Thinking About Value Creation to Find the Truth

2021/01/18

The information used by physicians to determine the optimal treatment plan for a patient is wide-ranging. This information is collected multi-dimensionally over time regarding the pathological conditions currently occurring in the body, and because it captures these changes (hereinafter "pathological changes") precisely and accurately to lead to predictions, the judgment of frontline clinicians is considered accurate.

In clinical settings, EBM (Evidence-Based Medicine) has become self-evident, and clinical research has flourished, leading to the handling of various data and statistical methods. On the other hand, since countless pieces of information are discarded when converting a patient's pathological changes into data, even precise results can lead to incorrect interpretations if the generation process is not accurately understood. Data scientists who do not know the clinical field should keep in mind the reality that medical data = life itself. Meanwhile, toward the realization of patient-centered Value-Based Medicine for more optimal healthcare, Precision Medicine—which utilizes all types of individual patient information, including genes—is advancing, and research has finally evolved to a level that can assist the tacit knowledge of frontline clinicians.

In business, the creation of shared social value has begun to be understood. We have entered an era where specific optimal solutions for individuals who make up society can be derived, suggesting that the challenges of individuals, society, and the planet—which have been seen as trade-offs—can be solved simultaneously. The analysis of "small big data," which also captures temporal changes in individuals, will make business even more precise and optimized.

Recently, the number of elites who say "evidence" instead of "scientific basis" has increased. However, when looking into the details, it becomes clear that they are using it to justify their own words and actions. Furthermore, interpreting results without understanding diversified analysis methods leads one far from the truth. In particular, the misuse of AI without examining algorithms is more dangerous than a cessation of thought. "In the world of belief, there is much deception; in the world of doubt, there is much truth" (Gakumon no susume (An Encouragement of Learning)), and a shift from "how" to "why" in education is an urgent matter.

However, a ray of light is shining through. Not everyone changes their behavior based on "evidence." The fact that some feel "it doesn't sit right" due to a sense of disconnect from the real world is proof of the excellence of human sensory knowledge, and it reminds us once again of the importance of "small big data." I want us to be a Keio Gijuku Shachu that can boldly challenge information that data cannot fully express, maintaining relationships where we continue to create value while evaluating each other and striving for mutual improvement.