Last week, I talked about the most common advice I give when a mission-driven organization already has a great idea. This week, I want to back up and begin at the beginning: where should we, as mission-driven organizations, apply ourselves to innovation and how do we do it?
I started thinking about this systematically and strategically when I worked at MIT. MIT’s cultural ethos is unlike any of the other universities I have studied or worked at. Their motto, “Mind and Hand” traces back to its founding as a technical university–not pursuing knowledge for its own sake (mind*), but with the primary aim of putting knowledge into practice (hands).
We think of innovations as iconic inventions like the steam engine, the Haber-Bosch process, or the computer, but in my view there is a subtle difference between invention and innovation, mind and hands. An invention may exist as a defensible piece of new intellectual property, but it only becomes an innovation by being put into practice–often a much more difficult journey filled with frustratingly mundane obstacles. Counterintuitively, innovations are rarely completely novel. Often, the same invention happens multiple times, independently, but the superior invention doesn’t always win out in terms of impact–the superior innovation does, the one that made itself amenable to adoption. Crossing that last boundary to practice requires extraordinary persistence and luck, and innovators know this. A great idea can be thwarted by difficulties in staffing, in supply chain, in sales. Having ideas is easy; doing things is hard.
Innovation can be strategically and purposefully cultivated as a way of fundamentally changing a system’s dynamics. The first part of developing a strategy to apply deliberate innovation is to create a theory of change. If this isn’t an exercise you have contemplated yet, I recommend starting there. Others have better methods for developing a theory of change than I do, so I refer you to guides like this. The end result of this process should be a conceptual map of the stakeholders and forces in the system you are targeting.
In this systems-level map, briefly inhabit the perspective of each stakeholder and ask, what are the goals, activities, and authorities of each player in the system? Then ask, would amplifying that part of the system have the impact you wish to see? Are their goals aligned to your impact mission or not? Try to be parsimonious and charitable in your assumptions, and do not chain together more than a few unknowns. I typically sketch out a literal diagram at this step, just to structure my thinking.
When you identify a stakeholder whose empowerment would have the impact you want to have, ask whether there is an existing process that needs to be automated or scaled. When there is a stakeholder whose activities or goals are working counter to your desired change, that is a candidate for disruption.
Now that you have identified the stakeholders, their goals, and their activities that you wish to either amplify or disrupt, it is time to consider an innovation strategy. There is scholarship on the theory and practice of innovation, an engaging and interdisciplinary field at the nexus of the history of science, organizational psychology, operations research, and management. If the topic interests you, one of my many brilliant mentors, Anthony Sinskey at MIT recommended a book, Doing Capitalism in the Innovation Economy, to me as I started to think deeply about the topic. I have found Matt Ridley’s How Innovation Works another nice overview, with a more historical perspective. I also recommend having a look at a business school’s course syllabus and readings for a class on strategic innovation, many of which are available online. It’s also perfectly acceptable to make a visit to your local university’s library and access texts from their collections or subscription base–public university libraries are especially likely to encourage community members to use their resources and sometimes offer borrowing privileges.
In actual practice, here are the methods I have found fruitful ways to begin innovating strategically.
At very large scale and moderately long timelines, like national and state-level government, undirected openness and generosity with data and intellectual property can encourage innovation. Many countries make a variety of non-sensitive data and intellectual property available, which people have turned into impactful innovations by stitching it together with other data or surfacing it at the right time or place. The time scales are long, and the economics support a more open-field approach to innovation that tolerates at least some kinds of failure.
At a smaller scale, strategic innovation is still possible, but the mechanisms are more directed. I think of them as innovation by analogy, remix, amplification, and disruption.
Innovation by analogy works by defining a problem or a goal and asking an expert in an unrelated field how they would solve the problem. This is more than just the luck of the naive (although that contributes to it). Experts in unrelated domains bring their own epistemic tools about how problems can be solved. I’ll give an example from my own life: when I was in graduate school, I met to cook dinner and socialize with a group of about seven other students who worked in other fields every Thursday night. There were experts in computer science, engineering, archaeology, physics, Chinese literature, and myself, a biologist. Most weeks passed with just a bit of yapping over cheap beers, but some weeks, a member of our group would come to dinner with a problem they were having in the lab. One week, I was at the end of my rope, having been doing delicate dissections of fruit flies with needle-sharp tweezers for weeks. The constant rubbing of the tweezers and insect pins had magnetized them, and now the whole process was being thwarted because I couldn’t release the pins easily. I complained about this to my friends, and the physicist perked up: he needed to degauss his equipment frequently for his experiments, and he could quickly put together a degaussing circuit for my tiny tweezers. No biologist in my lab had a solution–it just wasn’t a common problem in our field. But, an expert from another field immediately saw the analogy to a problem with a simple solution from his point of view. Nearly every member of our group had a similar experience in our years of graduate school–sometimes you just need an expert who is equipped with a different set of tools to look at your problems.
The next strategic approach to innovation I have found useful in practice is remix. From my perspective, this mode of innovation gave birth to much of the field of data science, one of the hot job titles of the decade and one I held myself for a number of years. Remix means treating existing data or methods as modules that can be stacked or chained in new ways to produce a novel product or insight. Much of the work of data science is stitching systems together at the data level, finding records that could or should exist in both systems and knitting them together to produce new insights. You can see in my work on this module that I took two pieces of data about garment manufacturers and shrimp farms in India, the records of their incorporation and data collected by India’s Customs authority, to produce a new insight: to a first-order approximation, you could identify specific manufacturers in the global supply chain that were likely to be using forced labor.
Sometimes an innovation is as straightforward as amplification of an existing process or idea. There may be some actor in your stakeholder map from the theory of change exercise whose process should have the impact you want to see, but they are too small or disempowered to tip the scales. Get into their process, ask them about what they wish they could do or know, see what they are doing manually that can be automated or something they produce that needs to be surfaced to someone else at a crucial decision point, and make it happen. Transferring manual work to machines in itself is morally neutral–it depends on what you’re doing and why. Sometimes it’s work like supply chain mapping, a process that in human hands is slow, costly, and tedious work that often lags behind other processes so much that the full picture arrives too late, and the facts have already changed. The process needed to be amplified and scaled by machines, using data that was collected by a more large-scale process, something that was noticed by many people (myself included) in parallel in the last 15 years.
Finally, another mode of strategic innovation is disruptive. It is foolish to direct disruptive innovation at any old thing; no one wants disruptive innovation to interfere with the functioning of a hospital or a school. There is a time and a place for disruptive innovation, and in my experience, there are some key features to look for. In some cases, one of the stakeholders in the map is rent-seeking, and their power over the system can be strategically disrupted. In 2003, I was living in Berkeley, California, and I can attest that the taxi medallion system in San Francisco had created such a shortage of taxis that the idea for distributed ride sharing was obvious to anyone who had spent hours in a rainstorm trying to hail a cab. Rent-seeking means there is a lower friction path that a process would take if it were available. Next, there are cases where industry fragmentation itself is driving exploitative behaviors. Many smart people in the field of labor rights have noted that a highly fragmented industry of employee-pays labor recruitment has created perverse incentives for the recruiters, and the recruiters themselves have low margins and no plausible exit. The result is an industry rife with exploitative recruitment businesses, many of which would leave the industry, except the business itself isn’t worth anything and does not accrue equity. This represents an opportunity for disruptive innovation. The incumbents are too fragmented to respond to a new entrant with a more scalable model in a coordinated way, and a rapid consolidation would enable a more sustainable (low-margin but large-scale) and less exploitative business model to develop. At the time of this writing, to my knowledge, the field is still looking for the right disruptive innovation.
Now that you have assembled the picture–the system, the forces, the goals and activities, and you have identified leverage points for innovation, the work begins. Try to find ways these techniques might encourage breakthroughs that empower the stakeholders aligned with your impact.
Next week, I’ll be attending events related to UNGA (get in touch here if you’d like to say hello), so I’ll be returning in two weeks with a discussion of business models, revenue models, and exit models for impact innovations.
*We can safely leave this to Harvard.