Friday, February 07, 2020

Experimenting to Improve Sleep Quality

comments on: Can a Humidifier Help You Sleep Better and Snore Less?

After doing some research I learned that humidifiers have helped folks snore less. So, after some more research, I picked up a slick little ultrasonic humidifier and gave it a try. Now, it’s been less than a week which I know isn’t enough to get too excited about statistically speaking. But one thing is becoming crystal clear…it’s most definitely helping me sleep better.

Interesting post, which includes control charts showing the impressive progress.

"I’m also still trying to figure out what caused the three special cause signals in January." One nice aspect of improvement is sometimes you can make a system improvement that even without knowing the causes of previous problems, the new improvement stops those from happening again. Maybe that won't be the case this time but maybe it will. Health related issues are so touchy that I could imagine it is something like a couple bad factors stacked on top just push things over the limit. So being a bit tired and say too low humidity and you didn't drink quite enough liquid and sleep quality is bad but just 1 or 2 of those and it might be a bit worse but not horrible.

Special cause signals will be more frequent if several factors together amplify each other (and they rarely happen together so those amplified results are rare). What happens is those rare amplified events will be special, outside of the system that generates that regular variation when they act alone but when all that variation lines up just right the result will be outside what is normal (due to the very large change in the result for that special case where the individual factors acting together (amplifying) create a very large change in the result.

Related: Gadgets to Mask Noise and Help You Sleep or Concentrate - Apply Management Improvement Principles to Your Situation - Zeo Personal Sleep Manager - Using Control Chart to Understand Free Throw Shooting Results

Tuesday, October 08, 2019

The Importance of Providing Context for Data

Data in Everyday Life: How Serious is the Student Loan Debt Crisis?

Did you know that 1 in 4 Americans have student loan debt? In the United States, there are more than 44 million people who collectively owe $1.56 trillion in student loans.

I thought 25% seemed too high. Thankfully this post also provides the number, 44 million. The USA population is currently estimated at 330 million. 44 million is closer to 14% than 25%. My guess is that the 25% is of some subset of the USA population (people between certain ages maybe)?

I think a point about the importance of providing the proper context when showing data has also been made in this post. There is certainly a sensible argument for why 25% of certain ages is a more useful figure for understanding how widespread student debt is (rather than saying 14% those in the USA have student debt). But in the case where that decision is made the details should be spelled out.

Related: Operational Definitions and Data Collection - Data Can’t Lie (data can be wrong) - Poorly Stratified Data Leads to Mistakes in Analysis - Understanding Data

Thursday, March 07, 2019

Take Risks to Learn and Improve, But Do So Wisely

My edited comments on: The Limits of Learning From Failure

Failure can be a great learning tool, especially if it is planned. Create an environment that supports and learns from failure, but also use the scientific method, coupled with experience, to understand and mitigate the risks.

I agree, I wrote about this on my blog: Accept Taking Risks, Don’t Blithely Accept Failure Though

The goal is to maximize innovation and improvement. To the extent we need to take risks and accept some failures to achieve this we should accept failure. But that doesn’t mean we don’t continually try to improve our management systems to reduce the costs of failure. Even while we take risks we want to do so intelligently.

It is true many organization are so fearful of being blamed for failure that sensible risks are avoided. We do need to create management systems that allow taking sensible risks but we need to learn while still limiting damage from failures. Do experiments on a small scale, iterate quickly and expand the scope as you learn.

Related posts: Learn by Seeking Knowledge, Not Just from Mistakes - Risks Should be Taken Wisely - What is the Explanation Going to be if This Attempt Fails?

Monday, February 04, 2019

Outside the Box Thinking

comment on: Is Thinking Outside the Box Out of the Box Thinking?

I remember Russel Ackoff* telling a story about that 9 dots problem where his daughter shared a solution to cover the dots in 1 line. She folded the paper to the dots were all lined up and drew one line that went through all of them. The teacher said that was wrong! Great teaching about "outside the box" thinking there. But it is a great illustration that just saying "outside the box" isn't the same as adopting that mindset.

* It has been a long time, I might be be wrong but I think it was Ackoff that told that story.

Related: The Psychology of Change is Often the Trickiest Part of Process Improvement - Children are Amazingly Creative At Solving Problems - Innovation Strategy

Sunday, January 27, 2019

Shared Principles for Managing People Engaged in Diverse Tasks

This post expands on my response to Michael Sweeney's (Cloud Infrastructure Engineering for Salesforce) comments on Linked In:

This is a great blog to follow [Curious Cat Management Improvement Blog] if you aren’t aware of it. I agree with John, in general, but in this post I felt the missed one basic thing that I’ve seen in my own career- software is not physical and people who write great software and people who make great physical things MUST think (and therefore be managed) differently. The crossover between Agile and Lean thinking, to me, is the ability to identify non-value added activity (waste) in the Toyota sense, and empower small teams to make decisions and charge forward in the Agile sense. Getting a combination of software and hardware thinking together will be the key to winning the Cloud Wars and moving into the Fourth Industrial Revolution.

Thanks for your comments. I do agree that the system within which people are operating determines how they must be managed. There are definitely features of software development that are significantly different than manufacturing scalpels or basketballs or tables. As there is a difference between a surgical team in an operating room, road construction, mining, editing books, investment banking, manufacturing industrial robots, researching new drugs, manufacturing drugs, teaching in a university, maintaining plane engines, coaching an athletic team...

I see universal principles of management (respect for people, customer focus, continual improvement...) that cross all different human enterprises. How those principles should be manifest in a particular situations depend on the work being done, the management system that is in place, the individual people involved, the specific focus of the effort right now... The way those principles are manifest will look very different in all the varied types of organizations we create and the different work and processes used within those organizations.

John Hunter, presenting at a Deming management seminar in Hong Kong

It is interesting (on the software v not software divide) to note that 100 years ago what was manufactured didn't contain software elements. And the manufacturing process also didn't involve software. That isn't very often the case today. Think of all the manufactured things you use and a high percentage (measured by the cost of the manufactured goods) have software components (cars, phones, appliances, speakers...) and they are built with a great deal of software involved in the manufacturing process.

In addition, the sales process and other processes involved in the organization doing the manufacturing rely heavily on software. As you say "Getting a combination of software and hardware thinking together" is indeed key today and will be continue to be in the future. While relying on software as part of the manufacturing process (and in the supporting processes) isn't the same as developing software the thought process on how to use software within manufacturing systems and how that software should work, be adjusted... is very different from the work of manufacturing tires 100 years ago.

I also discuss related ideas in: Deming and Software Development.

Related posts: How to Manage What You Can’t Measure - Create a System That Lets People Take Pride in Their Work - Good Process Improvement Practices - The Importance of Management Improvement - Thinking Required, No Simple Management Recipe to Follow -Unpacking the Components of Hard Work to Design Better Work Conditions - Do We Need to Find Management Ideas from Our Industry? (No) - Avoiding Difficult Problems

Monday, November 19, 2018

Using Control Chart to Understand Free Throw Shooting Results

comment on: Is Andre Drummond Sustaining His Free Throw Improvements?

Nice use of data to understand the system results (and if there is a measurable improvement or not). I still want to see these chronically poor free throw shooters use the pretty clearly better underhand free throw style. I wrote about this previously in Why Do People Fail to Adopt Better Management Methods?

It really is remarkable how much effort is put into so many aspects of gaining small advantages yet a fairly obvious big advantage (underhand free throws continues to be ignored).

Related: Lessons for Managers from the Wisconsin and Duke Basketball Programs - Change Management - Post Change Evaluation and Action - Taking Risks Based on Evidence

Friday, September 14, 2018

Understanding and Using Data: Waffle House Example

Comments on, Why FEMA is Monitoring Waffle House this Weekend

look outside your organization for risk indicators that might help you make better (and faster) decisions, particularly when those risks are activated. Second, that you should explore crowdsourced risk data as a source of up-to-date information.

I agree. Also, just look at data close to where the action is (internal or external).

And don't just look at aggregated data but dig into what individual data points tell you. Aggregated data is very useful but it also can mask meaningful insights available when data is looked at more closely. It isn't a perfect match to Waffle House data but I think the principle is visible in the Waffle House example.

The Waffle House closure data is based on actually closing based existing conditions while warnings and evacuation recommendations are based on predictions about the weather and the impacts those will have on locations. The warnings are necessarily predictions (to be useful for the whole community they need lead times to take action) where the Waffle House has more flexibility and the organization has managed their system to be more capable of adapting to harsh conditions. There is a real similarity with designing a agile software development process that is able to be more flexible and react quicker than old "waterfall" style organizations that have to predict far in advance and adapt slowly as conditions change.

Waffle House closures are a useful data point for conditions on the ground that FEMA can use with other data to make decisions on how to react.

Related: Bad Weather is Part of the Transportation System - Leadership: Taking Action When Others Are Unsure - Lessons on Competition from Mother Nature - All Data is Wrong, Some is Useful

Thursday, May 17, 2018

Understanding Variation Doesn't Mean Crushing Any Variety

It doesn't follow that because Dr. Deming sought to reduce the variation that caused processes to be unreliable and that harmed customers it meant he was against variety or failed to understand the importance of variation in different contexts than the context where it caused problems. Drawing such a conclusion is just not sensible when looking at Deming's work. It is a misunderstanding that is usually caused by taking one quote and drawing poor conclusions about what that quote meant.

quote text: Standardization does not mean that we all wear the same color and weave of cloth, eat standard sandwiches, or live in standard rooms with standard furnishings. Homes of infinite variety of design are built with a few types of bricks, and with lumber of standard sizes, and with water and heating pipes and fittings of standard dimensions.

Dr. Deming understood the organization as a system and how understanding variation fit within that system. When variation within the system causes problems and reduces efficiency then reducing variation important. It is a mistake to attempt to take thinking that is part of a system and analyze it without understanding the context within which it has meaning. Reducing variation has a specific context within Deming's thinking and that did not mean reducing variety or reducing variation when it was useful.

W. Edwards Deming understood you didn't use the same improvement thinking every time you wanted to improve. You selected the useful management tools and concepts that fit the current situation. It is important to have a wide variety of tools and thinking to allow finding the best ways to improve different situations.

Iteration is an extremely important part of improvement efforts. Why? Because, trying a variety of ways to improve and a variety of changes to the existing conditions will lead to finding the most valuable improvements. The PDSA improvement cycle is designed specifically to introduce more variation into improvement experiments. The value of many small attempts using different tactics (introducing variation to learn what works best) is a core part of a Deming management system.

W. Edwards Deming stressed the importance of understanding psychology and appreciating how different people provided important contributions and how that variety helped the organization. You need to design systems to maximize the benefit gained due to some forms of variation.

It is a mistake to think that W. Edwards Deming didn't understand the value of variety or of variation in the right context. One must reduce the variation that is damaging to the ability of a system to deliver reliable value to customers. That doesn't mean variety and variation in other contexts are not understood to be valuable.

Related: How to Improve Your Understanding Variation and to Use Data to Improve - We Need to Understand Variation to Manage Effectively - Standardization Doesn’t Stamp Out Creativity

This is an edited comment I wrote in response to post on Linked In but since they have repeatedly broken links over the years I don't link to that site any more.