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The Best Reviewed Scientific Notation Calculators
The days when calculators just did simple math are gone. Today’s scientific calculators can perform more functions than ever, basically serving as advanced mini-computers to help math students solve problems and graph. If you’re looking for a scientific notation calculator, how do you figure out the best option? With such a broad range of functions and prices, these calculators all have a lot to offer, but you can always rely on the opinions of other users to help you decide. Here are the best reviewed scientific notation calculators on the market.
Casio FX-991EX Engineering/Scientific Calculator
The Casio FX-991EX is a good option for an affordable price. A clear display allows you to place data in spreadsheets and work with them easily. The calculator runs on solar power with a battery backup, and reviewers love the clarity of the display as well as the speed. You can scroll through your work on a problem to fix mistakes, rather than starting over. Although you can’t graph on the calculator display, the FX-991EX allows you to generate a QR code to scan and see the graph of the equation.
Texas Instruments TI-Nspire CX Graphing Calculator
At the other end of the price spectrum, the TI-Nspire CX is a high-end scientific calculator with a beautiful full color display. It includes a dedicated alphabet keyboard in addition to the numeric keys and numerous functions. Reviewers rave about the color display as well as the advanced functionality and durability of the TI-Nspire CX. It has a rechargeable battery and a charger to make sure you never have to worry about running out of power. You can use the TI-Nspire CX for the SAT, ACT and college tests. The price point is definitely an investment, but reviewers have noted its durability.
Texas Instruments TI-34 MultiView Scientific Calculator
Texas Instruments has been the gold standard for scientific notation calculators for years, and the TI-34 is a solid, affordable addition to the family. It handles fractions without converting them to decimals and uses pull down menus to enhance the display. You can look back through your entries to look for mistakes and patterns in your calculations. Reviewers compliment the slim, sleek design and praise its functionality and durability. You can perform many of the most common functions with one or two clicks. It’s got everything you need for high school math, so it’s a good lower-priced option for teenagers.
HP G8X92AA LA Prime v2 Graphing Calculator
People who use HP calculators often won’t buy another brand, and the HP Prime is one of the main reasons users are so loyal to the name. One of the best features of the Prime is the touchscreen capabilities, and you can communicate with other Prime users via a wireless dongle. Reviewers love the long lasting rechargeable battery as well as the feature-rich capabilities of the Prime. It’s a slick-looking, high-end machine as well, so if price is a factor, you may want to look at other brands.
Casio fx-9750GII Graphing Calculator
Casio has produced a good mid-range calculator in the fx-9750GII. The high resolution display allows you to see formulas, graphs and charts in clear detail, and USB functionality gives you the opportunity to connect to computers and projectors. You can create graphs in one step and perform statistical functions with ease. This calculator takes non-rechargeable AAA batteries and boasts more than 200 hours of battery life. Reviewers say the fx-9750GII is intuitive, easy to use, and fast. Those who compared the fx-9750GII to more expensive calculators say there’s no reason to waste your money on a pricier calculator.
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The Scientific Method isn't Just for Scientists
Companies face challenges on a regular basis. As such, employees need to know how to problem solve . A tried and true problem-solving process is the scientific method. I know many of us haven't thought about the scientific method since our school days but it does provide a logical way of tackling business problems. As a reminder, here are the steps to the method:
1. Identify the problem. The first step in the scientific method is to identify and analyze a problem. Data regarding the problem can be collected using a variety of methods. One way we're all accustomed to is the classic: who, what, where, when, how, and to what extent? The scientific method works best when you have a problem that can be measured or quantified in some way.
2. Form a hypothesis. A hypothesis is a statement that provides an educated prediction or proposed solution. A good format for a hypothesis would be, “If we do XX, then YY will happen.” Remember, the hypothesis should be measurable so it can help you solve the business problem identified in step one.
3. Test the hypothesis by conducting an experiment. This is when an activity is created to confirm (or not confirm) the hypothesis. There have been entire books written about conducting experiments. We won't be going into that kind of depth today but it's important to keep in mind a few things when conducting your experiment:
- The experiment must be fair and objective. Otherwise, it will skew the result.
- It should include a significant number of participants or it will not be statistically representative of the whole.
- Allow for ample time to collect the information.
4. Analyze the data . Once the experiment is complete, the results can be analyzed. The results should either confirm the hypothesis as true or false. If by chance, the results aren't confirmed, this doesn't mean the experiment was a failure. In fact, it might give you additional insight to form a new hypothesis. It reminds me of the famous Thomas Edison quote , “I have not failed. I've just found 10,000 ways that won't work.”
5. Communicate the results . Whatever the result, the outcomes from the experiment should be communicated to the organization. This will help stakeholders understand which challenges have been resolved and which need further investigation. It will create buy-in for future experiments. Stakeholders might also be in a position to help develop a more focused hypothesis.
Now let's use the scientific method in a business example:
Step 1 (identification): Human resources has noticed an increase in resignations over the past six months. Operational managers have said that the company isn't paying employees enough. The company needs to figure out why employees are resigning?
Step 2 (hypothesis): If we increase employee pay, then fewer resignations will occur.
Step 3 (test): For the next three months, HR will have a third-party conduct exit interviews to determine the reason employees are resigning.
Step 4 (analysis): The third-party report shows that the primary reason employees are leaving is because health care premiums have increased and coverage has decreased. Employees have found new jobs with better benefits.
Step 5 (communication): After communicating the results, the company is examining their budget to determine if they should:
- Increase employee pay to cover the health insurance premium expense or
- Re-evaluate their health care benefits package.
I've found using the scientific method to be very helpful in situations like the example where a person or small group have a theory about how to solve a problem. But that theory hasn't completely been bought into by everyone. Offering the option to test the proposed solution, without a full commitment, tells the group that their suggestion is being heard and that the numbers will ultimately provide insight - after the full scientific method has been followed.
Have you ever used the scientific method to solve a business problem? Share your experience in the comments.
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Chapter 6: Scientific Problem Solving
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Scientific Problem Solving Video
Science is a method to discover empirical truths and patterns. Roughly speaking, the scientific method consists of
2) Forming a hypothesis
3) Testing the hypothesis and
4) Interpreting the data to confirm or disconfirm the hypothesis.
The beauty of science is that any scientific claim can be tested if you have the proper knowledge and equipment.
You can also use the scientific method to solve everyday problems: 1) Observe and clearly define the problem, 2) Form a hypothesis, 3) Test it, and 4) Confirm the hypothesis... or disconfirm it and start over.
So, the next time you are cursing in traffic or emotionally reacting to a problem, take a few deep breaths and then use this rational and scientific approach. Slow down, observe, hypothesize, and test.
Explain how you would solve these problems using the four steps of the scientific process.
Example: The fire alarm is not working.
1) Observe/Define the problem: it does not beep when I push the button.
2) Hypothesis: it is caused by a dead battery.
3) Test: try a new battery.
4) Confirm/Disconfirm: the alarm now works. If it does not work, start over by testing another hypothesis like “it has a loose wire.”
- My car will not start.
- My child is having problems reading.
- I owe $20,000, but only make $10 an hour.
- My boss is mean. I want him/her to stop using rude language towards me.
- My significant other is lazy. I want him/her to help out more.
6-8. Identify three problems where you can apply the scientific method.
*Answers will vary.
Application and Value
Science is more of a process than a body of knowledge. In our daily lives, we often emotionally react and jump to quick solutions when faced with problems, but following the four steps of the scientific process can help us slow down and discover more intelligent solutions.
In your study of philosophy, you will explore deeper questions about science. For example, are there any forms of knowledge that are nonscientific? Can science tell us what we ought to do? Can logical and mathematical truths be proven in a scientific way? Does introspection give knowledge even though I cannot scientifically observe your introspective thoughts? Is science truly objective? These are challenging questions that should help you discover the scope of science without diminishing its awesome power.
But the first step in answering these questions is knowing what science is, and this chapter clarifies its essence. Again, Science is not so much a body of knowledge as it is a method of observing, hypothesizing, and testing. This method is what all the sciences have in common.
Perhaps too science should involve falsifiability, which is a concept explored in the next chapter.
Return to Logic Home Next (Chapter 7, Falsifiability)
Click on my affiliate link above (Logic Book Image) to explore the most popular introduction to logic. If you purchase it, I recommend buying a less expensive older edition.
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Article • 5 min read
Using the Scientific Method to Solve Problems
How the scientific method and reasoning can help simplify processes and solve problems.
By the Mind Tools Content Team
The processes of problem-solving and decision-making can be complicated and drawn out. In this article we look at how the scientific method, along with deductive and inductive reasoning can help simplify these processes.
‘It is a capital mistake to theorize before one has information. Insensibly one begins to twist facts to suit our theories, instead of theories to suit facts.’ Sherlock Holmes
The Scientific Method
The scientific method is a process used to explore observations and answer questions. Originally used by scientists looking to prove new theories, its use has spread into many other areas, including that of problem-solving and decision-making.
The scientific method is designed to eliminate the influences of bias, prejudice and personal beliefs when testing a hypothesis or theory. It has developed alongside science itself, with origins going back to the 13th century. The scientific method is generally described as a series of steps.
The first step is to develop a theory about the particular area of interest. A theory, in the context of logic or problem-solving, is a conjecture or speculation about something that is not necessarily fact, often based on a series of observations.
Once a theory has been devised, it can be questioned and refined into more specific hypotheses that can be tested. The hypotheses are potential explanations for the theory.
The testing, and subsequent analysis, of these hypotheses will eventually lead to a conclus ion which can prove or disprove the original theory.
Applying the Scientific Method to Problem-Solving
How can the scientific method be used to solve a problem, such as the color printer is not working?
1. Use observations to develop a theory.
In order to solve the problem, it must first be clear what the problem is. Observations made about the problem should be used to develop a theory. In this particular problem the theory might be that the color printer has run out of ink. This theory is developed as the result of observing the increasingly faded output from the printer.
2. Form a hypothesis.
Note down all the possible reasons for the problem. In this situation they might include:
- The printer is set up as the default printer for all 40 people in the department and so is used more frequently than necessary.
- There has been increased usage of the printer due to non-work related printing.
- In an attempt to reduce costs, poor quality ink cartridges with limited amounts of ink in them have been purchased.
- The printer is faulty.
All these possible reasons are hypotheses.
3. Test the hypothesis.
Once as many hypotheses (or reasons) as possible have been thought of, then each one can be tested to discern if it is the cause of the problem. An appropriate test needs to be devised for each hypothesis. For example, it is fairly quick to ask everyone to check the default settings of the printer on each PC, or to check if the cartridge supplier has changed.
4. Analyze the test results.
Once all the hypotheses have been tested, the results can be analyzed. The type and depth of analysis will be dependant on each individual problem, and the tests appropriate to it. In many cases the analysis will be a very quick thought process. In others, where considerable information has been collated, a more structured approach, such as the use of graphs, tables or spreadsheets, may be required.
5. Draw a conclusion.
Based on the results of the tests, a conclusion can then be drawn about exactly what is causing the problem. The appropriate remedial action can then be taken, such as asking everyone to amend their default print settings, or changing the cartridge supplier.
Inductive and Deductive Reasoning
The scientific method involves the use of two basic types of reasoning, inductive and deductive.
Inductive reasoning makes a conclusion based on a set of empirical results. Empirical results are the product of the collection of evidence from observations. For example:
‘Every time it rains the pavement gets wet, therefore rain must be water’.
There has been no scientific determination in the hypothesis that rain is water, it is purely based on observation. The formation of a hypothesis in this manner is sometimes referred to as an educated guess. An educated guess, whilst not based on hard facts, must still be plausible, and consistent with what we already know, in order to present a reasonable argument.
Deductive reasoning can be thought of most simply in terms of ‘If A and B, then C’. For example:
- if the window is above the desk, and
- the desk is above the floor, then
- the window must be above the floor
It works by building on a series of conclusions, which results in one final answer.
Social Sciences and the Scientific Method
The scientific method can be used to address any situation or problem where a theory can be developed. Although more often associated with natural sciences, it can also be used to develop theories in social sciences (such as psychology, sociology and linguistics), using both quantitative and qualitative methods.
Quantitative information is information that can be measured, and tends to focus on numbers and frequencies. Typically quantitative information might be gathered by experiments, questionnaires or psychometric tests. Qualitative information, on the other hand, is based on information describing meaning, such as human behavior, and the reasons behind it. Qualitative information is gathered by way of interviews and case studies, which are possibly not as statistically accurate as quantitative methods, but provide a more in-depth and rich description.
The resultant information can then be used to prove, or disprove, a hypothesis. Using a mix of quantitative and qualitative information is more likely to produce a rounded result based on the factual, quantitative information enriched and backed up by actual experience and qualitative information.
In terms of problem-solving or decision-making, for example, the qualitative information is that gained by looking at the ‘how’ and ‘why’ , whereas quantitative information would come from the ‘where’, ‘what’ and ‘when’.
It may seem easy to come up with a brilliant idea, or to suspect what the cause of a problem may be. However things can get more complicated when the idea needs to be evaluated, or when there may be more than one potential cause of a problem. In these situations, the use of the scientific method, and its associated reasoning, can help the user come to a decision, or reach a solution, secure in the knowledge that all options have been considered.
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- Scientific Method
The scientific method is a form of problem solving that focuses on causes and effects within a specific situation. You can use the scientific method to troubleshoot issues and, by process of elimination, discover the true causes.
Steps of the Scientific Method
Define the problem. Make sure that you fully understand the problem, all of the components, the people involved, and what the desired resolution is. You can use these analysis tools to fully define the problem.
List variables. Think of all of the possible causes of the problem. Write them down. Use root-cause analysis to discover the various factors involved.
Create a hypothesis. Predict the outcome when you test the situation.
Control all variables but one. Create a situation in which all of the possible causes are ruled out except the one you are testing.
Design an experiment. Identify the problem, your hypothesis, your method, and how you will control variables.
Conduct the experiment and record data. Does changing the one factor change the outcome? If not, what other factor or set of factors is most likely to be the true cause?
Conclude whether the experiment supported the hypothesis. If so, you have your solution. If not, you can create a new hypothesis, selecting a new variable to test.
Define the Problem
Usually, problems identify themselves: Something fails. It might be a product, service, plan, machine, or even relationship.
Customer complaints about our website double every Wednesday.
After you’ve identified the problem, you should list the possible causes for the problem.
Does our website have double the traffic on Wednesdays?
Are website problems caused by updates on Tuesday nights?
Is there a specific type of complaint that shows up mostly on Wednesdays?
Are customers using a specific web service most often on Wednesdays?
Is there a bandwidth bottleneck or other ISP problem on Wednesdays?
Create a Hypothesis
After you have identified the possible causes of the problem, you need to choose one possible cause that you want to test for and create a hypothesis about it. Start by identifying the cause that you want to test for.
Then you create a prediction that connects the possible cause to the problem. This is your hypothesis. State your hypothesis as a fact (to be tested).
Customers most often make ticketing purchases on Wednesdays, preparing for events over the weekend, so the problem lies in our ticketing service.
Hypotheses and Variables
Start by identifying the variables that you want to control:
Then figure out how to rule out or control all of these variables:
I need to check website analytics to make sure that Wednesday does not have inordinate levels of overall traffic.
I need to check with IT to find out what, if any, routine updates roll out on Tuesday nights.
I need to review the complaint logs for the last two months to find out if a specific type of issue shows up most on Wednesdays.
I need to check with our internet service provider to make sure that our bandwidth is consistent throughout the week.
Design an Experiment
List your problem and hypothesis. Then outline the method you will use to test the hypothesis:
I will use a company ID to buy tickets every hour from 8:00 a.m. to 6:00 p.m. on Wednesday and record any website issues that occur. From complaint logs, I have gleaned the following most common issues on Wednesdays:
"Dropped" ticket requests
Tickets being sold out from under customers
Failure of promo codes or discount offers
I will make sure that Wednesday web traffic is similar to other days and that IT does not routinely roll out website updates on Tuesday evenings. I will also ensure that our bandwidth is consistent throughout the week.
Conduct the experiment and record data.
Make measurements according to your experimental design and write them down. If you have many measurements, record them in a spreadsheet so that you can easily search them for patterns. If possible, output different columns and rows of your spreadsheet as graphics (bar graphs, line graphs, pie graphs, and so on) to help you recognize patterns.
First, check to see whether your prediction matched the outcome of the experiment. If it did, your hypothesis has been supported. If not, consider whether the hypothesis should be rejected. Whatever the outcome, think about whether any flaws in experiment design skewed the results.
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The Scientific Method
Why the Scientific Method is supremely important
An example of how scientists use the scientific method, how problem solvers use the scientific method, how environmentalism has used the scientific method, where environmentalism erred in use of the scientific method, an alternative paradigm that could possibly work.
"Solution of problems too complicated for common sense to solve is achieved by long strings of mixed inductive and deductive inferences that weave back and forth between the observed machine and the mental hierarchy of the machine found in the manuals. The correct program for this interweaving is formalized as Scientific Method ." ~ Robert Pirsig, 1974, Zen and the Art of Motorcycle Maintenance: An Inquiry into Value, p99
1. Observe a phenomenon that has no good explanation.
2. Formulate a hypothesis that explains the phenomenon.
3. Design an experiment(s) to test the hypothesis.
4. Perform the experiment(s).
5. Accept, reject, or modify the hypothesis.
The Scientific Method is a rigorous, time tested process for determining the probable truth of any cause-and-effect proposition. The proposition is known as a hypothesis . The method of testing is experimentation . The process has five steps.
As simple as the process looks, it has utterly changed the course of history. So much so that's now called "The Father of All Processes."
The Scientific Method's great claim to fame is it is the only known method for producing reliable new cause-and-effect knowledge. It thus forms the entire foundation of science and all that depends on science, which for modern civilization is all major advances since the Scientific Revolution begin in 1543. That year saw publication of two monumental works that instantly changed the way problem solvers worked: Nicolaus Copernicus's On the Revolutions of the Heavenly Spheres and Andreas Vesalius's On the Fabric of the Human Body . The Scientific Method in its early modern form appeared shortly thereafter with the work of Galileo. Centuries later, Einstein summarized Galileo's accomplishment: 1
Purely logical thinking [untested by experimentation] cannot yield us any [reliable] knowledge of the empirical world; all knowledge of reality starts from experience [observation and experimentation] and ends with it. Propositions arrived at by purely logical means are completely empty as regards reality. Because Galileo realized this, and particularly because he drummed it into the scientific world , he is the father of modern physics—indeed, of modern science altogether.
The Scientific Method is the most influential discovery since the invention of agriculture because it changed the way we think about thinking. Before the Scientific Method, scientific knowledge was based on tradition and common sense. There was no concept of rigorous systematic testing of new propositions. Afterwards there was. Today, any scientist who puts forth a new major hypothesis without first subjecting it to the Scientific Method (theoretically or physically) will not survive as a scientist for long.
There are many versions of what the Scientific Method actually is. We have boiled down the concept to its simplest essential form. The method derives its power from the way it forces hypotheses to evolve via cycles of experimentation until they are either rock solid or tossed out as unworthy of being added to the world's storehouse of proven scientific knowledge. The method is not perfect. False or weak hypotheses slip through. But it's several orders of magnitude better than what came before it, which was no hypothesis testing at all.
Step 1. Observe a phenomenon that has no good explanation
For a scientist the problem to solve is what is the cause of a particular effect ?
For the 17 th century English physician John Snow , the problem to solve was what is the cause of diseases like cholera and the Black Death? There was no good explanation for the phenomenon of cholera at the time, which had a mortality rate of about 50%. Snow's scientific approach to solving the cause of cholera problem is one of the great classics of science. His eventual solution was so profound, and so epitomized the practical use of the Scientific Method, that he is remembered as the father of epidemiology (the study of contagious diseases in a population).
Step 2. Formulate a hypothesis
John Snow had long been skeptical of the then dominant miasma theory that diseases like cholera were caused by a noxious form of foul air: 2
Miasma was considered to be a poisonous vapor or mist filled with particles from decomposed matter (miasmata) that caused illnesses. The Miasmatic position was that diseases were the product of environmental factors such as contaminated water, foul air, and poor hygienic conditions. Such infection was not passed between individuals but would affect individuals who resided within the particular locale that gave rise to such vapors. It was identifiable by its foul smell.
Here in John Snow's own words is the reasoning he went through to develop his hypothesis: 3
On proceeding to the spot, I found that nearly all the deaths had taken place within a short distance of the [Broad Street] pump . There were only ten deaths in houses situated decidedly nearer to another street-pump. In five of these cases the families of the deceased persons informed me that they always sent to the pump in Broad Street, as they preferred the water to that of the pumps which were nearer. In three other cases, the deceased were children who went to school near the pump in Broad Street.... With regard to the deaths occurring in the locality belonging to the pump, there were 61 instances in which I was informed that the deceased persons used to drink the pump water from Broad Street , either constantly or occasionally... The result of the inquiry, then, is, that there has been no particular outbreak or prevalence of cholera in this part of London except among the persons who were in the habit of drinking the water of the above-mentioned pump well.
On the basis of this evidence Snow concluded that drinking water from the Broad Street well pump caused cholera. It was a radical hypothesis for the time.
Step 3. Design an experiment(s) to test the hypothesis
Snow then devised an experiment so simple it rings in the minds of scientists to this day. The experiment was to remove the Broad Street pump handle immediately. If the hypothesis was true this would stop the cholera epidemic. Continuing the above quote:
I had an interview with the Board of Guardians of St James's parish, on the evening of the 7th inst [Sept 7], and represented the above circumstances to them. In consequence of what I said, the handle of the pump was removed on the following day .
Step 4. Perform the experiment(s)
The pump handle was removed. The epidemic ended. Deaths quickly trailed off and fell to zero. Those who had fled the neighborhood moved back and life soon returned to normal.
Step 5. Accept, reject, or modify the hypothesis
Since the epidemic had already started to fade it was not clear if the experiment proved the hypothesis or not:
There is no doubt that the mortality was much diminished, as I said before, by the flight of the population, which commenced soon after the outbreak; but the attacks had so far diminished before the use of the water was stopped, that it is impossible to decide whether the well still contained the cholera poison in an active state, or whether, from some cause, the water had become free from it.
Snow had been working on his hypothesis before the London cholera epidemic of 1854. He had first published On the Mode of Communication of Cholera in 1849. Using what he learned from the 1854 epidemic, he improved his argument and published a second edition in 1855 with the spot map of deaths. The report concluded that: 4
Diseases which are communicated from person to person are caused by some material which passes from the sick to the healthy, and which has the property of increasing and multiplying in the systems of the persons it attacks. In syphilis, smallpox, and vaccinia, we have physical proof of the increase of the morbid material, and in other communicable diseases the evidence of this increase, derived from the fact of their extension, is equally conclusive. As cholera commences with an affection of the alimentary canal, and as we have seen that the blood is not under the influence of any poison in the early stages of this disease, it follows that the morbid material producing cholera must be introduced into the alimentary canal [and] must, in fact, be swallowed accidentally, for persons would not take it intentionally....
However, due to paradigm change resistance : 5
After the cholera epidemic had subsided, government officials replaced the Broad Street Pump Handle. They had responded only to the urgent threat posed to the population, and afterward they rejected Snow's theory. To accept his proposal would be indirectly accepting the oral-fecal method transmission of disease, which was too unpleasant for most of the public.
The local officials were not scientists. They listened to their voting public rather than the muse of the Scientific Method and all of science, which believes The Truth Has No Higher Master . Science soon accepted Snow's new theory and the field of epidemiology was born.
For scientists working on fundamental cause-and-effect problems, the problem is "What is the cause of a particular effect?" For problem solvers in general we must restate how the Scientific Method is used, since its application is not that obvious.
Showing how the solution hypothesis is the cause and the desired goal state is the effect. This is a cause-and-effect relationship.
From a systems thinking point of view a system with a problem has two states: the present state and the goal state . In the goal state problem symptoms are gone. Systems thinking problem solvers thus state their hypothesis as "This solution will cause the effect of the system moving to the goal state." The solution is the cause. The solved problem is the effect.
Next we examine how environmentalism has used the Scientific Method. Then we examine how, without realizing it, environmentalism made a critical error in use of the Scientific Method. Finally we present how the error can be corrected.
The goal of the environmental movement is to solve the environmental sustainability problem. There is "no good explanation" in the sense there is no solution that would explain how to solve the problem.
The environmental movement has formulated one solution hypothesis after another. Here's a short history:
Successive Generations of Solutions
1. Conservation parks , beginning with Yellowstone National Park in 1872. The idea was that wilderness areas and wildlife were fast disappearing and that the problem could be solved by creation of conservation parks.
2. End-of-pipe regulation , such as pollution limits, fines, and cleanup funding, like Super Fund.
3. Beginning-of-pipe regulation , such as mandated use of best technology. This solution was preferred to end of pipe regulations because it is much cheaper to prevent pollution in the first place than to deal with it later.
4. International treaties , like the Montreal Protocol and the Kyoto Protocol.
5. Economic instruments , like carbon taxes and emission permit trading.
The hypothesis is proposing these solutions will solve the problem . This is different from saying these solutions will solve the problem , a subtle but critical distinction. If a solution is proposed but never accepted, it's a failed solution. Environmentalists tend to miss this distinction. To them, solution failure means a solution was implemented and then failed to solve the problem.
The experiment is to design solutions like those listed above and then propose them to political institutions at the local, national, and international level. In systems thinking terms, the hypothesis is proposing these solutions will cause the effect of the system moving to the goal state of an acceptable level of problem symptoms.
The experiment was performed. Every one of the classes of solutions listed above has failed, which is why the successive generations of solutions were devised. Solution failure was apparent long ago. For example, here's what the results looked like in 2000: 6
The task of developing an ecologically sustainable society is a major challenge facing current social institutions. However, the results achieved so far make this imperative appear to be only a utopian fantasy, fast receding from our grasp. Since the first Earth Day of 1970, a number of actions have been taken in the United States [and elsewhere] to deal with environmental degradation. Although there has been some incremental progress in reversing some of the worst forms of visible pollution, it pales in comparison to the changes that are needed.
The third edition of Limits to Growth in 2004 painted the results even more bluntly: (page xvi)
…we are much more pessimistic about the global future than we were in 1972. It is a sad fact that humanity has largely squandered the past 30 years in futile debates and well-intentioned, but half-hearted, responses to the global ecological challenge. We do not have another 30 years to dither. Much will have to change if the ongoing overshoot is not to be followed by collapse during the twenty-first century.
For further proof the experiment failed examine the graph below. The environmental movement has had little effect on footprint growth.
The experiment failed so the hypothesis cannot be accepted. It must be rejected or modified. Environmentalists have chosen to modify their hypotheses (solutions) and try them again, with all sorts of little tweaks and improvements. This has not worked, which indicates something is fundamentally wrong with the entire collection of hypotheses.
It would seem that environmentalism has slipped into a rut. Without realizing it, the field is promoting solutions that differ superficially but are all fundamentally the same because they all fail. This brings to mind a popular quote misattributed to Albert Einstein:
The definition of insanity is doing the same thing over and over and expecting different results.
What is environmentalism doing wrong? Where have they erred in use of the Scientific Method?
It's pretty simple. Environmentalism has failed to reject the hypothesis that proposing solutions like those listed above will work. The field has ignored massive proof its hypothesis is false. When a long series of solutions (each is a hypothesis) fail no matter how you modify them, that's proof you should reject the hypothesis. But this has been impossible for environmentalism to do because they have no alternative hypothesis.
Click a node to read about it.
Let's shift gears to a higher level of abstraction . Environmentalism is in the Prescience stage of the Kuhn Cycle . It has no central paradigm that works. If it did it would be producing solutions that work.
Environmentalism uses the pre-paradigm of Classic Activism . This process generated the field's long string of solutions that have mostly failed. Environmental activists have stubbornly refused to abandon Classic Activism because, as Thomas Kuhn explains: 7
...once it has achieved the status of a paradigm, a scientific theory is declared invalid only if an alternative candidate is available to take its place. Once a first paradigm through which to view nature has been found, there is no such thing as research in the absence of any paradigm. To reject one paradigm without simultaneously substituting another is to reject science itself.
Classic Activism has worked on other large social problems like slavery, universal suffrage, and civil rights. But it hasn't worked on the environmental sustainability problem. The world's environmental activists, however, have no other paradigm to turn to, so they are making a mistake that comes natural.
A paradigm is a comprehensive model of understanding that provides a field's members with viewpoints and rules on how to look at the field's problems and how to solve them. For example:
The life sciences use the paradigm of Darwinian evolution and build from there.
Physics starts with Newton's three laws of motion and the universal law of gravity.
Chemistry begins with Mendeleev's Periodic Table of the Elements as its all encompassing foundation.
As we saw above, epidemiology builds on the principle that diseases like cholera and the Black Death are spread by microorganisms that are contagious.
What comprehensive foundational paradigm will work for environmentalism?
The pattern in the life sciences, physics, chemistry, and epidemiology is the kernel of truth is small, elegant, and somehow provides a solid foundation that can be built on indefinitely. We believe the starting kernel of truth for environmentalism can be a single principle:
The only way to solve a difficult problem is to resolve its root causes.
The analysis at Thwink.org found the reason sustainability solutions failed in the past was they did not resolve at least four main root causes, as listed in this Summary of Analysis Results . From this we can extract a comprehensive set of foundational principles:
Principle 1. Root Cause Resolution
All problems arise from their root causes . From this principle arises the need for all the rest.
Principle 2. Sufficient Process Maturity
All problems are solved by a series of steps. Different problems require different steps. Difficult problems require different steps from easy problems. A process is a reusable series of steps and related practices to achieve a goal. Therefore the process must fit the problem . This principle can be restated. From the viewpoint of process maturity, the more difficult the problem, the better the process used to solve it must be. The sustainability problem is so difficult it requires a formal mature process that fits the problem.
Principle 3. Causal Structure
The behavior of a complex system emerges from its causal structure . This can be understood only by modeling a problem's essential causal structure, which must include the root causes.
Principle 4. Subproblem Decomposition
The sustainability problem is too complex to solve without first decomposing it into subproblems . All difficult social problems contain at least these three subproblems: 1. How to overcome change resistance 2. How to achieve proper coupling 3. How to avoid excessive model drift
Principle 5. Solution Chain Identification
Each subproblem can be solved by identifying its solution chain . Finding the causal structure of a subproblem will reveal its symptoms , intermediate causes , and root causes . You can then identify the high leverage points for resolving the root causes. Solution elements can then be developed to push on the high leverage points. The causal chain running from the solution elements to symptoms is the solution chain.
The last principle is the payoff for this approach. The solution hypothesis is "this is the solution chain for this subproblem." Compare this to environmentalism's present solution hypothesis of "proposing these solutions will solve the problem." The reason usually given is "because it resolves these causes." That hypothesis states a solution chain of only three links : solutions, causes (really intermediate causes), and symptoms. Principle 5, when implemented via the System Improvement Process , uses a solution chain of eight links :
1. The solution evolution plan for how to manage the solution elements. 2. The solution elements for pushing on the high leverage points. 3. The high leverage points for activating the loops in link 4. 4. The feedback loops that need to go dominant to resolve the root causes. 5. The root causes , which cause the intermediate causes. 6. The intermediate causes , which drive the loops in link 7. 7. The immediate cause feedback loops causing the symptoms. 8. The problem symptoms .
How all this works is shown below. Note how each of the principles maps to something in the table. The solution evolution plan is analysis and model driven.
The Summary of Analysis Results table essentially is the paradigm, just as the Periodic Table is the paradigm in chemistry.
The table offers two important insights into why environmentalism's current solutions fail:
1. Current solutions do not resolve root causes. The analysis shows that current solutions use a solution chain of symptomatic solutions, low leverage points, intermediate causes, immediate cause loops, and symptoms. (One such chain is shown above in red. It's where most environmental movement and government effort goes.) Since root causes are nowhere on that chain, solution failure is inevitable.
2. Current solutions ignore the change resistance subproblem. As a result, most solutions are rejected by the system.
Suppose environmentalism adopted something like the above principles and built upon them. This could lead to:
Imagine a world where environmental activists work totally differently from today. There's little emphasis on motivating the masses by inspirational messages, articles about what you can do to be green, demonstrations, boycotts, or appeals to Corporate Social Responsibility. There's also little work by activists on developing more sustainable technologies or focusing on particular industries (like fossil fuel) and trying to convert them to a more sustainable approach. Small amounts of this occur, but the bulk of the movement's energies now go to methodically finding and resolving the root causes of the sustainability problem.
In short, environmentalists have become scientists.
In this brave new world the average environmentalist spends most of her time in analysis. Environmentalists have become the world's R&D department for how to solve the sustainability problem by use of the powerful tools of root causes analysis , process driven problem solving , and model based analysis . They are no longer classic activists . They now see themselves as analytical activists with a passion to firmly establish The Normal Science of Sustainability, as defined in the Kuhn Cycle . Some, especially those who have trained for years in their new analytical specialities, wear white coats with things like " In Search of The Analytical Truth and Other Silly Things " or " The Truth Has No Higher Master " on the back.
These days when you interview for a job at an established environmental organization, the questions are tough:
How would you apply Six Sigma or Hoshin Kanri to an investigation of how to improve our problem solving process?
What projects have you worked on that experimentally verified their root cause conclusions?
What root causes have you personally played a hand in finding?
Here's a one page description of a problem we're working on. There's a white board. Show us how you would strategically go about solving the problem if you were the project manager.
What's your modeling background?
What approaches have your models taken to memetic infection and social agent adaptation?
What's your top ten network of contacts in the area of problem solving process management and improvement?
When designing a targeted lobbying campaign for a proposed solution element, what approach would you take to analytical preparation to ensure its success?
How would you compare European, American, and Chinese environmental organizations, including those at the government level, on their problem solving processes? Which do you think work better and why?
The salaries are excellent. In fact, they exceed industry averages because public interest problems are inherently more difficult to solve than business problems. Smart environmental managers know this and budget accordingly.
All that top talent combined with a root cause analysis approach has led to one success after another. Funding is pouring into the movement from private and public sources. The growing success of the movement has led to a spike in sustainability problem solving and solution management employment. It's now a high paying, high status professional career, right up there with engineering and law.
It's a vision that dozens of fields have achieved. It all starts when a few innovators pioneer what becomes a field's first foundational paradigm that works.
(1) The Einstein quote about Galileo is from Ideas and Opinions , by Albert Einstein, 1954, p271.
(2) The quote about miasma is from the Wikipedia entry on miasma theory .
(3) The quote on John Snow's investigation is from the Wikipedia entry for the 1854 Broad Street cholera outbreak .
(4) From John Snow's Mode of Communication of Cholera , 1855.
(5) From the political controversy about the cholera epidemic.
(6) Quote from Agency, Democracy, and Nature: The U. S. Environmental Movement from a Critical Theory Perspective , by Robert Brulle, 2000, page 1.
(7) Quote from The Structure of Scientific Revolutions by Thomas Kuhn, 1996, pages 77 and 79.
What Is Six Sigma?
Here's what iSixSigma has to say:
Six Sigma at many organizations simply means a measure of quality that strives for near perfection . Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects... in any process.... According to the Six Sigma Academy, Black Belts save companies approximately $230,000 per project and can complete four to 6 projects per year. General Electric, one of the most successful companies implementing Six Sigma, has estimated benefits on the order of $10 billion during the first five years of implementation. GE first began Six Sigma in 1995 after Motorola and Allied Signal blazed the Six Sigma trail. Since then, thousands of companies around the world have discovered the far reaching benefits of Six Sigma.
The book Hoshin Kanri: The Strategic Approach to Continuous Improvement , by David Hutchins, 2008, describes it this way:
The results of the quality revolution have been mixed. Global competition has elevated the most successful companies, in terms of providing goods and services, but even then initiatives such as total quality , business process re-engineering and Six Sigma have been heralded as the solution, only to have been replaced with the next 'big thing' when it came along. Hoshin Kanri is not the next big thing in quality, it is a strategic approach to continuous improvement that provides a context for all of the individual elements such as Six Sigma or Lean Manufacturing.
Six Sigma and Hoshin Kanri are generic processes. They allow general overall process optimization. However, for your core competencies you need a process that fits your problem closely.
For that Thwink.org has developed the System Improvement Process (SIP). It was designed from scratch to solve difficult social problems. SIP is a wrapper for root cause analysis so that tool can be applied to social problems.
Start with SIP. After a few years with that it will be obvious what additional processes you need.
Start your reading here:
Mastering the Science of Striking at the Root
Analysis is the breaking down of a problem into smaller easier to solve problems. Exactly how this is done determines the strength of your analysis.
You will see powerful techniques used in this analysis that are missing from what mainstream environmentalism has tried. This explains why a different outcome can be expected.
The key techniques are proper subproblem decomposition and root cause analysis .
The analysis was performed over a seven year period from 2003 to 2010. The results are summarized in the Summary of Analysis Results , the top of which is shown below:
Click on the table for the full table and a high level discussion of analysis results.
This is the solution causal chain present in all problems. Popular approaches to solving the sustainability problem see only what's obvious: the black arrows. This leads to using superficial solutions to push on low leverage points to resolve intermediate causes .
Popular solutions are superficial because they fail to see into the fundamental layer, where the complete causal chain runs to root causes . It's an easy trap to fall into because it intuitively seems that popular solutions like renewable energy and strong regulations should solve the sustainability problem. But they can't, because they don't resolve the root causes.
In the analytical approach, root cause analysis penetrates the fundamental layer to find the well hidden red arrow. Further analysis finds the blue arrow. Fundamental solution elements are then developed to create the green arrow which solves the problem. For more see Causal Chain in the glossary.
First the analysis divided the sustainability problem into four subproblems. Then each subproblem was individually analyzed. For an overview see The Four Subproblems of the Sustainability Problem .
This is no different from what the ancient Romans did. Its a strategy of divide and conquer. Subproblems like these are several orders of magnitude easier to solve because you are no longer trying (in vain) to solve them simultaneously without realizing it. This strategy has changed millions of other problems from insolvable to solvable, so it should work here too.
For example, multiplying 222 times 222 in your head is for most of us impossible. But doing it on paper, decomposing the problem into nine cases of 2 times 2 and then adding up the results, changes the problem from insolvable to solvable.
Change resistance is the tendency for a system to resist change even when a surprisingly large amount of force is applied.
Overcoming change resistance is the crux of the problem, because if the system is resisting change then none of the other subproblems are solvable. Therefore this subproblem must be solved first. Until it is solved, effort to solve the other three subproblems is largely wasted effort.
The root cause of successful change resistance appears to be effective deception in the political powerplace. Too many voters and politicians are being deceived into thinking sustainability is a low priority and need not be solved now.
The high leverage point for resolving the root cause is to raise general ability to detect political deception. We need to inoculate people against deceptive false memes because once people are infected by falsehoods, its very hard to change their minds to see the truth.
Life form improper coupling occurs when two social life forms are not working together in harmony.
In the sustainability problem, large for-profit corporations are not cooperating smoothly with people. Instead, too many corporations are dominating political decision making to their own advantage, as shown by their strenuous opposition to solving the environmental sustainability problem.
The root cause appears to be mutually exclusive goals. The goal of the corporate life form is maximization of profits, while the goal of the human life form is optimization of quality of life, for those living and their descendents. These two goals cannot be both achieved in the same system. One side will win and the other side will lose. Guess which side is losing?
The high leverage point for resolving the root cause follows easily. If the root cause is corporations have the wrong goal, then the high leverage point is to reengineer the modern corporation to have the right goal.
Solution model drift occurs when a problem evolves and its solution model doesnt keep up. The model drifts away from whats needed to keep the problem solved.
The worlds solution model for solving important problems like sustainability, recurring wars, recurring recessions, excessive economic inequality, and institutional poverty has drifted so far its unable to solve the problem.
The root cause appears to be low quality of governmental political decisions. Various steps in the decision making process are not working properly, resulting in inability to proactively solve many difficult problems.
This indicates low decision making process maturity. The high leverage point for resolving the root cause is to raise the maturity of the political decision making process.
In the environmental proper coupling subproblem the worlds economic system is improperly coupled to the environment. Environmental impact from economic system growth has exceeded the capacity of the environment to recycle that impact.
This subproblem is what the world sees as the problem to solve. The analysis shows that to be a false assumption, however. The change resistance subproblem must be solved first.
The root cause appears to be high transaction costs for managing common property (like the air we breath). This means that presently there is no way to manage common property efficiently enough to do it sustainably.
The high leverage point for resolving the root cause is to allow new types of social agents (such as new types of corporations) to appear, in order to radically lower transaction costs.
There must be a reason popular solutions are not working.
Given the principle that all causal problems arise from their root causes, the reason popular solutions are not working (after over 40 years of millions of people trying) is popular solutions do not resolve root causes.
This is Thwink.orgs most fundamental insight.
Using the results of the analysis as input, 12 solutions elements were developed. Each resolves a specific root cause and thus solves one of the four subproblems, as shown below:
Click on the table for a high level discussion of the solution elements and to learn how you can hit the bullseye.
The solutions you are about to see differ radically from popular solutions, because each resolves a specific root cause for a single subproblem. The right subproblems were found earlier in the analysis step, which decomposed the one big Gordian Knot of a problem into The Four Subproblems of the Sustainability Problem .
Everything changes with a root cause resolution approach. You are no longer firing away at a target you cant see. Once the analysis builds a model of the problem and finds the root causes and their high leverage points, solutions are developed to push on the leverage points.
Because each solution is aimed at resolving a specific known root cause, you can't miss. You hit the bullseye every time. It's like shooting at a target ten feet away. The bullseye is the root cause. That's why Root Cause Analysis is so fantastically powerful.
Nine Sample Solution Elements
1. Freedom from Falsehood
2. The Truth Test
3. Politician Truth Ratings
4. Politician Corruption Ratings
5. No Servant Secrets
6. Corporation 2.0 Suffix
7. Servant Responsibility Ratings
8. Sustainability Index
9. Quality of Life Index
The high leverage point for overcoming change resistance is to raise general ability to detect political deception. We have to somehow make people truth literate so they cant be fooled so easily by deceptive politicians.
This will not be easy. Overcoming change resistance is the crux of the problem and must be solved first, so it takes nine solution elements to solve this subproblem. The first is the key to it all.
In this subproblem the analysis found that two social life forms, large for-profit corporations and people, have conflicting goals. The high leverage point is correctness of goals for artificial life forms. Since the one causing the problem right now is Corporatis profitis , this means we have to reengineer the modern corporation to have the right goal.
Corporations were never designed in a comprehensive manner to serve the people. They evolved. What we have today can be called Corporation 1.0. It serves itself. What we need instead is Corporation 2.0. This life form is designed to serve people rather than itself. Its new role will be that of a trusted servant whose goal is providing the goods and services needed to optimize quality of life for people in a sustainable manner.
Solution element: Corporation 2.0
Whats drifted too far is the decision making model that governments use to decide what to do. Its incapable of solving the sustainability problem.
The high leverage point is to greatly improve the maturity of the political decision making process. Like Corporation 1.0, the process was never designed. It evolved. Its thus not quite what we want.
The solution works like this: Imagine what it would be like if politicians were rated on the quality of their decisions. They would start competing to see who could improve quality of life and the common good the most. That would lead to the most pleasant Race to the Top the world has ever seen.
Solution element: Politician Decision Ratings
Presently the worlds economic system is improperly coupled to the environment. The high leverage point is allow new types of social agents to appear to radically reduce the cost of managing the sustainability problem.
This can be done with non-profit stewardship corporations. Each steward would have the goal of sustainably managing some portion of the sustainability problem. Like the way corporations charge prices for their goods and services, stewards would charge fees for ecosystem service use. The income goes to solving the problem.
Corporations gave us the Industrial Revolution. That revolution is incomplete until stewards give us the Sustainability Revolution.
Solution element: Common Property Rights
Cutting Through Complexity: The Engineers Guide to Solving Difficult Social Problems with Root Cause Analysis
This presents our research results, including SIP, analysis of the environmental sustainability problem, and twelve sample solution elements.
The Dueling Loops of the Political Powerplace: Why Progressives Are Stymied and How They Can Find Their Way Again
This analyzes the worlds standard political system and explains why its operating for the benefit of special interests instead of the common good. Several sample solutions are presented to help get you thwinking.
Change Resistance as the Crux (journal paper)
Solving Problems with Root Cause Analysis (journal paper)
Democratic Backsliding (working paper)
Striking at the Root with Common Property Rights
The Trump Phenomenon
The Powell Memo
Breaking the Thirty Year Deadlock: The Three Essays
What Is an Analytical Approach?
Root Cause Analysis: How It Works at Thwink.org
Bridging the Sustainability Gap with Common Property Rights
It's best to start with the first one and watch them all in sequence.
1. Overview of the Dueling Loops , 11 min
Part 1. Basic Concepts of Systems Thinking and the Problem
2. Discovery of the Sustainability Problem by LTG Project , 6 min 3. The Basic Concept of Feedback Loops, with Pop Growth , 9 min 4. How Simulation Models Work, with Pop Growth , 10 min 5. The Importance of Structural Thinking, 3 types , 8 min
Part 2. Deriving the Dueling Loops Shape from Past System Behavior
6. What Jared Diamonds Collapse Book Attempted to Do , 6 min 7. Extracting the Competitive Spiral from Collapse , 8 min 8. The Two Fundamental Loops of All Political Systems , 5 min 9. The Four Loop Model of Why Some Societies Collapsed , 7 min 10. The Basic Dueling Loops Shape , 15 min
Part 3. How the Basic Dueling Loops Simulation Model Works
11. The Race to the Bottom Simulation Model , 6 min 12. The Five Main Types of Political Deception , 18 min
The Democracy in Crisis Film Series
Introduction to the WorldChange Model , 27 min
Adding Change Resistance to IGMs , 29 min
Part 1. Introduction to Common Property Rights , 15 min
Part 2. The 7 Components of Common Property Rights , 23 min
Truth or Deception , 10 min
The Progressive Paradox Film , 123 min
Introduction to Analytical Activism , 48 min
Agent Based Modeling
Broken Political System Problem
Causal Loop Diagram
Competitive Exclusion Principle
Complex Social System
Cycle of Acceptance
Event Oriented Thinking
Fundamental Attribution Error
Intuitive Process Trap
Law of Root Causes
Laws of Root Cause Analysis
MECE Issue Trees
Model Based Analysis
More of the Truth
New Dominant Life Form
Principle of Cumulative Adv.
Process Driven Problem Solving
Root Cause Analysis
Social Force Diagrams
System Improvement Process
Three Pillars of Sustainability
The glossary is the foundation for the entire website. It defines the conceptual framework required to "move toward higher levels" of thinking.
Meet the Thwinkers
How You Can Help
What Does Thwink Have to Offer?
Democratic Backsliding (active)
Politician Truth Ratings (inactive)
Atlanta Analytical Activists (inactive)
The World of Simulation
One way to get started is The Common Property Rights Project .
This can be done by switching to Root Cause Analysis , which will lead to Environmentalism 2.0 .