Reliability in Emerging Technology

High customer satisfaction with low reliability (is reliability still important?)

Most customers aren’t happy with products that break down a lot. 

Product unreliability has been behind a lot of losses, cancellations and bankruptcies. A great example is the Yugo – a small, inexpensive car from the former Yugoslavia that gained notoriety in the 1980s and 1990s. It was about half as expensive as similar cars when it hit the US market. And despite a lot of initial ‘excited’ purchasers, it simply stopped selling when people realized how comically unreliable and unsafe it was.

Now there is Rivian. When Rivian burst onto the electric vehicle (EV) scene, it quickly gained a devoted following. The Rivian R1T truck and R1S SUV were praised for their funky designs and innovative features. Owners and enthusiasts love the company’s approach to off-road lifestyles, reinforced by early partnerships with Amazon and promises of building a nationwide ‘outdoor-centric’ charging network.

(and Why It Matters)

In the world of reliability engineering, few tools are as powerful – or as misunderstood – as Weibull analysis. It is a statistical tool, which can turn people ‘off’ straight away, as we can immediately leap to a list of equations and tables of numbers that we need to memorize and embrace. But Weibull analysis is different. You actually don’t need equations.

Check out the chart below, which is called a ‘Weibull plot.’ The different shapes and colours representing the failures of different components can tell us so many things without having to evaluate a single equation.

… and why we still make rubbish products that break a lot

Modern militaries don’t win many wars these days. The most dominant, well-funded, highly-trained armies have consistently lost (or at least not won) the Korean War, Vietnam War, Afghanistan War, arguably the Iraq War, and plenty of others. And many dominant, well-funded, highly-trained companies are consistently spitting out unreliable or unimaginative products that smaller and less dogmatic companies have no problem bettering.

To understand why, let’s look at a man called Robert McNamara.

Because the people that make them lie. 

Not ‘obvious’ lying where lightbulb manufacturers calculate one reliability number and deliberately choose to put another number on their lightbulb packaging. But ‘insidious’ lying where they deliberately choose to measure the wrong thing to get a better number.

There might not ever be a better demonstration of the saying that …

… a fish rots from it’s head.

Boeing is responsible for the half-baked Maneuvering Characteristics Augmentation System (MCAS) that was forced into its new 737 Max aircraft. This involved a decidedly awful attempt to convince the Federal Aviation Administration (FAA) that there was no need to subject said aircraft through all the checks and balances that you need to go through if it is in fact a brand-new and different type of plane. Which it was. This resulted in the deaths of 346 passengers and crew (along with plenty of claims that it was pilot error). And just to be clear, Boeing has since admitted that it’s employees defrauded the FAA during the original certification process – an admission it was not required to make if it was able to complete a three-year period of increased monitoring and reporting. Which it could not.

It is no small irony that a software application that is designed to protect IT systems from malicious actors was behind the biggest IT outage in the history of computers. A company called Crowdstrike provides a ‘Falcon Sensor’ product that is intended to scan computers that use Microsoft operating systems for vulnerabilities. And this product is deployed so deeply into its host operating systems that it has access to the ‘kernel,’ which is the program that runs the basic code that links applications to the computer hardware (like memory, central processing unit and other devices). Unfortunately a Falcon Sensor update that Crowdstrike sent to its customers had a bug that was not picked up by its own validation programs (because it too had a bug). And unfortunately, it accesses a ‘forbidden’ part of the memory that causes the infamous BSOD or ‘blue screen of death.’ So airlines, hospitals, banks, hotels and lots of other companies simply couldn’t operate.

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Many of us like to think that we can, at least sometimes, be objective. Which is the opposite of being subjective.

What does this mean? Something is ‘objective’ if it only depends on the world around it, and nothing else. Like the ‘perfect juror’ who is only swayed by facts and evidence when determining if he or she thinks someone is guilty of murder. Something is ‘subjective’ if it can be influenced … by itself. Like the ‘imperfect juror’ who decides to acquit a murder suspect regardless of the evidence … because the suspect is his or her brother. This is called bias.

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Boeing has somehow managed to make the bad public relations created by those pesky onboard batteries catching fire in 2013 practically disappear. Not through good management. But through a never-ending series of disasters and catastrophes that shows no sign of letting up which is dominating Boeing’s news cycle that there is no remaining airtime for missteps like those battery fires.

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Apple recently did something that it isn’t in the habit of doing. And that is – admitting failure. After spending $ 10 billion on ‘Project Titan’ whose aim was to produce a ‘really cool car,’ Apple decided to pull the pin and cancel it.

Simplifying Apple’s Project Titan ambitions to something as pithy as creating a ‘really cool car’ might seem a little condescending. The problem for Apple was that unfortunately, this was the practical truth. And that is why it failed.

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We like to think we make decisions based on information. We don’t. We make decisions based on emotions. And the most important emotion we rely upon for decision-making is confidence. We can be provided all the information in the world, but if we can’t understand it, trust it or believe it, we look for confidence in other ways. Often to disastrous outcomes. 

The number of ‘well-funded’ production efforts full of ‘very smart people’ that routinely generate expensive but unreliable products is sadly, very high. And it all comes down to the wrong types of confidence that well-paid decision-makers chase. 

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