Every day, UPS has to predict where millions of packages are going to originate on future days and where they are going to go. Many of these are going to be overnight deliveries from far-flung cities and need to be delivered to specific addresses before 10:30am the next morning. Why does UPS need to predict this information far into the future? Because that’s how the company can optimize how to use its fleet of aircraft and trucks to deliver on time, on budget, meet its promise to customers, and make a profit. This is very hard to do and yet, I can’t remember the last time UPS or Fedex failed to deliver on their promise to me in the midst of sun, rain, snow, or storms all over the country and the world.
Pre-COVID (and even as we work through the impact of COVID), every airline has to predict how many passengers will fly from any one of the nearly 20,000 airports in the country to any of the others. That’s 400 Million options with almost no certainty of which one of 330 Million Americans is going to decide to get up one day and decide to go from Airport A to Airport B possibly through Airport C on some future date. At an affordable cost and of course with a huge emphasis on safety. Why do airlines have to do this? Because that’s how they can price each seat on each flight, staff each flight based on the type of aircraft, schedule aircraft, and engine maintenance. It’s how airlines determine how to hire and maintain their fleet of pilots, flight crews, and ground staff. It’s how these airlines decide on the airports they want to fly in and out of, and how they make thousands of similar decisions that impact their own viability and the quality of the traveler’s experience. Yet, for decades, millions of people have flown to their destinations every day.
There are dozens of such examples—Uber matching volatile demand and supply at each street corner, or Waze / Google Maps coming really close to predicting how long it will take to get from point X to point Y on any date/time into the future, and in real-time rerouting through point Z, or Marriott and other hotel chains planning and pricing every bed night. What’s common about all these examples and healthcare is that these are asset-intensive businesses that have deployed a lot of capital and hired a lot of people that results in a high fixed costs of operation. On the margin, however, “increasing access at lower cost” (e.g. filling another airplane seat, delivering another package, reserving another hotel room, matching another passenger and driver) is pure profit to the company involved while making customers happier.
In the healthcare world, that OR that is empty for 3 continuous hours during business hours, the infusion chair that’s unoccupied when we have the staffing and drugs on hand to do a treatment, the examination room in the clinic that is empty are all examples of under-utilized assets that are perishable and, if unused, the capacity is lost forever. While that full waiting room or the patient in the OR waiting for the PACU or ICU to clear up are everyday examples of a terrible customer experience. Healthcare just hasn’t caught up yet and needs to. Fast.
Why have airlines, transportation companies, hotels and others done a better job of asset utilization, maximizing access, and lowering unit costs? Because of the invisible hand of market forces. Historically healthcare has been shielded from the market pressures these other industries have faced (e.g. airline customers have choices, hotel chains have to provide price transparency, the payor is the user for the most part) and so they have not been forced to use sophisticated tools that take existing data and make apolitical, logical, and rational decisions for the future in the best interest of the customer.
As market forces visibly disrupt healthcare (no more access to cheap capital, reimbursement pressures, rising demand in the face of constrained supply), efficiency is no longer a luxury that’s nice to have. Like with the banks, retailers, transportation, lodging, and entertainment sectors it is now time for healthcare to pursue efficiency as vigorously as possible. Capacity management committees armed with dashboards that “admire the problem” will no longer be enough. Kicking the can down the road “because we don’t believe the data” won’t be acceptable. Health systems that use the predictive and prescriptive tools required to move to a new way of managing capacity will have an edge as we are already starting to see.
This post originally appeared on the Forbes Marketplace blog.