Components of Project Management and Stakeholder Management
There are several components of project management that encompass the spectrum of project management. Right from the initial setting up of the project to the closure, each phase brings a new set of challenges and components to the art of project management. Specifically, the project manager has to manage the team and take bottom-line responsibility […]
Robot Advisors in Asia
The integration of cutting-edge technology with financial services has resulted in several innovative methods and tools which use sophisticated technology to serve potential clients better. One such innovation in financial services is the use of Robot Advisors or Automated Software also known as Bots to connect retail customers with the financial institutions. Worldwide, there has […]
Selecting the Correct Hypothesis Test
Hypothesis testing is a very detailed subject. Understanding how to correctly conduct these tests is beyond the scope of this manual or the Six Sigma methodology itself. However, since the Six Sigma project team is expected to be applying these tests to uncover facts and these facts will then be used to base decisions on, […]
Database Concepts and its Application in HRIS
Information Technology is the application of computers and techniques to restore retrieve and manipulate data often within an organization. To facilitate the functioning of HR and make it more proactive, IT and HR have been merged to form HRIS. In short, one can describe HRIS as an online solution for the entry, tracking of data, […]
Japanese View on Business Process Management
While Fredrick Taylor’s scientific management had help create huge American corporations that were quick to adopt the viewpoint, the 1970’s saw the emergence of Japanese corporations. These corporations were very small at the end of World War-2 when Japan had been economically devastated. However within two decades, a group of Japanese companies completely turned the […]
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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