hr analytics alexandra dass and mursal nassimi willamette shrm student chapter
TRANSCRIPT
![Page 1: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/1.jpg)
HR AnalyticsAlexandra Dass and Mursal Nassimi
Willamette SHRM Student Chapter
![Page 2: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/2.jpg)
![Page 3: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/3.jpg)
What is HR Analytics?
A form of business intelligence
Correlates business data and people data
Establishes a cause and effect relationship
![Page 4: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/4.jpg)
Why HR Analytics?
Engage in evidence-based decision making
Improve employee performance
Get a better return on investment
Make relevant decisions
![Page 5: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/5.jpg)
HR Analytics
Source: Lisbeth Claus and Kendal Callison, Global HR Analytics, in Global HR Practitioners Handbook, Volume 3 , 2014 (Forthcoming)
ORGANIZE ANALYZE INTERPRET
Efficiency • Effectiveness • Impact
HR METRICS, SCORECARDS, DASHBOARDS
Type
of d
ata
Sour
ce o
f dat
a
Empl
oyee
seg
men
tsJo
b gr
oups
Leve
lLo
catio
n, e
tc.
Stati
stica
l too
ls &
te
chni
ques
Valu
e cr
eatio
nRO
ICo
st-b
enefi
t
![Page 6: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/6.jpg)
HR Analytics – More than HR MetricsMetrics Analyticstangible intangiblepast data future insightsreporting analyzingcontrolling optimizingHR ownership management
ownership
![Page 7: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/7.jpg)
Types of Metrics
Efficiency Effectiveness Impact
Source: Boudreau and Ramstad, Beyond HR,2003
![Page 8: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/8.jpg)
Table Discussion
Which types of leaves apply to your organization?
Handout: Types of leaves of absences
![Page 9: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/9.jpg)
Table Discussion
Do you have any idea of what absenteeism looks like in your organization?
![Page 10: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/10.jpg)
The Process What specific (employee) data is needed to turn this
topic into HR analytics? Where (internal/external) does HR get that data? Who ‘owns’ that data and how does HR get access
to that data? What are common HR metrics related to this topic? What does your spreadsheet look like? What will your sample dashboards look like? What types of actions would you be able to take?
Source: Lisbeth Claus and Kendal Callison, Global HR Analytics, in Global HR Practitioners Handbook, Volume 3 , 2014 (Forthcoming)
![Page 11: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/11.jpg)
What type of data would you need in this case? Unit of analysis (employee record)
Data
employee number gender
age job group (function)
job level (hierarchy) job classification (exempt, non exempt)
salary(rate) Performance review
location leave classification (type)
leave status duration
![Page 12: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/12.jpg)
Internal Scan: Absenteeism
Monda
y
Tues
day
Wed
nesd
ay
Thur
sday
Frid
ay0
10
20
30
40
50
60
70
80
90
100
All leaves
Monda
y
Tues
day
Wed
nesd
ay
Thur
sday
Frid
ay0
10
20
30
40
50
60
70
80
90
100
MedicalNon-medical
Monday Tuesday Wednesday Thursday Friday0
10
20
30
40
50
60
70
80
90
100
ABC
Monda
y
Tues
day
Wed
nesd
ay
Thur
sday
Frid
ay0
102030405060708090
100
SalemPortlandEnterprise
![Page 13: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/13.jpg)
Advantages and Disadvantages of HR Analytics
Advantages DisadvantagesRecognize skills and vulnerabilities of the workforce
Human behavior cannot be controlled
Predict and measure turnover
Access to the right information
Understand and mitigate risk
Difficulty in integrating data
![Page 14: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/14.jpg)
Leading Practices
Build a numeracy culture
Use evidence-based knowledge
Ensure integrity of data
Identify relevant data
Sample data
![Page 15: HR Analytics Alexandra Dass and Mursal Nassimi Willamette SHRM Student Chapter](https://reader035.vdocuments.net/reader035/viewer/2022062321/56649dd85503460f94acdc60/html5/thumbnails/15.jpg)