Tag Archives: robust

Design the Management System with an Appreciation of Confirmation Bias

photo of John Hunter with a walking stick

John Hunter hiking at Fraser’s Hill, Malaysia, when I was a bit younger.

To create strong organizations we must create management systems using an appreciation of psychology. We must understand that people have tendencies that must be addressed by designing a management system built to take advantage of the strength those people bring and mitigate the risks the weaknesses (such as confirmation bias) that those people also bring.

One way to do this is to seek out voices in your organization that question and challenge accepted positions. Often organizations promote those that make things easiest for everyone, which correlates very well with supporting existing biases within the organization while making things difficult for those that challenge the existing thinking.

As I wrote previously in, How We Know What We Know:

the way people build up beliefs, is full of all sorts of systemic problems.
… [people] tend to think someone entertaining is more educational than someone not entertaining. They may be more entertaining, but taking the ideas of those who are entertaining and rejecting the ideas of people who are not is not a great strategy to build up a great system of knowledge.

To more effectively adopt good ideas and reject bad ideas, understanding the theory of knowledge (how we know what we know) and then applying that knowledge to how you learn is a better strategy. Learning to recognize confirmation bias and take steps to avoid it is one positive step. Learning to recognize when you accept ideas from those you like without critical judgment and reject ideas from those you find annoying and then learning to evaluate the ideas on the merits is another positive step…

I also wrote about these ideas in, The Importance of Critical Thinking and Challenging Assumptions:

Often we have created cultural norms that make it difficult for people to ask for evidence of claims. And the culture in many organizations can make those that seek evidence for claims as being difficult or even personally attacking those that support a certain course of action. However this is a dangerous attitude and it is directly counter to the fundamental aspects of management improvement efforts (evidence decision making, continual improvement, etc.).

Learning to challenge confirmation bias in your own thinking is hard. Often it is much harder to learn how to get the organization as a whole to change from one where confirming (and maybe ignoring anything that might make it difficult to maintain the existing belief) what most of us believe (or wish to be true) to one where challenging the assumptions underlying our thought process is appreciated.

Great benefits flow to organizations that encourage the challenging of beliefs, ideas and the lessons we draw from data. But such a culture can create friction in organizations without other strong management practices (respect for people, an understanding of what data does and does not reveal…). Often creating such a culture is something best left until the process of building the capability of the organization is well underway.

Understanding Design of Experiments (DoE) in Protein Purification

This webcast, from GE Life Sciences, seeks to provide an understanding Design of Experiments (DoE) using an example of protein purification. It begins with a good overview of the reason why multi-factorial experiments must be used while changing multiple factors at the same time in order to see interactions between factors. These interactions are completely missed by one-factor-at-a-time experiments.

While it is a good introduction it might be a bit confusing if you are not familiar with multi-factorial designed experiments. You may want to read some of the links below or take advantage of the ability to pause the video to think about what he says or to replay portions you don’t pick up immediately.

I have discussed the value of design of experiments in multiple posts on this blog in the past, including: Introductory Videos on Using Design of Experiments to Improve Results by Stu Hunter, Design of Experiments: The Process of Discovery is Iterative and Factorial Designed Experiment Aim.

He also provides a good overview of 3 basic aims of multivariate experiment (DoE):

screening (to determine which factors have the largest impact on the results that are most important)
optimization (optimize the results)
robustness testing (determine if there are risks in variations to factors)

Normally an experiment will focus on one of these aims. So you don’t know the most important factors you may choose to do a screening experiment to figure out which factors you want to study in detail in an optimization experiment.

It could be an optimized set of values for factors provides very good results but is not robust. If you don’t have easy way to make sure the factors do not vary it may be worthwhile to choose another option that provides nearly as good results but is much more robust (good results even with more variation within the values of the factors).

A Good Management System is Robust and Continually Improving

imagine various people working within it, somehow swapping out gears and cogs without the clock stopping or slowing down even a little.

This is a fairly good quote on a good management system. Some people might not like the mechanistic model – comparing an organization to a clock, and I agree that isn’t the right model, but even so it is a good quote.

The quote, from a story about the San Antonio Spurs captures what should happen with a good management system. Things just keep running well as inevitable changes take place (and keep getting better in the case of a management system).

A good management system doesn’t rely on heroic efforts to save the day. The organization is designed to success. It is robust. It will succeed with all the variation thrown at it by the outside world. A good management system takes advantage of the contributions people offer, but it is not perform poorly when others are relied on.

A well run organization has graceful degradation (when one component fails or one person is missing the performance doesn’t suffer, bad results are avoided).

With software for example, a decently created web sites may use javascript to enhance the user experience but if javascript is unavailable the site works fine (just missing some neat features that are nice but don’t prevent users from getting what they need). Poorly designed software has critical dependencies on conditions that cannot be guaranteed to be present for end users and the software just fails to work when those conditions are not met. Ungraceful degradation is too common in software. It is also too common in our management systems.

An organization succeeds because of the efforts of many great people. But the management system has to be created for an organization to prosper as what we all know will happen, happens: people will leave and need to be replaced. And the people that stay will need to adjust to new conditions inside the organization and in response to external forces. A good management system is constantly improving performance, innovating, increasing the robustness of systems and increasing the capability of people.

Bad Weather is Part of the Transportation System

The job of managers is to create a robust system that delivers value to customers. A system that fails constantly (fails during the continual variation the system faces) is a failed system. Bad weather is part of the variation airlines face. Any management system has to cope with the variation that it faces. The management system must be designed and managed so that the organization successfully delivers value to customers under the conditions the organization will face.

The air travel system in the USA is a disgrace for so many reasons it is hard to catalogue them all. One, of many, is how fragile the system is; causing massive (nation-wide) customer harm multiple times a year due to weather. Weather is sometimes bad. If your organization fails when there is bad weather, fix that problem (make your system robust in the face of bad weather), because you are not going to be able to fix the weather to let your un-robust system be effective as it is.

Instead airlines only response seems to be to get their friends in government to approve anti-competitive mergers to eliminate competition and allow failed organizations to become even larger and harm even more people. Airlines should design robust systems that work in the environment they will face (which they don’t do now).

Their planes don’t fall out the sky when they face bad weather. The engineers behind designing planes have made them very robust. Pilots have been trained to handle variation they will face. And yes, the system has been designed with adjustments to avoid flying into conditions that are risky.

The safety of the air transportation system is very good. The management of airlines in most every other aspect is pitiful, and has been for decades.

The managers running the airlines have done amazingly bad job of creating robust organizations capable of delivering given the variation they know they will face (weather, mechanical problems, IT problems, etc.) for decades. Poor management is the cause of these failures that result in harm to customers. Weather is not the cause. Poor management, over decades, resulting in incredible fragile systems that constantly punish customers is the responsibility of the airlines. And they have done an incredibly bad job at creating a robust system to deliver value to customers.

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