Using "lean" concepts, urban mobility can evolve as rapidly as iPhone apps.
Why are new car models released every calendar year? How come there's a new iPhone every 6 to 12 months? And, why do those apps on your phone download updates every few days? These consumer products are the outcomes of a design and production process that values prototyping, rapid iteration, and a learn-from-mistakes approach to production that minimizes the costs of design while increasing the end value to users. These concepts represent what has come to be known as "lean production," or simply "lean."
So why should transportation planners, engineers, or even the public at large care about lean? At an event last month, SPUR and the Young Professionals in Transportation asked attendees that same question. Transportation projects have a reputation for taking an inordinate amount of time to complete and don't keep up with the pace of change people expect. As professionals serving the public in a sector with limited and uncertain funding, transportation planners can better serve their communities by embracing a more nimble and proactive process.
All this isn't to cast aside the tried-and-true (and often required) methods of the transportation planning process. That process, developed over decades, has evolved with the best intentions to think comprehensively, invest equitably, and implement projects with local support. Still, there may be strategies we can borrow from the successes of other industries to improve outcomes for our cities and their residents.
You may not have heard of what SPUR and YPT have dubbed "lean transportation planning," but already there are several illustrative examples. These projects demonstrate that there are opportunities in both the public and private sectors to experiment with prototyping, agile service development, validated learning, pivoting, and launching minimum viable products—all lean techniques designed to achieve better outcomes at lower cost and in a less risky way. Here are a few recent examples.
Better bus queues in Vancouver. The lean concepts of prototyping and iteration (a loop process in which potential solutions are continuously implemented and improved upon) were used to improve bus queuing along one of North America's busiest bus lines. Planners used inexpensive, temporary materials (i.e. "minimum viable products") combined with time-lapse video to test different alignments of bus waiting lines. Their process used a non-traditional approach to site planning and arrived at a more effective solution than one relying on models or simulations, which, in the case of Vancouver, had predicted human decision making and behavior incorrectly.
Pop-up workshops in Downtown Ann Arbor. Would you skip dinner to attend a planning meeting? Or would you rather stop and chat on your way to the grocery store or coffee house? Ann Arbor's Downtown Street Framework Plan team needed a catchy, creative, and cost-effective way to engage the residents who were actually using its streets. So instead of asking people to come to them, city planners went to the people, using Twitter to generate interest on the group's next roving location. The result was a cheaper and more effective process that eliminated overhead costs (no rooms to rent) while speaking to over 250 people in about 4.5 hours—that's almost one person every minute. Since then, the city has considered pivoting its entire outreach approach to involve more pop-up workshops.
Pivoting and prototyping street design in Memphis. The City of Memphis recently demonstrated that, with political support for a change in vision, the public sector is capable of "pivoting" its approach in the midst of a planning process. Riverside Drive, previously a high-speed four-to-five lane boulevard, was reconfigured into a two-lane street with a median-separated bicycle and pedestrian promenade. This reconfiguration was a major pivot from the initially proposed redesign and was made possible through visionary support from Mayor A.C. Wharton, who requested a study that led to a redesign recommendation. As is important with any prototype, over the next 12 to 18 months, the city's transportation staff will evaluate the traffic impacts of the new design and use this "validated learning" to figure out the next improvement.
Agile transit service development. Fixed-route transit is getting a lot of new attention from the private sector. Companies in Detroit, San Francisco, Oakland, Boston, and Chicago are testing out different service models that can quickly be updated based on changing demand. They've streamlined the planning process by relying on revealed demand and performance (how many users sign up; GPS data) rather than on stated or estimated demand (ridership models; community feedback). Fundamental elements of "lean" that many of these companies embrace are iteration, evaluation, and validated learning.
Clearly, certain transportation projects lend themselves to a lean approach more than others. As an example, the construction of a bridge doesn't leave much opportunity to update or reshape its built form. But a bridge's functionality can be modified through striping experiments and continual evaluation.
There are countless opportunities like this for leaner transport planning. In transit, we might not easily prototype new transit routes, but what about bus-stop designs or interventions to improve the circulation of passengers inside a crowded bus? In parking, we could test and learn from different parking models at special events over the course of the year and apply that validated learning to whole parking districts later on. These certainly aren't the only examples out there, but the point is to start—and continue—looking for them.
Critics of lean transportation planning will argue that the costs of failure are too high to risk implementing projects that might not work. We argue that that is precisely why we should learn from the lean approach. Planners could spend many years and lots of money to find out ideas aren't perfect, or we could spend a few hours, days, or weeks to try something and pivot based on what we learn. People today expect this frequent change. We might not get things right the first time, but if we show that we're willing to try and try again, people just might end up waiting in line for our new BRT like it's the next iPhone release.