-capability layer, I read your concepts of processification, professionalization, replication, and automation as a sequencing logic for building operational capability without destroying flexibility. You define a process as an organized set of related tasks that reliably produces value for a clearly identified customer, and you distinguish between designing a process and executing it. Early ``hacks'' become proto-processes, which then require standardization, measurement, and ownership before they can be reliably replicated or delegated; however, freezing processes too early can create dangerous rigidities. Replication, in your examples, is about copying refined processes and business models across locations or segments, often with platformization and culturalization to support consistency while still allowing local adaptation. Automation, by contrast, is framed as especially risky when it amounts to ``outsourcing without understanding'': if we automate before we truly understand the process, we lock in hidden assumptions and make later learning and reconfiguration costly. I therefore interpret your repeated warnings against premature automation, automated processification, and automated replication as saying that entrepreneurs should first processify and replicate with human-understandable routines, then selectively automate once the process is stable and well understood. Your discussion of process bottlenecks and the ``product development factory'' reinforces this emphasis on system-level thinking. When multiple projects share scarce resources, the true constraint on clockspeed and throughput lies in those bottleneck resources rather than in the local critical-path schedules of individual projects. Someone below the CEO must ``own the process'' of measuring, managing, and reconfiguring these bottlenecks. In my OR language, I interpret this as a call to map the venture’s development and delivery activities as a queuing network, identify where expected demand exceeds capacity, and treat those constraints as decision variables rather than as exogenous facts. This directly informs how I model experimentation capacity and the cost of learning in my Bayesian entrepreneurship work. Finally, I interpret your parameter ``$c' (in my notes on founder controllability) as summarizing how deliberately entrepreneurs choose architectures and processes that keep key levers within their control. Efficient founders, in your view, bias toward more controllable aspects of sellability or deliverability and avoid locking themselves into automated or outsourced solutions that they do not yet understand. This perspective shapes how I design my own research tools: when I construct a six-dimensional FAT--3DCE description (Focus, Architecture, Technology, Product, Process, Supply Chain) for a project, I try to respect your principle that process design and supply-chain architecture should increase controllability before attempting heavy automation or financial capitalization. In combination with Professor Stern's emphasis on strategic choice and experimental design, your mental model gives me a concrete operational grammar for translating Bayesian beliefs and test-two-choose-one strategies into actual supply-chain, process, and organizational designs that can evolve coherently from Nail to Scale to Sail.