City Hoppers Company - Report Example

Statistical report Name: Course: Tutor: Date: Table of Contents Table of Contents 1 Introduction 2 Ratio Pie Chart 2 Accumulative Ratios Analysis 5 Pareto Chart 6 Data Collection 8 The control charts 10 Root cause analysis 13 Conclusion 13 Bibliography 15 Introduction United Arab Emirates is one of the regions of the world and has big schools within its environs. Young children schooling in those schools were to be picked every morning and taken to their various schools. City Hoppers is a company that has been assigned with this duty. Currently, they need to improve their services to avoid lateness and other vices that may affect the performance of its clients. In addition, the company is opting to undergo a number of changes since the current market is actually changing and is turning out to be more competitive. A company which does not embrace change ill obviously die (Crwaley, 2011). The organization has divided its buses to eight stations. Out of the 8 stations 40 buses in the 8stations 40 cases of lateness were reported t have reached their various paces of work late to different schools. At the beginning of the year, as part of their review on performances of each of the eight stations separately. The regions that were analyzed are identified as Western, Eastern, Southern, Northern, Dubai, Section 13, Section 44 and Section 46. Out of all this are allocated with quality managers who take charge of each section. The company is decentralized but quality is observed as one. The management decided to undertake a survey on the lateness which had been reported by parents that their children came late both to school and to their homes (Johnson & Bhattacharyya, 2009). Ratio Pie Chart The first step was to find their ratios on a pie chart Figure 1 Station Number of lateness Northern 4 Southern 8 Western 6 Eastern 10 Dubai 4 Section 13 3 Section 44 2 Section 46 3 Total 40 The figure above is a pie that illustrates the distribution of busses of city hopper among the 8 stations as at January 2012. It is clearly illustrated that Eastern station has the largest number of buses and is represented by 25% being the leading in the distribution chart. This can be learned there are many children in the region as they have many buses. The southern station comes second with 20%. The other stations have lower percentages and can be arranged in an ascending order as Western (15%), Dubai (10%), Northern (10%), Section 46 (8%), section 13 (7%), and Section 44 comes last with 5% of the total buses that were distributed to the eight stations (Jaisingh, 2000). Accumulative Ratios Analysis Figure ii Buses lateness (January 2012) Station Number of lateness Percent of lateness distribution Accumulative Percent Northern 4 10% 10% Southern 8 20% 30% Western 6 15% 45% Eastern 10 25% 70% Dubai 4 10% 80% Section 13 3 7% 87% Section 44 2 5% 93% Section 46 3 7% 100% Total 40 100% 100% In the figure ii illustrate a table of data that were collected as per the bus distribution to the eight stations. It also gives cumulative percentages. Pareto Chart Figure iii Pareto Chart for cars that delay in their services and that complaint were launched by parents and teachers. As per the chart above, Eastern station has appears to be a good study media, in determining the causes that made all the buses that were reported to be late seemed to have increased to 40 thus making the clients to be dissatisfied as quality was deteriorating. In order to come up with impressive results through daily practical work with the customers, the duration that is taken on the road should be reduced so that the time which will spent in general will be shorter. This concept is attached to arrival time. For bus drivers, arrival time is the time that the time picks a child at home to the time that it offers the child to the authorities by all the eight stations (Plunkett, 2006). In addition, it is the time that the same buses go to the respective schools, pick up the children and deliver them home in the evening. The arrival time is measured by the number of minutes that each bus takes right after picking children to the time they alight at the school compound. On the first the buses should start early at their various stations in order to avoid the jam which may be the main causer of lateness of buses. Data Collection The service managers who are in charge of quality at City Hopper Company conducted a thorough survey at Eastern station so as to come up with proper reasons that made such huge lateness of pupils both to school and to their homes from schools. The reasons that will be collected will assist formulating long lasting solutions to the lateness. The first move was data collection of Eastern station, they were then divided into two sections and named X and Y. group A represented lateness of buses of the stations when taking the children to school and section B represents lateness recorded when returning children to their parents. According to the data that was earlier presented, Eastern station contributes 25% of the total lateness recorded by City Hoppers of the eight stations which was done in January 2012. The represents 10 trips that were made were late for the groups X and Y. Percentage of late trips that were made for the two regions The figure above gives an illustration on the percentage lateness for the two identified regions X and Y. As illustrated in the pie chart, above, region X had the most trips that were late with a percentage of 70% unlike region Y which had 30% of the total trips that were recorded to have been late during that period of time. In the actual sense, region X had made 7 late trips while Y had made 3 late trips. The data of the two regions will be discussed in detail with the aid of tables as illustrated below. A sample of 16 buses will be focused and the time that will be required of them in order to reach at their destination without being late. These tables are the core data that will lead to further diagrams in order to help assess the performance and to determine key processes that require some attention (Klugh, 2007). Region X Buses number and the time expected of them January 2012 Bus No. Time needed(Min.) Bus No. Time needed(Min.) 1 47 9 43 2 51 10 42 3 54 11 50 4 47 12 45 5 53 13 39 6 53 14 48 7 51 15 54 8 42 16 46 The data above is a summary of number of buses that has been allocated to region X and the time needed of them to reach their destinations without being late. Region Y Buses number and the time expected of them January 2012 Bus No. Time needed (Min.) Bus No. Time needed (Min.) 1 21 9 17 2 29 10 19 3 22 11 31 4 28 12 26 5 33 13 30 6 27 14 25 7 34 15 24 8 32 16 23 The table above illustrates the number of buses that have been allocated to region Y and the time that is required of them to reach their destinations without being late. The control charts The control charts that were used are X-bar chart, the reason is that the data in place are variables not an attribute, also, this chart used to monitor the condition of continuous variable process. To establish a control chart, values of the sample mean standard deviation and upper control limits should be calculated first. In determining a lower control limits it should be that which is relevant to this type of data because the lower time is better for arrival time. So we will determine a value of zero as a bottom line. In addition, we can determine other values such as warning lines be more accurate in determining the areas of defect. Referring to the data given in the tables above, values as sample mean, standard deviation, UCL and UWL calculated and plotted at the control charts below. As for region (X), mean were 47, standard deviation 4.7. UCL was calculated by referring to the 3 sigma rule, value of its equals to 44 minutes. UWL was calculated be assuming 2 sigma and equals to 50. The control chart above is an illustration of region X These values plotted at the control chart above and clearly there were eight values which are out of control call numbers 51, 54, 53, . Those that exceeded the warning limit were 9 values; those that exceeded control as listed above and 46. Focusing on region Y, another 16 sample were chosen as shown in table below. Another 16 have been selected as shown above. The mean for region Y was 26 and standard deviation 5.08. UCL was calculated by referring to the 2 sigma rule, value of its equals to 24 minutes. UWL was calculated be assuming 2 sigma and equals to 28. . As illustrated in the control chart above, we realize that there are seven points which are out of control which are 29, 33, and 34. After careful study for both charts and the data within, there is several points which exceeding the upper control limits, a total of 15 points out of a sample 32, which indicate that the process is at average. 46.9% of the samples exceeded the statistical control limit; this percentage which is 15/32 for each of the regions can not meet the needed requirements in all the contracted schools. This has therefore called for a further investigation to adjust to the process. Therefore a fish point diagram is considered for further examine the problem. Root cause analysis Despite analyzing the control charts, solutions were not reached. City Hopper went ahead to call for a meeting in order to discuss the causes of the lateness which has lead to many parents complaining. The meeting is aimed at reaching on goals that will satisfy the customer. Traffic overloads poor training Long distance lack of attitude Bad weather failing to report to work Misunderstanding on time mechanical failure conflicts between the parent and driver vehicle accident New places that maybe far insufficient fuel Conclusion Buses have been analyzed on the likelihood of what actually made it to be late in ferrying children to their various destinations. The graphs and charts have been used and major cause has been found out. The organization should ensure that they develop a system of communication that is effective to all the staff of its organization. Regions with poor terrain and poor climatic conditions, time can be adjusted so that they reach to school early. Bibliography Crwaley, MJ 2011, Statistics: An Itroduction Using R, John Wiley & Sons. Damned lies and statistics: Untanling Numbers from the media, Politicians, and Activities 2001, Damned lies and statistics: untangling numbers from the media, politicians, and activists, reprint edn, University of California. Jaisingh, LR 2000, Statistical for the utterly confused, illustrated edn, McGraw-Hill Professional. Johnson, RA & Bhattacharyya, GK 2009, Statistics: Principles and Methods, 6th edn, John Wiley & Sons. Klugh, HE 2007, Statistics: the essentials for research, 2nd edn, Wiley. Plunkett, JW 2006, Plunkett's outsourcing and offshoring Industry Almanac 2007 (E-book): Outsourcing and Offshoring Industry Market Research Statistics, Trends and Leadind Companies, Plunkett Research, Ltd. Read More

Accumulative Ratios Analysis Figure ii Buses lateness (January 2012) Station Number of lateness Percent of lateness distribution Accumulative Percent Northern 4 10% 10% Southern 8 20% 30% Western 6 15% 45% Eastern 10 25% 70% Dubai 4 10% 80% Section 13 3 7% 87% Section 44 2 5% 93% Section 46 3 7% 100% Total 40 100% 100% In the figure ii illustrate a table of data that were collected as per the bus distribution to the eight stations. It also gives cumulative percentages. Pareto Chart Figure iii Pareto Chart for cars that delay in their services and that complaint were launched by parents and teachers.

As per the chart above, Eastern station has appears to be a good study media, in determining the causes that made all the buses that were reported to be late seemed to have increased to 40 thus making the clients to be dissatisfied as quality was deteriorating. In order to come up with impressive results through daily practical work with the customers, the duration that is taken on the road should be reduced so that the time which will spent in general will be shorter. This concept is attached to arrival time.

For bus drivers, arrival time is the time that the time picks a child at home to the time that it offers the child to the authorities by all the eight stations (Plunkett, 2006). In addition, it is the time that the same buses go to the respective schools, pick up the children and deliver them home in the evening. The arrival time is measured by the number of minutes that each bus takes right after picking children to the time they alight at the school compound. On the first the buses should start early at their various stations in order to avoid the jam which may be the main causer of lateness of buses.

Data Collection The service managers who are in charge of quality at City Hopper Company conducted a thorough survey at Eastern station so as to come up with proper reasons that made such huge lateness of pupils both to school and to their homes from schools. The reasons that will be collected will assist formulating long lasting solutions to the lateness. The first move was data collection of Eastern station, they were then divided into two sections and named X and Y. group A represented lateness of buses of the stations when taking the children to school and section B represents lateness recorded when returning children to their parents.

According to the data that was earlier presented, Eastern station contributes 25% of the total lateness recorded by City Hoppers of the eight stations which was done in January 2012. The represents 10 trips that were made were late for the groups X and Y. Percentage of late trips that were made for the two regions The figure above gives an illustration on the percentage lateness for the two identified regions X and Y. As illustrated in the pie chart, above, region X had the most trips that were late with a percentage of 70% unlike region Y which had 30% of the total trips that were recorded to have been late during that period of time.

In the actual sense, region X had made 7 late trips while Y had made 3 late trips. The data of the two regions will be discussed in detail with the aid of tables as illustrated below. A sample of 16 buses will be focused and the time that will be required of them in order to reach at their destination without being late. These tables are the core data that will lead to further diagrams in order to help assess the performance and to determine key processes that require some attention (Klugh, 2007).

Region X Buses number and the time expected of them January 2012 Bus No. Time needed(Min.) Bus No. Time needed(Min.) 1 47 9 43 2 51 10 42 3 54 11 50 4 47 12 45 5 53 13 39 6 53 14 48 7 51 15 54 8 42 16 46 The data above is a summary of number of buses that has been allocated to region X and the time needed of them to reach their destinations without being late. Region Y Buses number and the time expected of them January 2012 Bus No. Time needed (Min.) Bus No.

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