Lamoureux CSE

What is Human Factors?

Evolving from Ergonomics (from the Greek: Ergon:Work; Nomos:Natural Laws), Human Factors is generally considered to represent a broader conception of ergonomics, encompassing cognitive work as well as more traditional physical work.  As with ergonomics, Human Factors is concerned with optimising the fit between the human and their workplace, resulting in less stress and strain on the human, and greater efficiency and productivity from the human.  But where ergonomics may have been more concerned with such things as chairs, table heights, keyboards and mice, Human Factors is more concerned with cognitive aspects of the workplace.  How is information presented to the person?  What colour?  What form?  How will the person think about and use this information?  Will they have to transform letters to numbers or groups?  How much information will they have to hold in their head to make a decision?  Do they even have all the information they need to make the correct decision in every situation?  Human Factors is more concerned with the cognitive (or mental) fit of the job to the person.

Consider the following two examples that illustrate ergonomics and Human Factors.

Many of us have seen the snow shovel with the curvy handle.  It says it’s ergonomic.  But a lot of things say that.  In fact, ‘ergonomically-designed’ and similar terms have very much become a marketing phenomena.  And this serves to devalue the science of ergonomics.  Coming back to the snow shovel, the handle is like that to reduce strain on the user’s back and arms. It forces them to lift with their legs, and the net result is that, for every ounce of effort put into the job by the user, that snow shovel will move more snow than a regular, straight, snow shovel.  Not only that, the user will experience less fatigue and is less likely to suffer any sort of injury (such as a strain or a tear).  This is classic ergonomics.

Now consider an air traffic controller.  These people sit in windowless rooms (at least, most of them do) and stare at a radar screen, occasionally utter some arcane incantation into a microphone and possibly

hearing an acknowledgment.  Nowadays they don’t necessarily get paper information strips anymore, but they are still presented with a lot of information about each flight.  Let’s say they have 30 pieces of information about a flight.  How many do they actually use, routinely, to do the job that the flight needs them to do?  Probably about five.  So the rest of the information is noise.  Does the noise obscure the needed information?  Is there a better way to present the important information (what colour? spatially? as sound?) so they don’t have to make any complicated mental translations?  These were all things considered by Human Factors practitioners when developing the next generation of air traffic control displays, resulting in systems that complement the controllers’ abilities and support any weaknesses they may have. These considerations should also lead to greater satisfaction in their work, arising predominantly through reduced stress (i.e. fewer moments that cause the controller to worry about safety) and greater productivity.  We’ll leave aside the fact that many air traffic systems have taken the controller out of an active control role and put them in a monitoring role, and that many of the new functions the system can perform serve to get in the way of the controller’s primary task of maintaining safety and efficiency.  There’s always additional considerations, such as operating costs, or ensuring the machine is getting its data.  In this example, the ergonomics (physical) considerations to fit the human were minimal.  The Human Factors (cognitive) considerations to fit the human were massive; and they still didn’t get them all right.  This example is classic Human Factors.

Ergonomics and Human Factors can be considered as being on two sides of a continuum: the one side is physical and the other side is cognitive.  As we move from one side to the other it’s very difficult to say when one ends and the other begins, hence many people’s confusion over the terms.

Many systems place a pretty heavy onus on the person to learn how to use the system, and to follow some pretty rigid procedures.  In many cases, however, reliance on training and procedures represents a failure of Human Factors to influence system design from the outset.  A system that fits the human does not require the human to complete much training; nor does it force the human to follow long and convoluted procedures.  A system that fits the human just makes sense.

Why should the system fit the human, and not the other way round?  Well, sure there’s a lot of variability between different people, but we generally conform to a narrow range in any particular characteristic.  Designers of physical objects design for people within the 5th and 95th percentile.  This is 90% of the population, but studies have shown that if you measure or describe any characteristic, this 90% of people are not actually that different.  Additionally, it is very difficult to change the characteristics of people.  A light switch that requires 300 lbs of force to operate isn’t very good, is it?  How can a person just become stronger?  Or bigger?  Or develop a left foot that is long and wide so we can stand on one leg to put our other leg out beside us so we can sit in this beautiful thing that is supposedly a chair?  We can’t.  So physical things are usually designed to fit the human characteristic with which it interacts.  And this is because we can easily measure these physical characteristics.  Measuring the mental or cognitive capabilities of a person; quantifying the range of cognitive abilities that characterise a population; this has proven elusive.  And so systems rely on training and procedures to circumvent the difficulty of fitting the cognitive characteristics of the human.  Judging by the example of the physical domain, this is not acceptable.  This is where the Human Factors practitioner comes in.

Human Factors is littered with different models and theories.  Lamoureux CSE adheres to two models in particular, and is particularly fond of one method.

Lamoureux CSE advocates that work follows a systems model; that is, in a job no one unit or person or thing operates in isolation.  It is always operating with some relationship to another thing in the system.  This model is true as you scale from small and simple to big and complex.  For instance, the man digging a ditch with a shovel is a system: He’s providing the effort, the shovel is the hardware component of the system, and the environment is also playing a role (maybe it’s raining, or the ground is frozen, or even strewn with discarded concrete).  You could even consider the instructions the man was given as a component of the system, as would be any training (or lack thereof) that the man has recieved.  Likewise the air traffic controller is part of a team, which is part of a larger team, which is part of a larger, geographically separated team.  All of these teams are combining information from several radars and other sensor systems, radios, computer systems, databases and each other in order that the one controller can make a decision that is optimal in terms of safety and efficiency.  On the other end of the radio is a pilot who is controlling an aircraft and is responsible for the actions and safety of not only the crew, but the passengers too.  Both air traffic control and the aircraft are influenced by the environment: temperature and air pressure affect how the aircraft can fly which in turn affects the decision making and problem solving of the controller.  This big and complicated air traffic management system has hundreds, maybe thousands, of components when considering how they might affect the one controller we are concerned with.

To help us follow a systems approach, Lamoureux CSE tries to consider the system in terms of the SHELL model: Software, Hardware, Environment, Liveware (and Liveware; see figure). In every rendition of this model you will see, you will find the Liveware component (i.e. the human operator) in the middle, betraying the authors’ belief that the human operator is the most important element.  Lamoureux CSE doesn’t necessarily believe that: all components are equally important.  But something’s got to go in the middle.  Earlier renditions of this model portrayed a triangle with Software, Hardware and Environment on the outside, and Liveware on the inside.  With increasing focus on individual performance and team performance, this evolved into the cross we see today.  Each of the components of the SHELL model is comprised of many potential specific elements.  For instance, software may include written procedures and training, not just code.  Hardware may include tools, and Environment may include layout as well as lighting and temperature.

The other model Lamoureux CSE follows is one of Human Information Processing (see figure).  As with the SHELL model, this is a simple model that belies its potential application to complicated things.  When considering the cognition of human operators in detail, the Human Information Processing model is invaluable because, like the SHELL model, we are reminded to consider each component part systematically.  Expanding upon the simple ‘input-output’ model, the Human Information Processor describes cognition, from the arrival of some stimulus (the model is basically repeated for each of the five senses) to the execution of some response by the human (including doing nothing).  It incorporates the notion that external data can be briefly stored at the level of the sensor (e.g. the eyes, ears, etc.) if the mind is busy attending to something else, giving rise to the ‘hang on, what was that?’ moment.  Once attended to and perceived, information is worked on, thought about, used for decisions and problem solving, in working memory.  Working memory also brings items in from long-term memory, where we store our preciously-held mental models about the world, how it it works, and what we expect to happen.  After working on the information, we decide what to do about it.  ‘Response Selection’ assumes that we have a repertoire of potential response.  This infers that we probably also have a repertoire of potential situations, against which we match incoming information, which allows us to quickly recognise what is going on, what is likely to happen, and what the most appropriate response is.  This theory that we recognise scenarios and have preset responses is one of the most influential theories in Human Factors (and, specifically, decision making) to arise in the last 30 years (the other probably being Situation Awareness).  The model also posits an undifferentiated pool of attentional resources, allowing us to multi-task, provided that pool of attentional resources is not depleted and provided different tasks aren’t competing for the same processing pathways.  Finally, the model includes a feedback loop, permitting the operator to learn from the success or failure of their response, or modify their response as it continues.

While generally here at Lamoureux CSE we try to simplify things, we are fond of the Cognitive Work Analysis method.  CWA is comprised of 5 different analyses, intended to exhaustively consider the system and result in revolutionary new designs (although the work of Lamoureux CSE has applied CWA to evolutionary design as well as revolutionary design), by considering the constraints operating on the worker.  Thereafter, any trajectory that achieves the work goal while not contravening valid constraints, is a viable design, no matter how radical.  The five analyses of CWA are: Work Domain Analysis, Control Tasks Analysis, Strategies Analysis, Social Organisation and Cooperation Analysis, and Worker Competencies analysis.  While we’re not so precious to insist that all our work must be done this way (the Canadian market could probably not support such a focused approach to Human Factors on the part of a contractor), CWA has informed much of our recent efforts.

Of course, there are many further models and methods in Human Factors.  Lamoureux CSE draws from many of them, and applies them as appropriate to the work at hand.  This is a significant advantage Lamoureux CSE has over other firms: our knowledge and experience allow us to quickly consider a problem and choose from amongst the huge array of potential Human Factors models and methods and choose the best ones to bring the project to a successful, timely, and cost-effective solution.