QNT 351 Week 2 Team Assignment Data Collection Set 1
QNT 351 Week 2 Team Assignment Data Collection Set 1
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Date Created: 11/14/15
Data Collection: Ballard Integrated Managed Services, Inc. QNT/351 Date Name Data Collection: Ballard Integrated Managed Services, Inc. Overview The Ballard Integrated Managed Services Inc. (BIMS) provides large organizations and businesses with food and housekeeping services. BIMS has 452 full and parttime employees and upper management employees. BIMS has held a turnover rate of 55 to 60%, however in the past four months the company’s turnover rate has increased to 64%. The management team at BIMS failed in obtaining the reason for the increased turnover rate, motivation of company’s employees to decline, performance levels reduce, and the use of employee sick leave to increase. These changes in employee behavior reduced BIMS customer satisfactory and increased the number of client complaints. Data Collection Instrument Team A created a survey instrument that would permit BIMS employees to voice his or her opinions on his or her personal experiences working at BIMS. Team A will ask employee’s various questions about his or her position at BIMS and the outlook and rapport he or she has with his or her immediate supervisor. Team A’s survey will also include demographic questions. These questions will identify the position each employee currently works and the length of time of employment at BIMS. Team A believes that BIMS increase in turnover rate is consistent and associated with employee issues concerning communications, low wages, and extended hours of work. Survey is the data collection instrument used for the collecting data. This instrument will assist in obtaining information concerning employee opinions, attitude, and job satisfaction. Types of Data The types of data contained within the BIMS Employee Survey, presented by Ballard Integrated Managed Services, Inc., contains both quantitative and qualitative data. BIMS performed the accumulation of the data by providing employees with a written survey to attain the required information. The survey first established to have 10 of the first questions answered in the quantitative arrangement. The instructions notify the employees to complete the questions through circling the closest number to their opinion. BIMS staff prepared for employees to circle the numbers from one through five to indicate the positivity and negativity regarding each question, number one signifies extremely negative and number five signifies very positive. The extra questions from “A thorough D” are of the qualitative form except for question B. The questions concentrate on years of service, their divisions of work, gender, and employee level. As soon as the employees respond to questions A thorough D the employees translate to the quantitative form for coding and access. Level of Measurement The BIMS used the ordinal, nominal, and interval levels of measurement in their opening survey for employees along with the exit interview data collection procedure. BIMS classified and calculated the numbers of observations for the measurements at the nominal level. These qualitative variables are in no specific order to the labels assigned (Lind, Marchal & Wathen, 2011). The utilization of ordinal levels of measurement by BIMS was primarily to categorize the residual data through groups of labels that have been assigned relative values. The illustration of the ordinal measurement displays an organized relationship among the numbers of variables. The amount of differences that need to be distinguished between the measurements is not essentially the same along the scale (Lind, Marchal & Wathen, 2011). To estimate the employee’s length of service with the organization, the calculation used the interval level of measurement for both of the surveys given. This type of measurement categorizes, orders, and identifies that the distances among each interval on thescale remain equal along thescale from a low number to a high number of months of service. BIMS changed each employee’s years and months of service into just total months (Lind, Marchal & Wathen, 2011). Code of Data To define the nominal, ordinal, and interval data the staff at BIMS used numeric codes as described in Appendix A. Team A, detected that BIMS organized and implemented assesses to evaluate the procedures. The management team used descriptive statistics in presenting a precise profile of the data. To describe the middle of group scores or ratings BIMS included averages, mean, median, and mode, in which described the middle of group scores or ratings. The ordinal measurements will assist BIMS staff in determining the central tendency by using the most common value known as the mode, or the middle ranking value, median. Team A observed that BIMS staff used descriptive statistics to disclose the results of the employee survey (Lind, Marchal & Wathen, 2011). Question 1 2 3 4 5 6 7 8 9 10 A B C D Mean 2.82 2.74 2.81 2.79 2.88 2.06 2.87 2.67 2.22 2.67 n/a 54 n/a n/a Median 3 2.5 3 2.5 3 2 3 2 2 2 2 2 2 2 Mode 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Question 1 4 6 8 Food Negative Positive Negative Negative mean=2.79 mean=3 mean=2.03 mean=2.42 median=2 median=3 median=2 median=2 mode=2 mode=5 mode=2 mode=2 House Negative Negative Negative Positive Keeping mean=2.83 mean=2.83 mean=2.17 mean=2.97 median=3 median=2 median=2 median=3 mode=2 mode=2 mode=2 mode=5 Maintenance Positive Positive Negative Negative mean=3.13 mean=2.75 mean=1.75 mean=2.25 median=3 median=3.5 median=2 median=2 mode=3 mode=4 mode=2 mode=5 Data Scrub To eliminate input errors in the sample data it is necessary for BIMS management to perform a data scrub. Input errors often occur when management makes internal decisions and enters a zero for questions left blank in the data. Team A has observed several input errors within the BIMS sample data consisting of 17 zeros within question from one through 10 and six zeros in the demographic questions. In addition Team A has observed a keystroke error in questions one through 10.This error resulted in six invalid values of ‘6’ present in questions one through 10. Survey responses for questions one through 10 valued at one through five. These values consist of ‘1’ demonstrating the value of ‘Very Negative’ and ‘5’ demonstrating the value of ‘Very Positive’ (University of Phoenix, 2011, BIMS, Inc. Part I) Despite the data scrub, figures changed only slightly from the original calculations and the integrity of the project should remain intact. 1 2 3 4 5 6 7 8 9 10 A B C D Mean 2.84 2.84 2.84 2.88 2.92 2.15 2.87 2.80 2.22 2.72 n/a 54 n/a n/a Median 3 2.5 3 2.5 3 2 3 2 2 2 2 2 2 2 Mode 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Final Analysis The staff at BIMS Inc. recently presented a survey to the company’s 449 employees on a voluntary basis. The survey team conducted the survey to obtain a consensus of the company’s employee’s perception on training, shifts, work conditions, fair treatment, compensation, job security, and company communications. The company also incorporated a small amount of demographics for filtering. The survey team at BIMS conducted the survey to present management with a reliable statistical analysis and to depict the main components of raw data and resolve company concerns about employee morale. The team at BIMS Inc. will use descriptive and frequency techniques used in statistical computation of the survey at a later date. This procedure will help to identify the correlation with the set of data obtained. Even though the survey method was not effective it produced a below average of 78 responses out of 449 employee in which consist of a total response rate of 17.3 % (University of Phoenix, 2011, BIMS, Inc. Part I). References: American Society for Quality, “Survey” retrieved October 2, 2012 from: http://asq.org/learnaboutquality/datacollectionanalysistools/overview/survey.html Lind, D. A., Marchal, W. G., and Wathen, S. A. (2011). Basic statistics for business and economics (7th ed.). New York, NY: McGrawHill/Irwin. University of Phoenix. (2011). Week Two supplement: Ballard Integrated Managed Services, Inc. Part 1. Retrieved from University of Phoenix, QNT/351 – Quantitative Analysis for Business course website. University of Phoenix. (2011). Week Two supplement: Ballard Integrated Managed Services, Inc. Part 2. Retrieved from University of Phoenix, QNT/351 – Quantitative Analysis for Business course website. Jens, S. (2012). Why Is It Important to Distinguish Between Data and the Interpretation of the Data? Retrieved from: http://ehow.com/facts_7499601_importantbetweendata interpretationdata.html
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