On August 28, 1830, there was a famous race between the first American-built steam engine, nicknamed Tom Thumb, and a horse-drawn rail cart. It happened along a 13-mile stretch of track and represented a seminal moment in the early days of the American rail system.
How did the race come about? According to reports from that day, the horse-cart driver felt threatened by the new technology and boastfully challenged the steam engine to the impromptu dual. The engine could top out at only around 18 miles-per-hour, which was about 10 miles-per-hour slower than a good horse. So the horse took an early lead — and could repeatedly regain the lead — but the engine overtook the horse again and again when the animal got tired.
It’s an interesting footnote that the horse actually won when Tom Thumb suffered mechanical failure. But the demonstration proved successful in favor of steam. Less than a year after the race, on July 31, 1831, all horse-drawn carts were replaced by steam engines on the B&O rail line. Keep in mind that horse-drawn carts had been the conventional transportation option for rail going back to the earliest part of the century in Europe.
So you see these long-standing conventions quickly find a tipping point when a new option is available — when it is tested and ready. We think Strategic Enrollment Management finds itself at a “horse vs. locomotive” moment.
There isn’t one way to tackle your enrollment problems, or your enrollment prediction problems. Your data is unique and has its own quirks. The methods you are using should be tailored to the exact prediction problem you are facing. Current methods square peg your data into an overly “simple seven” rather than embracing the messiness and non-linearities inherent in predicting enrollment behaviors of adolescents. The conventional methods, with their decades of assumptions, are breaking under the weight of wide datasets and can no longer keep up with today’s techniques and tools.
In data science, the notion of open competition is as vital a component for innovative growth as sunlight is to plants. That’s why you see such amazing innovations emanate from online competition sites like Kaggle. Touting your accuracy in your own marketing materials is easy. Proving it is hard. Proving it in a head-to-head competition, using a common success metric and the same data set, is hardest. But it is most necessary.
We believe if more and more companies started to be public about what they were able to do in advance of asking you for money — before asking you for a contract — there would be a significant shift in the way prediction is done in higher education.
That’s why were offer our Free Envision Trial.
If you are working with a vendor to do enrollment predictions, or if you are doing them in-house, we are willing to exchange data with you and show you publicly — just bare it all open — what we are able to do. This is free. No obligation.
The tipping point is here.
By Thom Golden, Ph.D., Vice President of Data Science, Capture Higher Ed