零氪科技：医疗大数据的商业化探索（B）

The cases (A/B) distinctively touch on a universal question: How do innovative tech companies (e.g., AI-and-big data start-ups) address the pain points of traditional vertical industries through technological innovations in order to empower those industries and create value? To address this problem, some have set ambitious goals from inception, which requires significant and sustained investments in R&D to realize. Owing to their weak ability to sustain themselves in the short term, however, they cannot find a commercial path to gain profits, and may even go under in the event of a funding crunch. However, in order to survive, some others have taken a shortcut to pursue a quick profit, deviating from their original goal; once slipping into path dependence, they will find it hard to put themselves back on track. Such companies are in no position to make their mark in history, despite their ability to cash in on their business. How should innovative tech companies strike a balance between "aiming too high" and "slipping into path dependence"? We have developed the LinkDoc Technology (hereinafter "LinkDoc") cases (A/B) to examine how this big data company in the vertical healthcare industry addressed the above question. More specifically, the cases reveal how LinkDoc identified and entered the market segment, harnessed technology to achieve value creation and gain a competitive advantage, and how Linkdoc explored and chose commercialization paths, and balanced and spent resources in multiple business lines. Case (A) is about the entrepreneurial background and story of Linkdoc, and mainly describes how the company collected valuable clinical data from massive healthcare big data, and structured them through AI and algorithms in order to create value. On the strength of its Clinical Data Integration System, LinkDoc helped hospitals establish a structured medical record database to improve efficiency in diagnosis, follow-up and research. Meanwhile, LinkDoc created structured electronic medical records covering more than 3,000 diseases to facilitate physicians' clinical research and treatment. Now, its big data platform covers 60% of tumor types. Case (B) describes how LinkDoc developed commercialized products and explored the paths to commercialization after figuring out ways to create value. Among the participants across the complicated healthcare value chain, who were most willing to pay for healthcare big data? How should LinkDoc design an effective business model to arouse the participants’ desire for its products? How should LinkDoc strike a balance between short-term profitability and long-term sustainability?