Instructions ILRHR583: Applied Predictive Analytics in HR ILR School, Cornell University Applied Predictive Analytics in HR Course Project Course Project Overview: For the course project, you will be...

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Instructions ILRHR583: Applied Predictive Analytics in HR ILR School, Cornell University Applied Predictive Analytics in HR Course Project Course Project Overview: For the course project, you will be asked to analyze an organization's workforce data in the four key areas of the framework: talent acquisition, diversity, engagement, and turnover. In Part Four, you will create a PowerPoint deck (no more than five slides) that outlines your findings and recommendations for senior leadership about the organization's overall workforce health. About the Data: You will be working with quarterly data from 30 different locations of a medium-sized organization. The data contains information for each unit for each of the last six quarters. Each column contains a header label that identifies which data belongs to a given year and quarter. For example, PYQ1 means Previous Year, Quarter 1 and CYQ2 means Current Year, Quarter 2. The Unit ID is the unique identifier for each location. There are four sets of data: talent acquisition, diversity, engagement, and turnover data. Part One: Analyzing Talent Acquisition Data In this part of the course project, you will focus on the talent acquisition. The data provided for talent below shows offer-acceptance rate information for each of the units. This metric represents the percentage of offers that job candidates accepted in a given quarter. Use the Part One Talent Acquisition tab to examine the data and complete the accompanying questions. Part Two: Analyzing Diversity Data In this part of the course project, you will evaluate the organization's progress in the area of diversity by examining one key metric: the percentage of female employees in each of the organization's 30 locations. Use the Part Two Diversity Data tab to examine the data and complete the accompanying questions. Part Three: Evaluating Employee Engagement Data In this part of the course project, you will evaluate the organization's progress in the area of engagement by examining quarterly engagement data across the organization's 30 locations. Below you will see average employee engagement scores from a quarterly survey given to all associates. The scores have been averaged across survey questions and across employees, and higher scores indicate higher engagement. Use the Part Three Engagement Data tab to examine the data and complete the accompanying questions. Part Four: Assessing Turnover and Retention Data (and Preparing a Final Report) This final part of the course project will be completed in two parts. In Part A, you will evaluate the organization's progress in the area of turnover by examining the voluntary turnover rate across the organization's 30 locations. Use the Part Four Turnover Data Tab to examine the data and complete the accompanying questions. In Part B, you will create a PowerPoint that illustrates your findings for the four areas of HR you have analyzed. Use the instructions below to complete Part B. Part B: Final Report The goal of the PowerPoint presentation is to tell a story regarding the key insights from the data. You should avoid simply “handing over” the data or results. You want to add narrative to your slides and use visuals drawn from the data/analysis to help you make your points. You are not expected to use advanced statistical modeling; at this point, the organization just wants to know answers to a few key questions: 1.    How is the organization performing in the four areas? 2.    How does the current quarter look compared to historical data? 3.    Are there trends (upward or downward) that are encouraging or concerning? 4.    What next steps should the organization take? Remember that you should use no more than five slides to present your findings and recommendations. Be sure to include data visualizations to help communicate the findings. Offer a point of view and ensure that you recommend next steps for the organization. Copyright © 2019 eCornell. All rights reserved. All other copyrights, trademarks, trade names, and logos are the sole property of their respective owners. Part One Talent Acquisition Unit IDPYQ1_PYQ2_PYQ3_PYQ4_CYQ1_CYQ2_ OfferAcceptOfferAcceptOfferAcceptOfferAcceptOfferAcceptOfferAccept 20510.580.50.630.480.50.5 26560.580.580.60.540.570.49 28680.590.740.530.490.420.43 36100.60.610.540.450.570.49 36880.540.590.560.50.540.57 37870.540.570.530.630.580.44 40200.510.580.580.470.630.47 41620.450.60.610.560.480.55 44610.620.560.570.50.560.55 46630.580.610.510.550.610.49 47890.610.580.510.470.530.51 48850.730.480.580.710.520.5 49190.530.560.660.60.490.53 52090.630.490.590.490.520.48 57030.610.560.510.520.490.49 62710.70.550.570.490.50.47 70240.520.650.550.550.570.45 71180.670.580.570.60.480.52 72000.540.510.560.430.580.44 76960.590.570.590.550.540.47 78550.690.460.60.570.570.41 83690.630.520.560.490.530.53 84180.750.570.580.580.430.49 89120.550.590.580.640.520.52 89250.670.590.580.560.640.49 89580.60.710.610.530.580.47 90130.510.550.590.620.50.45 90930.520.610.620.560.540.5 91480.450.50.540.470.410.43 99680.390.430.390.450.380.37 1. What does the data show over time? 2. Is the organization trending in the right direction? 3. Can you forecast or predict what might happen, given historical trends? 4. What are the interesting trends/findings overall? 5. What are the key insights? 6. Are there areas of opportunity/concern? 7. Are there specific locations that are performing well or that need attention? What recommendations do you have for further analysis, action steps, change, etc.? 8. What might the organization do to better manage its investments in human resources with regard to talent acquisition? Part Two Diversity Data Unit IDPYQ1_PctFemPYQ2_PctFemPYQ3_PctFemPYQ4_PctFemCYQ1_PctFemCYQ2_PctFem 20510.390.440.490.350.410.42 26560.360.470.350.390.440.5 28680.410.440.420.480.420.46 36100.330.440.370.430.350.49 36880.320.380.450.410.580.43 37870.410.430.430.510.370.47 40200.390.430.450.470.40.43 41620.40.530.420.470.350.46 44610.320.470.420.450.380.4 46630.480.480.510.490.40.4 47890.370.430.430.290.370.43 48850.350.420.390.460.520.39 49190.460.430.380.390.40.48 52090.40.280.470.460.410.44 57030.340.410.450.330.470.46 62710.450.380.410.40.380.42 70240.480.420.40.360.510.5 71180.340.310.370.450.50.45 72000.420.470.510.490.410.42 76960.350.360.430.550.390.45 78550.380.430.470.350.460.42 83690.310.410.480.390.430.47 84180.30.430.390.430.340.5 89120.360.560.390.350.440.41 89250.410.370.420.50.50.49 89580.410.370.410.370.460.5 90130.360.430.550.50.520.52 90930.410.440.30.450.460.49 91480.410.470.350.380.520.41 99680.360.410.370.460.380.48 1. What does the data show over time? 2. Is the organization trending in the right direction? 3. Can you forecast or predict what might happen, given historical trends? 4. What are the interesting trends/findings overall? 5. What are the key insights? 6. Are there areas of opportunity/concern? 7. Are there specific locations that are performing well or that need attention? What recommendations do you have for further analysis, action steps, change, etc.? 8. What might the organization do to better manage its investments in human resources with regard to diversity? Part Three Engagement Data Unit IDPYQ1_PYQ2_PYQ3_PYQ4_CYQ1_CYQ2_ EngageEngageEngageEngageEngageEngage 20513.833.623.363.473.213.12 26563.284.163.884.24.34.06 28683.3643.313.613.764.33 36102.844.323.634.424.54.24 36883.483.543.283.793.244.03 37873.593.323.433.023.493.13 40203.374.033.733.673.894.05 41623.023.713.733.643.653.57 44613.682.993.483.383.944.03 46632.873.584.134.1444.31 47893.563.653.923.543.543.7 48853.934.373.733.674.113.32 49193.963.673.483.623.313.37 52093.073.93.484.014.163.8 57033.534.073.793.154.143.92 62712.93.723.953.563.513.29 70243.653.13.653.314.094.26 71184.254.284.624.864.774.73 72003.463.183.352.94.423.14 76963.743.33.253.783.453.66 78553.684.144.14.123.823.46 83692.742.862.52.832.832.75 84183.373.493.074.083.933.72 89123.613.734.073.653.673.89 89253.013.153.174.114.063.55 89583.973.474.164.393.353.53 90133.523.583.313.133.874.53 90933.44.244.24.363.913.55 91483.283.693.423.383.733.47 99684.664.324.54.233.943.25 1. What does the data show over time? 2. Is the organization trending in the right direction? 3. Can you forecast or predict what might happen, given historical trends? 4. What are the interesting trends/findings overall? 5. What are the key insights? 6. Are there areas of opportunity/concern? 7. Are there specific locations that are performing well or that need attention? What recommendations do you have for further analysis, action steps, change, etc.? 8. What might the organization do to better manage its investments in human resources with regard to engagement? Part Four Turnover Data PPYQ1_VolTurnPYQ2_VolTurnPYQ3_VolTurnPYQ4_VolTurnCYQ1_VolTurnCYQ2_VolTurn 205118.30%23.50%33.70%24.70%25.30%33.20% 265625.50%26.60%28.40%21.30%35.40%28.60% 286817.50%12.40%11.40%25.30%26.60%34.40% 361023.60%27.20%26.00%21.70%27.10%30.50% 368814.90%19.50%27.60%24.10%19.20%27.00% 378728.60%32.60%26.50%17.10%21.50%27.10% 402024.00%33.70%39.30%29.90%20.90%26.80% 416248.70%47.70%53.60%53.10%64.90%59.10% 446128.40%24.00%23.00%26.40%25.70%22.70% 466322.30%11.20%18.40%32.90%17.40%34.10% 478918.70%22.20%25.60%29.40%38.00%28.80% 488525.60%29.30%36.40%39.10%29.70%35.90% 491918.60%24.10%15.80%20.80%21.10%20.90% 52097.40%16.40%29.70%27.20%22.50%15.50% 570316.50%11.60%23.80%38.80%36.40%27.80% 627131.90%23.60%21.10%28.90%38.60%23.70% 702427.60%23.10%40.90%23.80%38.90%30.40% 711821.60%14.50%23.50%34.70%30.80%28.90% 720017.30%20.10%15.70%31.10%34.20%44.20% 769621.80%30.10%29.20%27.20%39.20%34.00% 785526.60%26.50%14.60%33.80%22.70%38.60% 836928.00%20.90%20.00%16.00%27.40%29.20% 841827.20%17.40%26.40%26.40%32.50%29.60% 891217.30%14.30%27.00%21.60%41.50%23.60% 892556.60%60.50%62.70%59.10%45.50%45.70% 895827.40%22.00%37.90%23.00%47.00%37.40% 901320.70%26.50%17.80%34.40%20.00%28.20% 909312.60%25.00%14.40%20.60%12.80%22.40% 914810.00%11.10%24.60%17.80%21.10%39.60% 996819.20%29.30%29.20%22.90%29.10%28.00% 1. What does the data show over time? 2. Is the organization trending in the right direction? 3. Can you forecast or predict what might happen, given historical trends? 4. What are the interesting trends/findings overall? 5. What are the key insights? 6. Are there areas of opportunity/concern? 7. Are there specific locations that are performing well or that need attention? What recommendations do you have for further analysis, action steps, change, etc.? 8. What might the organization do to better manage its investments in human resources with regard to turnover? ILRHR583: Applied Predictive Analytics in HR ILRHR583:AppliedPredictive
Answered Same DayFeb 07, 2021

Answer To: Instructions ILRHR583: Applied Predictive Analytics in HR ILR School, Cornell University Applied...

Kishor answered on Feb 09 2021
132 Votes
The power of PREDICTIVE ANALYTICS to enhance organizational performance.
Definition
Definition
We can define Predictive analytics as to the method that is data-driven and goal-focused to study all processes, functions, challenges, and opportunities in the workplace to elevate the value and achieve sustainable organization.             
Benefits to the company:-
Enhanced business turnover of the company.
The hiring process will be more smooth.
Aimed at the retention and attrition of the employees.
Risk Management
Predicting talent for improvement of the organization.
In...
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