Part 5: Why Sustainability Metrics Needs to Blend Complexity With Simplicity

Part 5: Why Sustainability Metrics Needs to Blend Complexity With Simplicity

By Matt Polsky and Claire Sommer

Editor’s note: This is part 5 in a series examining the pitfalls of sustainability measurements that draws on examples from outside the business world. See Parts 1, 2, 3, 4, 5, 6 and 7.

Recent events in Egypt have cast doubt on the belief that a democracy-felling coup never could be justified. As of this writing, it’s hard to tell if the Egyptian Army’s move to bring down President Morsi is for the better or worse.

This has us thinking about the faith the sustainable business world places on metrics. We think we know which direction is better and which is not, but how sure should we be and how could we enhance our confidence?

Over the course of this series, I’ve described pitfalls where steps that look like the right course sometimes backfire. Life cycle analysis, for instance, may lead to a surprise about the assumed high priority of recycling for every item.

Further, neglecting the possible outcomes from non-linear systems, as shown in Part IV, can lead to nasty unexpected outcomes. A current example is the proposal to take down the last green space in a park in Turkey, which spurred a nationwide revolt.

We’ve also noticed an undeclared and fascinating debate on GreenBiz about whether to keep things simple or to think big (the systems thinking camp).

We think you really need to do both. In part, this offers the best prospects that our actions really are moving us forward. On one hand, plan to do the incremental: the basic things that in good faith appear to improve sustainability — and simultaneously, give some thought to the systems-informed pitfalls in this series. The latter provides a perspective for the former, including possibly providing an alert about one of those non-obviously wrong incremental steps.

But systems thinking is hard. So in this piece, while we continue to provide additional reasons why it’s essential, we add some “practically idealistic” ideas to make it more feasible.

Pitfall: Overreliance on data as a leverage point

For those uncomfortable with talk of complexity and who believe in a strong emphasis on data even if big changes are necessary, the late Donella Meadows offered some relevant guidance. She was the leading historical systems figure in the sustainability field and wrote the classic article “Leverage Points: Places to intervene in a system.”

In it, she ranked 12 strategies by how well they could serve as key leverage points to actually change a system fundamentally. Not by inches, but by whole. Meadows said that the most powerful way to change a system is through paradigm change. Data or numbers do make the list, but they are dead last at No. 12. If Meadows is right, numbers-based metrics have a useful role to play, but they should not be the “go-to guy.”

Pitfall: Setting an easy goal because a bold one is deemed impractical or too hard to communicate

We often see ambitious sustainability proposals, including in the metrics area, reduced to something far simpler in order to get something done. This often comes with a usually unsaid corollary of: “You don’t want to scare people.”

Many communications-oriented articles also strongly advocate to keep it simple because “you have to be practical” or “meet people where they are.” Further, a simplified project scope is sometimes justified to the impatient among us by the claim that some early wins, even if very small, build momentum towards further ones.

These arguments are compelling. You certainly don’t want to be seen as devoid of common sense, impractical or going against the flow without some really good reason.

But there’s that complex reality thing again.

Hybrid thinker Joe Robertson, who writes under the name “the Poet Economist,” puts it this way:

Complexity is not an outlandish tendency of troubled souls and pretentious intellects; it is the basic state of nature as we know it.

If we first admit this, we can work with complexity, instead of fearing it.

He adds in another article, “The Future is Not Simplicity, but Complexity, Better Understood“:

Science is demonstrating that … complexity is better able to explain what really is the truth of the physical universe than is simplicity.

… (T)o consider complexity is to begin to ask the right questions … as we come to understand the immense complexity of everything we touch, we will be better able to envision the solutions…that arise from our fumbling. … (W)e will recognize that complexity was, all along, the best source of the solutions to the problems complexity demands that we confront.

A few suggestions

We don’t have the full answer on the best ways to incorporate and communicate complexity. The challenge is there for metrics practitioners, communications professionals and others. But here are three suggestions:

1. Acknowledge from the beginning that a problem is truly complex, even if that complexity is not immediately addressed. This serves as a placeholder and reminder of what we need to get back to.

2. Adapt for our field the hybrid term “simplexity” and see what we can do with it. Simplexity is described as “an emerging theory that proposes a possible complementary relationship between complexity and simplicity.” How could we use this, along with innovative communications? How can we pursue this goal while being fully aware that people want simplicity, not complexity, as Anderson and Rainie of the Pew Internet and American Life Project state about smart systems?

If this seems hopelessly contradictory, remember that our field actually was started by and built through efforts to reconcile what was once thought impossible: “You can’t have business success while seriously protecting the environment.” We have watched our hybrid field get better and better at this “impossibility.”

As a start, Robertson helps reconcile part of this paradox, stating, “elegant (and simple-looking) theories (like E=MC²) do not eliminate complexity; they harmonize with it.” He also coined the term “simple complexities” that might help find convergences between these apparent opposites.

3. Here are seven resources and ideas that look helpful for this challenge:

• Cloud’s webinar on systems thinking
• Doppelt’s fishbone diagrams
• Unilever’s Open Innovation Process
• Elk’s fluid business boundary diagram
• Dorner’s computer-based simulations
• USAID-Nike Launch Partnership
• Shell’s Scenarios

Overall, we hope these ideas help sustainability metrics practitioners take the best from our usual strong preference for the simple, and reconcile it with the messy reality of complexity, for outcomes which truly do move us forward in both small and not-so-small steps.