Criticisms of Globalization: Threats to National Sovereignty
It is not only about Profits Of the many criticisms of globalization, the prominent critique relates to the fact that globalization erodes national sovereignty and takes away the power of governments. By allowing international corporations and multinational businesses to set the economic (and often, the political agenda), critics argue that the nation state becomes irrelevant. […]
Systems Considerations in the Design of HRIS
For implementing any Human Resource Information System (HRIS) project successfully, the system design requirements should be given utmost importance and it must have scope for customizations as per the requirements of the end users. The system should have various inbuilt provisions and be developed by carefully analyzing the end users/customers’ requirements and the technicalities involved […]
Non Random Patterns – Part 2
Shift in the Process: A shift in the process is defined as a pattern in which seven consecutive data points appear on only one side of the mean. Statistical studies have shown that if the number of points on one side of the mean is less than 7 then it is not a non-random pattern […]
Material Handling – Principles, Operations and Equipment
Introduction Raw materials form a critical part of manufacturing as well as service organization. In any organization, a considerable amount of material handling is done in one form or the other. This movement is either done manually or through an automated process. Throughout material handling processes significant safety and health challenges are presented to workers […]
International Businesses and Resistance to their Activities
Global Capital, Local Resistance The previous articles in this module discussed how international businesses expand into overseas markets both for selling their products as well as to extract the resources in mineral rich countries. We discussed how the international expansion of these businesses has to equitable and follow the rules of justice. What happens when […]
Apart from accuracy and precision, there are more factors that determine the soundness of a measurement system. Two of these important factors are as follows:
Resolution: Resolution is the ability to see fine details in a system. This ability also gives the system, the ability to distinguish different readings from one another.
A good example would be that of the system that records late coming employees. If the measurement system designed to monitor employees coming late measures it only in hours i.e. uses the wrong resolution, then any employee who is up to 59 minutes late will appear to be on time. This is because the system will display 0 till the 60th minute is reached. In effect the organization will lose its ability to distinguish between employees coming on time and those that come late.
A good thumb rule is to build an extra decimal place in the system. If you need data up to 2 decimal places, build a system that records data up to 3 decimal places. Wrong resolution can seriously hamper the process and lead to wrong decisions.
Linearity: A system is said to be linear if proportional changes in input measurements produce proportional changes in output measurement. This means that if I know for a fact that an employee coming 10 minutes late would lead to a 2% loss of productivity in his daily output, then the same employee if he comes 30 minutes late should ideally lead to a 6% loss in his daily productivity.
The method used to find out linearity is fairly simple. Any given measurement is considered, the input variables are varied in a controlled manner and the resultant output is recorded. It is essential that at least 10 measurements be taken throughout the possible range of measurement. These points are then charted on a graph and an attempt is made to fit a line through these points. The degree to which all the points lie on this line of best fit is the degree of linearity of a system.
The degree to which the points lie away from the line of best fit is called the bias of the measurement system. For instance, if a machine shows a more accurate measurement at the centre of its operating range than at the upper or lower ends then the equipment is biased.
Common reasons for measurements not being linear are as follows:
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Characteristics of Data – Central Tendency and Dispersion
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Steps Involved in Conducting a Measurement System Analysis
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