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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.

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    QSO 510 Absent causes by ill health Analyze the impact of ill health on employee absenteeism, distinguishing between culpable and non - culpable absenteeism. Use statistical data to support your analysis and discuss how absenteeism due to ill health affects productivity and customer satisfaction in o rganizations. 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 her company. Thus, if the health both mental and physical of a person is not good he will not go to the office. It will cause a huge loss to the company as the essence of marketing and business is the 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 employers across 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 of monetary loss and efficiency and effectiveness of work and customer satisfaction. People misses work for variety of reasons and even without reason many times. When they do not attend office with a real reason it is called non - culpable absenteeism and whe n they do not have any real reason to not go for their work than it is called culpable absenteeism. Here, we are dealing with absent cases caused by ill health 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 by various health issues including Alzheimer's and depressions. The pattern of lifestyle and the social 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 the workload are easily becom e the non - regular employ. This topic is even more significant than it looks 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 increase the graph of Absenteeism. Illness causes bed rest, appointment with t he physician or doctor and even injuries. These all turn to decrease the productivity of the company and also the utility driven from each employee. The major contributing factor for the illness is the season. For example, in the cold and flu season less attendance is marked in the registers of the company. The data indicates that 98 ,000 employees employed in 12 most important occupation in the U.S. and came to conclusion that 77% of the people who fits into the survey definition are facing serious health disorders such as Cancer, Asthma, diabetes and depressions. The statistics also shows that the mental health and depression plays an important role i n the absenteeism. The loss due to absent causes by health issues accounts for low productivity which is around worth 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 stu dies it still needs a firm catastrophic change in perception of the employee so that he or she can boost their mind each morning that this is the job he or she has dreamt for and this is his or her passion Data of a bsent causes by ill health

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    Sex Age Ht Wt Pulse Chol Bmi Medic al problems: 1 = Yes; 0 = No Children? Total absent day s level of risk Male 58 70.8 169.1 68 522 23.8 1 4 22 Med Male 22 66.2 144.2 64 127 23.2 0 2 28 High Male 32 71.7 179.3 88 740 24.6 1 3 37 High Male 31 68.7 175.8 72 49 26.2 1 1 33 High Male 28 67.6 152.6 64 230 23.5 1 2 1 Low Male 46 69.2 166.8 72 316 24.5 1 4 22 Med Male 41 66.5 135 60 590 21.5 1 0 37 High Male 56 67.2 201.5 88 466 31.4 1 4 17 Med Male 20 68.3 175.2 76 121 26.4 0 2 15 Med Male 54 65.6 139 60 578 22.7 0 4 20 Med Male 17 63 156.3 96 78 27.8 1 0 12 Med Male 52 73.1 191.1 56 250 25.2 0 4 14 Med Male 25 67.6 151.3 64 265 23.3 1 1 16 Med Male 29 68 209.4 60 273 31.9 1 2 11 Med Male 17 71 237.1 64 272 33.1 1 0 2 Low Male 41 61.3 176.7 84 972 33.2 1 4 10 Med Male 52 76.2 220.6 76 75 26.7 1 0 39 High Male 32 66.3 166.1 84 138 26.6 1 5 2 Low Male 20 69.7 137.4 88 139 19.9 0 1 16 Med Male 20 65.4 164.2 72 638 27.1 0 1 15 Med Male 29 70 162.4 56 613 23.4 0 4 20 Med Male 18 62.9 151.8 68 762 27 1 0 6 Low Male 26 68.5 144.1 64 303 21.6 1 3 19 Med Male 33 68.3 204.6 60 690 30.9 1 2 10 Med Male 55 69.4 193.8 68 31 28.3 1 1 25 Med Male 53 69.2 172.9 60 189 25.5 1 3 22 Med Male 28 68 161.9 60 957 24.6 1 3 6 Low Male 28 71.9 174.8 56 339 23.8 0 1 38 High Male 37 66.1 169.8 84 416 27.4 1 1 26 Med Male 40 72.4 213.3 72 120 28.7 1 4 20 Med Male 33 73 198 84 702 26.2 0 4 16 Med Male 26 68 173.3 88 1252 26.4 0 1 4 Low Male 53 68.7 214.5 56 288 32.1 1 5 31 High Male 36 70.3 137.1 64 176 19.6 0 5 18 Med Male 34 63.7 119.5 56 277 20.7 1 1 30 High Male 42 71.1 189.1 56 649 26.3 0 3 24 Med Male 18 65.6 164.7 60 113 26.9 1 0 10 Med

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    Male 44 68.3 170.1 64 656 25.6 1 1 1 Low Male 20 66.3 151 72 172 24.2 1 1 8 Low Female 17 64.3 114.8 76 264 19.6 1 1 3 Low Female 32 66.4 149.3 72 181 23.8 1 5 4 Low Female 25 62.3 107.8 88 267 19.6 0 1 13 Med Female 55 62.3 160.1 60 384 29.1 0 0 5 Low Female 27 59.6 127.1 72 98 25.2 1 2 15 Med Female 29 63.6 123.1 68 62 21.4 1 2 21 Med Female 25 59.8 111.7 64 89 27.5 1 1 26 Med Female 41 67.9 218.8 68 531 33.5 1 1 33 High Female 32 61.4 110.2 68 130 20.6 1 0 3 Low Female 31 66.7 188.3 80 175 29.9 0 1 8 Low Female 19 64.8 105.4 76 44 17.7 1 1 20 High Female 19 63.1 136.1 68 8 24 0 1 18 High Female 23 66.7 182.4 72 112 28.9 1 3 50 High Female 40 66.8 238.4 96 462 37.7 1 5 6 Low Female 23 64.7 108.8 72 62 18.3 1 2 28 High Female 27 65.1 119 68 98 19.8 1 1 37 High Female 45 61.9 161.9 72 447 29.8 1 1 21 Med Female 41 64.3 174.1 64 125 29.7 1 1 4 Low Female 56 63.4 181.2 80 318 31.7 1 3 30 High Female 22 60.7 124.3 64 325 23.8 1 2 16 Med Female 57 63.4 255.9 80 600 44.9 0 2 18 Med Female 24 62.6 106.7 76 237 19.2 0 3 20 High Female 37 60.6 149.9 76 309 28.5 1 2 8 Low Female 40 58.6 94.3 80 94 19.3 1 1 4 Low Female 45 60.2 159.7 104 280 31 1 1 24 Med Female 52 67.6 162.8 88 254 25.1 0 3 7 Low Female 31 63.4 130 60 123 22.8 0 0 37 High Female 32 64.1 179.9 76 596 30.9 1 2 4 Low Female 23 62.7 147.8 72 301 26.5 1 2 18 Med Female 23 61.3 112.9 72 223 21.2 1 1 11 Med Female 47 58.2 195.6 88 293 40.6 1 4 35 High Female 36 63.2 124.2 80 146 21.9 1 2 30 High Female 34 60.5 135 60 149 26 0 1 11 Med Female 37 65 141.4 72 149 23.5 1 5 27 Med Female 18 61.8 123.9 88 920 22.8 1 0 10 Med Female 29 68 135.5 88 271 20.7 1 3 4 Low Female 48 67 130.4 124 207 20.5 0 2 1 Low

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