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The Sage Economy · BML-11.07

Summary: The Economics of Purpose

Series 11: The Sage Economy

By Syam Adusumilli · 3 min read · Finding Purpose
Executive Summary Read the full article.

Diane Ortega ran the first set of numbers. She is 47, CFO of a regional foundation in Minneapolis that funds community health and civic capacity projects. When BGO approached the foundation about funding two pilot deployments, she pulled out the calculation she runs for every capacity investment proposal: what would this intervention cost the receiving institutions if they obtained equivalent expertise through traditional channels?

Jonathan Reeves ran the second set. He is 52, a health economist at a university research center in Chicago. He does not study organizational capacity. He studies retirement and health outcomes. He ran a different calculation: what does purposeless retirement cost the healthcare system relative to what a BGO deployment costs to fund?

The two calculations come from different directions. They arrive at the same place: the case for funding the BGO model is not philanthropic. It is economic.

Diane’s calculation is the more straightforward one. A twelve-week BGO deployment runs approximately $8,000 to $15,000 for a community institution. The comparison: a twelve-week consulting engagement of equivalent scope runs $85,000 to $120,000. An interim management placement runs $150,000 to $200,000. A full-time staff hire at Carolyn Marsh’s level runs $250,000 to $350,000 annually. The cost differential is not marginal. For community institutions with limited budgets, it is often the difference between accessing COO-level thinking and not accessing it at all. Diane funded two BGO pilots on institutional effectiveness logic, not purpose philanthropy. The cost per institution served was the lowest she had seen for a strategic capacity intervention with measurable outputs.

Jonathan’s calculation requires more exposition. The starting point is the research on purposeless retirement and healthcare costs. Depression rates among recently retired adults are significantly elevated in the first two years following retirement. Social isolation rates rise sharply without structured engagement. Preventable hospitalization rates in socially isolated older adults are substantially higher than in engaged peers. Each of these outcomes produces healthcare costs: primary care utilization, emergency department visits, delayed diagnosis, and the chronic disease progression that results from reduced preventive care engagement. Jonathan estimated the healthcare cost differential between a deployed Sage and a matched non-deployed peer over two years. His conservative analysis, excluding the cognitive health dimension entirely, puts the healthcare cost difference at several multiples of the deployment cost.

The insurance coverage argument runs through both calculations. Physical therapy is covered because it produces measurable functional outcomes that reduce downstream healthcare costs. A BGO deployment, if the cognitive and health outcome data shows what the research predicts, meets exactly the same coverage logic: an intervention that costs $8,000 to $15,000, preventing healthcare costs in the range of $50,000 to $100,000 in the same individual. The argument is prospective. The BGO outcome data does not yet exist at scale. The data is being generated now.

Three failure modes for the economic argument, named specifically. The cognitive health data may not show what the research predicts; if it does not, the insurance coverage argument loses its foundation. The commercial market may not generate sufficient volume to cross-subsidize purpose deployments at the required ratio. Foundation funding is time-limited; if the model does not reach sustainability before the grant period ends, the purpose deployment program faces a gap. These are not rhetorical hedges. They are the honest economics.

The foundation program officer who evaluated the BGO grant application read Jonathan’s healthcare cost differential calculation and said: the purpose story is what makes the model meaningful. The numbers are what makes it fundable. Both are necessary. Neither alone is sufficient. Both are in development.

Read the full article on BlueMirror.life.