Eli MacLaren

Scale: How Well Do We Understand It?

This week, I had the good fortune of being invited to an expert convening on the subject of optimal child development, hosted by the National Institute for Children’s Health Quality (NICHQ), Ariadne Labs, and the Einhorn Family Charitable Trust.

Our two days together focused on a single design challenge:

“How might we promote optimal social-emotional child development for a 0–3 pediatric population?”

It is a huge question, that came with a few constraints that were framed by co-host Atul Gawande:

  • Solutions must be delivered thru the existing primary care system
  • Solutions must be immanently scalable

“These two constraints go hand in hand,” Gawande explained. “It’s easier to change the existing system them build a whole new one.”

The conversation moved on from there, but the statement left me wondering:

Do we really know enough about transformation at scale to make this assumption? Do we know how to do it most efficiently and effectively? Do we know what is hard and what is easy? Is there one best way to scale an innovation?

These are the juicy questions that have fascinated me through most of my career. At Ashoka, I worked with social entrepreneurs to design the business models that would help promising social innovations scale, and today I continue to help leaders in social systems design, test, and scale new business models. The more I learn about scale, the more I think it is important that we explore our assumptions about scale.

Here’s why:

Embracing the both/and of scale.

We often frame the scale option as Gawandi did: work within the system or build another one. But there is an “and.” At BIF, we seek to borrow the capabilities of the existing system, creating an adjacent space in order to organize them in new and different ways. In effect, we work within the system to build a new one.

The existing system has important capabilities at scale. Whether bought or built, establishing these capabilities requires significant money and talent — resources that nascent innovations often don’t have. By working within the system, our goal is to recognize the value of existing capabilities, but imagining transformational ways to deploy them.

Keep in mind, however, that this is easier said then done. There are challenges of working in the existing system, and in doing so through an adjacent space.

The first challenge is getting leaders and employees to shift their lens — such that they are imagining a transformational new model. The default behavior will be to see new ideas through the lens of an existing model and when they do, new models begin to look less transformational, as they get diluted into something more resembling the existing business.

The second challenge is creating an adjacent space where we can carve out the capabilities we want to play with in order to organize them in new and different ways. The notion is we want to test new models before we consider how to shift the entire business from old to new.

That said, the homeostatic system exists to be efficient, and efficiency requires that the capabilities “hum” in their current delivery. There is glue that keeps these capabilities humming — and cutting through that glue requires industrial strength super powers. When capabilities are deployed into the adjacent space, small questions create huge barriers:

Who gets billed? Who is liable? Does our insurance cover this? Who is accountable? How do we measure return on investment? How do we explain to the public what we are doing?

Often these questions lead to immobility, and the capabilities remain where they are. This is where leadership is critical. A great leader signals and enables these barriers to get hurdled quickly.

Fly first, scale later.

People love to ask how something will scale before we know what that something is.

We need to be able to see, touch, and feel the innovation before we know how it’ll scale. We need to know something about how it works, how it creates value for users, how it is delivered in a real world environment, how it captures value (and maybe even makes a profit), and the conditions that accelerate or hinder its growth. Until we know these things, we can’t answer how it will scale.

At BIF, when we prototype a new model our goal is to introduce the “minimal viable business model.” We introduce a business model that serves a small population — small enough to measurably observe how the model works and how it will improve people’s lives. Small enough such that we can iterate on it in real time until it is viable and repeatable. Small enough so that we can understand the conditions that make it successful. From here, we figure out what the next level of scale is and how to get it there.

I heard Joe McCannon, cofounder of the Billions Institute, describe this point with a Wright Brothers analogy:

“The Wright Brothers were trying to figure out how to fly. They weren’t trying to figure out how to mass produce air travel.”

I love this analogy.

Figuring out how to fly first, doesn’t preclude aspiring for scale. At BIF, we tell leaders to think big, start small, and scale fast.

Scale comes in many shapes and sizes.

Scale is not universally meaningful. When people ask how something will work at scale, my question is always “at what scale?”

We’ve built in an assumption that scale means “high volume, highly efficient, industrial era scale.” Its a dangerous assumption. We forget that scale is relative, different degrees of scale are useful, and small is often beautiful.

Degree is relative to the innovation or offering. Some businesses need to be small. Farm to table restaurants, for example, and other businesses that serve, and rely on, the local economy. Further, there are other sizes of scale — city-wide and regional. There are other forms of scale that aren’t about the organization at scale but focus on impact at scale, e.g. networked models.

Developing a scaling strategy, like business model generation, is a creative act. There are a number of great models to learn from — like franchising or train the trainer — but there is not an infinite set of models to choose from.

I think, more often then not, innovators perseverate about scale because funders and investors ask them to. When this happens, we put on our “expert” hats, at a time when we need a beginner’s mindset.

I think figuring out how to rapidly scale innovations that improve people’s lives is the imperative. But getting there will require many more of us trying more approaches, sharing our experiences, and not worrying too much about having the “right” answer.

Scale is an contact sport that requires more interactions in the real world to figure out how to win.

Post originally featured on BIF Speak, a Medium.com publication. 

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