Is Your Investment in Tourism Paying Off? Analyze the Impact.

Is Your Investment in Tourism Paying Off? Analyze the Impact.

Since its launch in 1993, Kansas sales tax and revenue bonds (STAR) have unlocked more than $1 billion in economic development financing. Each attraction financed through the program aims to bring job creation and improved quality of life to Kansas residents, yet the program’s primary goal is to create new spending in the Kansas economy by attracting tourists.

The Kansas Department of Commerce is responsible for selecting STAR bond attractions and districts, largely based on their feasibility to bring new tourism to the state.

However, the department lacks sufficient before-and-after data or consistent processes to evaluate if such attractions are actually boosting tourism. Without this information, it’s difficult to accurately determine if certain attractions will bring in the necessary revenues to pay off their bonds — and with billions of dollars at play, this absence of data could put Kansas’ economic welfare at risk.

To get a deeper understanding of the impact STAR bond attractions have on state tourism, the Kansas Legislative Division of Post Audit (LPA) conducted a performance audit of visitation data at 16 sites. With the help of StreetLight Data, LPA uncovered surprising insights on the efficacy of the attractions, and gained an in-depth understanding of how data-driven auditing can optimize the STAR bond program.

Tapping Into Tourism Trends

While the Department of Commerce received visitation projections of each selected STAR attraction amid feasibility assessments, it did not have the authority to require ongoing visitation data from attractions until 2021. As a result, LPA did not have access to any comprehensive or reliable visitation data to support its audit of the state’s completed STAR sites — leaving StreetLight to help fill in the gaps.

Using StreetLight’s Origin-Destination Metrics, LPA discovered that only three of the 16 evaluated attractions met the Department of Commerce’s tourism-related goals in 2018 and/or 2019. Interestingly, these three attractions — the Kansas Speedway, Topeka’s Heartland Park and the Hutchinson Underground Salt Museum — all shared one commonality: Unlike other STAR sites, these are unique attractions that are not otherwise available in the region.

With this data, LPA could identify a core problem with the state’s STAR attraction program: Officials may not be financing the right types of attractions for their intended goals. While some attractions like children’s parks or retail centers can improve local quality of life, the data shows they don’t necessarily draw in the intended audience of out-of-state-visitors, hindering the site’s ability to generate new revenue for the state.

Learning Hard Lessons With Hard Data

While the availability of travel data has exploded since the STAR bonds financing program was introduced, Kansas officials have not taken advantage of it to measure the impact of their investments — which is a common problem among government-funded investments. Using data to practice consistent, widespread before-and-after studies is becoming increasingly critical to measure goals and optimize spending, as LPA demonstrated in its audit.

To encourage this practice among officials, LPA drafted key recommendations to help the state better monitor the STAR bonds program. Such recommendations suggested the Department of Commerce collects consistent, comprehensive visitation data from STAR bond sites, and the Kansas Legislature considers amending the program’s goals to ensure attractions are generating the intended revenues.

The Department of Commerce questioned the methodologies and nuances of LPA and StreetLight’s assessment in response to these recommendations, though it did acknowledge the need for more comprehensive data and transparency within the STAR bonds program. Such data will soon be required under SB 124, signed into law by Kansas Gov. Kelly in April 2021.

Until then, LPA’s study remains a key lesson in the importance of data-driven decisions that are not based on optimistic projections or assumptions. It’s also a reminder for governments and agencies to remain consistent in their data assessments as time passes. By collecting and sharing relevant data, it’s possible to get ahead of challenges or reallocate resources to protect investments and economic prosperity. And when we replace our existing beliefs or political pressures with reliable data, we can unlock the opportunities that are proven to create a more prosperous economy.

We invite you to download the STAR Bond case study for additional detail or listen to the podcast debrief STAR Bond Financing: Is It Working?

6 Tips for Adapting Your Transportation Planning Amid Increased Uncertainty

Transportation planning has gotten even more unpredictable in 2020. Sure, we were already dealing with the unknowns of autonomous vehicles, micromobility, and more, but at least those were exciting, innovative trends. Now we’re just stuck in a land of existential short-term pandemic fog.

When will VMT return to normal? What will our budgets be for 2021? Will people go back to transit? What will congestion do? Nobody knows.

The new economic reality means that many agencies can’t even plan their budgets. Planners still have a desired future, now we must figure out how to chart that path with so many factors outside our control.

Balancing Short and Long Term Plans

Over the course of nearly 20 years working as a transportation planner for the Mid-America Regional Council in Kansas City, my colleagues and I became accustomed to dealing with crises and uncertainty related to funding – -reauthorization of federal transportation programs, national economic recessions, failed state and local ballot initiatives, you name it! While these were painful at the time, they taught me a lot about how to navigate short-term obstacles while maintaining a focus on long-term goals. If I were still working at a transportation agency, here’s what I would be studying, and how I would be setting myself up for both short- and long-term flexibility.

Understand what has and what hasn’t changed. We know that on an aggregate level travel has decreased during the pandemic, but where and by how much? Analyzing average daily traffic (ADT) road by road reveals nuances that can inform project prioritization. For example, some roads may have lighter loads but others may have actually increased. There are still corridor needs out there, and you need to know where they are.
Prioritize projects effectively. Now is the time to decide which projects should proceed and which should go on hold. Make data-based decisions based on accurate and current information, not last year’s (or even last month’s) metrics so that you can move quickly and effectively if budgets suddenly grow or shrink.
Run as many scenarios as possible. If you have the resources, consider running multiple scenarios for existing plans. Scenario planning accounts for uncertainty in the planning process, and leads to better informed decisions by stakeholders. The more scenarios you have in place, the better your forecasting, and the more flexible your plan can be. This is where a subscription to a big data platform like StreetLight can really help since you can run endless analyses for one annual price.
Keep your eye on long term goals. It’s easy to get distracted by short-term challenges, but the goals you set pre-pandemic are still important. Of course, those plans were developed under certain assumptions, and at some point you will have to go back and test those assumptions. Start thinking about the metrics you’ll need for re-evaluating them.
Support workers and commutes to help resuscitate the economy. Transportation planners alone can’t help people afford a new car, or work from home. But we can study people’s travel, and optimize for it. Identify your region’s essential workers, and understand their travel patterns using current information, not yesterday’s data. Are those movements changing during the current situation, and if so, how? You may find low-cost operational changes that can improve mobility, like tweaking bus timetables or routes.
Monitor mobility to enhance quality of life during the pandemic. People are clearly spending more time outdoors. Help local parks understand the frequency and number of visitors so they can adequately allocate resources, or identify areas with high levels of cycling and pedestrian activity for potential safe or slow streets programs.

Data to Fuel Quick Pivots

Here’s the good news: We now know what happens in an economic downturn. Instead of running modeled scenarios and guessing what happens, we actually have empirical data.

Because scenarios are shifting so quickly, we need to work with real, updated metrics instead of “typical conditions,” or last year’s data, or outdated models.

I believe that data is our way forward. To get through 2020, we need to get comfortable with a new level of uncertainty. But with a wider range of real data available, we can get the answers we need to pivot even more quickly.

7 Ways Big Data Can Help with Transportation Grant Applications

Landmark federal grants are funding planning and capital investments to upgrade American infrastructure such as roads, bridges, transit, rail, ports, or intermodal transportation. Since 2009, DOTs, transit agencies, and several other public agencies have received millions of dollars, and are poised to receive billions more from the Bipartisan Infrastructure Bill.

While these grants are competitive, we’ve seen that using Big Data adds a unique level of measurable detail that offers advantages for both urban and rural areas. And these takeaways can apply to any grant application.

The 7 Best Data Sets for Grants

Over the last few years, we’ve helped more and more agencies use our data to apply for similar grants. What works? Overall we see seven key metrics bolstering most types of grant applications:

1. Traffic counts
These building blocks measure levels of traffic for any road, from busy urban highways to neighborhood streets, to rural roads where traditional counts aren’t current or even available at all. Bonus: they can be used to analyze Vehicle Miles Traveled to evaluate air quality benefits of a project.

2. Speed
Using Big Data to determine speed can help grant applicants identify the intensity of congestion on roadway networks. This data can also be used to measure the benefits of proposed congestion reduction strategies, quantify travel time savings, and in turn, establish a baseline for calculating economic benefit.

3. Freight travel patterns
Big Data offers the ability to segment commercial trucks from personal vehicles, and analyze Origin-Destination (O-D) pairs, travel times, parking data, and more.

4. Bike and pedestrian travel patterns
Demonstrate projected health benefits by identifying hot spots where vehicle trips can be converted to non-motorized modes.

5. Top routes
When you know the most common O-Ds for trips crossing a bridge, you can assess the travel market, predict the benefits of improving that piece of infrastructure, and show why that project should be prioritized.

6. Before-and-after studies
Since we can’t predict the future, determining the benefits of a proposed project can be challenging. Using Big Data for before-and-after studies of similar projects in other regions can help.

7. Demographic and visitor information
Learn more about who’s visiting your destination to contextualize analyses of economic benefits due to tourism. Demographic data can also inform goals relating to equitable distribution of projects.

Big Data in Action: Butler, Pennsylvania

A great example of these metrics in action is in Butler County, Pennsylvania. They applied for the $100M INFRA grant from the U.S. Department of Transportation. Kelly Maurer, Operations Engineer for Cranberry Township, coordinated with Whitman, Requardt and Associates on traffic data for the application.

Within StreetLight InSight, WRA ran analyses looking at current traffic volume, segment speed, segment delays, congestion and O-D analysis. “The best part was we were able to get the results within a day, including the figures,” Maurer said. “It saved us time, and obtaining the origin and destination information was invaluable to show the regional benefit of this grant.”

We hope this gives you some ideas as you prepare to apply for (and win!) any grant application. If you have any questions, please feel free to contact our team.

The Climate Impact Index helps us think in this comparative way, particularly because most cities are never going to build a subway system like New York’s. Yet, there are still big things they can do that have huge climate impact, and those changes should be recognized and rewarded. With this list we wanted to remind everybody that finding the answer is not one-size-fits-all.

Why Congestion Doesn’t Matter

There are so many lists out there focusing on congestion. Sure, congestion is annoying and wastes time, but today’s efficient cars don’t really cause more transportation emissions when they are moving slowly. Congestion in some sense is actually good, because horrible congestion may make people look at alternatives, like transit or bikes.

For our Climate Impact Index we agonized over what factors to weight and how high. In fact, we originally planned to have sliders instead of set weights, so that planners could adjust the weights themselves and see the results. But then we decided our list would have more power if it sparked real conversations around the real issues that affect transportation emissions.

Planting a stake in the ground like that was really hard for me. I’m an academic, and I like to debate pros and cons. I know there’s no perfect algorithm for measuring the impact of transportation emissions. What we can do, however, is push thinking about how data can measure concrete outcomes.

But Maybe Horses Count

Judging from the conversations that have already come back from my colleagues, creating this list was totally worth it. We’ve got people thinking in creative ways.

Some people have responded with strong opinions about what to measure, and why. And I like that they feel deeply about these issues. Maybe they’ll take this transportation emissions impact idea even further than we did.

We’ve gotten a lot of questions about the non-obvious cities on the “Top 10” list like Des Moines and Madison. People ask me how a city like Des Moines can be “sustainable” when they don’t have a developed transit system. Well, it’s because they drive less.

I don’t care how you drive less. I don’t care if it’s because your area has transit, or bike lanes, or a compact environment, or whatever. I’ll take it any way I can get it.

People have really glommed on to the horse and buggy situation in Lancaster as a solution, which I think is fantastic. I’ve ended up in more than a few entertaining conversations about the impact of horse methane emissions (about which I know absolutely nothing).

Let’s Find a Fast Fix

When it comes to climate change, we are running out of time. We need to reduce vehicle miles traveled (VMT) in the most sprawling, most SUV and truck-filled places in the U.S., and we need to do it now.

We studied the factors that we judged important. But it’s infinite really, the data to analyze for understanding and managing transportation emissions. I encourage others to explore their own analyses.

I know that influencing transportation is the most powerful thing I can do in my limited time on earth, because changes in transportation infrastructure deeply affect our carbon output for the next 30 years. That’s where StreetLight works hard to have an impact. After all, if you can’t measure it, you can’t manage it.

Exploring Bike Infrastructure Opportunities in Dallas

With the right support and infrastructure, bikes can extend access to and from other modes like transit, serving an important last-mile connection. In fact, as transit ridership drops in the U.S., boosting bike infrastructure may help reverse that trend. A recent study by researchers at the University of Kentucky found the introduction of bike share increases rail ridership.

Bike riding is not only a healthy and affordable method of transportation, it’s also an important mode to link with public transit and extend mobility options. But bike-riding numbers in the U.S. are still quite low.

Dallas is one city that recently took a closer look at the bike-rail transit connection, with an eye to identifying where bike infrastructure could be improved.

Bike Infrastructure for “Complete Streets”

Many public officials at the local, regional, state and Federal levels are working to build better bike infrastructure. The concept of “complete streets” is now mainstream in transportation planning, as all levels of government strive to design and build streets that safely accommodate all transportation modes and users.

But the reality is that government agencies have a lot of competing priorities. Practically and financially, public agencies will never have sufficient resources to perfectly accommodate every type of user on every single road. However, they can, and should, prioritize complete networks for all modes, addressing coverage and gaps strategically.

We recently put together a report for Dallas officials interested in exploring options for evaluating bike infrastructure and prioritization.

Here is how we applied those metrics to the Dallas analysis.

1. Prioritize corridors for bike infrastructure. Our analysis helped us understand Dallas bicycle trip origin/destination patterns. This sort of analysis can be run in minutes for any type of geography in any location in the U.S. and Canada. The map below depicts the start locations of bicycle trips that end near light rail stations in downtown Dallas.

Fig 1: Heat map shows concentration of bike trip origins, with the red zone revealing a higher number of bike trip destinations.

Fig 2: A closer look at bicycle trip origins that end near five light rail stations in downtown Dallas.

Knowing the origin and destination of bike trips helps transportation officials prioritize corridors for bike infrastructure. Additionally, a before/after analysis can be run to measure change in bike trips to/from light rail stations.

Fig 3: Proposed corridors to prioritize for bike infrastructure.

2. Understand characteristics of who is traveling by bicycle. Next, we applied a demographic overlay to our analysis. Not only could we see where and when trips are made, but who is actually making them. Understanding the demographic characteristics of transportation users is critical to designing a system that is accessible and useful to everyone.

Figure 4: Income distribution for bicycle trips, summarized by origin.

3. Understand relative bicycle activity levels throughout the day. Finally, we analyzed levels of bicycle activity at specific locations throughout the day to identify peak bike commuting times. We did this because connections to light rail stations involve operational elements in addition to physical bike infrastructure. For example, traffic engineers can help ensure safe, efficient travel for bicyclists when timing traffic signals to accommodate busier travel times and corridors.

Fig 5: Percentage of bicycle trips by hour for Commerce Street in Dallas.

As Dallas works to build a world-class transportation system for current and future travelers, it will need high-fidelity data for all modes to make the right decisions. Regardless of the size or location of a city, planners across the country can rely on Big Data to inform recommendations and drive decisions.