### 4.1 Case Study Applications **Segway Case Summary (PCS Framework)** – _Segway’s journey illustrates missteps in **segmentation**, **collaboration**, and **capitalization** under uncertainty._ The table below maps key strategic moves to the PCS action categories and the primary uncertainty each move failed to resolve: |**Segway Strategic Move**|**PCS Action Type**|**Uncertainty Type**| |---|---|---| |Launched broadly without clear target market or use-case (mass-market gamble) – no compelling need identified.|`a_segment`|**u_demand** (Market demand remained highly uncertain, resulting in overestimated demand and low adoption)| |Neglected to coordinate with regulators and infrastructure – lacked a supportive usage context (no defined lanes, parking, charging) and faced bans on sidewalks/streets.|`a_collaborate`|**u_supply** (Operational/regulatory feasibility was uncertain, making product deployment impractical in many areas)| |Committed full-scale R&D and manufacturing upfront (spent ~$100M on development) before validating market fit.|`a_capitalize`|**u_investor** (Investment viability was uncertain – huge capital was gambled on unproven assumptions, heightening investor risk)| **Projecting (Perception).** Segway’s founders and backers projected an overly optimistic vision of demand. The device was hyped as _“the future of transport”_ on par with the personal computer or internet, yet it solved no urgent problem for any specific customer segment. This grand misperception of **demand uncertainty (u_demand)** led to wildly unrealistic sales forecasts (50k+ units in the first year) versus only ~6,000 actually sold by 2003. A PCS _Perception_ approach would have urged early **market sensing** – e.g. pilot trials or user research – to gauge real user needs and calibrate expectations, rather than relying on hype. By gathering evidence on who would value the Segway and why, PCS-guided projecting could have revealed the limited initial demand and prevented the assumption that “everyone will adopt it” from driving the strategy. **Coordinating (Coordination).** Segway treated its product as a standalone invention rather than part of a mobility ecosystem. It **failed to coordinate** with key stakeholders (city planners, regulators, infrastructure providers) to ensure the environment could accommodate this new vehicle. There was _“no proper infrastructure to support it”_ – users didn’t know where to ride, park, or charge the Segway. Worse, the company was caught off-guard by legal barriers: many cities and countries banned Segways on sidewalks and roads since they didn’t fit any category. This reflects unaddressed **supply uncertainty (u_supply)** in the adoption environment (regulatory and logistical feasibility). The PCS _Coordination_ lens would have encouraged **collaborative action** to reduce such uncertainty – for example, partnering with municipalities to define safe Segway lanes or policies, and working with early corporate/government adopters to integrate Segway into controlled settings. By synchronizing product roll-out with infrastructure and policy, Segway could have created a supportive context for its device, rather than launching into a vacuum of misaligned infrastructure and rules. **Sequencing.** Segway’s execution sequence was essentially _backwards_ from a PCS standpoint – they built everything first and learned critical lessons later. The company spent years and massive capital developing a polished product in secrecy (with _no user testing or iteration_ prior to launch). This meant **investor uncertainty (u_investor)** remained high: huge resources were committed before confirming market viability. When the Segway finally hit the market, its design was met with surprises (e.g. being seen as “dorky”) and its value proposition needed rethinking, but by then most of the budget was spent. PCS’s _Sequencing_ principle would have dictated a more incremental rollout – **sequence experiments to learn before large investments**. In practice, PCS would suggest starting with affordable, low-risk tests (e.g. small pilot programs for a specific segment) to systematically reduce demand and supply uncertainties, and only then scaling up production. This staged approach would align investment decisions with validated learning, ensuring that each next big expenditure is justified by evidence (thereby protecting investors and the venture from all-or-nothing bets). In short, a PCS-guided sequence could have caught design and market fit issues early, saving time and capital and improving Segway’s odds of success. ### 4.2 Validation and Performance Analysis | **Step** | **Substep** | **Evaluate (Metrics)** | **Example (Segway)** | | ---------------- | ------------------------ | ------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | **3. Solutions** | | | | | | **3.1 Nature** | 1. Satisfying axiom: Action sequence depends on stakeholder weights and initial state | >> Axiom Satisfiability: Initial State Axiom: Bottleneck respects: True Random respects: False Weight Axiom: Bottleneck respects: True Random respects: False | | | **3.2 Individual level** | 2. Efficiency: Decreased uncertainty per cost for each stakeholder type | A pilot demonstration where customers, partners, and investors could simultaneously observe the Segway in action would reduce uncertainty across all stakeholders efficiently | | | | | >> Bottleneck Sequence: a_demand, a_invest, a_demand, a_demand, a_supply, a_supply, a_invest, a_supply, a_invest <br><br>>> Segway Sequence (PRISM taxonomy): a_supply, a_supply, a_supply, a_invest, a_invest, a_invest, a_demand, a_demand, a_demand | | | | Efficiency: Maximized uncertainty reduction per dollar spent | Segway needed a coordinated approach to satisfy multiple stakeholders (users, regulators, investors) whose decisions were interdependent | | | | 3. Tractability: Increased success probability per cost | Segway should have prioritized market validation tasks ($0.25M) before committing to production design ($5M) and supply chain ($3M) to gain critical market insights at lower cost<br><br>⭐️use sublime system - where stakeholders have clear theshold (test statistis - durability, cost, greenness) | ## 5. Results Describe specific results, including a careful explanation of the uncertainty. ### 5.1 Plotting Summary ### 5.2 Uncertainty Assessment and Limitations