Jeremy Doyle discusses people analytics and the future of work. People analytics uses data on individual and team behaviors to correlate them with organizational key performance indicators. Capturing unstructured behavioral data provides new visibility for decision making. Case examples show how people analytics identified important behaviors driving performance, such as informal relationships, expertise transfer, cohesion, and employee integration. Changes based on analytics insights improved productivity, job satisfaction, and sales.

1. Jeremy Doyle
People Analytics
Digital transformation
and the future of work

5. What does it take to win in your
business?

6. vs.

7. A Regular Day

11. Generating Data

12. 62
%
38
%
12
%
88
%
21
%
79
%
29
%
71
%
Speaking Time

13. Interactivity
88%
38%
79%
71%

14. Individual Behaviour
30◦
9 AM 10 AM 11 AM 12 PM 1 PM 2 PM

15. Pitch and Volume

16. We all generate reams of data traces. By tracking social behaviors over time one can identify
communication problem areas and solutions as well as demonstrate how behavioral patterns
drive success.
Team 1 Employee
Team 2 Employee
How it Works

17. What is People Analytics?
The basic concepts of people analytics are:
• View the organization from a holistic perspective with People at the center
• Individual and team behavior correlateto organizational KPI’s
• Data on these behaviors can be objective and quantifiable
• Capturing this often unstructured data will provide new visibility for decision making
“You can’t manage what you don’t measure” – Peter Drucker
$50x
$10x
$1x
Human Capital
(Salaries, wage, benefits)
Workplace Investment
(Real estate, IT, services)
ROI
(Revenue, earnings, growth)
People Analytics
provides data to
understand the
organization like
never before, and
to make optimal
investments for
performance

18. Sensing Technology
1997 2014

19. Social Sensing

20. • Ability to link key behaviors with
specific KPIs
• Enables employees to drive
change through understanding of
behavioral profiles and self set
goals and benchmarks
• Enables senior leaders to unlock
the behavioral differences in high
performing teams
• Enables direct line managers to
spot delivery risks based on
communication gaps early
• Enables continuous improvement
in all aspects of business
The Technology
Social Sensing & Analytics
Sociometer
Participants
Registration Data
Insights
Email/Chat Data
KPI Data
Dashboards
Analytics Data
Algorithms
Study Results
Targeted Improvements

21. A/B Test Everything

24. Privacy Policy
• Individual information must be kept confidential
• Only users should have access to their individual data
• Others can only see aggregated data
• Conversations are not recorded
• Only features such as tone of voice and volume level are
collected
• No content is captured
• Only patterns of communication
• Opt-In required

25. Quantifying Collaboration
Cohesion - How tightly knit
is the group?
• Productivity
• Engagement
• Trust
Centrality – How freely
does information flow?
• Autonomy
• Bottlenecks
• Influence
Exploration – Cross-
functional collisions
• Adaptability
• Innovation
• Openness
F2F vs Digital – Volume
across mediums
• Workload
• Job Satisfaction
• Retention

26. What do we need to know?
Past success
linked to informal
relationships?
Generational
expertise
(to be transferred)
Informal
leadership
Organizational
Gaps

27. 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07
Information Vitality Analysis
Dependence on a few influential individuals to share knowledge?
 Formal leaders are significantly more influential than most staff, but they are not alone
 The highlighted individuals are integral to the business, however their extreme centrality may represent
process inefficiency or risks to knowledge retention
 Are other team members building influence and expertise to fill gaps?
Centrality (Influence)
Exploration(Innovation)

28. Integration Initiatives
Can we increase INTEGRATION to drive productivity?
YES

29. 0.7
0.8
3.1
-4.1
-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0
Time Change (hours/week)
F2F
Email
Phone/Lync
Physical Activity
Fewer long
meetings
Workload
grows with new
connections
Impacts of Change on Culture

30. wyze
Drill into your data to find what
behaviors you’re doing well…
…and what needs some work
Track your improvement over
time

31. Online travel company: Amenities and office layout Software firm: Work process and employee integration
10%
30%
0%
5%
10%
15%
20%
25%
30%
Productivity Job Satisfaction
AttributeImprovement
Network Size
• F2F network size
• Drives productivity (software code)
• Supports job satisfaction post layoff process
• F2F network size driven by lunch habits
• Lunch space redesign aimed to increase network size
• Interaction frequency improves completion of
interdependent code by 32%
• Remote teams communicated 8% less about
dependencies which added cost of over $150 million/year
Collocated
Remote
Time and expense
Interaction Frequency
$150MM cost
-32%
time
Highest Performing Lowest Performing Typical
• Extremely cohesive group
• Promoted group achievement
goals over individual rewards
• Three new employees (circled) were
not socially integrated with cohesive
core - even after over one month they
only spoke with their direct manager
Floor 1 Floor 2
• F2F network clearly shows two groups
• The physical layout of the branch
inhibited information sharing
• Future locations all one floor
Retail Banking: Layout and employee integration
• Performance driven by cohesion
• Physical distance impedes knowledge sharing
• New employee integration is essential
Case Examples

32. Case Examples
0%
5%
10%
15%
20%
Sales
Redesign Impact on Sales
0%
2%
4%
6%
8%
10%
Cohesion Productivity Engagement
F2F Cohesion Drives Engagement
• F2F interactions driven by coffee machine location
• Redesign aimed to increase F2F time and decrease email volume
0%
2%
4%
6%
8%
10%
12%
Exploration Sales
F2F Effects on Performance
Pharmaceutical Sales & Marketing
German Bank
• Identify processes responsible for human capital bottlenecks
• Reveal informal processes driving performance
IT Firm / Engineering Processes
• Identified informal experts; extreme centrality may be barrier
• Informal experts had average completion rate
• Compensation system discouraged expertise sharing

33. info@humanyze.com
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