- Theories of causality
- Research from different and like settings
(From “Sources of New Knowledge,” A Learning Based Approach to Leading Change, Barry Sugarman, Lesley College and the Society for Organized Learning, December, 2000.)
Then just last week, a colleague included this quote inside a client product,
Ascertaining cause and effect relationships between expenditures and end outcomes is a necessary part of governing-for-results.
National Conference of State Legislatures
These quotes intrigued me. They caused me to reflect on what we have been learning about causality inside our work on Budgeting for Outcomes. I decided to look at cause-and-effect maps from different jurisdictions on the same topic - mobility.
Mobility is an outcome that citizens want from their government. It is often expressed as 'fix my potholes' or 'solve traffic jams', but the end result desired is "Moving people and goods quickly and safely." Or, one team in Snohomish County simply dubbed it, "Getting there."
The Texas Transportation Institute estimates that, in 2000, the 75 largest metropolitan areas experienced 3.6 billion vehicle-hours of delay, resulting in 5.7 billion gallons in wasted fuel, and $67.5 billion in lost productivity. Obviously, the absence of mobility is a big deal. Yet, how much do we know about what 'causes' mobility? For me, each of the following three maps - from a city, a state, and a county - offered up a new insight.
Azusa
A city of 43,000 in Los Angeles County, CA.
(Click on the image for a larger PDF version of the map.)
What I thought was cool about this map was
- How apparent multiple modes of transportation are - from feet (i.e. sidewalks) to bikes to cars to mass transit. In one picture, decision-makers start to see the interplay across modes. And, this map provoked new conversation, such as whether to design fast moving and slow moving modes side by side.
- It doesn't stop at the city limits. It clearly shows that connection to other entities or providers matters for ease of entering or exiting the city. It was no accident that their result statement ended up stated as "improving the safety and ease of traveling to, from, and throughout Azusa."
WA State - POG 1
In the first iteration of Priorities of Government in Washington State in 2003, the mobility results team created the following map -
What I like about this map is its simplicity. Simply put, mobility is "caused" when traffic demand does not exceed available capacity. But, this map shows more secondary factors than simply laying more pavement (that is, adding to the supply of roads). It shows, for example, that user choice in the use of cars is an important factor - and one that could be influenced. This map provoked a strategic conversation about the availability and use of alternatives to cars - from mass transit to telecommuting.
Snohomish County
A county of 700,000 residents northeast of Seattle, WA.
(Click on the image for a larger PDF version of the map.)
A lot of things were 'cool' about this map. The highlight for me though was that this map distinguished the difference between "recurring and non-recurring incidents". What does that mean?
This results team found, in a combination of recent studies and analytical work, that roughly half of the congestion experienced by Americans is what is known as recurring congestion - caused by demands that exist virtually every day, where road use exceeds existing capacity. However, more than half of all congestion is non-recurring—caused by adverse weather, work zones, special events and other temporary disruptions. As you can see in Figure 1, a full twenty-five percent of all congestion is caused by impaired vehicles on the roadways. And, travelers and shippers are especially sensitive to these unanticipated disruptions.
Knowledge of this research helped spur new questions. Questions such as "How can we clear crashes more quickly?" and "How can we better influence driver behavior - and avoid crashes in the first place?" While these questions won't solve congestion alone, putting the main 'cause-and-effect' factors on the table demonstrated that the County, as one team member said, "could not engineer their way out of congestion." Multiple strategies were needed.
How did you react to these maps - and the factors they portray? In my experience, in each case they did "spark" a new debate. If we must understand the 'cause-and-effect' to outcomes as the National Conference of State Legislature says, these maps are getting there!
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