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“Diversity of thought” is the “all lives matter” of corporate inclusion efforts

For at least the last decade, engineering companies have talked a great deal about “diversity and inclusion”. Inevitably, many people1 have the takeaway that this means “diversity of thought”. This is like telling a Black Lives Matter supporter that “all lives matter”; of course all lives matter, but that’s completely missing the point2. Diversity of thought is important to avoid groupthink and promote innovation; but that’s not the point of diversity and inclusion efforts3.

Diversity and inclusion means making sure that teams are actually diverse, across a range of visible and not-visible features. Why does that matter?

The business case

There are a lot of business justifications for fostering diverse teams. The consulting firm McKinsey has published some slick reports with charts and stock photos4 to make the case to business leaders: inclusion = performance = profits. There are also arguments about finding and retaining top talent, regulatory mandates, and employee engagement.

The thing is, who cares? This blog isn’t about corporate profit, it’s about effective engineering practices. In my experience, engineers tend not to care much about profit except as a means to do fun and innovative work5. Getting some business benefits from diversity and inclusion is a nice side effect, and if it helps get corporate buy-in it’s hard to complain too much. But it still doesn’t feel right.

The innovation case

All the talk about business case often neglects to consider the mechanism, why do diverse teams perform better and how do we leverage that to enhance performance? It’s actually fascinating. As Harvard Business Review puts it, “diverse teams feel less comfortable“, which slows down their decision making and causes them to think more critically.

If you’re a fan of Daniel Kahneman’s book Thinking, Fast and Slow, you may recognize this as engaging the “slow” system. We tend to rush to decisions with fast thinking, which is efficient but not always the most effective. The friction caused by diversity forces us to engage the more creative and thoughtful slow thinking. That’s interesting to understand and is a more compelling argument to the technically-minded, but it still doesn’t feel right.

The human case

When I think about diversity and inclusion, I always end up back at the same rationale: it’s just the right thing to do. We live in a world where some members of society have fewer opportunities because of historical racism, sexism, and homophobia, including the aftereffects of that discrimination that are still present today.

Ideally, we would live in a world that was a true meritocracy where everyone has equal opportunity to succeed based on their fit for the role, regardless of skin color, nationality, physical disability, cognitive disability, sex, gender identity, sexual orientation, religion, age, hairstyle, height, fashion sense, bench press ability, body modification, etc. Though we are getting to that world, we are still far from actually achieving it. A few representative statistics:

  • U.S. patent data show that women are inventing at an all-time high, but still less than a quarter of patents issued each year include a female inventor.
  • The American Bar Association analyzed the demographics of patent attorneys (who require a strong technical and legal background) and found that, despite recent gains, less than 7% are non-white.
  • Black and Hispanic people are underrepresented in STEM fields according to data from Pew Research.

We’re moving in the right direction, but it’s hard to argue that these are the outcomes of equitable opportunity. My personal opinion is that there actually is plenty of opportunity for those who know where to look for it, but that students don’t pursue technical fields because they don’t see it as an option for them.

And who can blame them, when the most famous Black inventor lived a century ago, when we celebrate Watson and Crick but not the female scientist whose work was critical to their discovery, when chemistry labs are not built to accommodate scientists with disabilities.

That’s changing too. There are excellent, diverse STEM role models and communicators out there: Neil deGrasse Tyson, Raven the Science Maven, Abigail Harrison, Helen Arney, the late but still extremely influential Stephen Hawking, just to name a few. This is great!

But is it enough? It’s easy to point to the high-profile success stories and say the problem is solved. It will still take a generation for the students currently looking up to these role models to pursue technical degrees, begin working in the field, and become role models themselves. With each successive generation we move closer to parity and equality. But that doesn’t mean we shouldn’t take a more active role in bringing about this change as soon as possible.

Consider your role

Equality is the soul of liberty; there is, in fact, no liberty without it.

Frances Wright

There is a project called “I Am A Scientist” which aims to show students that anyone can be a STEM professional. In a few decades this effort will no longer be necessary; of course anyone can be a scientist or engineer, who would think otherwise? In the meantime, we (as a society, as engineers interested in fostering the next generation, as teachers and leaders) have to make a deliberate choice6 to recognize, affirm, and support the widest possible range of people who may be interested in STEM, including promoting diverse voices so every student can find a role model that appeals to them.

We must think about the way in which we approach diversity. So many efforts are mere tokenism, made obvious by phrases such as “diversity hire7 and by carefully arranging corporate photos to “‘highlight” “diversity”8. If you recognize these types of practices at your company, take a moment to consider if the priority is to foster true inclusion or merely to tick a box.

We have to keep promoting inclusion in our workplaces to serve our peers today and in the future. After all, a diverse crowd of STEM degree holders isn’t helpful if they aren’t actually included in the real work. It’s easy to make fun of “unconscious bias training” and the like. But when you actually speak to people from discriminated categories and ask about their experiences you learn about the small inequities that compound to hold people back from participating and from career success. Countering those inequities can be as simple as making sure that everyone is heard and respected, that everyone has the resources and support to advocate for their career opportunities, and offering mentorship.

Clear data exists and can be collected about diversity in STEM fields and that should be our metric for success. When patents issued, papers published, degrees earned, and other outcome measures reach parity with the demographics of the general population, we can claim success. We should all do our small parts to make that happen.

Are you a “diversity candidate” with an experience to share? Do you have other suggestions for increasing inclusion? Leave your comments below.

Human Factors Design Drives System Performance

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.

Ergonomics

The term ergonomics was coined by Wojciech Jastrzębowski in 1857 to mean “the science of work”1 with the goal of improving productivity and profit. He described the importance of physical, emotional, entertainment, and rational aspects of the labor and employee experience, but the context was squarely on factory-type production.

Over time, this has evolved into two, slightly different definitions.

Workplace safety

In the United States, ergonomics is most often associated with equipment or workplace design. An “ergonomic” computer mouse is supposedly more comfortable and less likely to result in repetitive strain injury. The Occupational Health and Safety Administration (OSHA) and National Institute for Occupational Safety and Health (NIOSH) provide guidance for workplace design to reduce the risk of occupational injury.

This definition is a subset of human factors engineering (HFE) that may be also called occupational health and safety. It’s related to anthropometrics (the study of human body measurements) and industrial engineering.

Human factors engineering

Around the world, ergonomics is more often synonymous with HFE. The International Ergonomics Association provides this definition: “scientific discipline concerned with the understanding of interactions among humans and other elements of a system, and the profession that applies theory, principles, data, and methods to design in order to optimize human well-being and overall system performance”.

Discussion

These different definitions of the same term came about by parallel evolution driven by broader demand for human engineering.

In the US, the term human factors engineering was coined to describe research into aviation human error during World War II. It began being applied to other industries and grew in scope to encompass a range of related fields. Some ergonomists began practicing HFE while ergonomics continued to focus on workplace impacts and fell under the umbrella of human factors.

The same demand existed for human engineering around the world for aviation and then computers, but the term HFE wasn’t in use. Instead, the application of ergonomics expanded to meet the need. This has lead to the different terms being used in different parts of the world.

Human Factors Engineering (HFE)

Human factors engineering (HFE) is a broad and multidisciplinary field that designs and evaluates the human interfaces of a system.

Don’t stop reading — that definition masks a lot of complexity. Let’s break it down:

System

INCOSE defines system as “an arrangement of parts or elements that together exhibit behaviour or meaning that the individual constituents do not. Systems can be either physical or conceptual, or a combination of both.”

Systems may include any combination of hardware, software, people, organizations, processes, information, facilities, services, tools, consumables, etc. A system can be as complex as the entire universe or as simple as two people interacting.

Human interfaces

When people hear “human interface”, they usually think software or hardware interfaces. But, interfaces really encompass any human interfaces with any of the other system components as defined above.

A great example is Crew Resource Management, which is a system for pilot interpersonal communication and shared decision making. No other system components are involved, just the humans in the cockpit1.

Think of a trip to the grocery store. You propel the cart, observe price tags and product packaging, smell the prepared foods, hear the muzak, talk to the butcher, handle products, place items on the checkstand conveyor belt, talk with the cashier, use the card reader to pay, check the accuracy of the receipt, etc. All of these are interfaces with some level of design. There’s a whole field of study on grocery store psychology.

Design and evaluate

What does it mean to design and evaluate an interface?

Obviously, it’s highly dependent on the requirements and context of the system. This is where relevant human factors expertise is required to understand the aims of the system and the interfaces to be designed, decompose those into human factors objectives, and specify how success will be evaluated.

It’s best to specify the verification method before designing, to ensure that you’re clear on the goal you’re working towards. Common metrics include user satisfaction, accuracy and error rate, speed, situation awareness, workload, usability, and engagement.

Broad and multidisciplinary

HFE covers a range of fields that may include: human-computer interaction, anthropometry, physiology, psychology, macroergonomics and organizational psychology, cognitive science, industrial design, user experience, and more.

Because HFE is such a broad field, it may take a team of experts with different specialties to effectively address the range of considerations applicable to any given system.

Summary

You should now have a better understanding of the full scope of what it means that HFE designs and evaluates the human interfaces of a system.

You may also be interested in the relationship between HFE and ergonomics and user experience (UX).

User Experience (UX)

The term user experience was coined in 1993 by Don Norman while working at Apple. He intended it to encompass a person’s entire experience related to a product, from any feelings they had prior to using it, to first seeing it in the store, getting it home, turning it on and learning how to use it, telling someone else about it, etc.

I highly recommend this short video where Mr. Norman explains this history and also complains about the frequent misuse of the word:

How does UX relate to human factors engineering?

Human factors is an umbrella term that covers a range of fields which design and evaluate the human interfaces of a system. We often think of a system as hardware and/or software, but it can also include social and organizational interfaces.

Thus, UX is very much a type of human factors. UX is distinguished from related specialties like human computer interaction (HCI) or interaction design by extending the scope of consideration beyond the product itself to any interface which might affect the user’s perceptions and feelings of the product. Yet, the goal is the same: understand the human’s needs in order to design interfaces that meet them1.

UX is very much a type of human factors.

Recently the field of customer experience (CX) has begun to emerge. CX focuses on whatever interactions a customer has with a business, which may be independent of a product user experience. CX and UX are the same basic concept, just with slightly varying scopes. CX emphasizes the design of the sales process and the customer as a user of that process. A product UX team may not consider the sales process if the “user” isn’t the same as the customer.

Why do we care about the user’s experience? For the same reason we care about all of the other functions of human factors. People seek out products and services to meet their needs. When we meet those needs better than the competition2, they’ll come back for more.

Learn from the mistakes of others

The problem with being too busy to read is that you learn by experience… i.e. the hard way. By reading, you learn through others’ experiences, generally a better way to do business…

General James Mattis

The most successful people in any profession learn from the experiences of others. You can learn from their successes, sure. But don’t focus on doing things exactly they way they did, you’ll stifle your own innovation. Instead, understand their successes, extract relevant lessons, and forge your own path.

More importantly, learn from others’ failures and mistakes.

That’s why I publish a Reading / Listening List. As of the publishing of this article, 5 of the 6 recommendations are about poor engineering and design1. I find these stories fascinating, enlightening, and valuable. By avoiding the pitfalls of the past, we improve the likelihood of success in our own projects.

It’s okay to make mistakes, but strive to at least make original mistakes.

A Functional Team is NOT an Integrated Product Team

“My name is Inigo Montoya. You won a government contract. Prepare to deliver CDRLs.”

TL;DR: An Integrated Product Team (IPT) is a cross-functional group. If everyone on the team has the same background, that’s a functional or discipline team. There’s a difference.

Read More

Board man gets paid

For years I’ve been advocating for the effective inclusion of human systems integration (HSI) in the systems engineering (SE) process. I had to address a persistent misunderstanding of what HSI is and how it relates to human factors; while that can be frustrating, I recognized that it wasn’t going to change overnight. Instead, I worked diligently to share my message with anyone who would listen.

Recently, my diligence paid off. I was contacted by a group putting together a proposal for a defense contract. The government’s request outlined their expectations for HSI as part of the systems engineering effort in a way that the proposal team hadn’t seen before. Someone on the team had heard me speak before, knew I had the right expertise they needed, and reached out to request my support.

It will be a while before we find out who won the contract, but I am certain that our proposal is much stronger for the inclusion of HSI. The HSI piece of the work is small but essential, and any competitors without the requisite expertise may not have understood its impact or importance to the customer.

This experience reminded me of basketball star Kawhi Leonard’s most popular catchphrase: “The board man gets paid.” See, Leonard is known for his skill at grabbing his team’s rebounds1. This is a key differentiator on the basketball court. The team has done all that work to get the ball up the court, yet failed to score. Grabbing the rebound before the opponent does gives the team another chance. Most of the time, the defensive team is in a better position to grab the rebound; Kawhi Leonard has made a career of getting to those balls first.

Leonard identified an underexploited opportunity and worked hard to develop the skill to take advantage of it. Throughout high school and college, he called himself “The Board Man”. He shaped his career around this unique skill and has been extraordinarily successful because of it.

That’s not to say you have to find a niche to be successful. Obviously there are superstars in every field. But, it’s a heck of a lot easier if you can identify those opportunities nobody else is taking advantage of2.

Bonus read: The top 5%. Share your own tips, inspiration, and niche in the comments below.

Diversity in engineering careers

I had the privilege to attend the Society of Women Engineers conference WE19 in Anaheim, CA last week. I left inspired and optimistic.

Speakers and panelists relayed their experiences over the previous decades. These women had been denied entrance into engineering schools, marginalized in the workplace, and forced to become ‘one of the guys’ to be accepted among their peers.

We’ve come a long way. It’s never been a better time to enter the workforce as a woman/person of color/LGBTQ/etc. Diversity in the workforce and leadership of engineering companies is on the rise, barriers are falling, and the value of diversity is being recognized. And yet, we still have so far to go.

We recognize that diversity is good for business 1 and companies are actively recruiting more diverse talent. Our organizational cultures are still adapting to this diversity. In many ways, we still expect all employees to conform to the existing culture, rather than proactively shape the inclusive culture we desire.

A great example is the “confidence gap” theory for why men are more successful in the workplace. Writing in The Atlantic  in 2014, Katty Kay and Claire Shipman explain that “compared with men, women don’t consider themselves as ready for promotions, they predict they’ll do worse on tests, and they generally underestimate their abilities. This disparity stems from factors ranging from upbringing to biology.”

Jayshree Seth‘s WE19 closing keynote combated the confidence gap with a catchy “confidence rap”. I was excited to share it with you in a gender-neutral post about combating imposter syndrome. In researching this post, I learned that the “confidence gap” is symptom, not a cause. Telling women to be more confident won’t close the gap because our workplace cultures are often biased against women who display confidence.

Jayshree Seth countered the “confidence gap” with the “confidence rap” in an excellent keynote.

Research demonstrates that an insidious double standard2 is what’s holding women back. Women who talk up their accomplishments the same way men do are perceived as less likeable. Women who are modest are more likeable, but nobody learns of their accomplishments and they appear to lack confidence. Women can be just as confident as men, but the cultural expectations of the workplace do not allow it.

That’s not to totally dismiss the confidence gap theory. This double-standard stems partly (primarily?) from continuing societal expectations. Though gender equality has advanced significantly in recent decades, many parents continue to raise girls and boys differently3. A girl raised to be modest and display less confidence will join the workforce with the same attitude.

That’s not the whole story, of course. Our behaviors and habits continue to be shaped by the workplace culture, especially for younger employees just learning to fit in at the office. Currently most office cultures encourage confidence in men and discourage it in women.

I think this is changing slowly over time along with other aspects of gender equality. I also think that a gradual change is not good enough. We owe it to ourselves, to our female peers, and to the advancement of the profession to consciously bring gender equality in engineering more swiftly.

We should define what a gender-equal workplace looks like, identify where our cultures diverge from this ideal, and create strategies for closing that gap. As a starting point, Harvard Business Review shared some management and organizational strategies. And all of us can contribute by recognizing our own biases and by finding ways to highlight others’ accomplishments.

What does workplace gender equality mean to you? How does the culture of your office support (or not) gender equality? What strategies would you recommend for addressing bias on an individual, team, or organizational level? Post in the comments below.