Sunday, June 26, 2016

Responsible Problem Management

Our present approach to producing products tends to limit the amount of information needed by those potentially affected by the products to adequately avoid waste and other adverse impacts. This can be traced to how businesses treat problems.

Some problems are known (identifiable and understood) and can be fixed based on experience and a basic learning curve; while others, or parts of others, are unknown along with how they can be fixed. A problem is typically identified by the differences between observations and expectations, which is the function of testing. Understanding the problem is more challenging because it involves finding the causes of those differences (troubleshooting). Testing and troubleshooting together are considered a task that is often performed by a person or team, just as fixing the problem can be considered a task performed by a person or team.

Both "finding" and "fixing" tasks are often performed simultaneously, resulting in some fraction of the overall problem being fixed over a given time. Fixing the problem stops when its total cost exceeds either the available resources or the cost of living with what's left to fix. This economic approach to fixing problems has the important downside that the finding task is also stopped, which limits knowledge about how much is really left to fix and makes its assessment more of a guess.

Some simple modeling using basic learning curves shows that, as a rule of thumb, the effort required to find and fix a practically unknown problem is three times the effort required to fix an entirely known problem, assuming that each task uses the same number of people and everyone performing those tasks has at least average preparation and proficiency. If guessing is unavoidable, then prudent planning would include this margin. If knowledge about the minimum effort is unavailable, then we can assume (also as a rule of thumb) that it will be ten times the effort that an ideal team under ideal conditions would need to expend.

In my experience, most of the "find" task is typically done during research and development, before large-scale production of a product is even attempted. Most potential problems are identified and fixed during redesign of the product. Also, it is common to complete only up to 80% of the find task prior to production, which my modeling suggests is the result of a plan to use the minimum effort for both finding and fixing (instead of just fixing).

The 20% difference in quality may or may not be found by customers, whose feedback could be incorporated into future "products" along with new features that justify them paying more. This is a way of masking and evading twice the acknowledged economic cost (whose largest component is essentially effort). The physical cost still exists, however; and can become much larger when the product is used in a dependent relationship with other products and conditions that are combined in a system. If a system's performance degradation becomes large enough due to multiple problems that haven't been totally fixed, then an additional cost may be added to fix it, some of which is indirectly due to deficiencies in an individual product and is thus passed along to the customer of the product.

One way that a producer can ensure keeping their own cost down is to define product performance to only include what they choose to totally fix. The success of this strategy depends on knowing what that is before they set expectations for the product with their customers, and having a way to deflect responsibility for the consequences of what they missed. This may be one reason that businesses try to eliminate government oversight in the form of inspections and regulations beyond what they explicitly promise to their customers, because accountability for consequences of what they missed could force the cost back on them.

Application of the precautionary principle would also force the cost on the producers, by making them assess the impact of their products on people and environments where the products might be used, and not deploying products where any of those impacts are negative. A major argument against this is the stifling of innovation which might result in advantages over existing products, an argument that is implicitly built into biological evolution, a process of creating "products" (species) that die out if they don't provide an advantage to procreation.

Since the main test of products is their continuing sale to customers, and sales can't be made if customers die before they buy, it might make better sense to ensure that full investigations of problems and potential problems are conducted, either by businesses or agencies of the public, and the the results released to everyone for evaluation. The investigations and release of results would continue as the conditions, environments, and underlying understandings change beyond those originally considered.

Key to enabling evaluation would be development of truly universal and quality education that includes unbiased access to basic knowledge, understanding, and skills, along with experience in the investigation of products over a wide range of types. If the complexity of products exceeds the ability to adequately investigate and evaluate them, then people would become less likely to accept them and they would ultimately be discontinued.

Thursday, May 26, 2016

Generations of Interaction

A new model of group interaction draws from lessons learned in reproducing global population and natural resource consumption by proposing that the result of two groups interacting depends on potential changes in three variables: available resources, population, and the available resources per person.

People in each group attempt to maximize those variables by choosing among three possible interactions: remaining isolated, taking over the other group's resources (domination), or combining the two groups and sharing all resources. Whether resources are appropriated or shared, people can choose to maintain the same resources per person by changing the group's population, or to divide the resources equally among them. Each group's success in pursuing these options depends on its population: the more people it has, the more successful it will be.

The net result is the generation of a new, integrated group that is a mix of all the possibilities based on their probabilities (likelihood of success) and another group of "lost" people and resources. Just as some energy becomes useless when two gases mix, the losses are the equivalent of "waste" as far as the original two groups are concerned. The integrated group still has some differentiation into subgroups, with five subgroups (corresponding to interactions) for each of the original groups. These subgroups can now interact to generate another version of the integrated group; this second generation also results in losses of people and resources to join the waste from the first generation.

Barring interaction between the integrated group and one or more new groups, further generations will change the integrated group until there is no one left (every person has been converted into waste). If a new group is encountered, then the new group's people and resources will interact with the integrated group to generate a larger integrated group, while also expelling more waste.

This model needs to be tested, a process that should yield some interesting insights. For example, a first attempt at using it to describe humanity's relationship with the rest of the biosphere has shown that our population and the equivalent population of other species will be equal at 7.9 billion members, which is also the peak value of population before per-capita ecological resource consumption is forced to drop in the backcast model of population and consumption (with no global warming). Unless we find a new biosphere, keeping humanity's population constant will require reducing the biosphere's population and resources over several more generations which each take much less actual time than the many millennia in the first generation.

Friday, April 15, 2016

The Happiness Approximation

One of the cornerstones of my understanding of global population and consumption is the mathematical relationship between happiness and ecological footprint (our individual consumption of ecological resources). While trying to derive real significance from the convenient abstraction, I gained insights into how much of the natural world we can safely use, the purpose and mechanics of the global economy, and how people's values influence the survival of our species. Yet still I didn't fully appreciate why it had the form it did.

In the mean time, I grappled with the dynamics of human behavior and how to derive a means of successfully communicating the lessons I was learning so they could be used to hopefully extend the lifetime of our species, which my research showed is uncomfortably limited. One approach was to focus on complexity and how it influences both comprehension and the completion of basic tasks. I studied the implications of a general relationship I had discovered in my own experience between efficiency and the timing of progress in various activities, including the propagation of error in product development and messages as represented by my writing and that of others.

I suspected that task completion might be related to the pace and nature of global consumption and population growth. While I couldn't find a close correlation, I did discover that our species is attempting to use all of the Earth's resources that don't threaten the planet's ability to meet our basic needs, and we have historically been doing so in at least four different ways at a speed that varies with how much we consume.

A few weeks ago I had the latest of a string of epiphanies that has marked my research since the beginning. I accepted the possibility that the timing of consumption might be independent of the timing of task completion, and sought to generalize how they might fit together to describe how much resources are consumed during a task. In the process, I derived a relationship of the form found between happiness and ecological footprint. I was then able to apply the generalization, which I came to call the "happiness approximation" to how happiness has changed over human history and how it could conceivably change over a person's lifetime.

As I studied the consequences of the happiness approximation, I homed in on the special cases of completion and consumption that involve full use of resources in the completion of a task, which would be optimum where resources are limited. A simple statistical simulation showed that optimum completion averaged out to 76%, and that general completion had an average of 87%. Averaging those two values produced the 82% that the happiness relationship had identified as maximum average happiness for a population (and also happens to be close to the 80% used as a rule of thumb for realistic completion by project managers.

The timing of task completion also rang a bell of familiarity. The minimum amount of time it takes to complete a task (in the simulation) is 19, which is close to the 20 years that is the lowest life expectancy in my historical data (at the earliest year: 10,000 BC). If this correlation is correct, then it is the earliest point in a person's life that they can achieve 100% happiness, which according to the simulation only happens in 14% of cases.

I also modeled a better match to traditional expectations of task completion time, including something close to achievement of historical values of happiness and life expectancy in 2015. It never achieved total or optimum completion, and still took three units of time to reach maximum consumption, which is what I typically use for planning purposes (where one unit of time represents best possible achievement). Only 2% of a general population achieves that or better, which speaks to how selective an organization must be to realistically promise such performance; much less than 1% could be expected to achieve the perfect performance that an organization might optimistically promise in one unit of time.

Wednesday, March 16, 2016

A Brief History of Civilization

About one million people inhabited the world twelve thousand years ago at the beginning of civilization, and were consuming just barely enough natural resources to increase the population by a paltry few hundred per year.

Five of every six people believed that humanity's destiny was to take over the world, while the rest respected Nature and wanted to consume as much as was safe for them and the other creatures in the world. The vast majority in each group preferred to maximize the number of people without improving their lifestyle, with the minority preferring to maximize their lifestyle without increasing the number of people.

Mathematically, the history of global population consumption appears to have unfolded as a result of the activities of these groups which grew proportionately with population. Each has succeeded according to their size and natural constraints, and together forming a spectrum that is a composite of all of them.

The group that respected Nature achieved its goal in the 1920s, when (on average) about one-fourth of renewable resources were being consumed by humanity, leaving half to other creatures and the remaining quarter as a surplus for use in hard times. With nearly two billion people in the world, the minorities had grown so that more than one million people wanting maximum happiness were in this group. In the other group, seven thousand people were working for happiness and world domination.

By 2015 we were three years from achieving the goal of using the maximum amount of resources that would keep the world habitable, but it was snatched away due to an unintended consequence of the pursuit of that goal: global warming. Our use of fossil fuels had unleashed the equivalent of a competing species, effectively consuming a growing share of the remaining resources, depriving us of their use, and then forcing us to consume less.

As long as the group that prefers population over happiness is dominant, we can expect population to stay constant while per-capita consumption drops to the minimum required to maintain a healthy population with food security, which is what it was about 1500 years ago (and what I've been calling "minimum footprint"). That level will be reached by 2040. The preceding decrease in consumption would have kept up with the removal of resources due to global warming.

After 2040 our consumption decrease will slow; but, as it drops, our population will drop with it. Even worse, our collective decrease in consumption will not keep pace with global warming. By 2063 our population will reach zero just as global warming "consumes" all of the resources needed by us and the species we have depended upon.

This narrative tracks with updates to my population-consumption model utilizing new data and insights. It includes the results of a "backcasting" exercise that reproduced basic features of past population and consumption, lending credibility to its projections. My narrative of the future is based on an observed correlation between average global temperature and humanity's global ecological footprint, and assumes that self-sustained global warming will have its own global footprint, independent of ours after 2015 (which is when it is calculated to impose a limit to growth of our own global footprint). As my Twitter feed will attest, I have been monitoring related news and have become convinced that global warming is currently self-sustaining and is having a significant impact on other species, especially those near the bottom of the food chain that will directly impact our survival.

Given our proximity to the limits my model postulates with and without global warming, the model is now making clearly observable predictions of the behavior of familiar global variables in the very near-term: global population, economy (Gross World Product), and wealth. Perhaps the most obvious of these predictions is a rapid decrease in growth rates for these variables over the next two years, beginning soon this year, and an unstoppable contraction of the economy and wealth beginning in 2017.

I likely won't live to test the most critical of the predictions, around 2040, when population either begins to fall because humanity has reduced consumption too far, or we will have already gone extinct after finding a way to survive while killing the rest of the species that historically kept us alive. If some people are alive when my projections show there will be none under any circumstances, then my model will be a glorious failure, glorious because I wish more than anything that the hideous future it projects never comes true.

Wednesday, January 6, 2016

Use It Or Lose It

Waste ultimately is created by expending effort and using resources without benefit to you or anyone else, or so that your actions cause harm or death in any timeframe. If you value life, then waste is bad by definition. If you make or acquire something and don't use it to benefit you or others, then to be good you must lose it – convert it into a form that isn't waste, or give it to someone who will use it appropriately.

My New Year's resolution was to reduce waste, personally and in general, embodied by the phrase "use it or lose it." In the worst case, it keeps new waste from being generated; in the best case, it increases the net amount of benefit in the world. Knowing how much discretionary time we have provides a means for determining what we can use, what to lose, and what we shouldn't make or acquire. If the actions we take during our work time create waste, then we need to change what we do for work; and since in most cases what we do for work is traded for things we acquire for personal use, we should find less wasteful ways of acquiring those things, including making them ourselves.

I personally like to read, watch TV and movies, and listen to music. Even more, I like to explore, daydream and assemble thoughts in writing, take photographs, and create music. Obviously I can provide much of my own knowledge and entertainment without acquiring it from others, thus reducing personal waste. Waste can be reduced further by trading what I create with people who don't have those skills (or the desire, resources, or ability to develop them) in exchange for things and experiences I can't or choose not to develop on my own. In that case, I have gained benefit already, and am creating a chance for the effort to accrue further benefit for someone else.

Paradoxically, forcing everything to be subject to trade, as is the trend here in the U.S. and with international trade agreements, promotes the chances of more waste being generated. The reason is that trade, to be profitable, exponentially increases consumption by enabling more people to consume, and each person to do more of it (by increasing the efficiency of converting resources into products). Consumption, as I define it in my research, is the conversion of resources into forms that cannot be used as resources by natural systems over a period of a year (which from an ecological perspective is "waste"). Creating something for your own use is less likely to be as efficient (in the economic sense), and your consumption – including generation of ecological waste – less likely to grow exponentially.

Ideally, each of us would create what we need, and then sell (or otherwise trade) what we can't gain benefit from, either in the process of creation or changes in what defines "benefit" in terms of what we created. We would use the proceeds to buy what we need but can't create on our own. Anything left from transactions would be converted into resources that can be used for other purposes by us or other species.

My personal application of "use it or lose it" is likely to be more practical than ideal, enabled by a simple change in expectations and a process of testing. Anything new that I create, such as a book or music track, will need to be personally satisfying in its creation and its usability, thus achieving a minimum degree of benefit. If possible, it would also preempt consumption of something similar from another source that would provide an equivalent amount of benefit. This would be my minimum acceptable expectation for creating it, and is totally under my control. If in the process I have to learn something, including a new skill, then the benefit of that learning would be factored into my expectation. What I create would be offered to others as a gift (such as this blog post) or for trade (such as a book) if there is a good reason to believe they would benefit from it and if any costs involved in the gifting or trade can be recoverable in either the satisfaction of gifting or the value of what was received in trade (otherwise the cost would be waste, so this assumption will need to be tested).

I plan to give away or trade things I currently own that cannot be expected to provide any future benefit to me (thus "losing" them). Like with new things, the costs should be recoverable as satisfaction or in what was received in trade. Throwing something away is committing it to being waste, and will be avoided if possible, such as by trying to give away or trade its parts (essentially, recycling). For things I've been selling that incur periodic costs (such as distribution of music), I will use testing to find justification for future costs (such as others benefitting from them), and will discontinue them if justification can't be found; otherwise the costs would qualify as waste.

"Use it or lose it" is a good rule to promote as well as to practice, which is why I'm discussing it here. The minimum benefit from doing so is the feeling of developing and shaping potentially meaningful and useful ideas. The greatest benefit would be evidence that I am contributing to my primary value: maximization of life's ability to survive and thrive for as long as possible.