System Mapping: ORTHOREBIRTH

Yes, we received a feedback from our reader who lost both her parents to cancer. Although she is not our investor nor invest, she read our blog and wrote to us, “I saw the system map on your blog and it made me cry.”

“Emotionless medical care” loop in the bottom left of this map represented her real experience. She said, “Doctors were constantly looking at laptop screens instead of patients, following treatment guidelines without any empathy.” The map mentions “aiming for medical care that gives hope til the last moment,” which deeply resonated with her and moved her to tears.
I’m a 20 years healthcare investment veteran, but this was the first time I received feedback from end beneficiaries. The fact that our meticulously crafted system map resonated with her and others made us incredibly happy and moved us to tears as well.

The system map clarified the unique features of J Pharma and the drug. One such feature was the “physician satisfaction rate” set as a short-term impact KPI. Being able to prescribe a drug with minimal side-effect to terminal cancer patients, who previously had no such option, provides physicians with a sense of purpose and satisfaction.

Orthorebirth is a company in the orthopaedic field, developing, manufacturing, and selling synthetic bone “ReBOSSIS”. They are currently developing a drug containing Bone Morphogenetic Protein (BMP), which promotes bone formation. BMP is already approved in countries like the United States.

Compared to cutting-edge technologies like regenerative medicine and AI, it might not attract much attention. Initially, we struggled with how to approach this. However, while gathering data, we focused on the issue of caregiving, a major issue in aging country like Japan.
The top three causes of long-term care are dementia, cerebrovascular disease (stroke), and fracture/fall. Elders who fracture bones take a long time to heal, reducing their activity levels, leading to cognitive and physical decline, eventually requiring care. In Japan, where the population is rapidly aging, fractures are a major social issue.
BMP can speed up bone formation, avoiding the need to harvest bone from other parts of the body, thus reducing treatment risks and damage. Patients can start rehabilitation sooner, decreasing the likelihood of becoming bedridden.

While creating the system map for J Pharma, we wondered if our method of identifying elements, or more specifically variables, might be biased. Although we interviewed many people to identify these variables the choice of interviewees and the interviews themselves were conducted by us, which might have introduced bias.
To avoid this bias, we considered web scraping, extracting and collecting data from the web. With help from AI engineers, we learned that AI such as ChatGPT could perform web scraping. Working with the engineers, we developed an optimal prompt. This led to the discovery of the overlooked variable “pain.”
Physicians often say, “Pain can be controlled with medication, so it’s not an issue.” However, patients still experience pain, which can prevent them from sleeping, leading to weakness. AI helped us identify this crucial variable.

Yes, we were also concerned about where to place variables within the map. As long as we arranged them based on our thinking, we tended to position them in a way that suited us. We sought advice from experts in mathematics and physics to objectively calculate the coordinates for these variables. They suggested using co-occurrence analysis.
Co-occurrence analysis identifies pairs of words frequently used together, indicating their closeness. We applied this to arrange variables that should be positioned close together in the system diagram.
For example, in our fund’s Theory of Change (ToC), we identified two leverage points “wellness literacy” and “social capital.” These variables, crucial to our investment themes and deal sourcing, should appear in the system map.
Initially, we placed these two variables at opposite ends of the map, thinking it was easier to address challenges from two leverage points. However, co-occurrence analysis revealed their close relationship, prompting a significant redesign of the system diagram.
After completing the system map, we met with Orthorebirth’s management. We explained, “Based on our research and analysis, we believe your product can improve fracture treatment in the elderly and prevent them from becoming bedridden, thus addressing caregiving issues.” Their enthusiasm was palpable as they began passionately discussing their product’s mission, leading to the new keyword “social pain.”

When the elderly require care, it gives rise to issues like caregiver resignation and young carers. Orthorebirth’s CEO termed this “social pain.” He said, “Our goal is to alleviate not only physical pain but also social pain through our research and development.” We incorporated this philosophy into the final system map.

For Orthrebirth, we thoroughly avoided bias by scraping the entire web. However, some level of bias might be necessary. For the next investment, we plan to input all related texts, including interviews and business content, into AI and see how it learns from this database.

When creating a system map we should depict the current state rather than make value judgments, allowing for an honest engagement with the issues.

Yes, every investment’s system map includes “wellness literacy” and “social capital.” As we continue to build our portfolio, we will understand holistic wellness system better