Getting Better at Getting Better

Velocity Made Good and the Challenge of Getting Better at Getting better

I first learned about the concept of velocity made good, or VMG, in sailboat racing. A sailboat can't sail directly into the wind, and VMG indicates the vector of the speed towards the direction of the wind. If the direction of the wind is aligned with the location of your destination your VMG might be slow, but fast enough to win a race over others unable to make an optimal VMG.

The concept of VMG is an apt metaphor for research and development activities in the pursuit of innovation to address complex challenges. For example, the biopharmaceutical R&D pathway for new medicines follows a proscribed pathway from discovery to market authorization based on long-standing regulatory requirements and well-accepted patterns of research. This proscribed sequence of studies and decision-making milestones brings discipline, transparency, and accountability to the R&D process. It is also optimized to maximize the velocity made good – regardless of whether a drug candidate succeeds or fails, the requisite information to approve or disapprove further investment is available at key decision-making milestones.

The concept of VMG is at the core of the pursuit of getting better at getting better - learning how to make progress against difficult challenges without making unforced errors that waste time, money, and the opportunity to advance innovation.

Complexity & Ambiguity - Obstacles to Innovation in Global Health

The concept of VMG in global health research and public policy-making is complicated by the complexity of the challenges. The 17 Sustainable Development Goals adopted by all United Nations Member states in 2015 recognize that ending poverty and its associated adversities must also be coupled with strategies that improve health and education, reduce inequalities, and spur economic growth while also addressing climate change and preserving the global ecology.

The complexity inherent in working to meet these goals originates in the wide scope of interconnections between these challenges. The complexity is shaped by a myriad of dynamic factors operating at the individual, community, societal, and global level that can lead to the emergence of unexpected conflicts and unintended outcomes with any proposed solution. Understanding the context of the challenges at each of these levels is vital to finding successful, scalable, and sustainable innovations.

The Challenge of VMG in Global Health

The fundamental obstacle in tracking the relevant context for global health research is that the problems encountered are often complex, interrelated, and not well defined.

While the strategic rationale for addressing a specific problem may be well-supported, the efforts to design and operationalize an action plan often generate innumerable questions about the specifics of the work and its likelihood for success. Research programs in global health are conceived and designed by independent academic researchers along different disciplinary lines; the studies consist of different study designs, different target populations, different inclusion and exclusion criteria, different endpoints, and so forth.

On the one hand, these varied research programs create a rich ecosystem of hypotheses, results and ideas that provide a glimpse of the many dimensions of the underlying complexity.

On the other hand, there is a lack of coherence across these multiple, independent research projects that makes it difficult to integrate results across studies and effectively guide future research planning and policy making. While we may get hints of progress at understanding complexity and context, the VMG for these programs can be disappointing.

Conceptual schemes are the lingua franca of interdisciplinary research

One way to begin understanding the complex systems inherent in global health is by describing them in detail: mapping out the many parts, multiple interactions, and how they change through time.

It has been 124 years since British scientist Sir Ronald Ross discovered that the female Anopheles mosquito transmits malaria between humans. This finding provided the foundation for scientists across the world to better understand the deadly role of mosquitoes in disease transmission. Over time, we developed a detailed understanding of the life cycle of the plasmodium parasite. This understanding, represented in a conceptual scheme showing the different stages of the lifecycle and their causal pathways, has been realized via constant iterations of our understanding based on the emerging science in entomology, biology, pathophysiology, and epidemiology of malaria. And we are still learning more as the technology evolves for measuring different forms of the parasite over its lifecycle.

Conceptual schemes like the one for the plasmodium parasite, provide a structured distillation of extant knowledge from the field and represents attempts to obtain a picture with a high signal to noise ratio. The schemes bring parsimony and transparency to the interdisciplinary collaborative process and assist in exploring the boundaries of disciplines, and the space between them, to identify knowledge gaps and assist in the design of studies to fill these gaps.

Tools for harnessing collective intelligence

Conceptual schemes are commonly used to describe the challenges in global health research, but often these become a static work of art rather than a dynamic living document. Imagine the value if we took these schemes as starting points - recognizing that they are likely incomplete - and make a societal commitment to continually refine the imperfections as new knowledge emerges.

The creation and vetting of conceptual schemes in a communal setting requires new tools and processes that foster (1) the systematic acquisition and integration of new knowledge into knowledge graphs, (2) the assembly of the relevant knowledge into conceptual schemes, and (3) a review process that can enable the vetting and adjudication process of conflicting ideas while communicating iterative improvements to the community for feedback.

An emerging public good

As we envision it, the knowledge graphs and conceptual schemes would be used by scientists, governmental agencies, funding agencies, and policy makers to immerse themselves in the complexity of a challenge. This immersion enables (1) the visualization of the multiple dimensions of the challenge, (2) accelerates recognition of connections to the adjacent possible, (3) facilitates the identification of relevant domains that need to be further explored, and (4) provides support for specifying RFIs and RFPs that generate the knowledge for iterative refinement of conceptual schemes.

The 21st century could be a great age of new commons. And unlike the tragedy of the commons that often occurs with unbridled access to community property, it is not possible to use up the ultimate commons - information and knowledge that can be used to help solve global health and development challenges. If we were to match the growing capabilities of our technology for managing and sharing collective intelligence with comparable social and organizational imagination to use this intelligence, we could confront the complexities we face and seek out truly impactful innovations for seemingly intractable problems.