Why How You Train Matters – and When it Matters Most
Part II of a IV Part Series
In the first part of this series on the science of training, we adopted a historical perspective to examine the introduction of an objective, science-based performance standard to the emerging realm of executive protection training in 1974, which in its earliest form consisted almost entirely of driver training. From there we took a closer look at the foundation of that performance standard, the Security Driving Triangle. This paradigm, which was adapted from an early industrial safety model by Tony Scotti, the originator of the “80% performance standard”, provides the context to the performance standard which is often been overlooked or ignored by those who have since adopted it.
In order to better understand how crucial this model is in terms of improving driver performance which is not only the goal of the model but the performance standard itself, we’ll need to first examine its individual facets. However, in doing so it must be acknowledged that in terms of performance where it matters the most – in the midst of a real-world event such as a potential accident or deliberate attempt to stop the vehicle – all three facets, the Driver, the Vehicle, and the Environment, each have tremendous potential to influence the outcome of those behind-the-wheel emergencies. This holds equally true in the training environment in terms of not just meeting a performance standard but, more importantly, when it comes to ensuring that the performance achieved in training is sustainable, repeatable, and applicable to the challenges of a wide range of operating environments. So, with that in mind, we’ll use that environment as our frame of reference for more closely examining the components of the Security Driver Triangle and their relationship to one another.
The Driver
The driver is without a doubt the one component that has the greatest potential to influence the outcome of any emergency situation. Yet, as counterintuitive as it may sound, the driver is also the one component that many approaches to protection training, be it driver training or some other discipline, simply take for granted from a performance standpoint. Often times the training model, and even trainers themselves, presumes is that all students are created equal, they all bring the same performance potential to the course, and it’s just a matter of repetition to bring them up to a predetermined level of performance. Now, if the only objective is for the student to achieve a given level of performance in a training environment, all of which inevitably present some degree of artificiality, then of course it may appear to some that this assumption is valid (at least where most students are concerned). But if the goal is to provide them with the knowledge, skill, and ability to achieve consistently high levels of performance in the far more dynamic environments in which they function on a daily basis, than that assumption has been proven to fall apart very quickly. This holds especially true if the objective is for the performance achieved in the training environment to be sustained over an extended period of time.
An understanding of the science of human performance goes a long way toward explaining exactly why that is the case. Not every driver enters the training environment with the same decision making capability, the same capacity for buffering the effects of stress or, for that matter, the same simple (or core) reaction time. And while the myriad of research available on human performance clearly demonstrates that those crucial performance factors can be improved upon, that same body of research also informs those who care to delve into it that performance gains achieved by simply repeating tasks under ideal conditions in a never-changing environment, regardless of the level of performance that is ultimately achieved, are typically only sustainable and repeatable under those same conditions or in those same environments.
So, if students – and those who train them – anticipate that there will only ever be a need for them to apply the skills developed in training under the exact same conditions or in environments that are exceedingly similar to those which they trained in, a repetitive approach that primarily results in developing “muscle memory” will suffice. But, for those who aren’t quite certain as to the conditions or environments they may find themselves in when it comes time to call upon their training, incorporating the science of human performance into the training paradigm isn’t just something that would be nice to have, it’s absolutely essential. Gains in critical areas of human performance such as improving decision making, buffering the effects of stress on physical and cognitive performance, and minimizing reaction times, all of which have proven to be achievable through well thought out and highly developed training approaches, ensure that the driver is better equipped to deal with the complexities of a wide range of situations and circumstances, regardless of the conditions and or the environment they occur in.
Among these human performance factors, decision making is often the most complex to develop in ways that are sustainable. In fact, the complexities of the human decision-making processes that apply to driving are so vast that they continue to present a major hurdle in the development of truly autonomous, self-driving vehicles. With that being said, the value of improving decision making performance is not that it provides one with new or different skill sets, it’s that it improves one’s ability to determine which of the available skills or skill sets are most appropriate to the situation, conditions, and/or environment. Whereas a training approach that never progresses beyond repetition results in a default physical response that may or may not be applicable to the situation, conditions, or environment the driver finds themselves in, conversely, a training regimen that integrates increasingly complex decision making into the process of skill-building results in a decision making being the default response. The end result couldn’t be more dramatically different; while the former may provide a range of skill sets, the latter not only provides a range of skill sets it also provides the ability to determine where, when, and how to apply specific skills to effectively resolve whatever the problem happens to be. In other words, a human performance-based approach to driver training that incorporates increasingly complex decision making goes a long way toward overcoming the classic “hammer and nail” conundrum.
Reaction time goes hand-in-hand with decision making, so if the objective is to achieve a high level of performance that is sustainable and repeatable over time and across the widest range of circumstances and conditions, it is absolutely incumbent upon trainers to incorporate these two factors in a manner that is conducive to achieving that objective. Otherwise, student performance may be impacted by one the most persistent and prevalent artificialities of the training environment. More often than not, these artificialities allow the student to “game” an exercise or scenario to their advantage by beginning to solve the problem at the earliest possible juncture – typically well before they would have the opportunity to do so in a real-world event. In this regard, what is referred to as simple or core reaction time, which is defined as the time it takes for the individual to recognize a potential problem and decide upon the appropriate course of action for solving the problem, should be the focal point in the training environment. As with virtually all areas of human performance, at this point, there is a tremendous amount of information available on just how much reaction times a driver is likely to be afforded when confronted by a behind-the-wheel emergency and, by inference, the amount of reaction time students should be afforded in the training environment in order to replicate real-world conditions as closely as possible. Of equal importance is the mechanism that introduces the reaction time into the exercise or scenario. Verbal cues present some unique challenges, not the least of which is the fact that outside of the training environment it is highly unlikely that the driver will have the luxury of someone telling them what to do if they find themselves in an emergency situation’ particularly someone who is intimately familiar with the event scenario and the most viable solution. Given that the first indications of virtually all behind-the-wheel emergencies tend to be visual, it stands to reason that properly configured visual cues are most effective for dictating reaction time. As always, properly configured is the operative phrase; the challenges associated with utilizing visual cues to dictate reaction time include where, when, and how to introduce the visual cue. The most effective approaches to defining the amount of reaction time rely on technology which ensures that the reaction time is consistent regardless of the vehicle speed, allows for the reaction time to be increased or reduced from one exercise iteration to another in order to provide students a more appreciable understanding of how increases and decreases in reaction time impact the outcomes of behind-the-wheel emergencies and allows for more complex decision making by providing more than one indicators as a means of defining the specificity of the problem (for example, different indicators for a potential crash versus a security-related incident). In the absence of this level of sophistication, or worse yet allowing the student to determine exactly where and when they start solving the problem replicated in the exercise, the driver’s capability to effectively manage real-world events in which the time and distance available for solving the problem is not theirs to decide is greatly diminished.
Like its counterparts decision making and reaction time, stress is a factor of human performance that should be introduced in an incremental manner following the student’s development of fundamental skills so that the process of building a foundation for enhanced performance isn’t impeded by the effects of stress on cognitive and physical functions. To do otherwise has the potential to significantly increase the safety risks to the students and instructors while, at the same time, impeding the student’s capability to assimilate information, learn new skills, and apply them properly. When it comes to determining where, when, and how much stress to introduce into a training exercise, it’s always best to remember that too much of a good thing is never as good as just enough. Push a student into “condition black”, i.e. heart rate above 170 beats per minute, and any semblance of cognitive performance is lost. Which brings us to an important point regarding which forms of stress are most effective from a training standpoint; while physical stressors have a place in the training environment any physical stressors introduced into the training scenario or exercise should directly correlate to the stressors the student can expect to encounter in their operating environment. Stressors such as fatigue, mild dehydration, even hunger can all impact human performance in meaningful ways; physical exertion such as running or exercising may be meaningful if the student anticipates having to physically exert themselves immediately before or during a real-world event. If that’s not the case, then as John Musser, a world-class strength and conditioning coach as well as a highly capable instructor of protection concepts and tactics has pointed out, in all likelihood you’re likely accomplishing nothing more than making your students tired and sweaty. Some of the inherent challenges associated with introducing physical stressors into any given training scenario include the time it may take to reach the appropriate point of exertion and, once reached, it may be difficult to sustain. The other factor that may – emphasis in may – limit the overall value of introducing physical stressors is that may take some time and effort to effectively decrease the impact that physical exertion may have on certain students. Conversely, psychological stressors, such as noise, light, sound, time compression, etc., are easily scalable, sustainable, and can be more effective in producing the desired physiological responses and deficits when properly introduced into the training environment. This is especially true when real-world events don’t necessarily require extraordinary levels of exertion, but will likely encompass psychological stressors.
As with many aspects of the science of human performance, it’s worth noting that factors such as decision making, buffering cognitive and physical stress, and reaction time have the potential to impact the protection practitioner regardless of whether or not he or she is behind-the-wheel when confronted by an emergency situation which presents then with limited time and limited distance within which to decide and act. In light of this fact, professional security drivers and other protection practitioners should be seeking out training that incorporates critical performance factors – including decision making, reaction time, and stress – in ways that contribute to increased performance for where it counts the most.
About the Author
Joseph Autera is the President and CEO of Vehicle Dynamics Institute, which has been carrying on the legacy Tony Scotti began in 1974 for more than 17 years. His practical experience includes freelance protection work focusing in large part on surveillance detection and secure transportation planning in semi-permissive environments in both moderate and high-risk locales as well as standing up the protective detail for a prominent technology concern. Additionally, he has also enjoyed tenures as Director of Global Security and Vice President of Global Security Operations for two different U.S. based multinational corporations. His articles on related topics have appeared in some of the professions most respected publications and he has presented on those same topics at a number of conferences and symposiums across the country.
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