Companies face these main issues : • Employees without kids are more likely to leave a job within the next 12 months. • Employees without kids are more likely to leave due to dissatisfaction with benefits. • Employees with kids are more likely to leave due to dissatisfaction with flexible work schedules. MSBA 625: Storytelling with Data (Part Two): Black Team 40
We suggest the following act ctio ions to reduce tu turn rnover: • Companies give employees the ability to work at home via a VPN when needed. • Companies revaluate their benefit packages to make them more comparable to the national average. • Companies examine and self-reflect on the culture and make it more inviting and healthier for employees. MSBA 625: Storytelling with Data (Part Two): Black Team 41
Yellow Team Better Workplaces, Better World (Part Two)
Conceptual Overview Goal Process Conclusions For this assignment we To successfully analyze The average total value of • • • were tasked with the data we were required flexibility and pay benefits examining the relationship to make a certain amount remained consistent between the reported of transformations as well despite differing ratings of importance/value of as rename some column overall satisfaction. benefits and their names which can be seen Flexibility and pay • satisfaction, potentially in the attached excel file. satisfaction seems to drop considering slightly as tenure congruence/discrepancy increases. in the process. It is important to • compensate fairly regardless gender as this is a a very important factor for women especially. MSBA 625: Storytelling with Data (Part Two): Yellow Team 43
The average to total l value lue of f fl flexib ibil ility and pay benefi fits re remain ined co consis istent despit ite diff ifferin ing rati tings of f overall ll sa satis isfactio ion. . MSBA 625: Storytelling with Data (Part Two): Yellow Team 44
Fle Flexib ibil ility ty an and pay ay sati atisfactio ion seems to to dro rop slig ightly ly as as te tenure increases. MSBA 625: Storytelling with Data (Part Two): Yellow Team 45
MSBA 625: Storytelling with Data (Part Two): Yellow Team 46
MSBA 625: Storytelling with Data (Part Two): Yellow Team 47
MSBA 625: Storytelling with Data (Part Two): Yellow Team 48
People le who lea leave th their ir cu current jo job are ofte ften diss issatis isfie ied with ith th the co communic icatio ions th that th they re rece ceiv ive. MSBA 625: Storytelling with Data (Part Two): Yellow Team 49
Some job characteristics, benefits and beliefs correlate stronger with those looking for a new job in the next 12 months more than others MSBA 625: Storytelling with Data (Part Two): Yellow Team 50
There are certain job characteristics, benefits and beliefs that are statistically significant for those that agree or strongly agree with the statement that they are “looking for a new job in the next 12 months” compared to those that responded neutral, disagree, or strongly disagree MSBA 625: Storytelling with Data (Part Two): Yellow Team 51
MSBA 625: Storytelling with Data (Part Two): Yellow Team 52
MSBA 625: Storytelling with Data (Part Two): Yellow Team 53
MSBA 625: Storytelling with Data (Part Two): Yellow Team 54
Recommendations on Retaining Emplo loyees • Improve communication of key events across the organization as well as how each event could affect each employee individually. • To maintain a competitive environment it is necessary to offer equal opportunities for men and women, as women value a competitive workplace more than men. • If employers would like to retain their top talent it may be beneficial to offer to match competing offers from other firms to retain good people. MSBA 625: Storytelling with Data (Part Two): Yellow Team 55
Red Team Better Workplaces, Better World (Part Two)
Data In Insights Data Insights Agenda General Data Trends. Multiple Models. Sentiment Analysis Open Ended Question – Response Analysis Satisfaction Index Estimating job satisfaction for employees based on survey responses. Impact of Salary on Job Satisfaction Understanding one of the major reasons for high attrition rate in Louisville. Conclusions & Recommendations Red Team Summary. MSBA 625: Storytelling with Data (Part Two): Red Team 57
MSBA 625: Storytelling with Data (Part Two): Red Team 58
Data In Insights Stress at Work MSBA 625: Storytelling with Data (Part Two): Red Team 59
Data Insights Comparing Salary per Job role in Louisville to other cities from US Direct comparison of salaries from different cities shows positive salary difference in Louisville for most of the Job Roles MSBA 625: Storytelling with Data (Part Two): Red Team 60
Data Insights Source of Turnover in Labor Market Employees are satisfied with benefits offered MSBA 625: Storytelling with Data (Part Two): Red Team 61
Data Insights Employee Satisfaction per Survey Question MSBA 625: Storytelling with Data (Part Two): Red Team 62
Data Insights Job Satisfaction & Benefits Satisfaction MSBA 625: Storytelling with Data (Part Two): Red Team 63
Data Insights Employee Satisfaction per Survey Question Majority of the work force is below 3 Years suggesting a High Attrition Rate MSBA 625: Storytelling with Data (Part Two): Red Team 64
Sentim iment Analysis Open-Ended Questions Sentiment analysis was performed on responses to the following open-ended questions: Do you have any other comments on leadership, work environment, recognition, and growth opportunities that you • value? Do you have any other comments on the flexibility, pay and benefits that are important to you? • Do you have any other comments on your engagement, stress and balance, and intentions to stay in your current • job? Polarity In sentiment analysis, polarity describes how negative or positive the overall sentiment of the text being analyzed is. Polarity score > 0: indicates the comment contains more positive words/ sentiments Polarity score = 0: indicates the text being analyzed is neutral in wording/ sentiment Polarity score < 0: indicates the text being analyzed contains more negative words/ sentiments Subjectivity In sentiment analysis, subjectivity describes how objective or subjective the overall sentiment of the text being analyzed is. If the subjectivity score is closer to 0, the comment is more objective (factual). If the subjectivity score is closer to 1, the comment is more subjective (opinionated). MSBA 625: Storytelling with Data (Part Two): Red Team 65
Sentim iment Analysis By Job Position MSBA 625: Storytelling with Data (Part Two): Red Team 66
Sentim iment Analysis By Industry MSBA 625: Storytelling with Data (Part Two): Red Team 67
Satis isfaction Sco core Creating a Mathematical Model to quantify the responses
Unders rstandin ing Jo Job Satis isfactio ion Using the responses for these questions a satisfaction score was calculated. MSBA 625: Storytelling with Data (Part Two): Red Team 69
Calc lculatin ing Jo Job Satis isfa factio ion Score Weighted criteria used for calculating satisfaction score. How Important How Satisfied -25 Ver ery Importa tant t 1 -5 Very Dissatisfied 2 -2 3 1 4 2 25 Ver ery Importa tant t 5 5 Very Satisfied
Calc lculatin ing Jo Job Satis isfa factio ion Score Steps used to Calculate Satisfaction Score Calculate Score Average all responses Divide Categories based Avg. all categories per Response per Category on Industry & for this division Job Role MSBA 625: Storytelling with Data (Part Two): Red Team 71 71
Unders rsta tandin ing Im Impact of f Sala lary on Jo Job Satis isfactio ion Cost of living index was used to standardize salary for all job roles in selected cities of the US & compared with each other.
www.bestplaces.net Salary Data from Bureau of Labor Statistics
Conclusions Supervisors & Managers are least satisfied • Executives are most satisfied with their jobs • Job satisfaction varies drastically by • Industry Salaries in Louisville are lower as compared • to other major cities in the region Louisville is more expensive than most of • the major cities in the region Employees are less satisfied with Pay in • Louisville as compared to other categories
Rec ecommendations For Better Granularity of Data Survey • Job Roles to align with US Labor Salary Data • No. of Years in the Job & Organization to include exact number of years & Months Improvements Im Diversify Respondents Majority of respondents from Healthcare & Higher Education Similar Surveys in different Cities Perform similar surveys in other cities in the region to have a better comparison factor
Orange Team Better Workplaces, Better World (Part Two)
Safe work environment Working from Home Pre-COVID-19 Preferences of Health Benefits Louisville Workers Job Security Salary Increment MSBA 625: Storytelling with Data (Part Two): Orange Team 78
Louisville’s COVID -19 19 Tim imeline 3/9 First Louisville Case 3/14 Closure of Most Public Gathering Places 3/16 Closure of Restaurants and Bars 3/18 All Public Facing Business Forced to Close MSBA 625: Storytelling with Data (Part Two): Orange Team 79
US unemployment claims in increase exponentially. MSBA 625: Storytelling with Data (Part Two): Orange Team 80
MSBA 625: Storytelling with Data (Part Two): Orange Team 81
MSBA 625: Storytelling with Data (Part Two): Orange Team 82
MSBA 625: Storytelling with Data (Part Two): Orange Team 83
How has COVID-19 impacted Jefferson County? Source: Kentucky Center For Statistics MSBA 625: Storytelling with Data (Part Two): Orange Team 84
Jefferson County Weekly Unemployment Claims MSBA 625: Storytelling with Data (Part Two): Orange Team 85
Who has Claimed Unemployment the Most as a Result of COVID-19? Source: Kentucky Center For Statistics MSBA 625: Storytelling with Data (Part Two): Orange Team 86
Women were impacted the more than men. MSBA 625: Storytelling with Data (Part Two): Orange Team 87
What industries are impacted during this pandemic? Source: Kentucky Center For Statistics MSBA 625: Storytelling with Data (Part Two): Orange Team 88
The fo food ser services ind industry was impacted the most by COVID-19 MSBA 625: Storytelling with Data (Part Two): Orange Team 89
Safe work environments become a priority Working from home becomes standard COVID- 19’s practice Impact on Worker Health benefits become non-negotiable Preferences Job security becomes paramount Salary increases are not guaranteed MSBA 625: Storytelling with Data (Part Two): Orange Team 90
Prioritize employee health Recommendations Prepare your business for future for Louisville work from home situations Employers post COVID-19 Become more flexible as an organization Invest in your employees MSBA 625: Storytelling with Data (Part Two): Orange Team 91
Purple Team Better Workplaces, Better World (Part Two)
EMPLOYEE DEMOGRAPHICS BETTER WORKPLACE BETTER WORLD
Regardless of f tenure, , more people ca care ab about th the Benefits a co company offe ffers rs th than an any other th theme. MSBA 625: Storytelling with Data (Part Two): Purple Team 94
Among emplo loyees tha that ag agreed the they were lik ikely to o leave, Ben Benefits and and Lea Leaders rship ip wa warranted the the mos ost com commentary. MSBA 625: Storytelling with Data (Part Two): Purple Team 95
Participation
HIG IGHLIGHTS TE TENURE AN AND JOB OB CL CLASSIFICATION REM EMOTE E VS. TR TRADITIONAL WORKERS Tenure = Dissatisfaction > AGE E & GEN ENERATION EMPLOYEE EM EES WITH CH CHIL ILDREN Age = Dissatisfaction No Kids Benefits Kids Flexibility Millennials Gen X - Different priorities Louisville vs. National
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