How Precise, Accurate and Efficient at Predicting Are You?
How to measure your progress as a forecaster
I like to be as accurate as I can in my forecasting. One thing I have found to be important here has to do with accuracy versus precision. They are not the same.
Don’t get confused here. The distinction between how accurate or precise you are will ultimately develop you clarity of communication, how well you collaborate with others, and how easily you are able to do what need to be done.
More on Precision and Accuracy
The distinction between precision and accuracy has to do with how they vary as measurement systems. If an individual or team is starting a quality improvement or forecasting project that involves collecting data to manage quality or to monitor changes in various group processes, it’s important that the systems for collecting measurements are free of flaws, especially flaws caused by cognitive biases, and or logical fallacies.
After all, if you can’t trust your measurement system, then you can’t trust the data that it produces, and if can’t trust the data that it produces, you cannot predict what is likely to happen or solve a problem.
The distinctions between accuracy and precision come into play, especially when isolating constraints in a system when you need to isolate measurement system errors that may be taking place?
Here’s where accuracy and precision come into play. Accuracy refers to how close measurements are to the “true” value, while precision refers to how close measurements are to each other. In other words, accuracy describes the difference between the measurement and the part’s actual value, while precision describes the variation you see when you measure the same part repeatedly with the same device. Any team of strategists needs to understand these details and any new consequential piece of data can change all predictions, estimates, and measurements.
Another way of describing true value is as a psychometric concept that refers to the measure that would have been observed on a construct were there not any error involved in its measurement. … The concept of a true value relates to the concepts of reliability and validity.
Precision is not concerned with true value. For instance, something can be precise yet not exactly accurate. Let’s explore this as we break down precision further into two components:
1. Repeatability: The variation observed when the same operator measures the same part repeatedly with the same device.
2. Reproducibility: The variation observed when different operators measure the
It’s important to note that measurement systems can suffer from both precision and accuracy constraints. Thus there are times where measurement will be any of the following:
1. Accurate and precise
2. Accurate yet imprecise
3. Inaccurate yet precise
4. Neither accurate nor precise.
If you still don’t get this distinction lets, try this simple example.
Have you ever seen those scales in the supermarket that are used to weigh produce?
You place an apple on the scale and there are little lines on the scale to indicate ounces. Here you may be testing the weight of the apple using a scale that measures the bags precisely (in other words, there is little variation in the measurements), but not accurately — measuring 2.3 oz., 2.35432 oz., and 2.31693 oz. for three samples. Here the measurement is precise but not accurate.
Or maybe your measurements are all over the place, with samples measuring at 11.64 oz., 12.35 oz., and 13.04 oz., in which case your scale may be neither accurate nor precise.
But how can you detect these problems in your measurement system?
By Evaluating Accuracy & Precision
For the forecaster, strategist or problem-solver who requires both accuracy and precision, there are specific measurement systems analysis tools in Minitab Statistical Software, including Gage Linearity and Bias Studies and Gage R&R Studies, which can help an expert reveal if a scale needs to be recalibrated or if a newly hired operator might be measuring ingredients consistently.
When putting accuracy and precision into action the question arises of what should a strategist do if they detect accuracy and/or precision errors?
The next step is to focus improve the measurement system. Only when this has been done can you rely on the data and moving forward with continually improving accuracy and precision
If your measurement correction system is built for accuracy and precision, then you will likely have other systems in place to help you decide if recalibrating a scale or conducting more training for new team members might be just what you need to get your measurement systems to be both accurate and precise.
At the end of the day, the way to measure accuracy and precision is by determining how productive you are.
Essentially, productivity describes various measures of efficiency, effectiveness, accuracy, and precision.
There are many different definitions of productivity (including those that are not defined as ratios of output to input) and the choice among them depends on the purpose of the productivity measurement and/or data availability. The key source of difference between various productivity measures is also usually related (directly or indirectly) to how the outputs and the inputs are aggregated into scalars (a combination of people, places, and things) to obtain such a ratio-type measure of productivity and specificity.
Productivity is a crucial factor in the forecasting that is done concerning small groups, collaborative communities, and even nations. Increasing productivity in an organization where there is gamification incentives measured through accuracy and precision , and which produces reasonable, if not perfect forecasts can raise living standards because more real income improves people’s ability to purchase goods and services, enjoy leisure, improve housing and education and contribute to social and environmental programs. Productivity growth also helps businesses to be more profitable. All of this is tied to precision and accuracy in forecasting and predictions.
When exploring accuracy and precision to measure success you can use one class of inputs or many. When using one class of input, but not multiple factors, it is called partial productivities. In the “real world” measurement in forecasting usually means measures of partial productivity, since there may be so many factors that it is hard to measure them to perfection.
The Takeaway
Measured and interpreted correctly, these components are indicative of forecasting accuracy and approximate the efficiency with which your resources are used in your personal life or your business. However, as I mentioned, productivity is only measured partially — or approximately. In a way, these measurements are somewhat inaccurate because they do not measure everything, but it is possible to interpret correctly the results of partial productivity and to benefit from forecasts and predictions here for practical situations. At an organizational level, typical partial accuracy in predicting, and productivity measures include worker hours, materials, resources, or energy used to achieve a goal. Accuracy and precision, along with effectiveness, and efficiency can be a synergetic approach to forecasting and problem-solving and each of these elements is linked to the others, so any failure in one affects all of them and will reduce the quality of the prediction.
Here is a story you might like:
The article you have just read is an excerpt from my Module on Urban Prepping in my online Course “The Self Improvement Lifestyle”. Join our Self-Improvement Community at…
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Author: Lewis Harrison is a professional futurist, and the creator of the Ask Lewis Mentoring Method as well as HAGT — Harrison’s Applied Game Theory. He and is the Executive Director of the International Association of Healing Professionals an educational organization that offers programs around the world in Intentional Living. He is also Independent Scholar and a Results-Oriented Success Coach, with a passion for knowledge, personal development, self-improvement, creativity, innovation, and problem-solving. You can read all of his Medium stories at [email protected].
For a decade, Lewis was the host of a humor-based Q & A talk show on NPR (National Public Radio) affiliated WIOX FM in NY.
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