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QSO 510 Absent causes by ill health

An assignment analyzing causes of absenteeism due to illness and its impact on operations.

David Rodriguez
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QSO 510Absent causes by ill healthAnalyzethe impact of ill health on employee absenteeism, distinguishing between culpable andnon-culpable absenteeism. Use statistical data to support your analysis and discuss howabsenteeism due to ill health affects productivity and customer satisfaction in organizations.Include a review of factors such as mental health, lifestyle, and seasonal influences.Word Count:1500-2000 words.

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THESIS:Ill health has a positive correlation with the periodicity of absent an person will do in his or hercompany. Thus, if the health both mental and physical of a person is not good he will not go tothe office. It will cause a huge loss to the company as theessence of marketing and business isthe employer’s committed and regular work whose prime goal is the customer satisfaction. Thus,ill health cause a genuine cause for the employee to not to go the office.INTRODUCTION:Absenteeism though most common but also most problematic issues faces by the employersacross the industry and sector. It includes both type of absenteeism culpable and non-culpable.Basically, absenteeism impact on the employers is severe both in terms ofmonetary loss andefficiency and effectiveness of work and customer satisfaction. People misses work for variety ofreasons and even without reason many times. When they do not attend office with a real reason itis called non-culpable absenteeism and when they do not have any real reason to not go for theirwork than it is called culpable absenteeism. Here, we are dealing with absent cases caused by illhealth that is a subpart of non-culpable or innocent absenteeism.This problem is quite significant as it relates to the real day to day lifestyle which are caused byvarious health issues includingAlzheimer'sand depressions. The pattern of lifestyle and thesocial background of the employee decide how much day in a week he or she comes to office.The people who are newly employed, having less morale and does not able to challenge theworkload are easily become the non-regular employ. This topic is even more significant than itlooks as when the company human resource (HR) department or manager does not try to support

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the employ and looks for the solution but takes decision quickly to fire off the employ. Thus,proper analysis of the topic using analytical and statistical tools is absolutely necessary.STATISTICS AS A TOOL FOR ANALYSIS OF ABSENTEEISM:Various research and studies were performed to get into the real problem and its consequences.The most common and simple analysis has shown the health is the prime factor which increasethe graph of Absenteeism. Illness causes bed rest, appointment with the physician or doctor andeven injuries. These all turn to decrease the productivity of the company and also the utilitydriven from each employee.The major contributing factor for the illness is the season. For example, in the cold and fluseason less attendance is marked in the registers ofthe company. The data indicates that 98,000employeesemployed in 12most importantoccupationin the U.S. and came toconclusion that77% of the people who fits into the survey definition are facing serious health disorders such asCancer, Asthma, diabetes and depressions. The statistics also shows that the mental health anddepression plays an important role in the absenteeism.The loss due to absent causes by health issues accounts for low productivity which is aroundworth of $84. This is really a challenging and most difficult task to handle by any company.Though many trends which are evaluated by various studies and case studies it still needs a firmcatastrophic change in perception of the employee so that he or she can boost their mind eachmorning that this is the job he or she has dreamt for and this is his or her passionData of absent causes by ill health

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SexAgeHtWtPulseCholBmiMedicalproblems:1 = Yes;0 = NoChildren?Totalabsentdayslevel of riskMale5870.8169.16852223.81422MedMale2266.2144.26412723.20228HighMale3271.7179.38874024.61337HighMale3168.7175.8724926.21133HighMale2867.6152.66423023.5121LowMale4669.2166.87231624.51422MedMale4166.51356059021.51037HighMale5667.2201.58846631.41417MedMale2068.3175.27612126.40215MedMale5465.61396057822.70420MedMale1763156.3967827.81012MedMale5273.1191.15625025.20414MedMale2567.6151.36426523.31116MedMale2968209.46027331.91211MedMale1771237.16427233.1102LowMale4161.3176.78497233.21410MedMale5276.2220.6767526.71039HighMale3266.3166.18413826.6152LowMale2069.7137.48813919.90116MedMale2065.4164.27263827.10115MedMale2970162.45661323.40420MedMale1862.9151.86876227106LowMale2668.5144.16430321.61319MedMale3368.3204.66069030.91210MedMale5569.4193.8683128.31125MedMale5369.2172.96018925.51322MedMale2868161.96095724.6136LowMale2871.9174.85633923.80138HighMale3766.1169.88441627.41126MedMale4072.4213.37212028.71420MedMale33731988470226.20416MedMale2668173.388125226.4014LowMale5368.7214.55628832.11531HighMale3670.3137.16417619.60518MedMale3463.7119.55627720.71130HighMale4271.1189.15664926.30324MedMale1865.6164.76011326.91010Med

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Male4468.3170.16465625.6111LowMale2066.31517217224.2118LowFemale1764.3114.87626419.6113LowFemale3266.4149.37218123.8154LowFemale2562.3107.88826719.60113MedFemale5562.3160.16038429.1005LowFemale2759.6127.1729825.21215MedFemale2963.6123.1686221.41221MedFemale2559.8111.7648927.51126MedFemale4167.9218.86853133.51133HighFemale3261.4110.26813020.6103LowFemale3166.7188.38017529.9018LowFemale1964.8105.4764417.71120HighFemale1963.1136.1688240118HighFemale2366.7182.47211228.91350HighFemale4066.8238.49646237.7156LowFemale2364.7108.8726218.31228HighFemale2765.1119689819.81137HighFemale4561.9161.97244729.81121MedFemale4164.3174.16412529.7114LowFemale5663.4181.28031831.71330HighFemale2260.7124.36432523.81216MedFemale5763.4255.98060044.90218MedFemale2462.6106.77623719.20320HighFemale3760.6149.97630928.5128LowFemale4058.694.3809419.3114LowFemale4560.2159.7104280311124MedFemale5267.6162.88825425.1037LowFemale3163.41306012322.80037HighFemale3264.1179.97659630.9124LowFemale2362.7147.87230126.51218MedFemale2361.3112.97222321.21111MedFemale4758.2195.68829340.61435HighFemale3663.2124.28014621.91230HighFemale3460.513560149260111MedFemale3765141.47214923.51527MedFemale1861.8123.98892022.81010MedFemale2968135.58827120.7134LowFemale4867130.412420720.5021Low
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Document Details

University
Southern New Hampshire University
Course
QSO 510
Subject
Operations Management

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