Metrics that Matter, Part 1 – Measuring What Counts in the Built Environment

New metrics should measure what really matters to us in the built environment.

New metrics should measure what really matters to us in the built environment.

Most of the metrics we use to manage the built environment tell us nothing about our experience, emotions, or behavior, and rarely tell us about quality in a complete way. Knowing that a “green building” is 50% more energy efficient than a baseline building is important, especially as we use peer pressure and comparison to compel building owners and occupants to reduce energy use. But is this hypothetical green building building comfortable and pleasant? Fortunately, greener buildings actually often turn out to be more comfortable, but we don’t learn that from an energy efficiency metric, which is largely what’s used to determine the relative “greenness” of buildings: energy use alone doesn’t tell a compelling story.

In examining the idea of "metrics" applied to the performance, value, and general livability if you will, of buildings and cities and other areas we inhabit, it's important to draw a distinction between metrics in the narrow sense - numbers that describe physical qualities that can be measures with sufficiently precise instruments, like electricity or gas use, air temperature or humidity - and metrics in a broad sense, which apply to things that are too complex or difficult to measure with precision instruments, things like occupant satisfaction, thermal or visual comfort, or indoor environmental quality. These we use rating systems for, and the two most widely recognized rating systems for buildings, LEED and the Living Building Challenge, try to address many important human factors and general quality measures. But both are focused almost entirely on resource use and waste reduction. They don’t deal with experience, emotions, and behavior as drivers for design decision making either, which is no surprise as they're largely the creation of engineers and building science people.

We’re rapidly developing and installing a vast global network of data collection systems and devices, all increasingly running on the Internet of Things to power “smart” buildings and cities, but what will we do with the tsunami of new data we collect? The companies and experts building and promoting this new technology don’t care as much about making it relevant to normal humans as much as they do about locking up protocols, selling increasingly complex systems, and charging rent on them forever. 

Because cities are becoming denser (and in the process potentially greener) we need planning and building practices that can adapt to this global sociological change. In order to do this we need new metrics that encompass human cognition, experience, behavior, and health as driving factors for the built environment- the old quantitative metrics alone no longer suffice. Fortunately, new widely available GIS data visualization tools allow any data to be complied and communicated dramatically, effectively and efficiently, so let’s use it to manage the things that matter most in planning, design, and decision making.

In the upcoming posts in this four-part blog series I discuss some of the kinds of metrics we need to be thinking about, for buildings, cities, and the built environment in general. Some of the relatively newer metrics, such as thermal comfort, are well under way and have been developed and promoted, and already have sophisticated software modeling tools. Some are well understood but may have encountered problems in implementation and interpretation. And some simply don’t exist yet, are proposed by me and perhaps a handful of practitioners. Most have several points in common:

1. They consider experience, emotions, and behavior as key factors, where traditional metrics do not.

2. They provide strong justification for implementing “big data” solutions productively (and easily understood reasons for implementing them) to citizens and communities who are typically bewildered by the complexity of technology and the decision making that it entails. 

3. They are frequently interconnected and interdependent.

4. They focus on services and amenities, such as improved environmental quality, health, and experience, that are provided by the use of resources, not solely on resource use.

5. Most represent a qualitative measure that is robust, relevant, and widely understood.

Of course “qualitative” metrics are harder to configure, standardize, and deploy than “quantitative” ones. Unfortunately, a prevalent research method today is still Survey Monkey, a check-off-the-radio-buttons web form, which only provides a superficial indication of what we actually experience. Methods like this are used because they’re cheap and fast, and they’re better than nothing. But much deeper, more powerful, and imminently more useful methods of observation, inquiry, and analysis are now affordable and widely available, enabled by amazing new technologies and, more importantly, combinations of technologies. With the increasing use of data gathering devices distributed throughout the built environment, such as sensors and cameras, and the use of technology like gaze-tracking glasses and affective computing, we can directly observe pedestrian circulation patterns, shopping behavior, facial expressions, gait, vocal inflection, eye movement, pupil dilation, and other unconscious physical manifestations of emotions, behavior and experience. These provide a much richer source of data upon which to measure things that really drive decision making, and learning, in the built environment.

It's time for us to move beyond energy efficiency, real estate value, or LEED certifications to determine the true value of our buildings and cities and how we can make them adapt to best enable our relentless quest for replication on Earth along with all of our neighbor species.