Congestion Analytics - Flipping the Script
PERSPECTIVES

Congestion Analytics – Flipping the Script

Crowded stores, congested roads, and conditions conducive for economic growth that can create more of the same — sounds like urban sprawl and a promising case for urban analytics (using data science to address big city problems) to deal with those challenges and to reduce the congestion! That scenario also describes a case for congestion analytics. Certainly, some brilliant data-driven analytics folks could use data to address this situation — traffic flows, office buildings, land development, public utility distribution, housing, schools, healthcare, fresh food markets, museums, and more.

Congestion Analytics - Flipping the Script

But wait! Less than an hour away from this congested scene is a struggling community. Its streets are quiet on most days and it’s losing businesses, many of which had been there for decades but are now shutting their doors and shuttering their windows.

Connecting these dichotomous communities is a stretch of highway where traffic flows busily every morning out of the quiet place towards the urban place, and where traffic gets busy again every evening, flowing in the opposite direction back into the uncongested community.

What we have here is a classic example of a bedroom community, where urban workers sleep and relax, and where locally run businesses are closing. The people work and consume and spend most of their money in the big city, where opportunities are plentiful, but they don’t want to live in all that congestion. So they have found an uncongested place to retreat to at the end of the day.

Life in a Bedroom Community

Congestion Analytics - Flipping the Script

My wife and I recently visited such a small town in Pennsylvania, just across the Maryland border. We journeyed there one Saturday morning to visit an artisan to buy some specialty craft items whose production he has mastered. Upon arrival, we observed that the town was largely unpopulated, many stores were closed, and traffic was nearly non-existent.

In his showroom, a converted garage behind his home, we mentioned these observations to the artisan and his wife. They said the reason for this situation is that theirs is a bedroom community, where most residents drive 1-2 hours to work each day into Baltimore or Washington DC. Accordingly, those same residents exercise their consumerism primarily in those sprawling urban locations, and not so much where they live.

That was the first time in my life that I can remember when the real meaning and impact of “bedroom community” became abundantly clear to me. It was not so much sad as it was a moment for informed reflection.

My reflections might have stopped there, to be forgotten as soon as my wife and I bought some items and then drove 1-2 hours back home to the Baltimore-Washington area. (Do you see the irony? We drove from the urban area to the rural area to buy stuff. The locals do the opposite.) But what made this more personal and professional to me was that this little weekend excursion was sandwiched between two remarkable data science workshops that I attended.

Those two workshops had amazingly coincidental parallels to the above story. One workshop was in the economically booming Washington DC metropolitan area, which is at a pinnacle of business growth and opportunity.

The other workshop was in Buffalo, a moderately large city in western New York State, where the peak of its economy and business opportunity was in its past, in the pre-computer mega-industrial age. This city’s brilliant future was behind it (to borrow a phrase that I sometimes heard at the university to describe the aging professor, any aging professor).


Read my article on The Year of Experience where I discuss how data informs and inspires engaging meaningful experiences for potential customers.

THE FIRST workshop was focused on urban analytics — how to use data and data science to address the urban congestion challenges mentioned at the top of this article.

THE SECOND workshop was focused on economic development — how to use data and data science to find solutions that will bring the businesses, the people, and jobs back. The good news was that this workshop’s host city Buffalo was on its way back, and the workshop was really about their success story and to show other struggling communities the way forward — the workshop participants didn’t refer to those communities as bedroom communities, but in my mind I did!

In fact, the “wheels” in my mind had already started turning towards the idea of flipping the meaning of congestion analytics. On the same day that my wife and I visited that small town in Pennsylvania, I thought: why not apply data and data science in the same way we do in any marketing analytics application? Using analytics to attract, engage, sell experiences, nurture fan loyalty, and grow some traffic for and into those uncongested communities. After initially becoming aware of the craft through online marketing, my wife and I were certainly attracted, we engaged, we became fans of this artisan’s work, and made some purchases!

When I attended the second workshop, the wheels had turned full circle in my mind. The presentations and panels at that workshop further clarified the “new congestion analytics” labeling because many of the presenters were already doing it, organically and without the label. The analytics strategy for this new version of congestion analytics is straightforward since marketing analytics has paved the way.

Two particular presentations stood out for me, one by an economic developer from the Pocono Mountains and one by an economic developer from a beach community on the Atlantic Ocean coast. Both presenters enumerated the numerous attractions and reasons for tourists to come to their communities, and they also showed hard numbers that proved that the tourist dollars really have grown significantly in the past few years since they started using the data about why tourists should come and what great things there would be to do there, a lot of which was informed directly by positive statements that existing tourists had already shared on social media posts.

Congestion Analytics as a Small Town Data Strategy

Congestion Analytics - Flipping the Script

Like the analytics strategy, the data strategy for congestion analytics seems equally straightforward — collect and share information about the good stuff and hidden treasures in your community: history, nature, crafts, artisans, family kitchens, famous people who lived there, home tours, and interesting artifacts from prior generations.

Let the data tell you what and how to share these nuggets: Are people discussing your natural wonders on social media? Are there historical events or monuments that you can advertise online that will draw visitors? Are there local craftspeople (makers) working out of their homes & garages who can combine wares for a summer fair or an online community store, perhaps to sell worldwide? Is there or could there be a shared office workplace within your community with broadband connectivity where people can work and telecommute to their jobs? These shared workspaces are now very common in cities, especially in sprawling cities, to allow people to work closer to home in a technology-friendly business environment, though not necessarily in their employer’s building.

Tell your stories. Offer souvenirs for the soul as the main course, with a side dish of modern technologies in these unexpected places. Yes, consider hiring a part-time social media manager too! People will come. My wife and I did, despite the two-hour drive in each direction!

Crowded stores, congested roads, and conditions conducive for economic growth that can create more of the same — sounds like an opportunity, not a problem, and a promising case for flipping the script on congestion analytics. Data makes that possible, and so do the hidden treasures in every community.


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Now, take your thoughts on flipping the script for Congestion Analytics to Twitter! Agree or disagree with Kirk Borne’s ideas and examples? Want to tell us your story? Tweet @KirkDBorne using the hashtag #datamakespossible right now!

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