Pittsburgh has a history of figuring out how man and machine come together in ways that can change the world – and they aren’t afraid to share those changes with other people.
It is a story that dates back to the early days of the Industrial Revolution in the 18th century. At that time, Andrew Carnegie made his fortune selling steel to our developing nation. Steel from Carnegie’s furnaces went into the trains traveling to the American frontier, it built the rails they rode on, and the guns the passengers carried. Carnegie did not create a new approach to making steel – he just figured out how to do it better than anyone else. Carnegie successfully adopted a new approach to making steel called the Bessemer process.
The Bessemer Steel Process was a method of producing high-quality steel by shooting air into molten steel to burn off carbon and other impurities. It was named after the British inventor Sir Henry Bessemer, who worked to develop the process in the 1850s.
Carnegie also brought in Henry Clay Frick as a partner in 1881, and put him in charge of company operations. Frick was an operational task master who was incredibly driven to build a better mouse trap. He drove the operations and processes that brought this new approach to life. Henry Clay Frick was my cousin.
Today, Andrew Carnegie is probably best known for his association with Carnegie Mellon University – which takes us to the focus of this post – higher education.
For today’s higher education institution, the status quo is not a viable path into the future. We’ve all read Grawe. We’ve all seen WICHE’s reports. The times of rising college-going rates and increased demand have come and gone. The competition for students is fierce. According to the Chronicle of Higher Ed, a large number of private colleges are expected to miss their enrollment goals for the fall semester.
The risks of employing yesterday’s strategies and not succeeding are actually greater than going in a new direction. The time is now to change and seek out a better way.
The 21st century’s version of the Bessemer Process involves technology and data. Said differently, data is a key ingredient to producing the new steel – personalized interactions – for the Information Age. In today’s world, machines can actually help us to be more customized in our interactions.
Higher education institutions are taking note. Sixty-one percent of all institutions in Ovum’s 2018/19 ICT Enterprise Insights survey ranked analytics as one of their top three projects for the next 18 months, with 24% of the institutions surveyed ranking it as their top priority. As departments increasingly recognizes the value provided by real-time data and insights, it is important that the analytics solutions they use are intuitive and actionable, even for nontechnical users. And as a Pittsburgh-based company, Othot has created an alternative that deliver these meaningful mix of benefits.
Analytics Deployments for Various Departmental Needs
Source: Ovum, ICT Enterprise Insights Survey 2018/19 – Higher Education
Most of us have heard the “buzzwords” like Artificial Intelligence and Machine Learning. Yet many organizations today are challenged with (a) understanding what benefits these advancements can bring and (b) how to bring these benefits to life.
Before investing in a future analytics strategy, teams need to educate themselves on key advancements that have been made in analytics today. Most colleges and universities have been using conventional predictive models to help them. But predictive analytics alone only gets higher ed halfway to what is needed to truly advance your institution and its goals. It tells you what will occur, but what happens when that outcome isn’t what you need or what you expected?
You need something that will tell you specifically how to change that outcome.
That’s where prescriptive analytics comes into play for colleges and universities.
Prescriptive analytics uses continuous data to go beyond anticipating what will happen to explain why something will happen and recommends specific actions to take. This type of advanced analytics is all about providing higher ed institutions advice on how to make something happen by prescribing a list of actions to guide you towards changing outcomes.
Prescriptive analytics attempts to quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made.
For example, it’s April, and your enrollment office receives a prediction that it’s currently tracking below enrollment targets and you need to find out how to change this outcome between now and May 1.
During that window, your institution is immersed in the appeals process as well as planning to host prospective students for a campus day visit.
If you have a pool of prospective students that are undecided and the two options above, wouldn’t it be nice to know which action to take and its impact to make up that gap to hit enrollment targets?
Prescriptive analytics is the next frontier in analytics and machine learning + technology are the vehicles that provide. But that alone will not deliver the impact that many institutions are seeking.
Higher education institutions must also reevaluate how they make decisions. The decision making model of the 21st century must be AI-driven and also include human judgment. One without the other misses the mark.
As Eric Colson shares in his recent article in the Harvard Business Review, What AI-Driven Decision Making Looks Like, humans and AI are both processors, with very different abilities. We are now at a point where decision making models that combine the best of machines and man will yield the best results.
As Colson states, “moving from data-driven to AI-driven is the next phase in our evolution. Embracing AI in our workflows affords better processing of structured data and allows for humans to contribute in ways that are complementary.”
It is also the most direct path to unlock the power of Prescriptive Analytics- and the benefits are incredibly impactful.
1. Prescriptive analytics’ superpower is explaining the ‘why’
Prescriptive analytics predicts not only what will happen, but also why it will happen. It provides recommendations regarding activities that will take advantage of those predictions. This allows for data-driven advice created by simulation and optimization.
2. Prescriptive analytics is applicable across higher education
Higher education institutions can use prescriptive analytics at all levels and functional groups within the organization.
Meaningful applications exist in marketing, recruitment, admissions decisions, financial aid awards, student advising, academic planning, financial forecasting, and executive planning.
On top of that, they can be utilized from the President down to individual recruiters and advisors.
3. Prescriptive analytics improves outcomes
Higher education institutions can use prescriptive analytics to improve the relationship between the student and the institution to change outcomes.
Colleges and universities using prescriptive analytics have been able to increase enrollment yield (see example above), optimize net tuition revenue, optimize financial aid, and improve retention or graduation rates.
By understanding what drives each student’s behavior and by how much, optimized plans can be created to meet goals.
4. Prescriptive analytics offers continuous, real-time advice
Prescriptive analytics runs 24-hours a day and continually processes new data as it becomes available to re-predict and re-prescribe solutions.
Taking into account the results of prescribed actions is important in continuing to be accurate with predictions and advice.
5. Prescriptive analytics is hard
Prescriptive analytics relies on sophisticated analytics tools, techniques, and technology—like artificial intelligence, machine learning, heuristics, and algorithms—which makes it a costly challenge to implement and manage.
This begs the questions on whether it’s in your institution’s best interest to build a prescriptive analytics engine internally or to partner with a point solution, which you can read about here.
Othot’s partner schools are finding that when they combine prescriptive analytics with this shift in their decision making model, they see tangible impact. Texas Tech University is a prime example of an institution that has worked to bring this magical combination together to see a 3% increase in yield. Our work with Jamie Hansard and her staff at TTU has been incredibly rewarding. I’ll never forget our first training session in which they brought together nearly 50 staff members to learn how to use our software. They have embraced this new model for decision making and the impact has been exceptional. This new way of operating is not limited to big public institutions. Massachusetts College of Art & Design has embraced this operating model in serving a much more specific type of student. Chris Wright and his team have managed to deliver consecutive record setting years while balancing enrollment growth, class shape, and net tuition revenue. We’ll have more details on that later this month.
AI Driven Decision Making + Personalized Insights with Prescriptions = Impact.
In some ways, I like to think that Othot’s mission is to help unlock the power of this formula. Like Carnegie and Frick, we did not create these approaches, but we are figuring out how to apply them better. I know – that Pittsburgh thing is back.
I think about my more famous cousin, Henry Clay Frick, and the role that he played in doing something innovative and entrepreneurial many years ago. I also think about how passionate he was in pursuing his mission. During the Homestead Strike of 1892, a striking worker burst into his office and shot him on a Friday afternoon. As the story goes, he was back at his desk working the following Monday.
We certainly live in a different age- so please don’t shoot the messenger!
Othot is a higher education software company that provides cloud-based predictive and prescriptive analytics solutions with explainable AI to identify and empower–in real time–higher education institutions to optimize its relationship with individual students from the day they first meet them through their days as active alumni.