The Economic Implications of Facebook Data Breach
Facebook is one of the most important firms in the American economy. The tech giant is a major employer in the United States. Its actions have a profound economic impact across the globe. This is the reason behind the hefty valuation that Facebook commands. However, this valuation and the entire business model came under siege […]
Non Random Patterns – Part 1
Cyclical Pattern: A cyclical pattern is defined as a predictive situation in which data points increase and decrease the process mean in a manner which is repetitive. While this may sound like a mouthful, we are all intuitively aware of what a cycle means. In the case of control charts, cyclical patterns signify special cause […]
Six Sigma and Quality Management
Six Sigma is a business management strategy which aims at improving the quality of processes by minimizing and eventually removing the errors and variations. The concept of Six Sigma was introduced by Motorola in 1986, but was popularized by Jack Welch who incorporated the strategy in his business processes at General Electric. The concept of […]
How Algorithms Rule our Lives and What Businesses, Consumers, and Citizens can Do
How Algorithms Rule Our Lives and Whether That is Necessarily a Good Thing We live in the Age of the Machine and the Era of the Algorithm. Right from our news feeds on which we depend on to know what’s happening in the world around us that are curated by Algorithms, to the Social Media […]
Is a Pollution Tax Worth it ?
Washington DC has seen several proposals for strange regulations. The latest one of these suggestions is a pollution tax. Many people believe that levying a tax may be the solution to eradicating the problem of climate change gradually. The world in general and Washington DC, in particular, wants to get rid of high levels of […]
The purpose of measurement system is to validate the measurements before they are considered as factual data and used as a basis for decision making. Any experienced Six Sigma executive knows the reality that the measurement system is nowhere nearly as good as you think it is. People who conduct the measurement system analysis for the first time are surprised to find that it is not rare to find measurements that are 30% or more off the mark in the organizations measurement system. Here is a review of the causes that lead to such widespread variations:
People: Probably the single most important cause of measurement system variation is the people involved. If measurements need to be taken repetitively, it becomes a monotonous task and sometimes errors are made. Also, many times employees wilfully avoid work and fudge the measurement numbers. A system where people were entrusted the job of taking measurements is a thing of the past. Quality guru Juran has made it explicit that measurements related to process efficiency must be collected by non-human means.
Equipment: Faulty equipment is another major factor which result in getting inaccurate measurements. It is not uncommon to find machines that are worn out and/or not properly calibrated. This is true particularly at the extreme ends of the operating range of the machine. Regular maintenance and calibration of the machines is essential. If the measurements are critical to the functioning of the process, the latest and the most high tech measurement systems need to be installed. If we get what we measure, we must measure in the best possible way, isn’t it!
Computational Complexity: This reason is closely linked to the human cause of measurement systems error. However, here the error is not caused by negligence or wilful manipulation. Sometimes, complex metrics are designed. However, the design of this metric is not correctly communicated to the concerned people. Hence we get faulty software tools and/or operators with incorrect knowledge.
Lack of Standard Procedures: It is important that the important metrics of the measurement systems be defined. Such a definition should be communicated to every person that needs to know it. The definition must be reached by consensus and the procedure to arrive at the numerical value of the metric must be explicitly stated inside a manual. Failure to do so can lead to different people having different notions about the same metric. Hence, at a systemic level, you could even end up comparing apples to oranges, if you are not careful enough!
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Characteristics of Data – Central Tendency and Dispersion
February 12, 2025
Steps Involved in Conducting a Measurement System Analysis
February 12, 2025
