Bottom Line Up Front:
- Human performance is a major factor in overall system performance
- Humans are increasingly the bottleneck for system performance
- Human factors engineering design drives human performance and thus system performance
Why care about humans?
In many system development efforts, the focus is on the capabilities of the technology: How fast can the jet fly? How accurately can the rifle fire?
We can talk about the horsepower of the engines and the boring of the rifle until the cows come home, but without a human pressing the throttle or pulling the trigger, neither technology is doing anything. A major mistake many systems engineering efforts experience is neglecting the impact of the human on the performance of the system.
A great example is the FIM-92 Stinger Man Portable Air Defense System. Stinger had a requirement to hit the target 60% of the time, which was met easily in developmental testing. However, put in the hands of actual soldiers, it only hit the target 30% of the time. An Army report found that the system suffered from several shortcomings including poor usability and a lack of consideration for the capabilities of the intended user population. The technology hit the mark, but the system as a whole failed1.
Let’s illustrate with a more everyday example. I play ice hockey and use a professional composite stick. I would guess that my fastest slap shot clocks in at around 50 mph. A pro using the exact same stick could easily break 100 mph. Clearly the technology isn’t any different, I just don’t have the same level of skill. The performance is the combination of the technology and the human using it.
System performance = technology performance * human performance
Once we acknowledge that fact, it’s clear that we must understand the capabilities and limitations of the users to understand how the system is going to work in the real world. Most human factors models capture this interaction in one way or another. My preferred model for most systems is the FAA human factors interaction model, shown below. This model shows a continuous loop. The human takes in information through sensory capabilities, makes a decision, and translates that decision into actions to the system; then, the system takes those inputs, responds appropriately, and updates the displays for the loop to repeat.
This just drives home the point that system performance is driven by both technology and human performance. But, simply accounting for human performance is the bare minimum. In most cases we can go much further, designing the human-technology interactions to enhance the performance of the human and thus the integrated system.
The human bottleneck
A related model, often used by the military, is the OODA loop: Observe, Orient, Decide, Act. In any competition from ice hockey to strategy games to aerial dogfights, an entity that can execute the OODA loop faster and more accurately than their opponent, all other factors being equal, will win. This is a useful paradigm for exploring human performance in complex systems.
Systems developers have paid more and more attention to the OODA loop in recent decades, as computer technologies have significantly sped up the loop. We have more ability to collect and act upon information than ever before, to the point that it can be overwhelming if not managed effectively. We’ve come a long way from WWII cockpits with dial gauges and completely manual controls to point-and-click control of otherwise-autonomous aircraft. Computers used to require tedious manual programming with careful planning for even relatively simple tasks, and lots of waiting around for programs to finish running. Now, computers can complete tasks nearly instantaneously2 and are often idle waiting for the human’s next command. Automation has taken over many simpler tasks, and can do them better and more reliably than a human.
In short, it’s not the technology delaying the OODA loop; the human is the bottleneck.
The role of human factors engineering
Even selecting the very best humans and providing them with the very best training can only improve performance so much, and that’s a pretty costly approach. The solution is obvious: engineer superhumans. However, effective human factors engineering can support and enhance human performance.
Human factors engineering (HFE) is a broad and multidisciplinary field that addresses any interface between human and technology. Depending on the needs of the system, this could be as simple as ensuring that displays are clearly readable. For advanced systems with autonomous capabilities, HFE supports effective functional allocation among the technology and human elements of the system, maximizing the value of both; the technology handles the things that don’t require human decision making to allow the user to focus on the tasks that do require uniquely human capabilities. Effective human interfaces support the human’s tasks by presenting the right information at the right time in the most useful manner, allowing the human sensory and cognitive components to work speedily and accurately. That’s followed by intuitive controls for transmitting the human’s decision back to the technology.
The OODA loop is sped up when the human gets the right information presented in an effective and timely manner and can act on that information also in an effective and timely manner. When the human is the bottleneck, any HFE design improvements that support human performance have a direct corresponding impact on system performance. In order to have the biggest impact, the HFE effort must be initiated early on when those allocation and design decisions have not yet been made. Additionally, the human must be captured in all system architectural, behavioral, and simulation models.
The Stinger example demonstrates the risk of pushing off human factors engineering, and that was for a relatively straightforward system. To enhance the OODA loop and maintain a competitive edge in advanced modern systems, HFE is a must. System performance is the product of technology and human performance, and HFE is essential for ensuring the human aspect of that equation.
Footnotes:
- After additional development efforts, the system was made more usable and modern versions are still in active use today. That additional work delayed fielding and cost money, both of which would have been saved if the human capabilities were considered in the early design phases.
- To the point that some apps add artificial delays because users may not trust that they’re working if they’re too fast.