Technology is changing the way we do business. There is no question that cloud computing, social media mapping, web analytics, and even predictive analytics, which GIS is a large part of, are changing the way business look at and interact with customers. The data, while larger, is richer and greater in scope.
A large part of this is demographic and population mapping. Thanks to Facebook, Google, and others population mapping is more accurate and dynamic than it has ever been. But businesses are not the only ones looking at this data: the government is looking at it too. In fact, agencies like the California Lottery are using it for the same reason: selling more product.
Targeting Number One
The California Lottery wants to be the largest lottery in the country, and they are using data analytics and big data to move toward that goal. Like any other business, they are taking customer and retailer data and feeding it into a model where “We have a predictive model for scratchers in terms of them going out of stock or out of inventory at retailers, and we’ve got a model to forecast or predict how well we believe a retailer will perform when it comes to selling lottery products.” Lottery CIO Chris Riesen says.
The Lottery, although designed to help fund public education, is a multi-billion dollar enterprise in the state, and is expected to grow to $8-9 billion by 2018-19. Growing such a large enterprise means that you need to understand your customer base: who they are, what they are buying and where they buy it, and how to expand that customer base.
The Lottery Customer
Who is the lottery customer? The data the Lottery is using to better their sales reveals a great deal about who is actually buying lottery tickets, A 2016 study shows that those in the lowest fifth according to socioeconomic status (SES) account for about 61% of lottery gambling, and on average gamble more days per year (26.1) than any other group.
Mapping the location of these buyers allows the lottery to accurately predict what retailers will sell more tickets, and even what kind. Tickets are sold in disproportionate numbers in disadvantaged neighborhoods.
This means those neighborhoods invest more in the lottery. So in theory they should get more back. But California, like many other states, does not allocate lottery spending based on where the money came from, but instead spreads it equally over school districts. Edbuild, in an article titled “Lotteries as School Funding: The Game is Rigged” illustrates this fact using specific examples:
“Berendo Middle School in Los Angeles Unified School District has just over 1,000 students, 90% of them eligible for free or reduced-price lunch (FRL). Lottery retailers in the school’s immediate neighborhood sold $1.2 million in lottery tickets last year. They got back $50,000 from the California State Lottery for education—a net loss of over $4,000 per student.”
This in a neighborhood where the unemployment rate is over 38% and the high school graduation rate is a mere 54%. The exact same per capita funding per student went back into neighborhoods where the median income is over $80,000 and there are no lottery retailers in the district at all.
Income and Retailers
A simple map shows the location of retailers within school districts shaded by their average income. Why are the retailers located in these specific locations?
The psychology behind lottery purchases is clear. A survey in 2006 of 1,000 Americans showed most felt their ability to save $200,000 to be “very unlikely” and even fewer thought that saving one million was possible.
The most staggering statistic perhaps was that 21% felt playing the lottery was the “Most practical path to wealth.” Those living in poverty often feel a sense of fairness from the lottery: everyone has an equal chance at instant wealth, no matter what their background.
Transfer of Wealth
So what does all of this mean? Rather than helping communities who are disadvantaged and truly benefitting education in neighborhoods where it is needed most, the Lottery appears to instigate an actual transfer of wealth from the poorest neighborhoods to the most wealthy.
The map above shows that per capita lottery sales are significantly higher in areas where median household income is lower. Once this money is distributed equally to schools, these neighborhoods actually experience a significant loss in overall community wealth.
Is Mapping the Answer?
States like California could reallocate lottery funds to districts based on the amount of their spend on lottery tickets. Using mapping and predictive analytics this could be a relatively simple solution. In many districts this would make a significant difference in the amount each school allocated per student.
Alternatively, states could reallocate funds to districts based on a need-based formula combining median income, student graduation rates, and unemployment rates in the area.
While neither of these systems provides a perfect outcome, the current system is clearly unfair. The vast disparity of economic challenges in California illustrates this, and could serve as a model to other states. But the state and the legislature will have to do more than simply map the data in an effort to sell more lottery tickets and be the number one lottery in the country.
They will have to turn the data to reallocating lottery funds to do the most good. Only then will the lottery be the right gamble for supplemental funding for education without taking more from those who need it most.
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