Pundits have identified Employee Experience (EX) as one of the top priorities for HR. A lot of the science and art of EX is based on the Customer Experience (CX) approach, which makes extensive use of data to understand the customer and identify their needs and aspirations. Workforce/people data has been notoriously siloed (in HRMS, CRM, Intranets, etc.) and are often unreliable and outdated. Is it possible to achieve good Employee Experience when Workforce/people data is not up to scratch? In this “free-range” online discussion we have a chat with a panel of CX, EX and Analytics experts about the better practices, challenges and opportunities for the use of HR/People Analytics for better EX design and implementation.

1. WWW.EXASSEMBLY.COM.AU
@exassembly
fb.me/exassembly
Sydney | Melbourne |Brisbane
SessionTips
• Use the chat window to
post your questions,
comments and insights.
• This is a free and
frank discussion.
Diversity of views is
welcome.
• This session is being
recorded and will be
available on
www.exassembly.com.au
1

2. WWW.EXASSEMBLY.COM.AU
PANEL
Ally Atmadja
Founder
We AreYour Friends
EX Assembly Melbourne MeetUp
Sandhya Krishnan
Lead -Workday HCM
Transformation
RACWA
2
(Moderator)
RobWilkins
Leader – Information
Management Systems
NSW Department of
Education
Robin Boomer
Director,Advisory HR
+Workforce Analytics
Gartner

3. WWW.EXASSEMBLY.COM.AU
1
● Intros/About EX
● Research & stats
2
● Share better practice/
Point of view (POV)
3
SESSION FLOW
Use the chat window to post
your questions, comments and
insights.
3
.
This is a free and frank
discussion. Diversity of views
is welcome

4. WWW.EXASSEMBLY.COM.AU
Meetups
Sydney 100 members
Melbourne 40 members
Brisbane – 20 members
Gatherings
Practice
Leadership
Unconference
Sydney - Planned for
after COVID
Better Practices
Collaborative
Projects (Collabs)
EX Assembly is a community of forward-
looking EX & HR professionals interested
in frank discussions about current issues
and trends in the science and art of
Employee Experience; and its application at
work.
Building inspiring workplaces through
Employee Experience
“Building inspiring workplaces through better Employee
Experience”
EX Awards
Webinars
Building
EX Capability
Workshops/
Certification
EX Consulting
4

5. WWW.EXASSEMBLY.COM.AU
Using Workforce
Analytics for Employee
Experience
Effectiveness
Employee
Wellness
WHAT IS COMING UP ?
@exassembly
5
AUG
Learner
Experience
MAY
Candidate
Experience
JUNE JULY
UNPACKING
EX
SEPT
Using Knowledge
Management for Better
Employee Experience
OCT

6. WWW.EXASSEMBLY.COM.AU
WHERE AND HOW CAN ANALYTICS BEST CONTRIBUTE
TO EX?
Q&A
6
WILL DATA PRIVACY AND SECURITY CONCERNS
HINDERTHE USE OF WORKFORCE ANALYTICS FOR EX?
CAN ARTIFICIAL INTELLIGENCE/ MACHINE LEARNING
FACILITATE EX?
ROBUST PEOPLE/HR DATA CRITICALTO GOOD
EMPLOYEE EXPERIENCE DESIGN. WHAT ARE THE
DANGERS OF RELYING ON UNSATISFACTORY PEOPLE
DATA?

7. WWW.EXASSEMBLY.COM.AU
EMPLOYEE EXPERIENCE (EX)
Our view is that :
• recognising employee’s own personal
journey is critical.
• workforce experience is more accurate
term.EX Assembly Framework Ver 0.8
EX
Employee’s
Personal Journey
Improve Organisational
Performance
Growth &
Value Add
Values
Alignment
Life stage
Career/ Life
Strategy
Physical Space
Navigation
Purpose
Value
Brand
Culture
Work Processes Systems & Tech
Measurement
Engagement
NPSetc
Leadership
7
Employee Experience (EX) is the mindset
and method where:
- companies and their people working
together
- to create personalized, authentic
experiences
- that ignite passion and tap into
purpose
- to strengthen individual, team, and
company performance.

8. WWW.EXASSEMBLY.COM.AU
SURVEY RESULTS
8

9. WWW.EXASSEMBLY.COM.AU
9
Confirms that
HR/People Data
needs improvement

10. WWW.EXASSEMBLY.COM.AU
10
Need for better
awareness

11. WWW.EXASSEMBLY.COM.AU
11
EX needs to use
People/HR data
better, if the data
quality can be
improved

12. WWW.EXASSEMBLY.COM.AU
12
Missed
Opportunity ?

13. WWW.EXASSEMBLY.COM.AU
RobWilkins
Leader – Information Management Systems
NSW Department of Education
13

14. WWW.EXASSEMBLY.COM.AU
USINGWORKFORCE
ANALYTICS FOR EMPLOYEE
EFFECTIVENESS.
Rob Wilkins

15. WWW.EXASSEMBLY.COM.AU
The internet of things supplies real time data

16. WWW.EXASSEMBLY.COM.AU
4 Dimensions model for Employee Experience Analytics
WHAT?
Data, Environments, Machines,
Contexts, Intranets, Collaboration Tools,
Conversations etc.
(e.g. HRIS, Staff Directory, Staff Vending
Machines, Staff Cafes, LMS, LRS,
Yammer, Slack, Jive, Trello, etc.)
WHY?
Objectives
(e.g. Monitoring, Analysis, Prediction,
Intervention, Tutoring, Mentoring,
Assessment, Feedback, Adaptation,
Personalisation, Recommendations,
Personal Awareness, Personal reflection.)
HOW?
Methods/Data Points.
(e.g. Statistics, Visualisation, Data
Mining, Intranet and Web Mining,
Social Network Analysis, Discourse
Analysis, Content Analytics, Historical
Context Analysis, Disposition Analysis,
Personal Preference Analytics.)
WHO?
Stakeholders.
(e.g. Employees, Learners, HR Business
Partners, Employee Managers, General
Managers, Leadership, the whole
organisation.)

17. WWW.EXASSEMBLY.COM.AU
WHATWE DON’T KNOW…..ANALYTICS
Statistics
Visualisation
Data
Mining
Social
Network
Analysis
Content
Analytics
Discourse
Analysis
Historical
Context
Analysis
Disposition
Analysis
Personal
Preference
Analytics

18. WWW.EXASSEMBLY.COM.AU
DON’T CALL IT LEARNING, MODELLING,ANALYTICS
KNOWLEDGE MGT OR INFORMATION MANAGEMENT....
IT IS NOW A PART OF OUR WORK
The accelerating rate of change in business forces everyone in every organisation to make a
choice: absorb, learn and use the knowledge from analysis while you work or become
obsolete.We don’t know what we don’t know about our employees.
Today’s knowledge work environment screams out for a never-ending cycle of analysis for
impact, predicated on:
• learning what you need to know from the analysis, when you need to know it
• reinforcing the analysis by applying responses to insights immediately you know there is a
need
• knowing where to find relevant real time analysis in lieu of lag data and indicators
• learning from your network of peers and comparing action and impact to refine
approaches.

19. WWW.EXASSEMBLY.COM.AU
Sandhya Krishnan
Lead - Workday HCMTransformation
RACWA
19

20. WorkforceAnalytics,
Gamification and EX
Sandhya Krishnan

21. Increased
people data =
more
opportunity
 Context of work has been rapidly changing
 When technology runs our lives, there’s information behind it
 Are we doing enough to seek patterns and insights in this
information?
 Are we making employee experience design decisions based on
these insights?
 How do we leverage contemporary concepts like gamification to
do this for us?

22. What is
Gamification?

23. Gamificationfor
EX
Scratching the surface with
opportunities
Collaboration Operations
Learning
RecognitionInnovation
Empowerment

24. Workforce
Analytics- the
backbone
Credits: Process of Gamification by Marache-Francisco and Brangier
 WFA provides the user preference and behaviour data to
determine if gamification is the right choice
 WFA is the source for the baseline metrics that need work
 WFA allows continuous monitoring of the metrics to measure the
impact of gamification
 New objectives, more feedback loops

25. WWW.EXASSEMBLY.COM.AU
25
Robin Boomer
Director,Advisory HR +Workforce Analytics
Gartner

26. © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates. This publication may not be reproduced or distributed in any form
without Gartner’s prior written permission. It consists of the opinions of Gartner’s research organization, which should not be construed as statements of fact. While the information contained in this
publication has been obtained from sources believed to be reliable, Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Although Gartner research
may address legal and financial issues, Gartner does not provide legal or investment advice and its research should not be construed or used as such. Your access and use of this publication are
governed by Gartner’s Usage Policy. Gartner prides itself on its reputation for independence and objectivity. Its research is produced independently by its research organization without input or
influence from any third party. For further information, see “Guiding Principles on Independence and Objectivity.”
Robin Boomer
Do’s and Don’ts of
Employee Data

27. 27 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
The Reasons We Use Employee Data
Employees Organization
Performance
Improvement
Productivity
Gains
Risk
Management
Compliance
Adherence
Convenience
Professional
Development
Employee
Safety
Personalization
Teams
Collaboration
Work Allocation

28. 28 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
Employees More Willing to Share Than You Think
n = 7,401
Source: 1Q19 Gartner Global Labor Market Survey
8%
9%
10%
10%
12%
16%
0% 10% 20%
Engagement
Collaboration
Technology Utilization
Physical Space
Self-Identification
Personal Health
Percentage of Employees Unwilling to Share Data, by Category
4% of employees are unwilling to share any category of data.

29. 29 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
Same Data, Different Risks
Data Used Use Case
Activity
Monitoring
Making
me safer.
Predicting if
I am going to quit.
Helping me be
more productive.
Determining
my performance
rating.
Personal
Life Details
Recommending
an ERG for me.
Selecting work
Opportunities
for me.
Determining
my pay.
Suggesting
benefits for me.
Work Metrics
Providing me with
performance
feedback.
Using as the only
input to determine
my promotion.
Helping me
improve customer
satisfaction.
Improving my
workspace.

30. 30 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
Risk Increases with Personal Impact
• What work do I do?
• Who do I work with?
• What are my skills and
competencies?
• What job opportunities are
there for me?
• What should I learn?
• Am I safe?
• Is my employer compliant?
• Am I compliant?
• Is the culture inclusive?
• What work
gets allocated to me or
to others?
• Will I be selected for this job?
• Will I get promoted?
• What pay will I get?
• Can I lose my job?
• Am I seen as a flight risk?
High Impact on MeLow Impact on Me
Seen
as Unfair
Seen
as Fair

31. 31 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
Four Aspects of Data Ethics
Data Ethics:
How should we responsibly use employee information and related analytics in
our decision making?
Safe and Secure
The responsibility to adequately secure employee data as
long as it is in existence.
Transparent
The necessity to inform employees what personal data is
processed, on which grounds and for what purposes.
Accurate
The responsibility to ensure all personal data processed on
employees is correct and serves a purpose and that
analysis is unbiased.
Purpose-Driven
The need to ensure the negative consequences of
using and analyzing employee data do not outweigh
the positive.

32. 32 © 2019 Gartner, Inc. and/or its affiliates. All rights reserved. Gartner is a registered trademark of Gartner, Inc. and its affiliates.
Transparency Key to Trust and Willingness
n = 7,401
Source: 1Q19 Gartner Global Labor Market Survey
30%
31%
32%
34%
35%
0% 20% 40%
Improved Connection to Organization’s
Vision, Strategy and Values
Improved Relationships
With Colleagues
Improved Understanding of Growth
and Development Opportunities
More Relevant Rewards
(e.g., Benefits, Compensation)
Job Responsibilities That More
Closely Align With Interests
Influence of Offers on Likelihood of Sharing Data
Percentage of Employees for Whom Each Offer Would Increase Their Willingness
RelevancetoEmployee

33. WWW.EXASSEMBLY.COM.AU
WHERE AND HOW CAN ANALYTICS BEST CONTRIBUTE
TO EX?
Q&A
33
WILL DATA PRIVACY AND SECURITY CONCERNS
HINDERTHE USE OF WORKFORCE ANALYTICS FOR EX?
CAN ARTIFICIAL INTELLIGENCE/ MACHINE LEARNING
FACILITATE EX?
ROBUST PEOPLE/HR DATA CRITICALTO GOOD
EMPLOYEE EXPERIENCE. WHAT ARE THE DANGERS OF
RELYING ON UNSATISFACTORY DATA?

34. WWW.EXASSEMBLY.COM.AU
KEEP IN TOUCH
www.exassembly.com.au
@exassembly
www.facebook.com/exassembly
www.linkedin.com/company/ex-assembly/
34